Long-term survival after neoadjuvant low-dose ipilimumab plus high-dose nivolumab in resectable stage III melanoma: the 5-year survival-update and biomarker analysis from the PRADO-trial

Long-term survival after neoadjuvant low-dose ipilimumab plus high-dose nivolumab in resectable stage III melanoma: the 5-year survival-update and biomarker analysis from the PRADO-trial | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Long-term survival after neoadjuvant low-dose ipilimumab plus high-dose nivolumab in resectable stage III melanoma: the 5-year survival-update and biomarker analysis from the PRADO-trial Christian Blank, Lotte Hoeijmakers, Petros Dimitriadis, Steven Wijnen, and 39 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7090131/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 28 Jan, 2026 Read the published version in Nature Medicine → Version 1 posted You are reading this latest preprint version Abstract Neoadjuvant ipilimumab plus nivolumab has become standard therapy for stage III melanoma based on the NADINA trial, though long-term data are lacking. In the phase 2 PRADO cohort of OpACIN-neo (NCT02977052), 99 patients with stage III macroscopic melanoma received this regimen. We report first-time 5-year survival data: 71% event-free survival, 74% relapse-free survival, 79% distant metastasis-free survival, and 86% overall survival. Ongoing grade 1-2 immune-related adverse events occurred in 69% of patients alive, predominantly vitiligo and hypothyroidism. Major pathologic response (MPR), high tumor mutational burden (TMB), high interferon-gamma signature (IFNg), and PD-L1 expression ≥1% were associated with favorable outcomes. Combined high TMB, IFNg, and PD-L1 expression yielded 100% MPR and 100% 5-year event-free survival, while triple low expression had only 18% MPR and 41% event-free survival. Our findings demonstrate favorable long-term outcomes for patients with an MPR and identify TMB, IFNg, and PD-L1 as promising baseline biomarkers. Biological sciences/Cancer/Skin cancer/Melanoma Biological sciences/Cancer/Tumour biomarkers Biological sciences/Cancer/Cancer therapy/Cancer immunotherapy Neoadjuvant therapy adjuvant therapy immune checkpoint blockade immunotherapy personalized therapy melanoma Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction During the last decade, neoadjuvant immune checkpoint blockade (ICB) has been widely investigated in many different cancer types 1-8 . This paradigm shift was driven by the hypothesis that the presence of more (neo)antigens prior to surgery results in a stronger and broader clonal expansion of tumor-specific T cells induced by neoadjuvant ICB. Results from early preclinical and clinical studies supported this hypothesis, suggesting superior outcomes for neoadjuvant compared to adjuvant ICB 9-13 . The randomized phase II SWOG-1801 and phase III NADINA trials in patients with macroscopic resectable stage III melanoma 1,2 subsequently confirmed these findings, showing superior clinical outcomes in those who received neoadjuvant ICB compared to those who received adjuvant ICB only. The SWOG-1801 trial evaluated pembrolizumab (anti-PD1, 200 mg every 3 weeks) given as 3 neoadjuvant cycles followed by 15 adjuvant cycles versus 18 cycles of adjuvant-only treatment. The neoadjuvant approach demonstrated superior outcomes with an estimated 2-year event-free survival (EFS) of 72% compared to 49% for adjuvant-only treatment 2 . The NADINA trial showed even greater benefits with an estimated 18-month EFS of 81% in patients treated with 2 cycles of neoadjuvant nivolumab (anti-PD1) plus ipilimumab (anti-CTLA4) followed by a response-directed adjuvant treatment regimen as compared to 54% in patients treated with 12 cycles of adjuvant nivolumab 1,14 . Identifying patients likely to respond to treatment could enable personalized therapy approaches, to improve responses and minimalize toxicity. In stage IV melanoma, tumor mutational burden (TMB) and Programmed Cell Death Ligand 1 (PD-L1) expression at baseline are associated with favorable treatment responses 15 , in stage III melanoma the interferon gamma gene signature (IFNg) and TMB, but not PD-L1 expression, are associated with pathological response and EFS 16 . Neoadjuvant ICB allows for pathologic response evaluation, a robust surrogate marker for relapse free survival (RFS) and distant metastasis free survival (DMFS) 14,17-19 . However, to date, all patients undergo potentially morbid surgery (therapeutic lymph node dissection; TLND) for pathologic response evaluation. The pathologic response in the largest lymph node metastasis at baseline (index lymph node; ILN) has shown to be representative of the pathologic response in the total lymph node bed 20,21 , suggesting that an initial removal of the ILN could tailor further personalized treatment or follow-up. The PRADO trial was the first trial in melanoma prospectively testing a surgical de-escalation approach, by marking and removing only the ILN for pathologic response evaluation after neoadjuvant immunotherapy 22 . We have previously reported that neoadjuvant ipilimumab plus nivolumab induced a pathologic response rate (≤50% residual viable tumor) of 72% (71/99 patients), including major pathologic response (MPR; ≤10% residual viable tumor) in 61% (60/99 patients), confirming the efficacy of this neoadjuvant regimen reported in the OpACIN-neo trial 13,22 . Of interest, the final pathological response analysis of the larger NADINA trial reported precisely the same MPR rate of 61% based on examination of the TLND specimen 14 . Early data from PRADO suggested that patients achieving a MPR in the ILN, can safely omit both TLND and adjuvant therapy, resulting in superior quality of life without increasing the individual risk of relapse at 3-years of follow-up 18,22 . Recently a large, pooled analysis from various studies and real-world patient databases confirmed the excellent outcomes for patients achieving an MPR, although these studies predominantly included TLND specimens 23 . However, patient outcome data beyond 3 years after neoadjuvant ipilimumab plus nivolumab, especially for those with an MPR in which subsequent surgery and adjuvant therapy were omitted, are lacking. Therefore, we report the 5-year update of the PRADO trial including survival, long-term toxicity, and the first biomarker analyses, and the 5-year survival-outcomes of the OpACIN-neo trial. In addition, we will be comparing the long-term outcomes to the previously conducted OpACIN-neo trial, where the same inclusion-criteria were handled. In OpACIN-neo patients were treated with different dosages of neoadjuvant ipilimumab + nivolumab, without personalized surgery or adjuvant treatment 13 . Results At the time of data-cutoff of 06/01/2025, the median follow-up was 60 months (interquartile range, IQR: 60 - 64 months), with a minimum follow-up of 31 months for all patients alive ( n =83). Survival outcomes At data cut off, 29/99 (29%) patients had an event (defined as disease progression resulting in inoperability, locoregional recurrence, distant metastases, or death, whichever comes first): six patients became inoperable due to progression before surgery, 23/92 (25%) patients had a locoregional recurrence after surgery, 18/92 (20%) had a distant metastasis after surgery, and 16/99 (16%) patients died, of whom 14 died from melanoma. One patient died of a cause not related to disease progression or toxicity and 1 patient died of an unknown cause without signs of disease progression. Patient-selection (99 patients versus 92 patients) for survival follow-up is displayed in Extended Data Fig. 10a . The estimated 5-year EFS, relapse free survival (RFS), distant metastasis free survival (DMFS), overall survival (OS) and melanoma specific survival (MSS) of patients treated in the PRADO trial were 71% (95% confidence interval (CI): 63-81%), 74% (95% CI: 65-84%), 79% (95% CI: 71-89%), 86% (95% CI: 79-93%) and 88% (95% CI: 81-94%) (Fig. 1a-e) . The median EFS, RFS, DMFS, OS and MSS had not been reached at time of data cutoff. In OpACIN-neo similar estimated 5-year survival rates were observed, without significant differences between the three treatment-arms in that study (Extended Data Fig. 4a-e & Extended Data Fig. 5a-d). When PRADO patients were grouped by pathologic response according to the International Neoadjuvant Melanoma Consortium (INMC) criteria 24 (Supplemental Table 1), the estimated 5-year RFS, DMFS and MSS were 86% (95% CI: 76-97%), 91% (95% CI: 83->99%) and 98% (95% CI: 95->99%) for patients with an MPR, 55% (95% CI: 32-94%), 55% (95% CI: 32-94%) and 64% (95% CI: 41->99%) for patients with a pathologic partial response (pPR; >10% and ≤50% residual viable tumor) and 48% (95% CI: 30-75%), 57% (95% CI: 40-83%) and 80% (95% CI: 64->99%) for patients with a pathologic non-response (pNR; >50% residual viable tumor) (Fig. 1f-h) . Baseline characteristics per pathologic response group are displayed in Supplemental Table 2. For patients with an MPR survival was improved as compared to patients without MPR, with 5-year RFS rates being 86% versus 50% (log-rank p -value<0.0001), DMFS 91% versus 56% (log-rank p -value<0.0001) and MSS 98% versus 74% (log-rank p -value=0.00034). These outcomes were similar to the outcomes observed in the OpACIN-neo cohort, with the exception for patients achieving a pPR, where these patients had higher landmark EFS, RFS, DMFS and MSS in the OpACIN-neo trial compared with PRADO. Neither group received adjuvant therapy (Fig. 1f-h & Extended Data Fig. 4f-h) . When dividing MPR into pathologic complete response (pCR; 0% viable tumor cells) and near-pCR (>0%-≤10% viable tumor cells), similar estimated 5-year survival-outcomes are observed in PRADO and in OpACIN-neo (data not shown). When searching for potential explanations of the outcome differences observed for the pPR patients from the PRADO vs OpACIN-neo cohorts, we compared their baseline characteristics (Supplemental Table 3) . We found that a larger proportion of patients in the PRADO pPR cohort were from Europe (10/11 in PRADO versus 5/12 in OpACIN-neo), no patients had an ulcerated tumor (0/10 in PRADO versus 5/12 in the OpACIN-neo; p -value=0.016) and a larger proportion of patients had a low tumor mutational burden (TMB; 100% in PRADO versus 44% in OpACIN-neo, p -value=0.026). There were no differences in measurable tumor burden (sum of diameter of target lesion and number of lymph nodes on imaging), BRAF -mutation status, frequency of grade ≥3 immune related adverse events (irAEs), use of prednisolone, or second line immunosuppression (Supplemental Table 3) .Three patients with a pPR in PRADO did not undergo a TLND, two patients refused additional surgery, and one patient was suspected to have stage IV disease, all three patients did not have disease progression at time of cutoff. BRAF -mutation status In PRADO, patients with a BRAFV600E/K -mutant melanoma had worse EFS than patients with BRAF -wildtype melanoma, with 5-year EFS of 60% versus 80%, respectively (Fig. 2a) (log-rank p -value=0.011 and Hazard Ratio of 2.63 (95% CI: 1.24-5.57, p =0.0118)). All patients with a distant metastasis on imaging at time of surgery had a BRAF -mutant melanoma. No significant differences between BRAF-mutant and BRAF-wildtype melanoma were found for RFS (80% versus 64%, log-rank p -value=0.12) and DMFS (84% versus 72%, log-rank p -value=0.23), though survival curves suggested a differential effect over time, complicating interpretation (Fig. 2b,c) . No differences for OS (86% versus 84%, log-rank p -value=0.79) and MSS (90% versus 84%, log-rank p -value=0.3) were observed (Fig. 2d,e) . In addition, presence of a BRAFV600E/K mutation in the tumor was not predictive for RFS, DMFS and OS in the univariable Cox-regression analysis (Fig. 3, Extended Data Fig. 2, Extended Data Fig. 3) . In the OpACIN-neo cohort, only numerical differences in EFS, RFS and DMFS were observed according to the BRAF mutational status, and no differences in OS and MSS (Extended Data Fig. 6a-e) .To investigate whether this difference was driven by the different doses of ipilimumab used in the OpACIN-neo cohort we divided the patients into different subgroups based on their BRAF mutational status (mutant versus wildtype) and treatment-arm (arm A (ipilimumab 3 mg kg -1 plus nivolumab 1 mg kg -1 ) versus arm B (ipilimumab 1 mg kg -1 plus nivolumab 3 mg kg -1 )) (Extended Data Fig. 6f,g) . Even though thesubgroups become too small to draw any conclusions, there is a slight trend towards a better response to higher dose of ipilimumab in patients with a BRAF -mutant melanoma (Extended Data Fig. 6f,g) . Safety In total, irAEs ≥ grade 3 occurred in 30% of the PRADO study population (Extended Data Fig. 1). Ongoing grade 1-2 irAEs occurred in 69% of the patients alive at data cut-off and were predominantly vitiligo and hypothyroidism (Extended Data Fig. 1). Subsequent therapies Six out of 60 (10%) patients in the MPR group had disease recurrence (Fig. 4) , including1/12 (8%) patients with a near-pCR and 5/47 (11%) patients with a pCR. Four of these six patients had a local recurrence that occurred within 20 months and were treated with surgery combined with BRAF-targeted therapy ( n =1), anti-PD1 ( n =2), or systemic targeted therapy alone ( n =1). Two out of the six patients in the MPR group had a distant metastasis as first recurrence, 60 and 61 months after registration (Fig. 4) . One of these patients had local progression in the jejunum that was treated with BRAF-targeted therapy, followed by surgery. The other patient had multiple metastatic sites including brain, and received re-induction with ipilimumab + nivolumab, however received only one dose due to toxicity and died soon thereafter. Five out of the 11 (45%) patients achieving pPR had disease recurrence. One patient had a local recurrence as first recurrence, which was surgically removed. Later the patient developed a distant metastasis and received high dose ipilimumab plus nivolumab followed by radiotherapy. Four out of the five patients with disease recurrence from the patients that achieved a pPR, had a distant metastasis at time of first recurrence. One elderly patient only received palliative radiotherapy at time of recurrence and died later of disease progression. The other patients were treated with surgery ( n =3) or radiotherapy combined with anti-PD1 ( n =1) ( Fig. 4) . Ten out of the 21 (52%) patients who achieved a pNR upon the neoadjuvant regimen had disease recurrence. Three of these eleven patients had a local recurrence and were treated with surgery +/- radiotherapy or T-VEC. Seven patients had a distant metastasis at time of the first recurrence and were treated with targeted therapy ( n =4), lenvatinib plus pembrolizumab ( n =1) or no systemic treatment ( n =2) (Fig. 4) . Of the two patients who did not receive any systemic treatment at time of progression, one received radiotherapy but later opted for best supportive care at time of further disease progression, and the other patient did not receive systemic due to previous toxicities. Six patients had a distant metastasis before surgery. Four out of these six patients received subsequent targeted therapy as first treatment after progression, one patient had long-term response to this subsequent targeted therapy. Four out of six patients with distant metastasis before surgery were treated with a combination of ipilimumab and nivolumab ( n =2 had a long-term response) before or after treatment with targeted therapy (Fig. 4) . Single biomarker analysis RNA sequencing data of the baseline biopsy is available in 80/99 (81%) patients (Extended Data Fig. 10) . Patients with a high IFNg score ( n =39) had improved EFS (5-year rate 81% versus 54%; log-rank p -value=0.0039), RFS (81% versus 57%; log-rank p =0.044) and DMFS (86% versus 63%; log-rank p -value=0.031) compared to patients with a low IFNg score ( n =41) (Fig. 5a,g) (RFS and DMFS not shown), but not OS (90% versus 70%; log-rank p -value=0.19) and MSS (92% versus 80%; log-rank p -value=0.22) (Fig. 5b,g) (MSS not shown). In OpACIN-neo similar trends were observed, with higher 5-year EFS, RFS, DMFS, OS and MSS in patients with a high IFNg score, though no significant log-rank test results (Extended Data Fig. 7) (RFS, DMFS and MSS not shown). Whole exome sequencing from the baseline biopsies is available in 75/99 (76%) PRADO patients. No statistically significant differences were observed in EFS (5-year rate 75% versus 58%; log-rank p -value=0.1), RFS (76% versus 60%; log-rank p -value=0.3), DMFS (80% versus 67%; log-rank p -value=0.45), OS (84% versus 81%; log-rank p -value=0.88) and MSS (90% versus 81%; log-rank p -value=0.45) when comparing patients with a high TMB ( n =32) to patients with a low TMB ( n =43) (Fig. 5c,d,h) (RFS, DMFS and MSS not shown). In OpACIN-neo, significant differences in EFS (5-year rate 86% versus 66%; log-rank p -value=0.032), DMFS (89% versus 69%; log-rank p -value=0.022), OS (96% versus 80%; log-rank p -value=0.014) and MSS (100% versus 79%; log-rank p -value=0.012) and numerical differences in RFS (86% versus 69%; log-rank p -value=0.061) were observed comparing patients with a high TMB to patients with a low TMB (Extended Data Fig. 7 ) (RFS, DMFS and MSS not shown). In 76 patients, the PD-L1 expression on tumor cells (TPS score) was determined in the baseline biopsy. Patients with a high PD-L1 expression of ≥1% ( n =43) had a significantly improved EFS (5-year rate 88% versus 60%; log-rank p -value=0.0036), RFS (87% versus 64%; log-rank p -value=0.045), OS (94% versus 79%; log-rank p -value=0.049) and MSS (97% versus 81%; log-rank p -value=0.029) compared to patients with a PD-L1 expression of <1%, respectively ( n =33) (Fig. 5e,f,i) (RFS and MSS not shown). No significant differences were found in DMFS (5-year rate 90% versus 73%; log-rank p -value=0.097) between the groups. In OpACIN-neo, only small differences in 5-year rates and no significant log-rank test results were observed for EFS (85% versus 76%; log-rank p -value=0.29), RFS (85% versus 78%; log-rank p -value=0.36), DMFS (85% versus 83%; log-rank p -value=0.49), OS (96% versus 88%; log-rank p -value=0.12) and MSS (96% versus 89%; log-rank p -value=0.25) when comparing outcomes of patients with a high PD-L1 expression of ≥1% to patients with a PD-L1 expression of <1% (Extended Data Fig. 7) (RFS, DMFS and MSS not shown). To investigate whether the missing PD-L1 expression of patients with an event influenced the predictive value of PD-L1 expression, we performed imputation by replacing these missing values by all low or all high. Although PD-L1 expression remained predictive for RFS, DMFS and OS (Supplemental Table 4) , the unavailability of the PD-L1 expression in some patients might have resulted in an overestimation of the differences observed in our cohort. Combined biomarker analyses Next, we analyzed the contribution of the most prominent baseline markers when combining them to a multiparameter baseline biomarker. In 61 patients the IFNg signature score, TMB and PD-L1 expression were available, and were distributed as displayed in Fig. 6a . As expected, having all three parameters low was associated with the lowest MPR rates (18%; 95% CI: 4-43%), while having all three parameters high was associated with a 100% chance for MPR (95% CI: 72-100%) ( Fig. 6b ). Patients with MPR had a higher IFNg signature score ( Fig. 6c) and a higher TMB ( Fig. 6d) . The IFNg signature score did not correlate with the TMB (Fig. 6e) . We did not include PD-L1 as this was a non-numeric variable. In line with the response data patients with a triple high score ( n =11) had the longest 5-year EFS (100%) while patients with triple low ( n =17) had the shortest (41%) Fig. 6f . The AUC curves of these two scenarios are shown in Fig. 6g. Similar survival-trends were observed in the OpACIN-neo trial, as in the patients with triple high ( n =3) 100% (95% CI: 29-100%) had MPR and an 100% estimated 5-year EFS and the patients with triple low ( n =11) had a 27% (95% CI: 6-61%) MPR-rate and 55% estimated 5-year EFS (Extended Data Fig. 8a-e) As clinical grade TMB evaluation is a costly procedure, we also analyzed the biomarker-combination of IFNg and PD-L1 expression alone. Patients with a low IFNg score and a low PD-L1 expression ( n =22) had MPR rate of 27% (Fig. 7b) and 5-year EFS of 48% (Fig. 7a, c) ,while patients with a high IFNg score and a high PD-L1 expression ( n =21) had MPR rate of 86% (Fig. 7a) and a 5-year EFS of 91% (Fig. 7d). The AUC curves for these biomarker doublets are shown in Fig. 7e and f and showed only slightly lower AUC compared to the model using all three biomarkers (Fig. 6g) (AUC of 0.745 in double low versus 0.756 in triple low; and an AUC of 0.692 in double high versus 0.712 in triple high). Similar results were observed in the OpACIN-neo cohort with MPR in 47% of patients with a low IFNg score and a low PD-L1 ( n =19) and 100% of the patients with high IFNg score and a high PD-L1 ( n =7). However, and in contrast to the PRADO cohort, only numerical differences were observed in EFS according to the combination of IFNg score and PD-L1 status (Extended Data Fig. 9a-d) . Other parameters associated with RFS, DMFS or OS Differences in baseline clinical parameters, grade of toxicity, immunosuppressives used, and baseline biomarkers for patients with or without a recurrence observed during follow-up are displayed in Table 1 . Univariable Cox regression analysis results for RFS, DMFS and OS are displayed in Fig. 3 , Extended Data Fig. 2 and Extended Data Fig. 3 . Given the relatively small number of events observed for these endpoints, we highlighted parameters with either statistical significance (i.e. p-value < 0.05) or an estimated HR ≤0.5 or ≥2. Selected variables according to these criteria were pathologic response (improved RFS and DMFS for MPR patients compared to pPR or pNR), lymph node location (improved DMFS and OS for neck compared to axilla), use of prednisolone (poorer OS when used), use of second line immunosuppressants (shorted DMFS and OS when used), IFNg (prolonged RFS, DMFS and OS if high IFNg), and PD-L1 (improved RFS, DMFS and OS if ≥1%). More patients with a BRAF -mutant melanoma had a recurrence, but presence of a BRAF mutation in the tumor was not predictive for RFS, DMFS and OS in the univariable Cox-regression analysis (Table 1, Fig. 3, Extended Data Fig. 2, Extended Data Fig. 3) . These associations remain similar in size and/or statistical significance when adjusting for other parameters, one at a time, in multivariable analyses. The conclusions remained the same when performing these analyses on multiply imputed data. Discussion In this five-year update of the PRADO-trial we present the first long-term survival outcomes of patients treated with neoadjuvant low-dose (1 mg kg -1 ) ipilimumab and standard-dose (3 mg kg -1 ) nivolumab, followed by response driven adjuvant therapy. These phase 2 study data are of interest as they may indicate what to expect from the long-term follow-up of the phase III NADINA trial 1 . Additionally, these results might support re-imbursement initiatives for this neoadjuvant treatment approach in various countries. In line with several previous reports 14,17-19 , achieving MPR after neoadjuvant ICB remains a robust surrogate marker for long-term outcome. Of interest, our results indicate that it might be safe to de-escalate surgery in patients with MPR in the ILN 18,22 , as the long-term outcomes in PRADO are comparable to that of the OpACIN 19 and OpACIN-neo trial cohorts where patients all underwent TLND. The OMIT (NCT06754904) and MSLT-3 (NCT07049276) trials will deliver additional prospective/randomized data for omitting TLND in patients with MPR in the ILN. In contrast to earlier observed good outcomes for patients with a pPR in neoadjuvant ICB trials 16,23,25 , in PRADO, these patients had worse outcomes than patients who had a pNR. Patients with a pNR had adjuvant therapy and pPR did not in PRADO. When comparing patients with a pPR from PRADO to patients with a pPR in OpACIN-neo 13,22 , different outcomes (higher EFS, RFS, DMFS and MSS landmarks in OpACIN-neo) are not likely driven by differences in patient-selection, measurable tumor burden, adverse event management or a difference in measured residual viable tumor at surgery. Differences in neoadjuvant or surgical regimen might drive these different outcomes, as higher doses of ipilimumab (in arm A and C OpACIN-neo) could induce better outcomes in these patients, particularly those with BRAF mutant melanoma 26,27 . Another cause might be the differences in surgical regimen for patients who are treated with one surgery (TLND) in OpACIN-neo and two surgeries (ILN and TLND) in PRADO, as this might induce an immunosuppressive state 28,29 . Larger cohorts are needed to confirm these findings, as very few patients have a pPR within each trial. We observed no ongoing grade 3-4 irAEs at five years follow-up, suggesting that this regimen has a manageable safety profile. However, potentially quality-of-life-impairing irAEs with hypothyroidism or adrenal insufficiency requiring life-long hormone replacement therapy were observed in 22% and 7% of patients in the total cohort and 25% and 8% in patients with MPR. In addition, we observed that the use of prednisolone and second line immunosuppressants remained associated with a worse OS in the multivariable analysis. This association was also observed in patients with advanced melanoma treated with ipilimumab +/- nivolumab, where peak dose prednisolone or second-line immunosuppression for irAEs was associated with impaired survival in a retrospective analysis 30-32 . Future research and prospective trials should prioritize identifying patients in whom neoadjuvant treatment could be de-escalated, for example to anti-PD1 monotherapy, to prevent unnecessary side effects. In PRADO, the lower EFS in patients with a BRAF -mutant melanoma was pre-dominantly driven by the patients developing distant metastasis before surgery. RFS and DMFS of patients with a BRAF -mutant melanoma are better or similar compared to patients with a BRAF -wild type melanoma in short term, most likely due to the 1 year of adjuvant dabrafenib plus trametinib in the patients with a pNR, but this is lost in years thereafter. Similar trends were observed in the patients treated with the same regimen (low-dose ipilimumab plus normal dose nivolumab) in OpACIN-neo. Our results suggest that patients with a BRAF -mutant melanoma might benefit from high-dose neoadjuvant ipilimumab, which is in line with what has previously been observed in stage IV melanoma 26,27,33 . OS and MSS of patients with a BRAF -mutant or a BRAF wild type melanoma are comparable, which is most likely due to more options in subsequent treatment-lines. If confirmed in the NADINA trial 1 the BRAF mutation status should be investigated further as a baseline biomarker for treatment escalation. Not all patients achieve good outcomes on this regimen. Some patients would benefit from alternative/intensified neoadjuvant schemes to achieve equally promising long-term outcomes as those observed in patients with MPR. In line with previous trials 16,34 , the 10-gene IFNg gene signature 35 was predictive for MPR and long-term EFS. In contrast to what was observed in OpACIN-neo 16 , PD-L1 expression was predictive and TMB was not predictive for long-term survival-outcomes. This inconsistency of TMB and PD-L1 as baseline biomarkers, warrants further analyses in larger (real world) cohorts 23 . Critically, other factors including neoadjuvant regimen, extent of surgery (ILN versus upfront TLND) and adjuvant therapy (type and/or in all patients or response driven) should be concurrently analyzed to understand the impact of each of these factors and their interaction with tissue biomarkers. The three tested baseline biomarkers (TMB, IFNg, and PD-L1) might be helpful tools in the future to identify patients who are not likely to respond to this regimen at baseline and include them into innovative neoadjuvant trials. For example, our previous DONIMI trial (NCT04133948) 34 showed that this baseline biomarker can be analyzed within clinically relevant timeframes to support neoadjuvant treatment decision-making. Another example is the NeoIReNi trial, that will use baseline biomarkers to enrich for those patients predicted to have non-MPR (NCT06999980). In addition, these promising baseline biomarkers should also be investigated in patient cohorts treated with other neoadjuvant treatments (e.g. anti-PD1 monotherapy, high-dose anti-CTLA4, anti-LAG3 or anti-TIGIT), since such analyses could help in personalizing neoadjuvant therapy for macroscopic melanoma further. The PRADO trial, and especially its biomarker subgroup analyses are limited by low patient numbers. Large, pooled analyses might deliver more significant data, that should be subsequently confirmed in prospective trials. In conclusion, this survival-update of PRADO shows promising long-term survival outcomes for patients treated with neoadjuvant ipilimumab and nivolumab, especially in patients who achieve MPR in the index lymph node. For patients without MPR, alternative neoadjuvant and adjuvant schemes are needed, and baseline biomarkers like the IFNg signature and PD-L1 expression might be promising biomarkers that could help identify these patients for escalation of therapy. Our data opens the possibility for biomarker-based personalization and response-driven personalization of surgery and adjuvant treatment. Methods Study design and participants The PRADO extension cohort from OpACIN-neo is an investigator-initiated phase II trial, testing 2 courses neoadjuvant ipilimumab 1 mg kg -1 plus nivolumab 3 mg kg -1 , followed by ILN response-based surgery (omitting the additional TLND in patients achieving MPR) and adjuvant therapy in patients achieving a pNR in the ILN (nivolumab for patients with a BRAF -wildtype and dabrafenib + trametinib for patients with a BRAF -mutant melanoma until week 52 +/- local radiotherapy). The detailed eligibility criteria, trial design, ethical approval and the first responses (pathologic responses, EFS, RFS, DMFS and OS) have been published earlier 22 . The trial enrolled participants in Australia at Melanoma Institute Australia (MIA) and at several Dutch centers [Netherlands Cancer Institute (NKI), Leiden University Medical Center (LUMC), Erasmus Medical Center (EMC), University Medical Center Utrecht (UMCU), and University Medical Center Groningen (UMCG)]. Pathologic response at week 6 was assessed according to INMC guidelines 24 and was categorized into MPR (≤10% residual viable tumor, which included patients with complete response (pCR; 0% residual viable tumor) and near-pCR (1 – ≤10% residual viable tumor), pPR (>10 – ≤50% residual viable tumor) or pNR (>50% residual viable tumor). Follow-up consisted of a radiologic assessment with CT or PET-CT, physical examination and laboratory testing every 12 weeks for 2 years post-surgery, and in year 3, 4 and 5 according to institute standards. Patients experiencing progression prior to surgery or recurrence after surgery, remained in the trial and were further followed for DMFS (in case of local recurrence only) and OS. Endpoints of the PRADO trial were pathologic response rate upon neoadjuvant two cycles ipilimumab 1 mg kg -1 plus nivolumab 3 mg kg -1 , to confirm the efficacy of arm B of the OpACIN-neo trail, and 24-month RFS of patients achieving MPR or pNR, to determine whether the TLND could be safely omitted in patients achieving MPR and to determine efficacy of adding adjuvant treatment in patients with a pNR. Secondary endpoints were short-term grade 3–4 irAEs, comparing surgical adverse events, radiologic response, DMFS, EFS, OS, health related quality of life, ongoing long-term irAEs, and biomarker analyses. The data cutoff for collection of the data presented here was on January 6, 2025. Validation cohort The investigator-initiated, randomized, phase II OpACIN-neo trial is used as a validation cohort in this manuscript, as the PRADO trial was designed as an extension cohort of the OpACIN-neo. The detailed eligibility criteria, trial design, ethical approval and the first responses (pathologic responses, EFS, RFS, DMFS and OS) are described in earlier publications 13,16,19 . Patients were randomized 1:1:1 to receive either two cycles of ipilimumab 3 mg kg -1 plus nivolumab 1 mg kg -1 every 3 weeks (arm A), two cycles of ipilimumab 1 mg kg -1 plus nivolumab 3 mg kg -1 every 3 weeks (arm B) or two cycles of ipilimumab 3 mg kg -1 every 3 weeks, directly followed by two cycles nivolumab 3 mg kg -1 every 2 weeks (arm C); all patients had a therapeutic lymph node dissection planned in week 6. None of the patients received any adjuvant treatment. DNA and RNA sequencing and analyses From 81/99 (81%) baseline patient samples declared to be sufficient fresh frozen pretreatment tumor material (≥30% tumor cells on an H&E-stained cryostat frozen section) RNA and DNA were isolated. The RNA and DNA were simultaneously isolated with the AllPrep DNA/RNA/miRNA Universal isolation kit (Qiagen, 80224) using the QIAcube. Furthermore, germline DNA was isolated from peripheral blood mononuclear cells using AllPrep DNA/RNA/miRNA Universal isolation kit (Qiagen, 80224) to be able to filter out single-nucleotide polymorphisms when determining TMB. In total, baseline biopsy material of n =80 samples for RNA-sequencing and n =75 samples for DNA-sequencing were available for analysis. For OpACIN-neo, a detailed description of the tissue processing and analysis of the RNA and DNA sequencing has been described in detail elsewhere 16 . Messenger RNA (mRNA) sequencing and whole-exome sequencing of the PRADO samples were performed by CeGaT. Initial sample quality control was performed with Qubit dsNDA BR or HS(Thermo Fisher) for the DNA sequencing data and Qubit RNA (Thermo Fisher) & Bioanalyzer RNA (Agilent) for the RNA sequencing . Strand-specific libraries were generated using the TruSeq Stranded mRNA sample preparation kit (Illumina) and sequenced with 2x 100bp reads on the NovaSeq 6000 system. Demultiplexing of the sequencing reads was performed with Illumina bcl2fastq (2.20). Adapters were trimmed with Skewer (version 0.2.2) 36 . The quality of FASTQ files was analyzed with FastQC (version 0.11.5-cegat). FASTQ files were mapped to the human reference genome (GRCh38.v82) using STAR (version 2.7.3a) with default settings 37 . Raw count data generated with HTseq-count (version 0.12.4) 38 were normalized for sequencing depth and RNA composition using the median of ratio’s method implemented in DESeq2 (version 1.40.1) 39 and log2-transformed. For the downstream analysis the data were analyzed using R (version 4.3.0). Log2-transformed normalized gene expression data was gene-wise median centered by subtracting each element of a row with the median of that row to improve Pearson’s correlation distances. The IFNg signature score was determined by calculating the average expression z-score of the 10 genes that compose the IFNg signature (STAT1, CXCL9, CXCL10, HLA-DRA, GZMA, PRF1, IDO1, CXCL11, CCR5, IFNG) 35 . Due to the batch-effect between the RNA-sequencing data from PRADO and OpACIN-neo separate cutoffs were determined. The optimal cutoff for the PRADO cohort was calculated by the maximize-metric function of cutpointr (version 1.1.2), using major pathologic response (MPR) status as the binary outcome. For OpACIN-neo the previously calculated cutoff for IFNg was used in this manuscript 16 . Exome libraries were generated using 50ng with the Twist Human Core Exome Plus (Twist Biosciences). The libraries were sequenced with 2 x 100-bp reads on a NovaSeq 6000 System according to the manufacturer’s protocols, with a sequence quality Q30 value of 90%. Data were analyzed in CeGaT exome analysis pipeline. Briefly, de-multiplexing of the sequencing reads was performed with Illumina bcl2fastq (version 2.20). The quality of FASTQ files was analyzed with FastQC (version 0.11.5-cegat) and multiQC (version 1.12) 40 . We used the nf-core/sarek pipeline v3.5.1 41 to analyze tumor and normal FASTQ files for the identification of Single Nucleotide Polymorphisms (SNPs) and small insertions and deletions (INDELs). The whole exome sequencing data were first preprocessed using FASTP. Subsequent alignment of the reads to the human reference genome (GRCh38) was performed using Burrows-Wheeler Aligner (BWA-MEM). Duplicate reads were marked, and base quality scores recalibrated using GATK MarkDuplicates, GATK BaseRecalibrator, and GATK ApplyBQSR. SNPs and small INDELs were called using MuTect2, and variants were annotated with Ensembl VEP. For further details, including the specific versions of each tool, we refer to the Sarek documentation. Using the VEP-annotated VCF files, we calculated the Tumor Mutational Burden (TMB) with cyvcf2 (version 0.31.1) in Python (version 3.12.5). Variants were filtered to include only those that passed the MuTect2 call, and having a Variant Allele Frequency of at least 0.05 (5% variant read depth). The TMB was calculated by summarizing the total number of non-synonymous mutations in the filtered VCF per patient. Mutations ≤ 2 were excluded from the analysis. The optimal TMB cut-off was identified with the maximize_metric method in cutpointr (v 1.1.2), using major pathologic response (MPR) status as the binary outcome. The TMB of the PRADO and OpACIN-neo samples by using this pipeline and the optimal TMB cut-off calculated based on the patients treated in OpACIN-neo arm B and PRADO, as they were treated with the same neoadjuvant regimen (neoadjuvant ipilimumab 1 mg kg -1 plus nivolumab 3 mg kg -1 ). Anti-PDL1 FFPE blocks of baseline tumor samples were used for PD-L1 immunohistochemistry staining using the BenchMark Ultra autostainer (Ventana Medical Systems). Briefly, paraffin sections were cut at 3 µm, heated at 75°C for 28 minutes and deparaffinized in the instrument with EZ prep solution (Ventana Medical Systems). Heat-induced antigen retrieval was carried out using Cell Conditioning 1 (CC1, Ventana Medical Systems) for 48 minutes at 95°C. Anti-PD-L1 mAb (clone 22C3, DAKO) was used in an 1:40 dilution for PD-L1 staining. Bound antibody was visualized using the OptiView DAB Detection Kit (Ventana Medical Systems). Slides were counterstained with Hematoxylin II and Bluing Reagent (Ventana Medical Systems). After staining slides were scanned with the P1000 (Sysmex) system. An experienced pathologist who was blinded to clinical outcome determined the tumor proportion score (TPS; the percentage of tumor cells with c­­­omplete or partial membranous staining at any intensity out of all tumor cells) using Slide Score ( www.slidescore.com ). The TPS was classified as being 50% or not evaluable (due to pigmentation or little to no tumor cells). Statistical analyses Differences in patient characteristics were assessed using Mann-Whitney’s test and Fisher’s exact test. Patients with an event before surgery were excluded from RFS and DMFS analysis (Extended Data Fig. 10) . Associations between baseline parameters and survival endpoints were estimated using univariable and multivariable Cox regression models. Pathologic response was measured post-baseline and hence not considered for OS analyses. Immune related adverse events, use of prednisolone and second line immunosuppressants were modelled as time-dependent covariates. Patients from the biospecimen cohort were included for survival-analysis of the different biomarker subgroups (EFS, RFS, DMFS, OS and MSS). One patient that did not undergo surgery ( n =1) was excluded from the subgroup-analysis of patients with RNA-sequencing data, DNA-sequencing data, PD-L1 expression and pathologic response available. A detailed overview is demonstrated in Extended Data Fig. 10. Spearman’s correlation coefficient was estimated for pairs of biomarkers. The reverse Kaplan-Meier method was used for estimating median follow-up time. The Kaplan-Meier method was used to generate EFS, RFS, DMFS, OS and MSS curves and to calculate the 5-year landmark survival estimates for the clinical cohort, also stratified by pathologic response and biomarker values. Overall comparisons in survival outcomes across the subgroups were tested using the log-rank test. Univariable Cox regression analyses were performed in forest plots, and relevant characteristics were further analyzed with multivariable Cox regression. Proportionality of hazards was assessed using Schoenfeld residual plots. Imputation of missing data by best- and worst-case scenarios was performed as sensitivity analysis, as well as using multivariate imputation by chained equations. No adjustments for multiplicity were performed. Statistical analyses were performed using R software (version 4.2.2). Declarations Data availability RNA-sequencing and DNA-sequencing data generated during the study will be deposited in the European Genome-phenome Archive (EGA) for PRADO under the accession codes EGAS50000000268 (DNA) or EGAS00001007601 (RNA). For OpACIN-neo under the accession codes EGAS00001004832 (DNA) or EGAS00001004833 (RNA). To minimize the risk of patient re-identification, de-identified individual patient-level clinical data are available under restricted access. Upon scientifically sound request, data access can be obtained via the NKI’s scientific repository at [email protected] , which will contact the corresponding author (C.U.B.). Data requests will be reviewed by the institutional review board of the NKI and will require the requesting researcher to sign a data access agreement with the NKI. Funding Acknowledgement We would like to thank the patients and their families for participating in these trials. The authors gratefully acknowledge the support of all colleagues from Melanoma Institute Australia, Royal Prince Alfred Hospital, Royal North Shore and Mater Hospital, University Medical Center Utrecht, Erasmus Medical Center, Leiden University Medical Center, University Medical Center Groningen and the Netherlands Cancer Institute; B. Schermers from Sirius Medical for providing magnetic seeds and a magnetic seed detector; S. Vanhoutvin for financial management; M.J. Gregorio, K. de Joode, A.M. van Eggermond, E.H.J. Tonk and J. Kingma-Veenstra for administrative support and data management; and A Evans and B Stegenga from Bristol Myers Squibb for scientific input and long-term support of our neoadjuvant immunotherapy efforts. A.M.M. is supported by an NHRMC Investigator Grant. R.P.M.S. is supported by Melanoma Institute Australia. R.A.S. is supported by a National Health and Medical Research Council of Australia (NHMRC) Investigator Grant (2022/GNT2018514). G.V.L. is supported by an NHMRC Investigator Grant and the University of Sydney Medical Foundation. Financial support for the study was provided by Bristol-Myers Squibb. Author contributions C.U.B. designed the trial and had written the protocol. The final amendment of the PRADO extension was written by E.A.R. together with C.U.B. in 20th Workshop on ‘Methods in Clinical Cancer Research’ (Zeist, Netherlands). A.C.J.v.A. and G.V.L. reviewed the trial protocol. I.L.M.R., A.M.M., R.P.M.S., J.M.V., W.v.H., E.A.R., E.K., A.A.M.v.d.V., K.P.M.S., H.E., G.A.P.H., J.A.v.d.H., D.J.G., A.J.W., J.M.L., W.M.C.K., C.Z., A.Bruining, A.A.M., T.E.P., K.F.S., S.Chong, A.S., J.B.A.G.H., A.v.A., G.V.L., and C.U.B. have included and treated patients, and collected clinical data. A.T.A., L.G.G.-O. and A.v.d.W. contributed to central and local data management. M.G. was a clinical project manager of the trial. S.Cornelissen performed DNA and RNA isolations. A.Broeks coordinated and contributed to translational laboratory logistics and immunohistochemistry and molecular laboratory work. P.D. and J.R. performed the bioinformatics analysis. A.J.C., R.V.R., R.A.S. and B.v.d.W. reviewed and scored the pathology of all cases. L.L.H. and M.Y.L. performed the statistical analyses. L.L.H. and C.U.B. wrote the first draft of the manuscript. All authors interpreted the data, reviewed the manuscript and approved the final version. Declaration of Interest No author has received financial support for the work on this manuscript, and no medical writer was involved at any stage of the preparation of this manuscript. A.M.M. has served on advisory boards for BMS, MSD, Novartis, Roche, Pierre-Fabre and QBiotics. R.P.M.S. has received honoraria for advisory board participation from MSD and Clinical Laboratories Pty Ltd. W.J.v.H. has received speakers honorarium regeneron, Sanofi, MSD, Belpharma, novartis, reports an advisory role Belpharma and has received a research grant from Amgen. E.K.A. has consultancy/advisory relationships with Delcath, Immunocore, and Lilly, and has received research grants unrelated to this paper from Bristol Myers Squibb, Delcath, Novartis, and Pierre-Fabre. These grants are unrelated to current work and are paid to the institute. A.A.M.v.d.V., received travel fees from Ipsen and consultancies fees (all paid to the institute) from BMS, MSD, Ipsen, Eisai, Pfizer, Novartis, Sanofi, Roche and Pierre Fabre. K.P.M.S. has consultancy/advisory relationships with Abbvie, Sairopa, has received research funding TigaTx, Bristol Myers Squibb, Philips, Genmab, Pierre Fabre, and has received honoraria from Bristol Myers Squibb (all paid to the institute). H.E. has received institutional research grants from SkyLineDx, BMS, Novartis and Pierre Fabre, speaker honorarium from Janssen, not personal speaker honorarium but to the hospital from BMS and Novartis, and served as expert board for Pierre Fabre and BMS. G.A.P.H consultancy/advisory relationships with Amgen, Bristol-Myers Squibb, Roche, MSD, Novartis, Sanofi, Pierre Fabre and has received research grants from Bristol-Myers Squibb, Seerave (all paid to the institute). S. Ch’ngreceives fees for professional services provided to MSD and SkylineDx. J.B.A.G.H. reports an advisory role for Achilles Therapeutics, AstraZeneca, BioNTech, Bristol-Myers Squibb, Immunocore, Instil Bio, Iovance Biotherapeutics, Ipsen, Molecular Partners, MSD Oncology, Neogene Therapeutics, Novartis, Roche/Genentech, Sanofi, Sāstra, Third Rock Ventures and T-Knife; has received research funding, paid to the institute, from Amgen, Asher Biotherapeutics, BioNTech, Bristol-Myers Squibb, MSD, Neon Therapeutics, Novartis; and is stockowner of Neogene Therapeutics and Sāstra. R.V.R. has received honoraria from Merck Sharp & Dohme. R.A.S. has received fees for professional services from SkylineDx BV, IO Biotech ApS, MetaOptima Technology Inc., F. Hoffmann-La Roche Ltd, Evaxion, Provectus Biopharmaceuticals Australia, Qbiotics, Novartis, Merck Sharp & Dohme, NeraCare, AMGEN Inc., Bristol-Myers Squibb, Myriad Genetics, GlaxoSmithKline. A.C.J.v.A. reports an advisory role in Amgen, Bristol-Myers Squibb, Daiichi Sankyo, Genmab, Menarini Silicon Biosystems, Merck Serono-Pfizer, MSD Merck, Neracare, Novartis, Pierre Fabre, Provectus, Replimune, Sanofi, Sirius Medical, SkylineDx, 4SC; has received research funding from Amgen, Merck Serono – Pfizer, SkylineDx. G.V.L. is consultant advisor for Agenus, Amgen, Array Biopharma, AstraZeneca, Bayer HealthCare Pharmaceuticals Inc, BioNTech SE, Boehringer Ingelheim International GmbH, Bristol Myers Squibb, Evaxion Biotech A/S, Fortiva Biologics (USA) Inc, GI Innovation Inc, Hexal AG (Sandoz Company), Highlight Therapeutics S.L., IOBiotech, Immunocore Ireland Limited, Innovent Biologics USA Inc, Iovance Biotherapeutics Inc, Merck Sharpe & Dohme, Novartis Pharma AG, OncoSec Medical Australia, PHMR Limited, Pierre Fabre, Regeneron Pharmaceuticals, Scancell Limited, SkylineDX BV. C.U.B.reports he has received compensation for advisory roles from BMS, MSD, Roche, Novartis, GSK, AZ, Pfizer, Lilly, GenMab, Pierre Fabre, Third Rock Ventures, Senya, received research funding from BMS, Novartis, NanoString, 4SC and reports to be co-founder of Immagene BV. All compensations and funding for C.U.B. were paid to the institute, except for Third Rock Ventures and Immagene. The other authors declare no conflicts of interest. References Blank, C.U. , et al. Neoadjuvant Nivolumab and Ipilimumab in Resectable Stage III Melanoma. The New England journal of medicine (2024). Patel, S.P. , et al. Neoadjuvant-Adjuvant or Adjuvant-Only Pembrolizumab in Advanced Melanoma. The New England journal of medicine 388 , 813-823 (2023). Forde, P.M. , et al. Neoadjuvant PD-1 Blockade in Resectable Lung Cancer. The New England journal of medicine (2018). Vos, J.L. , et al. Neoadjuvant immunotherapy with nivolumab and ipilimumab induces major pathological responses in patients with head and neck squamous cell carcinoma. Nature communications 12 , 7348 (2021). Chalabi, M. , et al. Neoadjuvant immunotherapy leads to pathological responses in MMR-proficient and MMR-deficient early-stage colon cancers. Nature medicine 26 , 566-576 (2020). van Dijk, N. , et al. Preoperative ipilimumab plus nivolumab in locoregionally advanced urothelial cancer: the NABUCCO trial. Nature medicine 26 , 1839-1844 (2020). Cascone, T. , et al. Neoadjuvant chemotherapy plus nivolumab with or without ipilimumab in operable non-small cell lung cancer: the phase 2 platform NEOSTAR trial. Nature medicine 29 , 593-604 (2023). Schmid, P. , et al. Pembrolizumab for Early Triple-Negative Breast Cancer. The New England journal of medicine 382 , 810-821 (2020). Liu, J. , et al. Improved Efficacy of Neoadjuvant Compared to Adjuvant Immunotherapy to Eradicate Metastatic Disease. Cancer discovery 6 , 1382-1399 (2016). Blank, C.U. , et al. Neoadjuvant versus adjuvant ipilimumab plus nivolumab in macroscopic stage III melanoma. Nature medicine 24 , 1655-1661 (2018). Huang, A.C. , et al. A single dose of neoadjuvant PD-1 blockade predicts clinical outcomes in resectable melanoma. Nature medicine 25 , 454-461 (2019). Amaria, R.N. , et al. Neoadjuvant immune checkpoint blockade in high-risk resectable melanoma. Nature medicine 24 , 1649-1654 (2018). Rozeman, E.A. , et al. Identification of the optimal combination dosing schedule of neoadjuvant ipilimumab plus nivolumab in macroscopic stage III melanoma (OpACIN-neo): a multicentre, phase 2, randomised, controlled trial. The lancet oncology 20 , 948-960 (2019). Lucas, M.W. , et al. LBA42 Distant metastasis-free survival of neoadjuvant nivolumab plus ipilimumab versus adjuvant nivolumab in resectable, macroscopic stage III melanoma: The NADINA trial. Annals of Oncology 35 , S1233-S1234 (2024). Cristescu, R. , et al. Pan-tumor genomic biomarkers for PD-1 checkpoint blockade-based immunotherapy. Science (New York, N.Y.) 362 , eaar3593 (2018). Rozeman, E.A. , et al. Survival and biomarker analyses from the OpACIN-neo and OpACIN neoadjuvant immunotherapy trials in stage III melanoma. Nature medicine 27 , 256-263 (2021). Menzies, A.M. , et al. Pathological response and survival with neoadjuvant therapy in melanoma: a pooled analysis from the International Neoadjuvant Melanoma Consortium (INMC). 37 , 9503-9503 (2019). Reijers, I.L.M. , et al. Impact of personalized response-directed surgery and adjuvant therapy on survival after neoadjuvant immunotherapy in stage III melanoma: Comparison of 3-year data from PRADO and OpACIN-neo. Eur J Cancer 214 , 115141 (2025). Versluis, J.M. , et al. Survival update of neoadjuvant ipilimumab plus nivolumab in macroscopic stage III melanoma in the OpACIN and OpACIN-neo trials. Ann Oncol 34 , 420-430 (2023). Reijers, I.L.M. , et al. Representativeness of the Index Lymph Node for Total Nodal Basin in Pathologic Response Assessment After Neoadjuvant Checkpoint Inhibitor Therapy in Patients With Stage III Melanoma. JAMA Surg 157 , 335-342 (2022). Schermers, B. , et al. Surgical removal of the index node marked using magnetic seed localization to assess response to neoadjuvant immunotherapy in patients with stage III melanoma. The British journal of surgery 106 , 519-522 (2019). Reijers, I.L.M. , et al. Personalized response-directed surgery and adjuvant therapy after neoadjuvant ipilimumab and nivolumab in high-risk stage III melanoma: the PRADO trial. Nature medicine 28 , 1178-1188 (2022). Long, G.V. , et al. LBA41 Long-term survival with neoadjuvant therapy in melanoma: Updated pooled analysis from the International Neoadjuvant Melanoma Consortium (INMC). Annals of Oncology 35 , S1232 (2024). Tetzlaff, M.T. , et al. Pathological assessment of resection specimens after neoadjuvant therapy for metastatic melanoma. Ann Oncol 29 , 1861-1868 (2018). Menzies, A.M. , et al. Pathological response and survival with neoadjuvant therapy in melanoma: a pooled analysis from the International Neoadjuvant Melanoma Consortium (INMC). Nature medicine 27 , 301-309 (2021). Wolchok, J.D. , et al. Final, 10-Year Outcomes with Nivolumab plus Ipilimumab in Advanced Melanoma. New England Journal of Medicine 392 , 11-22 (2025). Ascierto, P.A. , et al. Ipilimumab 10 mg/kg versus ipilimumab 3 mg/kg in patients with unresectable or metastatic melanoma: a randomised, double-blind, multicentre, phase 3 trial. The lancet oncology 18 , 611-622 (2017). Angka, L. , et al. Natural Killer Cell IFNγ Secretion is Profoundly Suppressed Following Colorectal Cancer Surgery. Annals of surgical oncology 25 , 3747-3754 (2018). Leaver, H.A., Craig, S.R., Yap, P.L. & Walker, W.S. Lymphocyte responses following open and minimally invasive thoracic surgery. Eur J Clin Invest 30 , 230-238 (2000). van Not, O.J. , et al. Association of Immune-Related Adverse Event Management With Survival in Patients With Advanced Melanoma. JAMA Oncol 8 , 1794-1801 (2022). Verheijden, R.J. , et al. Corticosteroids for Immune-Related Adverse Events and Checkpoint Inhibitor Efficacy: Analysis of Six Clinical Trials. J Clin Oncol 42 , 3713-3724 (2024). Verheijden, R.J. , et al. Corticosteroids and other immunosuppressants for immune-related adverse events and checkpoint inhibitor effectiveness in melanoma. Eur J Cancer 207 , 114172 (2024). Not, O.J.v. , et al. BRAF and NRAS Mutation Status and Response to Checkpoint Inhibition in Advanced Melanoma. JCO Precision Oncology , e2200018 (2022). Reijers, I.L.M. , et al. IFN-gamma signature enables selection of neoadjuvant treatment in patients with stage III melanoma. J Exp Med 220 (2023). Ayers, M. , et al. IFN-gamma-related mRNA profile predicts clinical response to PD-1 blockade. The Journal of clinical investigation 127 , 2930-2940 (2017). Jiang, H., Lei, R., Ding, S.W. & Zhu, S. Skewer: a fast and accurate adapter trimmer for next-generation sequencing paired-end reads. BMC Bioinformatics 15 , 182 (2014). Dobin, A. , et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29 , 15-21 (2013). Putri, G.H., Anders, S., Pyl, P.T., Pimanda, J.E. & Zanini, F. Analysing high-throughput sequencing data in Python with HTSeq 2.0. Bioinformatics 38 , 2943-2945 (2022). Love, M.I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome biology 15 , 550 (2014). Ewels, P., Magnusson, M., Lundin, S. & Käller, M. MultiQC: summarize analysis results for multiple tools and samples in a single report. Bioinformatics 32 , 3047-3048 (2016). Hanssen, F. , et al. Scalable and efficient DNA sequencing analysis on different compute infrastructures aiding variant discovery. NAR Genom Bioinform 6 , lqae031 (2024). Table Table 1. Characteristics for patients with or without recurrence observed at 5 years follow-up All ( n =99) Recurrence ( n =27) No Recurrence* ( n =72) Baseline characteristics Continent (%) Europe Australia 65 (66) 34 (34) 20 (74) 7 (26) 45 (63) 27 (38) Age (median (IQR)) 58.0 [51.0- 69.5] 54.0 [51.0, 69.5] 60.0 [52.0, 69.3] Sex (%) Men Women 65 (66) 34 (34) 16 (59) 11 (41) 49 (68) 23 (32) T-stage (%) T1-2 T3-4 Tx MUP 43 (43) 41 (41) 2 (2) 13 (13) 12 (44) 11 (41) 2 (7) 2 (7) 31 (43) 30 (42) 0 (0) 11 (15) Ulceration (%) No Yes Unknown 58 (72) 23 (28) 18 14 (64) 8 (36) 5 44 (75) 15 (25) 13 BRAF- mutation (%) Wildtype V600E/K mutant Unknown 52 (54) 45 (46) 2 8 (30) 19 (70) 0 44 (63) 26 (37) 2 Location of the lymph node (%) Neck Axilla Groin 24 (24) 39 (39) 36 (36) 4 (14) 9 (33) 14 (52) 20 (28) 30 (42) 22 (31) Number of positive lymph nodes on PET-CT (%) 1 >1-3 >3 57 (58) 33 (33) 9 (9) 15 (56) 9 (33) 3 (11) 42 (58) 24 (33) 6 (8) Sum of diameter target lesions, mm (median, IQR) 25.0 [18.0, 33.0] 26.0 [19.0, 31.5] 23.5 [18.0, 34.0] LDH (median [IQR]) 186.0 [163.0, 215.5] 192.0 [172.5, 206.5] 184.0 [161.5, 216.0] Response Pathologic response *(%) MPR pPR pNR Distant metastasis Not evaluable 60 (61) 11 (11) 21 (21) 6 (6) 1 (1) 6 (22) 5 (19) 10 (37) 6 (22) 0 (0) 54 (75) 6 (8) 11 (15) 0 (0) 1 (1) Toxicity Grade ≥3 irAE(%) 30 (30) 9 (31) 21 (30) Prednisone (%) 50 (51) 16 (55) 34 (49) Second line immunosuppressives (%) 11 (11) 4 (14) 7 (10) Subsequent surgery/therapy ILN (%) 94 (95) 24 (89) 70 (97) TLND (%) 33 (33) 16 (59) 17 (24) Adjuvant (%) Nivolumab BRAF + MEK inhibitors 7 (7) 10 (10) 3 (11) 5 (19) 4 (6) 5 (7) Radiotherapy (%) 8 (8) 5 (19) 3 (4) Biomarkers IFN g signature score (mean (SD)) 0.37 [-7.28, 7.65] -1.84 [-9.75, 0.37] 2.08 [-4.17, 9.16] IFN g (%) L ow H igh unknown 41 (51) 39 (49) 19 19 (76) 6 (24) 2 22 (40) 33 (60) 17 Number of nonsynomous mutations (mut/mb; median [IQR]) 9.12 [5.61, 17.73] 8.50 [4.56, 12.31] 10.73 [6.80, 22.26] TMB labels (%) Low H igh unknown 43 (57) 32 (43) 23 19 (70) 8 (30) 2 24 (50) 24 (50) 21 PDL1 (%) <1% ≥1%-<50% ≥ 50% unknown 43 (57) 26 (34) 7 (9) 23 17 (85) 3 (15) 0 (0) 7 26 (46) 23 (41) 7 (13) 16 PDL1 (%) <1% ≥1% unknown 43 (57) 33 (43) 23 17 (85) 3 (15) 7 26 (46) 30 (54) 16 Data are median (IQR) or n (%). Percentages may not sum up to 100 because of rounding. Percentages are derived of the patients per column with known parameters. *The patients that died from non-melanoma related cause, were included in the group of patients with “no recurrence” since these patients did not have any signs of recurrence before death. IQR, interquartile range; MUP, melanoma of unknown primary; LDH, Lactate dehydrogenase; ILN, index lymph node; TLND, therapeutic lymph node dissection; MPR, major pathologic response; pPR, pathologic partial response; pNR, pathologic non-response; irAE, immune related adverse events; IFNg, interferon gamma gene signature; TMB, tumor mutational burden; PD-L1, Programmed Cell Death Ligand 1; Additional Declarations Yes there is potential Competing Interest. No author has received financial support for the work on this manuscript, and no medical writer was involved at any stage of the preparation of this manuscript. A.M.M. has served on advisory boards for BMS, MSD, Novartis, Roche, Pierre-Fabre and QBiotics. R.P.M.S. has received honoraria for advisory board participation from MSD and Clinical Laboratories Pty Ltd. W.J.v.H. has received speakers honorarium regeneron, Sanofi, MSD, Belpharma, novartis, reports an advisory role Belpharma and has received a research grant from Amgen. E.K.A. has consultancy/advisory relationships with Delcath, Immunocore, and Lilly, and has received research grants unrelated to this paper from Bristol Myers Squibb, Delcath, Novartis, and Pierre-Fabre. These grants are unrelated to current work and are paid to the institute. A.A.M.v.d.V., received travel fees from Ipsen and consultancies fees (all paid to the institute) from BMS, MSD, Ipsen, Eisai, Pfizer, Novartis, Sanofi, Roche and Pierre Fabre. K.P.M.S. has consultancy/advisory relationships with Abbvie, Sairopa, has received research funding TigaTx, Bristol Myers Squibb, Philips, Genmab, Pierre Fabre, and has received honoraria from Bristol Myers Squibb (all paid to the institute). H.E. has received institutional research grants from SkyLineDx, BMS, Novartis and Pierre Fabre, speaker honorarium from Janssen, not personal speaker honorarium but to the hospital from BMS and Novartis, and served as expert board for Pierre Fabre and BMS. G.A.P.H consultancy/advisory relationships with Amgen, Bristol-Myers Squibb, Roche, MSD, Novartis, Sanofi, Pierre Fabre and has received research grants from Bristol-Myers Squibb, Seerave (all paid to the institute). S. Ch’ng receives fees for professional services provided to MSD and SkylineDx. J.B.A.G.H. reports an advisory role for Achilles Therapeutics, AstraZeneca, BioNTech, Bristol-Myers Squibb, Immunocore, Instil Bio, Iovance Biotherapeutics, Ipsen, Molecular Partners, MSD Oncology, Neogene Therapeutics, Novartis, Roche/Genentech, Sanofi, Sāstra, Third Rock Ventures and T-Knife; has received research funding, paid to the institute, from Amgen, Asher Biotherapeutics, BioNTech, Bristol-Myers Squibb, MSD, Neon Therapeutics, Novartis; and is stockowner of Neogene Therapeutics and Sāstra. R.V.R. has received honoraria from Merck Sharp & Dohme. R.A.S. has received fees for professional services from SkylineDx BV, IO Biotech ApS, MetaOptima Technology Inc., F. Hoffmann-La Roche Ltd, Evaxion, Provectus Biopharmaceuticals Australia, Qbiotics, Novartis, Merck Sharp & Dohme, NeraCare, AMGEN Inc., Bristol-Myers Squibb, Myriad Genetics, GlaxoSmithKline. A.C.J.v.A. reports an advisory role in Amgen, Bristol-Myers Squibb, Daiichi Sankyo, Genmab, Menarini Silicon Biosystems, Merck Serono-Pfizer, MSD Merck, Neracare, Novartis, Pierre Fabre, Provectus, Replimune, Sanofi, Sirius Medical, SkylineDx, 4SC; has received research funding from Amgen, Merck Serono – Pfizer, SkylineDx. G.V.L. is consultant advisor for Agenus, Amgen, Array Biopharma, AstraZeneca, Bayer HealthCare Pharmaceuticals Inc, BioNTech SE, Boehringer Ingelheim International GmbH, Bristol Myers Squibb, Evaxion Biotech A/S, Fortiva Biologics (USA) Inc, GI Innovation Inc, Hexal AG (Sandoz Company), Highlight Therapeutics S.L., IOBiotech, Immunocore Ireland Limited, Innovent Biologics USA Inc, Iovance Biotherapeutics Inc, Merck Sharpe & Dohme, Novartis Pharma AG, OncoSec Medical Australia, PHMR Limited, Pierre Fabre, Regeneron Pharmaceuticals, Scancell Limited, SkylineDX BV. C.U.B. reports he has received compensation for advisory roles from BMS, MSD, Roche, Novartis, GSK, AZ, Pfizer, Lilly, GenMab, Pierre Fabre, Third Rock Ventures, Senya, received research funding from BMS, Novartis, NanoString, 4SC and reports to be co-founder of Immagene BV. All compensations and funding for C.U.B. were paid to the institute, except for Third Rock Ventures and Immagene. The other authors declare no conflicts of interest. Supplementary Files Extfig1toxPRADO0606.pdf Extended Figure 1: Overall toxicity and long-term toxicity of the PRADO trial Extfig2forestRFSPRADO1007.pdf Extended Figure 2: Forest Plot of Hazard Ratios for relapse free survival by baseline variables Extfig3forestOSPRADO1007.pdf Extended Figure 3: Forest Plot of Hazard Ratios for overall survival by baseline variables Extfig4survivalcurvesOPACINneo0707.pdf Extended Figure 4: 5-year survival analysis for validation-cohort OpACIN-neo Extfig5survivalcurvesOPACINneoperarm0707.pdf Extended Figure 4: 5-year survival analysis for validation-cohort OpACIN-neo per treatment arm Extfig6BRAFOPACINneo0707.pdf Extended Figure 6: 5-year survival analysis for validation-cohort OpACIN-neo of patients with or without BRAF mutation Extfig7biom1OPACINneo0707.pdf Extended Figure 7: Biomarker analysis of the interferon gamma gene signature (IFNγ), tumor mutational burden (TMB) and PD-L1 staining for conformation-cohort OpACIN-neo Extfig8biom2OPACINneo1007.pdf Extended Figure 8: Combination of biomarkers for conformation-cohort OpACIN-neo Extfig9biom3OPACINneo1007.pdf Extended Figure 9: Combination of IFNγ and PD-L1 for conformation-cohort OpACIN-neo Extfig10biospecimenPRADO0707.pdf Extended Figure 10: Biospecimen selection for survival- and biomarker-analysis 10072025HoeijmakeresetalSupplementaryappendix.docx Supplementary appendix Cite Share Download PDF Status: Published Journal Publication published 28 Jan, 2026 Read the published version in Nature Medicine → Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7090131","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":485184874,"identity":"07e8a343-664d-4858-97bc-5451c701ff92","order_by":0,"name":"Christian Blank","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAqklEQVRIie3LoQ7CMBDG8Vtq283OAK9QwguVkKxmSyYnb6aoeR5jjuHa1I7wDAuaB0CQwIJB3hzi/ubuEz8AjvvLZOIBzPpzEaCmEZjJ7kv0ArJHOQ8KyVB5/xwKe5YRRU0huU9N6MayunQtihOFaJDaK9dU/S1BIakkvFxj9SISlSuNvrZEksfUxJUrtv0YMJJIduzC9HCHjR7tdJcNgYD4+T0FcBzHcYTeIAc0YrItl7sAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0002-7945-5846","institution":"The Netherlands Cancer Institute","correspondingAuthor":true,"prefix":"","firstName":"Christian","middleName":"","lastName":"Blank","suffix":""},{"id":485184875,"identity":"9046ef4d-9317-4cad-b128-115607aaf5b2","order_by":1,"name":"Lotte Hoeijmakers","email":"","orcid":"https://orcid.org/0009-0003-8431-7557","institution":"Netherlands Cancer Institute","correspondingAuthor":false,"prefix":"","firstName":"Lotte","middleName":"","lastName":"Hoeijmakers","suffix":""},{"id":485184876,"identity":"649bd08a-f246-4cf8-9797-998306e54e87","order_by":2,"name":"Petros Dimitriadis","email":"","orcid":"https://orcid.org/0000-0002-3546-285X","institution":"Netherlands Cancer Institute","correspondingAuthor":false,"prefix":"","firstName":"Petros","middleName":"","lastName":"Dimitriadis","suffix":""},{"id":485184877,"identity":"b6ff3c53-d250-45cd-a75f-262c7170f1b3","order_by":3,"name":"Steven Wijnen","email":"","orcid":"https://orcid.org/0009-0009-9985-0753","institution":"Netherlands Cancer Institute","correspondingAuthor":false,"prefix":"","firstName":"Steven","middleName":"","lastName":"Wijnen","suffix":""},{"id":485184878,"identity":"74709eb4-436a-444b-a531-1e5361bc4f56","order_by":4,"name":"Irene Reijers","email":"","orcid":"","institution":"Netherlands Cancer Institute","correspondingAuthor":false,"prefix":"","firstName":"Irene","middleName":"","lastName":"Reijers","suffix":""},{"id":485184879,"identity":"8c260934-c49e-4971-8d46-872c8c0be9ad","order_by":5,"name":"Marta Lopez-Yurda","email":"","orcid":"https://orcid.org/0000-0003-3678-3222","institution":"Antoni van Leeuwenhoek Hospital","correspondingAuthor":false,"prefix":"","firstName":"Marta","middleName":"","lastName":"Lopez-Yurda","suffix":""},{"id":485184880,"identity":"1c704e34-412a-41dd-98c3-3bf58d3e7ce9","order_by":6,"name":"Alexander Menzies","email":"","orcid":"","institution":"Melanoma Institute Australia","correspondingAuthor":false,"prefix":"","firstName":"Alexander","middleName":"","lastName":"Menzies","suffix":""},{"id":485184881,"identity":"87a597b8-fc6d-40f1-841a-cbf4ac9fdc19","order_by":7,"name":"Annegien Broeks","email":"","orcid":"","institution":"Division of Molecular Pathology, The Netherlands Cancer Institute","correspondingAuthor":false,"prefix":"","firstName":"Annegien","middleName":"","lastName":"Broeks","suffix":""},{"id":485184882,"identity":"7cbfc9a7-0cbc-409d-b253-a7c7c81b474d","order_by":8,"name":"Sten Cornelissen","email":"","orcid":"","institution":"Netherlands Cancer Institute","correspondingAuthor":false,"prefix":"","firstName":"Sten","middleName":"","lastName":"Cornelissen","suffix":""},{"id":485184883,"identity":"6cd1618e-e2f4-4542-a01d-1376a688fa11","order_by":9,"name":"Alex Torres Acosta","email":"","orcid":"","institution":"Netherlands Cancer Institute","correspondingAuthor":false,"prefix":"","firstName":"Alex","middleName":"Torres","lastName":"Acosta","suffix":""},{"id":485184884,"identity":"bd2e1433-f72c-49ee-a16e-0a25ee4c37de","order_by":10,"name":"Anja van der Wal","email":"","orcid":"","institution":"Netherlands Cancer Institute","correspondingAuthor":false,"prefix":"","firstName":"Anja","middleName":"van der","lastName":"Wal","suffix":""},{"id":485184885,"identity":"b73ed176-d39d-4ca6-9475-e1cf22645061","order_by":11,"name":"Robyn Saw","email":"","orcid":"https://orcid.org/0000-0002-3354-806X","institution":"Melanoma Institute Australia","correspondingAuthor":false,"prefix":"","firstName":"Robyn","middleName":"","lastName":"Saw","suffix":""},{"id":485184886,"identity":"35419737-0ed5-45a0-bf3f-e888f2dd290d","order_by":12,"name":"Judith Versluis","email":"","orcid":"https://orcid.org/0000-0002-3423-9912","institution":"Netherlands Cancer Institute","correspondingAuthor":false,"prefix":"","firstName":"Judith","middleName":"","lastName":"Versluis","suffix":""},{"id":485184887,"identity":"4461e908-3b4e-4aef-a70f-b86fecd66986","order_by":13,"name":"Winan van Houdt","email":"","orcid":"","institution":"Antoni van Leeuwenhoek Hospital","correspondingAuthor":false,"prefix":"","firstName":"Winan","middleName":"van","lastName":"Houdt","suffix":""},{"id":485184888,"identity":"456a0c24-11a4-463c-801a-e1d594171446","order_by":14,"name":"Michel Wouters","email":"","orcid":"https://orcid.org/0000-0001-6173-0662","institution":"Antoni van Leeuwenhoek Hospital","correspondingAuthor":false,"prefix":"","firstName":"Michel","middleName":"","lastName":"Wouters","suffix":""},{"id":485184889,"identity":"0d20b4d6-da1a-47e4-aa5f-89584fb51010","order_by":15,"name":"Jurriaan Romano","email":"","orcid":"","institution":"Netherlands Cancer Institute","correspondingAuthor":false,"prefix":"","firstName":"Jurriaan","middleName":"","lastName":"Romano","suffix":""},{"id":485184890,"identity":"0f398ffd-c651-451f-a460-20d0de123b0e","order_by":16,"name":"Eliza Rozeman","email":"","orcid":"","institution":"Netherlands Cancer Institute","correspondingAuthor":false,"prefix":"","firstName":"Eliza","middleName":"","lastName":"Rozeman","suffix":""},{"id":485184891,"identity":"1dee6bd9-aba9-4405-bfb7-46035a03143b","order_by":17,"name":"Lindsay Grijpink-Ongering","email":"","orcid":"","institution":"Department of Biometrics, The Netherlands Cancer Institute","correspondingAuthor":false,"prefix":"","firstName":"Lindsay","middleName":"","lastName":"Grijpink-Ongering","suffix":""},{"id":485184892,"identity":"a18dad72-b53f-4e3e-aaff-b683ba56fa3e","order_by":18,"name":"Ellen Kapiteijn","email":"","orcid":"https://orcid.org/0000-0002-4814-6426","institution":"Leiden University Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Ellen","middleName":"","lastName":"Kapiteijn","suffix":""},{"id":485184893,"identity":"6dce3f54-886c-488f-b943-74f938337837","order_by":19,"name":"Astrid Van der Veldt","email":"","orcid":"","institution":"Erasmus Medical Center-Cancer Institute","correspondingAuthor":false,"prefix":"","firstName":"Astrid","middleName":"Van der","lastName":"Veldt","suffix":""},{"id":485184894,"identity":"ef9954e9-b329-4a9e-90d2-791afd56cf49","order_by":20,"name":"Karijn Suijkerbuijk","email":"","orcid":"https://orcid.org/0000-0003-3604-5430","institution":"University Medical Center Utrecht","correspondingAuthor":false,"prefix":"","firstName":"Karijn","middleName":"","lastName":"Suijkerbuijk","suffix":""},{"id":485184895,"identity":"b5ccd1ad-e939-415d-bdcc-f3294abc3532","order_by":21,"name":"Hanna Eriksson","email":"","orcid":"","institution":"Karolinska Institute","correspondingAuthor":false,"prefix":"","firstName":"Hanna","middleName":"","lastName":"Eriksson","suffix":""},{"id":485184896,"identity":"19a0b45c-feb7-44dc-bde9-2b40701e1f5c","order_by":22,"name":"Geke Hospers","email":"","orcid":"https://orcid.org/0000-0002-3047-7892","institution":"University Medical Center Groningen","correspondingAuthor":false,"prefix":"","firstName":"Geke","middleName":"","lastName":"Hospers","suffix":""},{"id":485184897,"identity":"74e54cc6-ca7c-4753-a7aa-46428bd05776","order_by":23,"name":"Jos van der Hage","email":"","orcid":"https://orcid.org/0000-0001-9040-1323","institution":"Leiden University Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Jos","middleName":"van der","lastName":"Hage","suffix":""},{"id":485184898,"identity":"cd842f9b-f049-420e-b192-cb05c65dcd6e","order_by":24,"name":"Dirk Grunhagen","email":"","orcid":"https://orcid.org/0000-0001-8293-6002","institution":"Erasmus MC-University Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Dirk","middleName":"","lastName":"Grunhagen","suffix":""},{"id":485184899,"identity":"91e973c5-259b-45b5-aa56-4d29e0ee0ae7","order_by":25,"name":"Arjen Witkamp","email":"","orcid":"","institution":"Department of Surgery, University Medical Center Utrecht","correspondingAuthor":false,"prefix":"","firstName":"Arjen","middleName":"","lastName":"Witkamp","suffix":""},{"id":485184900,"identity":"5e43f95b-e2f4-4317-9470-fd8d036c646a","order_by":26,"name":"Judith Lijnsvelt","email":"","orcid":"","institution":"The Netherlands Cancer Institute","correspondingAuthor":false,"prefix":"","firstName":"Judith","middleName":"","lastName":"Lijnsvelt","suffix":""},{"id":485184901,"identity":"374fb16f-609b-4eb6-be9d-bb989e7f6461","order_by":27,"name":"Willem Klop","email":"","orcid":"","institution":"Netherlands Cancer Institute","correspondingAuthor":false,"prefix":"","firstName":"Willem","middleName":"","lastName":"Klop","suffix":""},{"id":485184902,"identity":"478c66cb-6f54-4e9d-a674-fe1f70f009b3","order_by":28,"name":"Charlotte Zuur","email":"","orcid":"https://orcid.org/0000-0002-1777-012X","institution":"The Netherlands Cancer Institute","correspondingAuthor":false,"prefix":"","firstName":"Charlotte","middleName":"","lastName":"Zuur","suffix":""},{"id":485184903,"identity":"eede4ad4-21a4-45ee-8146-3776d23a5525","order_by":29,"name":"Annemarie Bruining","email":"","orcid":"","institution":"Department of Radiology, The Netherlands Cancer Institute","correspondingAuthor":false,"prefix":"","firstName":"Annemarie","middleName":"","lastName":"Bruining","suffix":""},{"id":485184904,"identity":"d802e0a1-2420-4611-a44c-0c1284f2bb5b","order_by":30,"name":"Abrahim Al-Mamgani","email":"","orcid":"","institution":"The Netherlands Cancer Institute","correspondingAuthor":false,"prefix":"","firstName":"Abrahim","middleName":"","lastName":"Al-Mamgani","suffix":""},{"id":485184905,"identity":"99994500-2531-4079-b3eb-a12fd45af810","order_by":31,"name":"Thomas Pennington","email":"","orcid":"","institution":"Melanoma Institute Australia","correspondingAuthor":false,"prefix":"","firstName":"Thomas","middleName":"","lastName":"Pennington","suffix":""},{"id":485184906,"identity":"843470e3-da62-403d-a75d-8dac4730471b","order_by":32,"name":"Kerwin Shannon","email":"","orcid":"https://orcid.org/0000-0001-8538-3132","institution":"Melanoma Institute Australia, The University of Sydney, NSW","correspondingAuthor":false,"prefix":"","firstName":"Kerwin","middleName":"","lastName":"Shannon","suffix":""},{"id":485184907,"identity":"661c50b7-c478-49de-a4bc-4ff548ef7ada","order_by":33,"name":"Sydney Ch'ng","email":"","orcid":"https://orcid.org/0000-0002-4011-1253","institution":"Melanoma Institute Australia, The University of Sydney","correspondingAuthor":false,"prefix":"","firstName":"Sydney","middleName":"","lastName":"Ch'ng","suffix":""},{"id":485184908,"identity":"57dcfcb4-ae97-4bd3-adb8-6390ba5fdb4c","order_by":34,"name":"Andrew Colebatch","email":"","orcid":"","institution":"Melanoma Institute Australia","correspondingAuthor":false,"prefix":"","firstName":"Andrew","middleName":"","lastName":"Colebatch","suffix":""},{"id":485184909,"identity":"c445d56a-13ac-4937-94d3-6f09079f4b52","order_by":35,"name":"Maria Gonzalez","email":"","orcid":"https://orcid.org/0000-0002-2197-6657","institution":"Melanoma Institute Australia","correspondingAuthor":false,"prefix":"","firstName":"Maria","middleName":"","lastName":"Gonzalez","suffix":""},{"id":485184910,"identity":"652491b9-81f8-411b-8359-ec8162e4c7dc","order_by":36,"name":"Andrew Spillane","email":"","orcid":"https://orcid.org/0000-0002-9520-0181","institution":"Melanoma Institute Australia","correspondingAuthor":false,"prefix":"","firstName":"Andrew","middleName":"","lastName":"Spillane","suffix":""},{"id":485184911,"identity":"cf28968e-5835-4db8-a2fc-41415a17bd20","order_by":37,"name":"John Haanen","email":"","orcid":"https://orcid.org/0000-0001-5884-7704","institution":"Netherlands Cancer Institute","correspondingAuthor":false,"prefix":"","firstName":"John","middleName":"","lastName":"Haanen","suffix":""},{"id":485184912,"identity":"14695276-91f0-4269-a346-23277573a8de","order_by":38,"name":"Robert Rawson","email":"","orcid":"","institution":"Royal Prince Alfred Hospital","correspondingAuthor":false,"prefix":"","firstName":"Robert","middleName":"","lastName":"Rawson","suffix":""},{"id":485184913,"identity":"8122946f-c45b-490a-924c-abac8afb3705","order_by":39,"name":"Richard Scolyer","email":"","orcid":"https://orcid.org/0000-0002-8991-0013","institution":"Melanoma Institute Australia, The University of Sydney","correspondingAuthor":false,"prefix":"","firstName":"Richard","middleName":"","lastName":"Scolyer","suffix":""},{"id":485184914,"identity":"36284fc2-54e0-44e6-a902-eda48ac62b3d","order_by":40,"name":"Bart Wiel","email":"","orcid":"","institution":"The Netherlands Cancer Institute","correspondingAuthor":false,"prefix":"","firstName":"Bart","middleName":"","lastName":"Wiel","suffix":""},{"id":485184915,"identity":"b1c98a17-426b-4911-b42e-fbbac010887f","order_by":41,"name":"Alexander van Akkooi","email":"","orcid":"https://orcid.org/0000-0002-3262-6935","institution":"Melanoma Institute Australia","correspondingAuthor":false,"prefix":"","firstName":"Alexander","middleName":"van","lastName":"Akkooi","suffix":""},{"id":485184916,"identity":"609387a8-63a6-416e-a26e-1ff22e7c03d0","order_by":42,"name":"Georgina Long","email":"","orcid":"https://orcid.org/0000-0001-8894-3545","institution":"Melanoma Institute Australia, The University of Sydney","correspondingAuthor":false,"prefix":"","firstName":"Georgina","middleName":"","lastName":"Long","suffix":""}],"badges":[],"createdAt":"2025-07-10 07:30:37","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7090131/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7090131/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41591-025-04158-9","type":"published","date":"2026-01-28T05:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":86773646,"identity":"25ca876c-a1f8-4534-ae79-b4fb235b78e2","added_by":"auto","created_at":"2025-07-15 12:17:52","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":75581,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003e5-year survival analysis for all patients and per pathologic response category\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Event free survival for all patients (\u003cem\u003en\u003c/em\u003e=99), (B) Relapse-free survival for all patients (\u003cem\u003en\u003c/em\u003e=92), (C) Distant metastases-free survival for all patients (\u003cem\u003en\u003c/em\u003e=92), (D) Overall survival for all patients (\u003cem\u003en\u003c/em\u003e=99), (E) Melanoma Specific survival for all patients (from registration to melanoma related death) (\u003cem\u003en\u003c/em\u003e=96), (F) Relapse-free survival per pathologic response category (\u003cem\u003en\u003c/em\u003e=92), \u0026nbsp;(G) Distant metastases-free survival per pathologic response category (\u003cem\u003en\u003c/em\u003e=92), (H) Melanoma Specific survival per pathologic response category (from surgery to melanoma related death) (\u003cem\u003en\u003c/em\u003e=89).\u003c/p\u003e\n\u003cp\u003eMPR, major pathologic response (green); pPR, pathologic partial response (orange); pNR, pathologic non-response (red).\u003c/p\u003e","description":"","filename":"Fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-7090131/v1/82a8e5b42fb152eb77a665cf.png"},{"id":86773644,"identity":"b7d498d7-b703-457c-b3aa-c3d88ca68a9a","added_by":"auto","created_at":"2025-07-15 12:17:52","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":54407,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003e5-year survival analysis of patients with or without \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eBRAF\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003emutation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA) Event free survival \u003cem\u003eBRAF\u003c/em\u003e-mutant (brown; \u003cem\u003en\u003c/em\u003e=45) versus \u003cem\u003eBRAF\u003c/em\u003e-wildtype (red; \u003cem\u003en\u003c/em\u003e=52), (B) Relapse-free survival \u003cem\u003eBRAF\u003c/em\u003e-mutant (brown; \u003cem\u003en\u003c/em\u003e=38) versus \u003cem\u003eBRAF\u003c/em\u003e-wildtype (red; \u003cem\u003en\u003c/em\u003e=52), (C) Distant metastases-free survival \u003cem\u003eBRAF\u003c/em\u003e-mutant (brown; \u003cem\u003en\u003c/em\u003e=38) versus \u003cem\u003eBRAF\u003c/em\u003e-wildtype (red; \u003cem\u003en\u003c/em\u003e=52), (D) Overall survival \u003cem\u003eBRAF\u003c/em\u003e-mutant (brown; \u003cem\u003en\u003c/em\u003e=45) versus \u003cem\u003eBRAF\u003c/em\u003e-wildtype (red; \u003cem\u003en\u003c/em\u003e=52).\u003c/p\u003e","description":"","filename":"Fig2.png","url":"https://assets-eu.researchsquare.com/files/rs-7090131/v1/a4a321ba4eaff40b5dad9b59.png"},{"id":86773645,"identity":"452600b3-75d2-4342-91d4-72fa4dc46a3f","added_by":"auto","created_at":"2025-07-15 12:17:52","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":61948,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eForest Plot of Hazard Ratios for distant metastasis free survival by baseline variables\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eForest plot of risk for distant metastasis calculated from surgery (\u003cem\u003en\u003c/em\u003e=92) using Cox-regression analysis expressed in hazard-ratios per variable, with a 95% confidence interval and \u003cem\u003ep\u003c/em\u003e-value compared to the reference variable.\u003c/p\u003e\n\u003cp\u003e* Time-dependent variable\u003c/p\u003e\n\u003cp\u003eEU, Europe; AUS, Australia; LN, lymph node; MPR, major pathologic response; pPR, pathologic partial response; pNR, pathologic non-response; irAE, immune related adverse events; IFNg, interferon gamma gene signature; TMB, tumor mutational burden; PD-L1, Programmed Cell Death Ligand 1; CI, confidence interval.\u003c/p\u003e","description":"","filename":"Fig3.png","url":"https://assets-eu.researchsquare.com/files/rs-7090131/v1/87dea0229ab493d0149576ee.png"},{"id":86774808,"identity":"a2fc0a32-c8e6-49c5-b7e3-c04f7a4fcbae","added_by":"auto","created_at":"2025-07-15 12:25:52","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":46830,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSwimmer plot of time to recurrence and subsequent therapies in patients who recurred (\u003c/strong\u003e\u003cem\u003e\u003cstrong\u003en\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e=27)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe time from registration to recurrence, distant metastasis and subsequent therapies are displayed from all patients with a recurrence.\u003c/p\u003e\n\u003cp\u003e*due to progressive disease before surgery\u003c/p\u003e\n\u003cp\u003eOther systemic treatments (purple) include RO7284755(\u003cem\u003en\u003c/em\u003e=1), IMC F106C (\u003cem\u003en\u003c/em\u003e=1), Antibody Drug Conjugate (\u003cem\u003en\u003c/em\u003e=1) and TIL-therapy alone (\u003cem\u003en\u003c/em\u003e=1), TIL combined with anti-PD1 (\u003cem\u003en\u003c/em\u003e=1), Lenvatinib plus Pembrolizumab(\u003cem\u003en\u003c/em\u003e=1), and anti-LAG3 plus anti-PD1 (\u003cem\u003en\u003c/em\u003e=1). Other local treatments include ruthenium brachytherapy (\u003cem\u003en\u003c/em\u003e=1) and T-VEC (\u003cem\u003en\u003c/em\u003e=1).\u003c/p\u003e\n\u003cp\u003eMPR, major pathologic response (green); pPR, pathologic partial response (orange); pNR, pathologic non-response (red); NE, non-evaluable due to progressive disease before surgery (dark red); aPD1, anti-PD1; aCTLA4, ant-CTLA4; aLAG3, anti-LAG3.\u003c/p\u003e","description":"","filename":"Fig4.png","url":"https://assets-eu.researchsquare.com/files/rs-7090131/v1/608b234fc7dfa62007a7cd72.png"},{"id":86773651,"identity":"5d6adf46-6215-4a71-83c2-9fdf1a612056","added_by":"auto","created_at":"2025-07-15 12:17:52","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":82354,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eBiomarker analysis of the interferon gamma gene signature (IFNg), tumor mutational burden (TMB) and PD-L1 expression\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) 5-year Event-Free Survival based on the IFNg score (high (red; \u003cem\u003en\u003c/em\u003e=39) vs low (blue; \u003cem\u003en\u003c/em\u003e=41)), (B) 5-year Overall Survival based on the IFNg score (high (red; \u003cem\u003en\u003c/em\u003e=39) vs low (blue; \u003cem\u003en\u003c/em\u003e=41)). Patients were included when RNA sequencing data was available (\u003cem\u003en\u003c/em\u003e=80); (C) 5-year Event-Free Survival based on the TMB (high (red; \u003cem\u003en\u003c/em\u003e=32) vs low (blue; \u003cem\u003en\u003c/em\u003e=43)), (D) 5-year Overall Survival based on the TMB (high (red; \u003cem\u003en\u003c/em\u003e=32) vs low (blue; \u003cem\u003en\u003c/em\u003e=43)). Patients were included when WES data was available (\u003cem\u003en\u003c/em\u003e=75); (E) 5-year Event-free Survival based on the PD-L1 expression (\u0026lt;1% (blue; \u003cem\u003en\u003c/em\u003e=43) vs ≥1% (red; \u003cem\u003en\u003c/em\u003e=33)), (F) 5-year Event-free Survival based on the PD-L1 expression (\u0026lt;1% (blue; \u003cem\u003en\u003c/em\u003e=43) vs ≥1% (red; \u003cem\u003en\u003c/em\u003e=33)), Patients were included when PD-L1 expression data was available (\u003cem\u003en\u003c/em\u003e=76), (G) Prediction of an event based on IFNghigh versus low using an ROC curve (AUC=0.662), (H) Prediction of an event based on TMB high versus low using an ROC curve (AUC=0.583), (I) Prediction of an event based on PD-L1 high versus low using an ROC curve (AUC=0.688).\u003c/p\u003e","description":"","filename":"Fig5.png","url":"https://assets-eu.researchsquare.com/files/rs-7090131/v1/5da267073af8787f66531003.png"},{"id":86775439,"identity":"6e849abe-9948-4a61-a818-0a650bb38238","added_by":"auto","created_at":"2025-07-15 12:33:52","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":102719,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCombination of biomarkers\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) VENN-diagram of patients with a high IFNg(purple), high TMB (green) and/or high PD-L1 (≥1%, blue), (B) Barplot of patients with a major pathologic response (including 95% confidence interval) according to the combination of biomarkers: low TMB, low IFNg and low PD-L1 (grey; \u003cem\u003en\u003c/em\u003e=17); low TMB, low IFNg and high PD-L1 (blue; \u003cem\u003en\u003c/em\u003e=4); high TMB, low IFNg and low PD-L1 (green; \u003cem\u003en\u003c/em\u003e=5); low TMB, high IFNg and low PD-L1 (pink; \u003cem\u003en\u003c/em\u003e=5); high TMB, high IFNg and low PD-L1 (medium purple; \u003cem\u003en\u003c/em\u003e=6); low TMB, high IFNg and high PD-L1 (light purple; \u003cem\u003en\u003c/em\u003e=9); high TMB, low IFNg and high PD-L1 (cyan; \u003cem\u003en\u003c/em\u003e=3); high TMB, high IFNg and high PD-L1 (dark purple; \u003cem\u003en\u003c/em\u003e=11); Patients were included when a pathologic response information, WES, RNA sequencing and PD-L1 expression data was available (\u003cem\u003en\u003c/em\u003e=61), (C) Boxplot of the IFNg gene signature score of patients achieving MPR versus non-MPR, colored by PD-L1 expression (\u0026lt;1% (blue) vs ≥1% (red), (D) Boxplot of the TMB of patients achieving MPR versus non-MPR, colored by PD-L1 expression (\u0026lt;1% (blue) vs ≥1% (red) \u0026nbsp;(E) Correlation plot for TMB and IFNg, (F) 5-year Event-Free Survival according to TMB, IFNg and PD-L1 as described at B, (G) Prediction of an event using ROC curves for low TMB, low IFNg and low PD-L1 versus the patients with other biomarker combinations (AUC=0.756) and for high TMB, high IFNg and high PD-L1 versus the patients with other biomarker combinations (AUC=0.712), (H) 5-year Event-Free Survival of patients with a low IFNg, low TMB and low PD-L1 (\u003cem\u003en\u003c/em\u003e=17) versus the patients with other biomarker combinations (\u003cem\u003en\u003c/em\u003e=43), (I) 5-year Event-Free Survival of patients with a high IFNg, high TMB and high PD-L1 (\u003cem\u003en\u003c/em\u003e=11) versus the patients with other biomarker combinations (\u003cem\u003en\u003c/em\u003e=49).\u003c/p\u003e","description":"","filename":"Fig6.png","url":"https://assets-eu.researchsquare.com/files/rs-7090131/v1/44a36534887c87e821b3fe8e.png"},{"id":86774810,"identity":"88a8123d-36a1-4d04-bfda-d349d09653e1","added_by":"auto","created_at":"2025-07-15 12:25:52","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":63600,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCombination of IFNg and PD-L1\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Barplot of pathologic response rate (including 95% confidence interval) according to IFNg score and high PD-L1 (≥1%), resulting in multiple subgroups: low IFNg and low PD-L1 (grey; \u003cem\u003en\u003c/em\u003e=23); low IFNg and high PD-L1 (blue; \u003cem\u003en\u003c/em\u003e=7); high IFNg and low PD-L1 (pink; \u003cem\u003en\u003c/em\u003e=11); high IFNg and high PD-L1 (light purple; \u003cem\u003en\u003c/em\u003e=22); Patients were included when a pathologic response information, RNA sequencing and PD-L1 expression data was available (\u003cem\u003en\u003c/em\u003e=61), (B) 5-year Event-Free Survival according to IFNg and PD-L1 as described at A, (C) 5-year Event-Free Survival of patients with a low IFNg and low PD-L1 (grey; \u003cem\u003en\u003c/em\u003e=22) versus the patients with other biomarker combinations (dark blue; \u003cem\u003en\u003c/em\u003e=42), (D) 5-year Event-Free Survival of patients with a high IFNg and high PD-L1 (light purple\u003cem\u003e; n\u003c/em\u003e=23) versus the patients with other biomarker combinations (dark blue; \u003cem\u003en\u003c/em\u003e=41), (E) Prediction of an event using an ROC curve for low IFNg and low PD-L1 versus the patients with other biomarker combinations (AUC=0.745), (F) Prediction of an event using an ROC curve for high IFNg and high PD-L1 versus the patients with other biomarker combinations (AUC=0.692).\u003c/p\u003e","description":"","filename":"Fig7.png","url":"https://assets-eu.researchsquare.com/files/rs-7090131/v1/b1f532425a500e8941933d45.png"},{"id":101389654,"identity":"475b8d1d-c2d0-4d32-9305-62656025c6c7","added_by":"auto","created_at":"2026-01-29 08:06:31","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2667131,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7090131/v1/13aec3dc-cad6-4d7c-824a-8b33642e5808.pdf"},{"id":86773647,"identity":"f78ff22b-a6e3-451b-a395-44e5c98c3569","added_by":"auto","created_at":"2025-07-15 12:17:52","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":383363,"visible":true,"origin":"","legend":"Extended Figure 1: Overall toxicity and long-term toxicity of the PRADO trial","description":"","filename":"Extfig1toxPRADO0606.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7090131/v1/5366bfc75f6807b6000c45ae.pdf"},{"id":86773649,"identity":"3a5b7676-1ac1-4f70-9d2d-793c0892ec03","added_by":"auto","created_at":"2025-07-15 12:17:52","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":581158,"visible":true,"origin":"","legend":"Extended Figure 2: Forest Plot of Hazard Ratios for relapse free survival by baseline variables","description":"","filename":"Extfig2forestRFSPRADO1007.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7090131/v1/d8caca4c83901a3fb3ebea7d.pdf"},{"id":86773650,"identity":"9e5b3ee4-88ce-4d5b-b552-f5bcecb1b828","added_by":"auto","created_at":"2025-07-15 12:17:52","extension":"pdf","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":572873,"visible":true,"origin":"","legend":"Extended Figure 3: Forest Plot of Hazard Ratios for overall survival by baseline variables","description":"","filename":"Extfig3forestOSPRADO1007.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7090131/v1/f46c39004687303078f8bc20.pdf"},{"id":86775440,"identity":"274cfa6d-184b-468f-a055-b5f3de9f5c98","added_by":"auto","created_at":"2025-07-15 12:33:52","extension":"pdf","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":759887,"visible":true,"origin":"","legend":"Extended Figure 4: 5-year survival analysis for validation-cohort OpACIN-neo","description":"","filename":"Extfig4survivalcurvesOPACINneo0707.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7090131/v1/d78cd161c5808cc26f715450.pdf"},{"id":86773661,"identity":"5d939641-ad43-45d6-9793-8f5be7d5ba2c","added_by":"auto","created_at":"2025-07-15 12:17:52","extension":"pdf","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":725142,"visible":true,"origin":"","legend":"Extended Figure 4: 5-year survival analysis for validation-cohort OpACIN-neo per treatment arm","description":"","filename":"Extfig5survivalcurvesOPACINneoperarm0707.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7090131/v1/70b6a2d2768e580e335cf210.pdf"},{"id":86774815,"identity":"62febf65-c9af-4709-909d-d5dd40228159","added_by":"auto","created_at":"2025-07-15 12:25:52","extension":"pdf","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":741636,"visible":true,"origin":"","legend":"Extended Figure 6: 5-year survival analysis for validation-cohort OpACIN-neo of patients with or without BRAF mutation","description":"","filename":"Extfig6BRAFOPACINneo0707.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7090131/v1/f20c3c17cde75ff28c1f127b.pdf"},{"id":86774813,"identity":"52776f87-c695-469b-9cfd-77775bc95f05","added_by":"auto","created_at":"2025-07-15 12:25:52","extension":"pdf","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":684574,"visible":true,"origin":"","legend":"\u003cp\u003eExtended Figure 7: Biomarker analysis of the interferon gamma gene signature (IFNγ), tumor mutational burden (TMB) and PD-L1 staining for conformation-cohort OpACIN-neo\u003c/p\u003e","description":"","filename":"Extfig7biom1OPACINneo0707.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7090131/v1/e20bf0b3f68b346eced9baeb.pdf"},{"id":86773658,"identity":"1ed76f96-2e7f-4e89-82a8-ce171f535925","added_by":"auto","created_at":"2025-07-15 12:17:52","extension":"pdf","order_by":8,"title":"","display":"","copyAsset":false,"role":"supplement","size":664732,"visible":true,"origin":"","legend":"Extended Figure 8: Combination of biomarkers for conformation-cohort OpACIN-neo","description":"","filename":"Extfig8biom2OPACINneo1007.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7090131/v1/a5f4fb744c61ede054d39361.pdf"},{"id":86775442,"identity":"7eb5fee8-0c80-4066-ad16-d616ac9bf6e9","added_by":"auto","created_at":"2025-07-15 12:33:52","extension":"pdf","order_by":9,"title":"","display":"","copyAsset":false,"role":"supplement","size":620994,"visible":true,"origin":"","legend":"Extended Figure 9: Combination of IFN\u0026#x03B3; and PD-L1 for conformation-cohort OpACIN-neo","description":"","filename":"Extfig9biom3OPACINneo1007.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7090131/v1/09ba23a3fc04a19c718ff1e3.pdf"},{"id":86775441,"identity":"c34d591b-3033-4027-81e1-bfb91599355c","added_by":"auto","created_at":"2025-07-15 12:33:52","extension":"pdf","order_by":10,"title":"","display":"","copyAsset":false,"role":"supplement","size":501964,"visible":true,"origin":"","legend":"Extended Figure 10: Biospecimen selection for survival- and biomarker-analysis","description":"","filename":"Extfig10biospecimenPRADO0707.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7090131/v1/302fb6f1829d8ffc01aa636b.pdf"},{"id":86773656,"identity":"86dffabf-5865-43fb-8c9d-4b51e06412c3","added_by":"auto","created_at":"2025-07-15 12:17:52","extension":"docx","order_by":11,"title":"","display":"","copyAsset":false,"role":"supplement","size":51158,"visible":true,"origin":"","legend":"Supplementary appendix","description":"","filename":"10072025HoeijmakeresetalSupplementaryappendix.docx","url":"https://assets-eu.researchsquare.com/files/rs-7090131/v1/e47a05f062714c7cf150592e.docx"}],"financialInterests":"\u003cb\u003eYes\u003c/b\u003e there is potential Competing Interest.\nNo author has received financial support for the work on this manuscript, and no medical writer was involved at any stage of the preparation of this manuscript. A.M.M. has served on advisory boards for BMS, MSD, Novartis, Roche, Pierre-Fabre and QBiotics. R.P.M.S. has received honoraria for advisory board participation from MSD and Clinical Laboratories Pty Ltd. W.J.v.H. has received speakers honorarium regeneron, Sanofi, MSD, Belpharma, novartis, reports an advisory role Belpharma and has received a research grant from Amgen. E.K.A. has consultancy/advisory relationships with Delcath, Immunocore, and Lilly, and has received research grants unrelated to this paper from Bristol Myers Squibb, Delcath, Novartis, and Pierre-Fabre. These grants are unrelated to current work and are paid to the institute. A.A.M.v.d.V., received travel fees from Ipsen and consultancies fees (all paid to the institute) from BMS, MSD, Ipsen, Eisai, Pfizer, Novartis, Sanofi, Roche and Pierre Fabre. K.P.M.S. has consultancy/advisory relationships with Abbvie, Sairopa, has received research funding TigaTx, Bristol Myers Squibb, Philips, Genmab, Pierre Fabre, and has received honoraria from Bristol Myers Squibb (all paid to the institute). H.E. has received institutional research grants from SkyLineDx, BMS, Novartis and Pierre Fabre, speaker honorarium from Janssen, not personal speaker honorarium but to the hospital from BMS and Novartis, and served as expert board for Pierre Fabre and BMS. G.A.P.H consultancy/advisory relationships with Amgen, Bristol-Myers Squibb, Roche, MSD, Novartis, Sanofi, Pierre Fabre and has received research grants from Bristol-Myers Squibb, Seerave (all paid to the institute). S. Ch’ng receives fees for professional services provided to MSD and SkylineDx. J.B.A.G.H. reports an advisory role for Achilles Therapeutics, AstraZeneca, BioNTech, Bristol-Myers Squibb, Immunocore, Instil Bio, Iovance Biotherapeutics, Ipsen, Molecular Partners, MSD Oncology, Neogene Therapeutics, Novartis, Roche/Genentech, Sanofi, Sāstra, Third Rock Ventures and T-Knife; has received research funding, paid to the institute, from Amgen, Asher Biotherapeutics, BioNTech, Bristol-Myers Squibb, MSD, Neon Therapeutics, Novartis; and is stockowner of Neogene Therapeutics and Sāstra. R.V.R. has received honoraria from Merck Sharp \u0026 Dohme. R.A.S. has received fees for professional services from SkylineDx BV, IO Biotech ApS, MetaOptima Technology Inc., F. Hoffmann-La Roche Ltd, Evaxion, Provectus Biopharmaceuticals Australia, Qbiotics, Novartis, Merck Sharp \u0026 Dohme, NeraCare, AMGEN Inc., Bristol-Myers Squibb, Myriad Genetics, GlaxoSmithKline. A.C.J.v.A. reports an advisory role in Amgen, Bristol-Myers Squibb, Daiichi Sankyo, Genmab, Menarini Silicon Biosystems, Merck Serono-Pfizer, MSD Merck, Neracare, Novartis, Pierre Fabre, Provectus, Replimune, Sanofi, Sirius Medical, SkylineDx, 4SC; has received research funding from Amgen, Merck Serono – Pfizer, SkylineDx. G.V.L. is consultant advisor for Agenus, Amgen, Array Biopharma, AstraZeneca, Bayer HealthCare Pharmaceuticals Inc, BioNTech SE, Boehringer Ingelheim International GmbH, Bristol Myers Squibb, Evaxion Biotech A/S, Fortiva Biologics (USA) Inc, GI Innovation Inc, Hexal AG (Sandoz Company), Highlight Therapeutics S.L., IOBiotech, Immunocore Ireland Limited, Innovent Biologics USA Inc, Iovance Biotherapeutics Inc, Merck Sharpe \u0026 Dohme, Novartis Pharma AG, OncoSec Medical Australia, PHMR Limited, Pierre Fabre, Regeneron Pharmaceuticals, Scancell Limited, SkylineDX BV. C.U.B. reports he has received compensation for advisory roles from BMS, MSD, Roche, Novartis, GSK, AZ, Pfizer, Lilly, GenMab, Pierre Fabre, Third Rock Ventures, Senya, received research funding from BMS, Novartis, NanoString, 4SC and reports to be co-founder of Immagene BV. All compensations and funding for C.U.B. were paid to the institute, except for Third Rock Ventures and Immagene. The other authors declare no conflicts of interest.","formattedTitle":"Long-term survival after neoadjuvant low-dose ipilimumab plus high-dose nivolumab in resectable stage III melanoma: the 5-year survival-update and biomarker analysis from the PRADO-trial","fulltext":[{"header":"Introduction","content":"\u003cp\u003eDuring the last decade, neoadjuvant immune checkpoint blockade (ICB) has been widely investigated in many different cancer types\u003csup\u003e1-8\u003c/sup\u003e. This paradigm shift was driven by the hypothesis that the presence of more (neo)antigens prior to surgery results in a stronger and broader clonal expansion of tumor-specific T cells induced by neoadjuvant ICB. Results from early preclinical and clinical studies supported this hypothesis, suggesting superior outcomes for neoadjuvant compared to adjuvant ICB\u003csup\u003e9-13\u003c/sup\u003e. The randomized phase II SWOG-1801 and phase III NADINA trials in patients with macroscopic resectable stage III melanoma\u003csup\u003e1,2\u003c/sup\u003e subsequently confirmed these findings, showing superior clinical outcomes in those who received neoadjuvant ICB compared to those who received adjuvant ICB only.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe SWOG-1801 trial evaluated pembrolizumab (anti-PD1, 200 mg every 3 weeks) given as 3 neoadjuvant cycles followed by 15 adjuvant cycles versus 18 cycles of adjuvant-only treatment. The neoadjuvant approach demonstrated superior outcomes with an estimated 2-year event-free survival (EFS) of 72% compared to 49% for adjuvant-only treatment\u003csup\u003e2\u003c/sup\u003e. \u0026nbsp;The NADINA trial showed even greater benefits with an estimated 18-month EFS of 81% in patients treated with 2 cycles of neoadjuvant nivolumab (anti-PD1) plus ipilimumab (anti-CTLA4) followed by a response-directed adjuvant treatment regimen as compared to 54% in patients treated with 12 cycles of adjuvant nivolumab\u003csup\u003e1,14\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eIdentifying patients likely to respond to treatment could enable personalized therapy approaches, to improve responses and minimalize toxicity. In stage IV melanoma, tumor mutational burden (TMB) and Programmed Cell Death Ligand 1 (PD-L1) expression at baseline are associated with favorable treatment responses \u003csup\u003e15\u003c/sup\u003e, in stage III melanoma the interferon gamma gene signature (IFNg) and TMB, but not PD-L1 expression, are associated with pathological response and EFS\u003csup\u003e16\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eNeoadjuvant ICB allows for pathologic response evaluation, a robust surrogate marker for relapse free survival (RFS) and distant metastasis free survival (DMFS)\u003csup\u003e14,17-19\u003c/sup\u003e. However, to date, all patients undergo potentially morbid surgery (therapeutic lymph node dissection; TLND) for pathologic response evaluation. The pathologic response in the largest lymph node metastasis at baseline (index lymph node; ILN) has shown to be representative of the pathologic response in the total lymph node bed\u003csup\u003e20,21\u003c/sup\u003e, suggesting that an initial removal of the ILN could tailor further personalized treatment or follow-up.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe PRADO trial was the first trial in melanoma prospectively testing a surgical de-escalation approach, by marking and removing only the ILN for pathologic response evaluation after neoadjuvant immunotherapy\u003csup\u003e22\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eWe have previously reported that neoadjuvant ipilimumab plus nivolumab induced a pathologic response rate \u0026nbsp;(≤50% residual viable tumor) of 72% (71/99 patients), including major pathologic response (MPR; ≤10% residual viable tumor) in 61% (60/99 patients), confirming the efficacy of this neoadjuvant regimen reported in the OpACIN-neo trial\u003csup\u003e13,22\u003c/sup\u003e. \u0026nbsp;Of interest, the final pathological response analysis of the larger NADINA trial reported precisely the same MPR rate of 61% based on examination of the TLND specimen\u003csup\u003e14\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eEarly data from PRADO suggested that \u0026nbsp;patients achieving a MPR in the ILN, can safely omit both TLND and adjuvant therapy, resulting in superior quality of life \u0026nbsp;without increasing the individual risk of relapse at 3-years of follow-up \u003csup\u003e18,22\u003c/sup\u003e. Recently a large, pooled analysis from various studies and real-world patient databases confirmed the excellent outcomes for patients achieving an MPR, although these studies predominantly included TLND specimens \u003csup\u003e23\u003c/sup\u003e. However, patient outcome data beyond 3 years after neoadjuvant ipilimumab plus nivolumab, especially for those with an MPR in which subsequent surgery and adjuvant therapy were omitted, are lacking.\u003c/p\u003e\n\u003cp\u003eTherefore, we report the 5-year update of the PRADO trial including survival, long-term toxicity, and the first biomarker analyses, and the 5-year survival-outcomes of the OpACIN-neo trial. In addition, we will be comparing the long-term outcomes to the previously conducted OpACIN-neo trial, where the same inclusion-criteria were handled. In OpACIN-neo patients were treated with different dosages of neoadjuvant ipilimumab + nivolumab, without personalized surgery or adjuvant treatment \u003csup\u003e13\u003c/sup\u003e.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eAt the time of data-cutoff of 06/01/2025, the median follow-up was 60 months (interquartile range, IQR: 60 - 64 months), with a minimum follow-up of 31 months for all patients alive (\u003cem\u003en\u003c/em\u003e=83).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eSurvival outcomes\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAt data cut off, 29/99 (29%) patients had an event (defined as disease progression resulting in inoperability, locoregional recurrence, distant metastases, or death, whichever comes first): six patients became inoperable due to progression before surgery, 23/92 (25%) patients had a locoregional recurrence after surgery, 18/92 (20%) had a distant metastasis after surgery, and 16/99 (16%) patients died, of whom 14 died from melanoma. One patient died of a cause not related to disease progression or toxicity and 1 patient died of an unknown cause without signs of disease progression. Patient-selection (99 patients versus 92 patients) for survival follow-up is displayed in\u003cstrong\u003e\u0026nbsp;Extended Data Fig. 10a\u003c/strong\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe estimated 5-year EFS, relapse free survival (RFS), distant metastasis free survival (DMFS), overall survival (OS) and melanoma specific survival (MSS) of patients treated in the PRADO trial were 71% (95% confidence interval (CI): 63-81%), 74% (95% CI: 65-84%), 79% (95% CI: 71-89%), 86% (95% CI: 79-93%) and 88% (95% CI: 81-94%) \u003cstrong\u003e(Fig. 1a-e)\u003c/strong\u003e. The median EFS, RFS, DMFS, OS and MSS had not been reached at time of data cutoff. In OpACIN-neo similar estimated 5-year survival rates were observed, without significant differences between the three treatment-arms in that study \u003cstrong\u003e(Extended Data Fig. 4a-e \u0026amp; Extended Data Fig. 5a-d).\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWhen PRADO patients were grouped by pathologic response according to the International Neoadjuvant Melanoma Consortium (INMC) criteria\u003csup\u003e24\u003c/sup\u003e \u003cstrong\u003e(Supplemental Table 1),\u0026nbsp;\u003c/strong\u003ethe estimated 5-year RFS, DMFS and MSS were 86% (95% CI: 76-97%), 91% (95% CI: 83-\u0026gt;99%) and 98% (95% CI: 95-\u0026gt;99%) for patients with an MPR, 55% (95% CI: 32-94%), 55% (95% CI: 32-94%) and 64% (95% CI: 41-\u0026gt;99%) for patients with a pathologic partial response (pPR; \u0026gt;10% and ≤50% residual viable tumor) and 48% (95% CI: 30-75%), 57% (95% CI: 40-83%) and 80% (95% CI: 64-\u0026gt;99%) for patients with a pathologic non-response (pNR; \u0026gt;50% residual viable tumor) \u003cstrong\u003e(Fig. 1f-h)\u003c/strong\u003e. Baseline characteristics per pathologic response group are displayed in \u003cstrong\u003eSupplemental Table 2.\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor patients with an MPR survival was improved as compared to patients without MPR, with 5-year RFS rates being 86% versus 50% (log-rank \u003cem\u003ep\u003c/em\u003e-value\u0026lt;0.0001), DMFS 91% versus 56% (log-rank \u003cem\u003ep\u003c/em\u003e-value\u0026lt;0.0001) and MSS 98% versus 74% (log-rank \u003cem\u003ep\u003c/em\u003e-value=0.00034). These outcomes were similar to the outcomes observed in the OpACIN-neo cohort, with the exception for patients achieving a pPR, where these patients had higher landmark EFS, RFS, DMFS and MSS in the OpACIN-neo trial compared with PRADO. Neither group received adjuvant therapy \u003cstrong\u003e(Fig. 1f-h \u0026amp; Extended Data Fig. 4f-h)\u003c/strong\u003e. When dividing MPR into pathologic complete response (pCR; 0% viable tumor cells) and near-pCR (\u0026gt;0%-≤10% viable tumor cells), similar estimated 5-year survival-outcomes are observed in PRADO and in OpACIN-neo (data not shown).\u003c/p\u003e\n\u003cp\u003eWhen searching for potential explanations of the outcome differences observed for the pPR patients from the PRADO vs OpACIN-neo cohorts, we compared their baseline characteristics \u003cstrong\u003e(Supplemental Table 3)\u003c/strong\u003e. We found that a larger proportion of patients in the PRADO pPR cohort were from Europe (10/11 in PRADO versus 5/12 in OpACIN-neo), no patients had an ulcerated tumor (0/10 in PRADO versus 5/12 in the OpACIN-neo; \u003cem\u003ep\u003c/em\u003e-value=0.016) and a larger proportion of patients had a low tumor mutational burden (TMB; 100% in PRADO versus 44% in OpACIN-neo, \u003cem\u003ep\u003c/em\u003e-value=0.026). There were no differences in measurable tumor burden (sum of diameter of target lesion and number of lymph nodes on imaging), \u003cem\u003eBRAF\u003c/em\u003e-mutation status, frequency of grade ≥3 immune related adverse events (irAEs), use of prednisolone, or second line immunosuppression \u003cstrong\u003e(Supplemental Table 3)\u003c/strong\u003e.Three patients with a pPR in PRADO did not undergo a TLND, two patients refused additional surgery, and one patient was suspected to have stage IV disease, all three patients did not have disease progression at time of cutoff.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eBRAF\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e-mutation status\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn PRADO, patients with a \u003cem\u003eBRAFV600E/K\u003c/em\u003e-mutant melanoma had worse EFS than patients with \u003cem\u003eBRAF\u003c/em\u003e-wildtype melanoma, with 5-year EFS of 60% versus 80%, respectively \u003cstrong\u003e(Fig. 2a)\u003c/strong\u003e (log-rank \u003cem\u003ep\u003c/em\u003e-value=0.011 and Hazard Ratio of 2.63 (95% CI: 1.24-5.57, \u003cem\u003ep\u003c/em\u003e=0.0118)). All patients with a distant metastasis on imaging at time of surgery had a \u003cem\u003eBRAF\u003c/em\u003e-mutant melanoma. No significant differences between BRAF-mutant and BRAF-wildtype melanoma were found for RFS (80% versus 64%, log-rank \u003cem\u003ep\u003c/em\u003e-value=0.12) and DMFS (84% versus 72%, log-rank \u003cem\u003ep\u003c/em\u003e-value=0.23), though survival curves suggested a differential effect over time, complicating interpretation \u003cstrong\u003e(Fig. 2b,c)\u003c/strong\u003e. No differences for OS (86% versus 84%, log-rank \u003cem\u003ep\u003c/em\u003e-value=0.79) and MSS (90% versus 84%, log-rank \u003cem\u003ep\u003c/em\u003e-value=0.3) were observed \u003cstrong\u003e(Fig. 2d,e)\u003c/strong\u003e. In addition, presence of a\u003cem\u003e\u0026nbsp;BRAFV600E/K\u003c/em\u003e mutation in the tumor was not predictive for RFS, DMFS and OS in the univariable Cox-regression analysis \u003cstrong\u003e(Fig. 3, Extended Data Fig. 2, Extended Data Fig. 3)\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003eIn the OpACIN-neo cohort, only numerical differences in EFS, RFS and DMFS were observed according to the \u003cem\u003eBRAF\u003c/em\u003e mutational status, and no differences in OS and MSS \u003cstrong\u003e(Extended Data Fig. 6a-e)\u003c/strong\u003e.To investigate whether this difference was driven by the different doses of ipilimumab used in the OpACIN-neo cohort we divided the patients into different subgroups based on their \u003cem\u003eBRAF\u003c/em\u003e mutational status (mutant versus wildtype) and treatment-arm (arm A (ipilimumab 3 mg kg\u003csup\u003e-1\u003c/sup\u003e plus nivolumab 1 mg kg\u003csup\u003e-1\u003c/sup\u003e) versus arm B (ipilimumab 1 mg kg\u003csup\u003e-1\u003c/sup\u003e plus nivolumab 3 mg kg\u003csup\u003e-1\u003c/sup\u003e)) \u003cstrong\u003e(Extended Data Fig. 6f,g)\u003c/strong\u003e. Even though thesubgroups become too small to draw any conclusions, there is a slight trend towards a better response to higher dose of ipilimumab in patients with a \u003cem\u003eBRAF\u003c/em\u003e-mutant melanoma \u003cstrong\u003e(Extended Data Fig. 6f,g)\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eSafety\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn total, irAEs ≥ grade 3 occurred in 30% of the PRADO study population \u003cstrong\u003e(Extended Data Fig. 1).\u0026nbsp;\u003c/strong\u003eOngoing grade 1-2 irAEs occurred in 69% of the patients alive at data cut-off and were predominantly vitiligo and hypothyroidism \u003cstrong\u003e(Extended Data Fig. 1).\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eSubsequent therapies\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSix out of 60 (10%) patients in the MPR group had disease recurrence \u003cstrong\u003e(Fig. 4)\u003c/strong\u003e, including1/12 (8%) \u0026nbsp;patients with a near-pCR and 5/47 (11%) patients with a pCR. Four of these six patients had a local recurrence that occurred within 20 months and were treated with surgery combined with BRAF-targeted therapy (\u003cem\u003en\u003c/em\u003e=1), anti-PD1 (\u003cem\u003en\u003c/em\u003e=2), or systemic targeted therapy alone (\u003cem\u003en\u003c/em\u003e=1). Two out of the six patients in the MPR group had a distant metastasis as first recurrence, 60 and 61 months after registration \u003cstrong\u003e(Fig. 4)\u003c/strong\u003e. One of these patients had local progression in the jejunum that was treated with BRAF-targeted therapy, followed by surgery. The other patient had multiple metastatic sites including brain, and received re-induction with ipilimumab + nivolumab, however received only one dose due to toxicity and died soon thereafter.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFive out of the 11 (45%) patients achieving pPR had disease recurrence. One patient had a local recurrence as first recurrence, which was surgically removed. Later the patient developed a distant metastasis and received high dose ipilimumab plus nivolumab followed by radiotherapy. Four out of the five patients with disease recurrence from the patients that achieved a pPR, had a distant metastasis at time of first recurrence. One elderly patient only received palliative radiotherapy at time of recurrence and died later of disease progression. The other patients were treated with surgery (\u003cem\u003en\u003c/em\u003e=3) or radiotherapy combined with anti-PD1 (\u003cem\u003en\u003c/em\u003e=1) (\u003cstrong\u003eFig. 4)\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003eTen out of the 21 (52%) patients who achieved a pNR upon the neoadjuvant regimen had disease recurrence. Three of these eleven patients had a local recurrence and were treated with surgery +/- radiotherapy or T-VEC. Seven patients had a distant metastasis at time of the first recurrence and were treated with targeted therapy (\u003cem\u003en\u003c/em\u003e=4), lenvatinib plus pembrolizumab (\u003cem\u003en\u003c/em\u003e=1) or no systemic treatment (\u003cem\u003en\u003c/em\u003e=2) \u003cstrong\u003e(Fig. 4)\u003c/strong\u003e. Of the two patients who did not receive any systemic treatment at time of progression, one received radiotherapy but later opted for best supportive care at time of further disease progression, and the other patient did not receive systemic due to previous toxicities.\u003c/p\u003e\n\u003cp\u003eSix patients had a distant metastasis before surgery. Four out of these six patients received subsequent targeted therapy as first treatment after progression, one patient had long-term response to this subsequent targeted therapy. Four out of six patients with distant metastasis before surgery were treated with a combination of ipilimumab and nivolumab (\u003cem\u003en\u003c/em\u003e=2 had a long-term response) before or after treatment with targeted therapy \u003cstrong\u003e(Fig. 4)\u003c/strong\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eSingle biomarker analysis\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRNA sequencing data of the baseline biopsy is available in 80/99 (81%) patients \u003cstrong\u003e(Extended Data Fig. 10)\u003c/strong\u003e. Patients with a high IFNg\u0026nbsp;score (\u003cem\u003en\u003c/em\u003e=39) had improved EFS (5-year rate 81% versus 54%; \u0026nbsp;log-rank \u003cem\u003ep\u003c/em\u003e-value=0.0039), RFS (81% versus 57%; log-rank \u003cem\u003ep\u003c/em\u003e=0.044) and DMFS (86% versus 63%; log-rank \u003cem\u003ep\u003c/em\u003e-value=0.031) compared to patients with a low IFNg\u0026nbsp;score (\u003cem\u003en\u003c/em\u003e=41) \u003cstrong\u003e(Fig. 5a,g)\u003c/strong\u003e (RFS and DMFS not shown), but not OS (90% versus 70%; log-rank \u003cem\u003ep\u003c/em\u003e-value=0.19) and MSS (92% versus 80%; log-rank \u003cem\u003ep\u003c/em\u003e-value=0.22) \u003cstrong\u003e(Fig. 5b,g)\u0026nbsp;\u003c/strong\u003e(MSS not shown). In OpACIN-neo similar trends were observed, with higher 5-year EFS, RFS, DMFS, OS and MSS in patients with a high IFNg\u0026nbsp;score, though no significant log-rank test results \u003cstrong\u003e(Extended Data Fig. 7)\u0026nbsp;\u003c/strong\u003e(RFS, DMFS and MSS not shown).\u003c/p\u003e\n\u003cp\u003eWhole exome sequencing from the baseline biopsies is available in 75/99 (76%) PRADO patients. No statistically significant differences were observed in EFS (5-year rate 75% versus 58%; log-rank \u003cem\u003ep\u003c/em\u003e-value=0.1), RFS (76% versus 60%; log-rank \u003cem\u003ep\u003c/em\u003e-value=0.3), DMFS (80% versus 67%; log-rank \u003cem\u003ep\u003c/em\u003e-value=0.45), OS (84% versus 81%; log-rank \u003cem\u003ep\u003c/em\u003e-value=0.88) and MSS (90% versus 81%; log-rank \u003cem\u003ep\u003c/em\u003e-value=0.45) when comparing patients with a high TMB (\u003cem\u003en\u003c/em\u003e=32) to patients with a low TMB (\u003cem\u003en\u003c/em\u003e=43) \u003cstrong\u003e(Fig. 5c,d,h)\u003c/strong\u003e (RFS, DMFS and MSS not shown). In OpACIN-neo, significant differences in EFS (5-year rate 86% versus 66%; log-rank \u003cem\u003ep\u003c/em\u003e-value=0.032), DMFS (89% versus 69%; log-rank \u003cem\u003ep\u003c/em\u003e-value=0.022), OS (96% versus 80%; log-rank \u003cem\u003ep\u003c/em\u003e-value=0.014) and MSS (100% versus 79%; log-rank \u003cem\u003ep\u003c/em\u003e-value=0.012) and numerical differences in RFS (86% versus 69%; log-rank \u003cem\u003ep\u003c/em\u003e-value=0.061) were observed comparing patients with a high TMB to patients with a low TMB \u003cstrong\u003e(Extended Data Fig. 7\u003c/strong\u003e\u003cstrong\u003e)\u003c/strong\u003e (RFS, DMFS and MSS not shown).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn 76 patients, the PD-L1 expression on tumor cells (TPS score) was determined in the baseline biopsy. Patients with a high PD-L1 expression of ≥1% (\u003cem\u003en\u003c/em\u003e=43) had a significantly improved EFS (5-year rate 88% versus 60%; log-rank \u003cem\u003ep\u003c/em\u003e-value=0.0036), RFS (87% versus 64%; log-rank \u003cem\u003ep\u003c/em\u003e-value=0.045), OS (94% versus 79%; log-rank \u003cem\u003ep\u003c/em\u003e-value=0.049) and MSS (97% versus 81%; log-rank \u003cem\u003ep\u003c/em\u003e-value=0.029) compared to patients with a PD-L1 expression of \u0026lt;1%, respectively (\u003cem\u003en\u003c/em\u003e=33) \u003cstrong\u003e(Fig. 5e,f,i)\u0026nbsp;\u003c/strong\u003e(RFS and MSS not shown). No significant differences were found in DMFS (5-year rate 90% versus 73%; log-rank \u003cem\u003ep\u003c/em\u003e-value=0.097) between the groups. In OpACIN-neo, only small differences in 5-year rates and no significant log-rank test results were observed for EFS (85% versus 76%; log-rank \u003cem\u003ep\u003c/em\u003e-value=0.29), RFS (85% versus 78%; log-rank \u003cem\u003ep\u003c/em\u003e-value=0.36), DMFS (85% versus 83%; log-rank \u003cem\u003ep\u003c/em\u003e-value=0.49), OS (96% versus 88%; log-rank \u003cem\u003ep\u003c/em\u003e-value=0.12) and MSS (96% versus 89%; log-rank \u003cem\u003ep\u003c/em\u003e-value=0.25) when comparing outcomes of patients with a high PD-L1 expression of ≥1% to patients with a PD-L1 expression of \u0026lt;1% \u003cstrong\u003e(Extended Data Fig. 7)\u003c/strong\u003e (RFS, DMFS and MSS not shown).\u003c/p\u003e\n\u003cp\u003eTo investigate whether the missing PD-L1 expression of patients with an event influenced the predictive value of PD-L1 expression, we performed imputation by replacing these missing values by all low or all high. Although PD-L1 expression remained predictive for RFS, DMFS and OS \u0026nbsp;\u003cstrong\u003e(Supplemental Table 4)\u003c/strong\u003e, the unavailability of the PD-L1 expression in some patients might have resulted in an overestimation of the differences observed in our cohort.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eCombined biomarker analyses\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNext, we analyzed the contribution of the most prominent baseline markers when combining them to a multiparameter baseline biomarker. In 61 patients the IFNg\u0026nbsp;signature score, TMB and PD-L1 expression were available, and were distributed as displayed in\u003cstrong\u003e\u0026nbsp;Fig. 6a\u003c/strong\u003e. As expected, having all three parameters low was associated with the lowest MPR rates (18%; 95% CI: 4-43%), while having all three parameters high was associated with a 100% chance for MPR (95% CI: 72-100%) (\u003cstrong\u003eFig. 6b\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003ePatients with MPR had a higher IFNg\u0026nbsp;signature score (\u003cstrong\u003eFig. 6c)\u003c/strong\u003e and a higher TMB (\u003cstrong\u003eFig. 6d)\u003c/strong\u003e. The IFNg\u0026nbsp;signature score did not correlate with the TMB \u003cstrong\u003e(Fig. 6e)\u003c/strong\u003e. We did not include PD-L1 as this was a non-numeric variable.\u003c/p\u003e\n\u003cp\u003eIn line with the response data patients with a triple high score (\u003cem\u003en\u003c/em\u003e=11) had the longest 5-year EFS (100%) while patients with triple low (\u003cem\u003en\u003c/em\u003e=17) had the shortest (41%) \u003cstrong\u003eFig. 6f\u003c/strong\u003e. The AUC curves of these two scenarios are shown in \u003cstrong\u003eFig. 6g.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSimilar survival-trends were observed in the OpACIN-neo trial, as in the patients with triple high (\u003cem\u003en\u003c/em\u003e=3) 100% (95% CI: 29-100%) had MPR and an 100% estimated 5-year EFS and the patients with triple low (\u003cem\u003en\u003c/em\u003e=11) had a 27% (95% CI: 6-61%) MPR-rate and 55% estimated 5-year EFS \u003cstrong\u003e(Extended Data Fig. 8a-e)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAs clinical grade TMB evaluation is a costly procedure, we also analyzed the biomarker-combination of IFNg\u0026nbsp;and PD-L1 expression alone. Patients with a low IFNg\u0026nbsp;score and a low PD-L1 expression (\u003cem\u003en\u003c/em\u003e=22) had MPR rate of 27% \u003cstrong\u003e(Fig. 7b)\u003c/strong\u003e and 5-year EFS of 48% \u003cstrong\u003e(Fig. 7a, c)\u003c/strong\u003e,while patients with a high IFNg\u0026nbsp;score and a high PD-L1 expression (\u003cem\u003en\u003c/em\u003e=21) had MPR rate of 86% \u003cstrong\u003e(Fig. 7a)\u003c/strong\u003e and a 5-year EFS of 91% \u003cstrong\u003e(Fig. 7d).\u0026nbsp;\u003c/strong\u003eThe AUC curves for these biomarker doublets are shown in\u003cstrong\u003e\u0026nbsp;Fig. 7e and f\u0026nbsp;\u003c/strong\u003eand showed only slightly lower AUC compared to the model using all three biomarkers \u003cstrong\u003e(Fig. 6g)\u003c/strong\u003e (AUC of 0.745 in double low versus 0.756 in triple low; and an AUC of 0.692 in double high versus 0.712 in triple high).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSimilar results were observed in the OpACIN-neo cohort with MPR in 47% of patients with a low IFNg\u0026nbsp;score and a low PD-L1 (\u003cem\u003en\u003c/em\u003e=19) and 100% of the patients with high IFNg\u0026nbsp;score and a high PD-L1 (\u003cem\u003en\u003c/em\u003e=7). However, and in contrast to the PRADO cohort, only numerical differences were observed in EFS according to the combination of IFNg\u0026nbsp;score and PD-L1 status \u003cstrong\u003e(Extended Data Fig. 9a-d)\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eOther parameters associated with RFS, DMFS or OS\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDifferences in baseline clinical parameters, grade of toxicity, immunosuppressives used, and baseline biomarkers for patients with or without a recurrence observed during follow-up are displayed in \u003cstrong\u003eTable 1\u003c/strong\u003e. Univariable Cox regression analysis results for RFS, DMFS and OS are displayed in \u003cstrong\u003eFig. 3\u003c/strong\u003e,\u003cstrong\u003e\u0026nbsp;Extended Data Fig. 2\u0026nbsp;\u003c/strong\u003eand\u003cstrong\u003e\u0026nbsp;Extended Data Fig. 3\u003c/strong\u003e. Given the relatively small number of events observed for these endpoints, we highlighted parameters with either statistical significance (i.e. p-value \u0026lt; 0.05) or an estimated HR ≤0.5 or ≥2. Selected variables according to these criteria were pathologic response (improved RFS and DMFS for MPR patients compared to pPR or pNR), lymph node location (improved DMFS and OS for neck compared to axilla), use of prednisolone (poorer OS when used), use of second line immunosuppressants (shorted DMFS and OS when used), IFNg\u0026nbsp;(prolonged RFS, DMFS and OS if high IFNg), and PD-L1 (improved RFS, DMFS and OS if ≥1%). More patients with a \u003cem\u003eBRAF\u003c/em\u003e-mutant melanoma had a recurrence, but presence of a\u003cem\u003e\u0026nbsp;BRAF\u003c/em\u003e mutation in the tumor was not predictive for RFS, DMFS and OS in the univariable Cox-regression analysis \u003cstrong\u003e(Table 1, Fig. 3, Extended Data Fig. 2, Extended Data Fig. 3)\u003c/strong\u003e. These associations remain similar in size and/or statistical significance when adjusting for other parameters, one at a time, in multivariable analyses.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe conclusions remained the same when performing these analyses on multiply imputed data.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this five-year update of the PRADO-trial we present the first long-term survival outcomes of patients treated with neoadjuvant low-dose (1 mg kg\u003csup\u003e-1\u003c/sup\u003e)\u0026nbsp;ipilimumab and standard-dose (3 mg kg\u003csup\u003e-1\u003c/sup\u003e)\u0026nbsp;nivolumab, followed by response driven adjuvant therapy. These phase 2 study data are of interest as they may indicate what to expect from the long-term follow-up of the phase III NADINA trial\u0026nbsp;\u003csup\u003e1\u003c/sup\u003e. Additionally, these results might support re-imbursement initiatives for this neoadjuvant treatment approach in various countries.\u003c/p\u003e\n\u003cp\u003eIn line with several previous reports \u003csup\u003e14,17-19\u003c/sup\u003e, achieving MPR after neoadjuvant ICB remains a robust surrogate marker for long-term outcome. Of interest, our results indicate that\u0026nbsp;it might be safe to de-escalate surgery in patients with MPR in the ILN\u0026nbsp;\u003csup\u003e18,22\u003c/sup\u003e, as the long-term outcomes in PRADO are comparable to that of the OpACIN \u003csup\u003e19\u003c/sup\u003e and OpACIN-neo trial cohorts where patients all underwent TLND. The OMIT (NCT06754904) and MSLT-3 (NCT07049276) trials will deliver additional prospective/randomized data for omitting TLND in patients with MPR in the ILN.\u003c/p\u003e\n\u003cp\u003eIn contrast to earlier observed good outcomes for patients with a pPR\u0026nbsp;in neoadjuvant ICB trials\u0026nbsp;\u003csup\u003e16,23,25\u003c/sup\u003e, in PRADO, these\u0026nbsp;patients had worse outcomes than patients who had a pNR. Patients with a pNR had adjuvant therapy and pPR did not in PRADO. When comparing patients with a pPR from PRADO to patients with a pPR in OpACIN-neo\u003csup\u003e13,22\u003c/sup\u003e, different outcomes (higher EFS, RFS, DMFS and MSS landmarks in OpACIN-neo) are not likely driven by differences in patient-selection, measurable tumor burden, adverse event management or a difference in measured residual viable tumor at surgery. Differences in neoadjuvant or surgical regimen might drive these different outcomes, as higher doses of ipilimumab (in arm A and C OpACIN-neo) could induce better outcomes in these patients, particularly those with \u003cem\u003eBRAF\u003c/em\u003e mutant melanoma \u003csup\u003e26,27\u003c/sup\u003e. Another cause might be the differences in surgical regimen for patients who are treated with one surgery (TLND) in OpACIN-neo and two surgeries (ILN and TLND) in PRADO, as this might induce an immunosuppressive state \u003csup\u003e28,29\u003c/sup\u003e. Larger cohorts are needed to confirm these findings, as very few patients have a pPR within each trial.\u003c/p\u003e\n\u003cp\u003eWe observed no ongoing grade 3-4 irAEs at five years follow-up, suggesting that this regimen has a manageable safety profile. However, potentially quality-of-life-impairing irAEs with hypothyroidism or adrenal insufficiency requiring life-long hormone replacement therapy were observed in 22% and 7% of patients in the total cohort and 25% and 8% in patients with MPR. In addition, we observed that the use of prednisolone and second line immunosuppressants remained associated with a worse OS in the multivariable analysis. This association was also observed in patients with advanced melanoma treated with ipilimumab +/- nivolumab, where peak dose prednisolone or second-line immunosuppression for irAEs was associated with impaired survival in a retrospective analysis \u003csup\u003e30-32\u003c/sup\u003e. Future research and prospective trials should prioritize identifying patients in whom neoadjuvant treatment could be de-escalated, for example to anti-PD1 monotherapy, to prevent unnecessary side effects.\u003c/p\u003e\n\u003cp\u003eIn PRADO, the lower EFS in patients with a \u003cem\u003eBRAF\u003c/em\u003e-mutant melanoma was pre-dominantly driven by the patients developing distant metastasis before surgery. RFS and DMFS of patients with a \u003cem\u003eBRAF\u003c/em\u003e-mutant melanoma are better or similar compared to patients with a \u003cem\u003eBRAF\u003c/em\u003e-wild type melanoma in short term, most likely due to the 1 year of adjuvant dabrafenib plus trametinib in the patients with a pNR, but this is lost in years thereafter. Similar trends were observed in the patients treated with the same regimen (low-dose ipilimumab plus normal dose nivolumab) in OpACIN-neo. Our results suggest that patients with a \u003cem\u003eBRAF\u003c/em\u003e-mutant melanoma might benefit from high-dose neoadjuvant ipilimumab, which is in line with what has previously been observed in stage IV melanoma \u003csup\u003e26,27,33\u003c/sup\u003e. OS and MSS of patients with a \u003cem\u003eBRAF\u003c/em\u003e-mutant or a \u003cem\u003eBRAF\u003c/em\u003e wild type melanoma are comparable, which is most likely due to more options in subsequent treatment-lines. If confirmed in the NADINA trial \u003csup\u003e1\u003c/sup\u003e the \u003cem\u003eBRAF\u003c/em\u003e mutation status should be investigated further as a baseline biomarker for treatment escalation.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNot all patients achieve good outcomes on this regimen. Some patients would benefit from alternative/intensified neoadjuvant schemes to achieve equally promising long-term outcomes as those observed in patients with MPR. In line with previous trials \u003csup\u003e16,34\u003c/sup\u003e, the 10-gene IFNg\u0026nbsp;gene signature\u0026nbsp;\u003csup\u003e35\u003c/sup\u003e was predictive for MPR and long-term EFS. In contrast to what was observed in OpACIN-neo\u0026nbsp;\u003csup\u003e16\u003c/sup\u003e, PD-L1 expression was predictive and TMB was not predictive for long-term survival-outcomes. This inconsistency of TMB and PD-L1 as baseline biomarkers, warrants further analyses in larger (real world) cohorts\u0026nbsp;\u003csup\u003e23\u003c/sup\u003e. Critically, other factors including neoadjuvant regimen, extent of surgery (ILN versus upfront TLND) and adjuvant therapy (type and/or in all patients or response driven) should be concurrently analyzed to understand the impact of each of these factors and their interaction with tissue biomarkers.\u003c/p\u003e\n\u003cp\u003eThe three tested baseline biomarkers (TMB, IFNg, and PD-L1) might be helpful tools in the future to identify patients who are not likely to respond to this regimen at baseline and include them into innovative neoadjuvant trials. For example, our previous DONIMI trial (NCT04133948)\u003csup\u003e34\u003c/sup\u003e showed that this baseline biomarker can be analyzed\u0026nbsp;within clinically relevant timeframes to support neoadjuvant treatment decision-making. Another example is the NeoIReNi trial, that will use baseline biomarkers to enrich for those patients predicted to have non-MPR (NCT06999980). In addition, these promising baseline biomarkers should also be investigated in patient cohorts treated with other neoadjuvant treatments (e.g. anti-PD1 monotherapy, high-dose anti-CTLA4, anti-LAG3 or anti-TIGIT), since such analyses could help in personalizing neoadjuvant therapy for macroscopic melanoma further. The PRADO trial, and especially its biomarker subgroup analyses are limited by low patient numbers. Large, pooled analyses might deliver more significant data, that should be subsequently confirmed in prospective trials.\u003c/p\u003e\n\u003cp\u003eIn conclusion, this survival-update of PRADO shows promising long-term survival outcomes for patients treated with neoadjuvant ipilimumab and nivolumab, especially in patients who achieve MPR in the index lymph node. For patients without MPR, alternative neoadjuvant and adjuvant schemes are needed, and baseline biomarkers like the IFNg signature and PD-L1 expression might be promising biomarkers that could help identify these patients for escalation of therapy. Our data opens the possibility for biomarker-based personalization and response-driven personalization of surgery and adjuvant treatment.\u0026nbsp;\u003c/p\u003e"},{"header":"Methods ","content":"\u003cp\u003e\u003cstrong\u003eStudy design and participants\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe PRADO extension cohort from OpACIN-neo is an investigator-initiated phase II trial, testing 2 courses neoadjuvant ipilimumab 1 mg kg\u003csup\u003e-1\u003c/sup\u003e plus nivolumab 3 mg kg\u003csup\u003e-1\u003c/sup\u003e, followed by ILN response-based surgery (omitting the additional TLND in patients achieving MPR) and adjuvant therapy in patients achieving a pNR in the ILN (nivolumab for patients with a \u003cem\u003eBRAF\u003c/em\u003e-wildtype and dabrafenib + trametinib for patients with a \u003cem\u003eBRAF\u003c/em\u003e-mutant melanoma until week 52 +/- local radiotherapy). The detailed eligibility criteria, trial design, ethical approval and the first responses (pathologic responses, EFS, RFS, DMFS and OS) have been published earlier\u003csup\u003e22\u003c/sup\u003e. The trial enrolled participants in Australia at Melanoma Institute Australia (MIA) and at several Dutch centers [Netherlands Cancer Institute (NKI), Leiden University Medical Center (LUMC), Erasmus Medical Center (EMC), University Medical Center Utrecht (UMCU), and University Medical Center Groningen (UMCG)].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePathologic response at week 6 was assessed according to INMC guidelines \u003csup\u003e24\u003c/sup\u003e and was categorized into MPR (≤10% residual viable tumor, which included patients with complete response (pCR; 0% residual viable tumor) and near-pCR (1 – ≤10% residual viable tumor), pPR (\u0026gt;10 – ≤50% residual viable tumor) or pNR (\u0026gt;50% residual viable tumor). Follow-up consisted of a radiologic assessment with CT or PET-CT, physical examination and laboratory testing every 12 weeks for 2 years post-surgery, and in year 3, 4 and 5 according to institute standards. Patients experiencing progression prior to surgery or recurrence after surgery, remained in the trial and were further followed for DMFS (in case of local recurrence only) and OS.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eEndpoints of the PRADO trial were pathologic response rate upon neoadjuvant two cycles ipilimumab 1 mg kg\u003csup\u003e-1\u003c/sup\u003e plus nivolumab 3 mg kg\u003csup\u003e-1\u003c/sup\u003e, to confirm the efficacy of arm B of the OpACIN-neo trail, and 24-month RFS of patients achieving MPR or pNR, to determine whether the TLND could be safely omitted in patients achieving MPR and to determine efficacy of adding adjuvant treatment in patients with a pNR. Secondary endpoints were short-term grade 3–4 irAEs, comparing surgical adverse events, radiologic response, DMFS, EFS, OS, health related quality of life, ongoing long-term irAEs, and biomarker analyses.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe data cutoff for collection of the data presented here was on January 6, 2025.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eValidation cohort\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe investigator-initiated, randomized, phase II OpACIN-neo trial is used as a validation cohort in this manuscript, as the PRADO trial was designed as an extension cohort of the OpACIN-neo. The detailed eligibility criteria, trial design, ethical approval and the first responses (pathologic responses, EFS, RFS, DMFS and OS) are described in earlier publications \u003csup\u003e13,16,19\u003c/sup\u003e. Patients were randomized 1:1:1 to receive either two cycles of ipilimumab 3 mg kg\u003csup\u003e-1\u003c/sup\u003e plus nivolumab 1 mg kg\u003csup\u003e-1\u003c/sup\u003e every 3 weeks (arm A), two cycles of ipilimumab 1 mg kg\u003csup\u003e-1\u003c/sup\u003e plus nivolumab 3 mg kg\u003csup\u003e-1\u003c/sup\u003e every 3 weeks (arm B) or two cycles of ipilimumab 3 mg kg\u003csup\u003e-1\u003c/sup\u003e every 3 weeks, directly followed by two cycles nivolumab 3 mg kg\u003csup\u003e-1\u003c/sup\u003e every 2 weeks (arm C); all patients had a therapeutic lymph node dissection planned in week 6. None of the patients received any adjuvant treatment.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDNA and RNA sequencing and analyses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFrom 81/99 (81%) baseline patient samples declared to be sufficient fresh frozen pretreatment tumor material (≥30% tumor cells on an H\u0026amp;E-stained cryostat frozen section) RNA and DNA were isolated. The RNA and DNA were simultaneously isolated with the AllPrep DNA/RNA/miRNA Universal isolation kit (Qiagen, 80224) using the QIAcube. Furthermore, germline DNA was isolated from peripheral blood mononuclear cells using AllPrep DNA/RNA/miRNA Universal isolation kit (Qiagen, 80224) to be able to filter out single-nucleotide polymorphisms when determining TMB. In total, baseline biopsy material of \u003cem\u003en\u003c/em\u003e=80 samples for RNA-sequencing and \u003cem\u003en\u003c/em\u003e=75 samples for DNA-sequencing were available for analysis. For OpACIN-neo, a detailed description of the tissue processing and analysis of the RNA and DNA sequencing has been described in detail elsewhere \u003csup\u003e16\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eMessenger RNA (mRNA) sequencing and whole-exome sequencing of the PRADO samples were performed by CeGaT. Initial sample quality control was performed with Qubit dsNDA BR or HS(Thermo Fisher) for the DNA sequencing data and Qubit RNA (Thermo Fisher) \u0026nbsp; \u0026amp; Bioanalyzer RNA (Agilent) for the RNA sequencing . Strand-specific libraries were generated using the TruSeq Stranded mRNA sample preparation kit (Illumina) and sequenced with 2x 100bp reads on the NovaSeq 6000 system. Demultiplexing of the sequencing reads was performed with Illumina bcl2fastq (2.20). Adapters were trimmed with Skewer (version 0.2.2) \u003csup\u003e36\u003c/sup\u003e. The quality of FASTQ files was analyzed with FastQC (version 0.11.5-cegat). FASTQ files were mapped to the human reference genome (GRCh38.v82) using STAR (version 2.7.3a) with default settings \u003csup\u003e37\u003c/sup\u003e. Raw count data generated with HTseq-count (version 0.12.4) \u003csup\u003e38\u003c/sup\u003e were normalized for sequencing depth and RNA composition using the median of ratio’s method implemented in DESeq2 (version 1.40.1) \u003csup\u003e39\u003c/sup\u003e and log2-transformed. For the downstream analysis the data were analyzed using R (version 4.3.0). Log2-transformed normalized gene expression data was gene-wise median centered by subtracting each element of a row with the median of that row to improve Pearson’s correlation distances.\u003c/p\u003e\n\u003cp\u003eThe IFNg\u0026nbsp;signature score was determined by calculating the average expression z-score of the 10 genes that compose the IFNg\u0026nbsp;signature (STAT1, CXCL9, CXCL10, HLA-DRA, GZMA, PRF1, IDO1, CXCL11, CCR5, IFNG)\u003csup\u003e35\u003c/sup\u003e. Due to the batch-effect between the RNA-sequencing data from PRADO and OpACIN-neo separate cutoffs were determined. The optimal cutoff for the PRADO cohort was calculated by the maximize-metric function of cutpointr \u0026nbsp;(version 1.1.2), using major pathologic response (MPR) status as the binary outcome. For OpACIN-neo the previously calculated cutoff for IFNg\u0026nbsp;was used in this manuscript\u0026nbsp;\u003csup\u003e16\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eExome libraries were generated using 50ng with the Twist Human Core Exome Plus (Twist Biosciences). The libraries were sequenced with 2 x 100-bp reads on a NovaSeq 6000 System according to the manufacturer’s protocols, with a sequence quality Q30 value of 90%. \u0026nbsp;Data were analyzed in CeGaT exome analysis pipeline. Briefly, de-multiplexing of the sequencing reads was performed with Illumina bcl2fastq (version 2.20). \u0026nbsp;The quality of FASTQ files was analyzed with FastQC (version 0.11.5-cegat) and multiQC (version 1.12)\u003csup\u003e40\u003c/sup\u003e. We used the nf-core/sarek pipeline v3.5.1 \u003csup\u003e41\u003c/sup\u003e to analyze tumor and normal FASTQ files for the identification of Single Nucleotide Polymorphisms (SNPs) and small insertions and deletions (INDELs). The whole exome sequencing data were first preprocessed using FASTP. Subsequent alignment of the reads to the human reference genome (GRCh38) was performed using Burrows-Wheeler Aligner (BWA-MEM). Duplicate reads were marked, and base quality scores recalibrated using GATK MarkDuplicates, GATK BaseRecalibrator, and GATK ApplyBQSR. SNPs and small INDELs were called using MuTect2, and variants were annotated with Ensembl VEP. For further details, including the specific versions of each tool, we refer to the Sarek documentation.\u003c/p\u003e\n\u003cp\u003eUsing the VEP-annotated VCF files, we calculated the Tumor Mutational Burden (TMB) with cyvcf2 (version 0.31.1) in Python (version 3.12.5). Variants were filtered to include only those that passed the MuTect2 call, and having a Variant Allele Frequency of at least 0.05 (5% variant read depth). The TMB was calculated by summarizing the total number of non-synonymous mutations in the filtered VCF per patient. Mutations ≤ 2 were excluded from the analysis. The optimal TMB cut-off was identified with the maximize_metric method in cutpointr (v 1.1.2), using major pathologic response (MPR) status as the binary outcome. The TMB of the PRADO and OpACIN-neo samples by using this pipeline and the optimal TMB cut-off calculated based on the patients treated in OpACIN-neo arm B and PRADO, as they were treated with the same neoadjuvant regimen (neoadjuvant ipilimumab 1 mg kg\u003csup\u003e-1\u003c/sup\u003e plus nivolumab 3 mg kg\u003csup\u003e-1\u003c/sup\u003e).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAnti-PDL1\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFFPE blocks of baseline tumor samples were used for PD-L1 immunohistochemistry staining using the BenchMark Ultra autostainer (Ventana Medical Systems). Briefly, paraffin sections were cut at 3 µm, heated at 75°C for 28 minutes and deparaffinized in the instrument with EZ prep solution (Ventana Medical Systems). Heat-induced antigen retrieval was carried out using Cell Conditioning 1 (CC1, Ventana Medical Systems) for 48 minutes at 95°C. Anti-PD-L1 mAb (clone 22C3, DAKO) was used in an 1:40 dilution for PD-L1 staining. Bound antibody was visualized using the OptiView DAB Detection Kit (Ventana Medical Systems). Slides were counterstained with Hematoxylin II and Bluing Reagent (Ventana Medical Systems). After staining slides were scanned with the P1000 (Sysmex) system. An experienced pathologist who was blinded to clinical outcome determined the tumor proportion score (TPS; the percentage of tumor cells with c­­­omplete or partial membranous staining at any intensity out of all tumor cells) using Slide Score (\u003ca href=\"https://checkpoint.url-protection.com/v1/r04/url?o=http%3A//www.slidescore.com\u0026amp;g=Y2UxZGJjNDMwMjI2NDFkMw==\u0026amp;h=NjZhMzNhMDRiYWQ0MWVmZmRmZTFhNWEzMDI0NDU4YWUxYmNlOGI4ZTFhY2ZmYTMxOTExMTUyMzllNWI1ODczOQ==\u0026amp;p=Y3A0YTptZWxhbm9tYWluc3RpdHVlOmM6bzo5ZWJiODE3YjU1YjRkMzA0ZTA5ZjhjZGU5ZDZmMDY3ZTo3OnA6VA==\"\u003ewww.slidescore.com\u003c/a\u003e). The TPS was classified as being \u0026lt;1%, 1-50%, \u0026gt;50% or not evaluable (due to pigmentation or little to no tumor cells).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analyses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDifferences in patient characteristics were assessed using Mann-Whitney’s test and Fisher’s exact test. Patients with an event before surgery were excluded from RFS and DMFS analysis\u003cstrong\u003e\u0026nbsp;(Extended Data Fig. 10)\u003c/strong\u003e. Associations between baseline parameters and survival endpoints were estimated using univariable and multivariable Cox regression models. Pathologic response was measured post-baseline and hence not considered for OS analyses. Immune related adverse events, use of prednisolone and \u0026nbsp; second line immunosuppressants were modelled as time-dependent covariates.\u003c/p\u003e\n\u003cp\u003ePatients from the biospecimen cohort were included for survival-analysis of the different biomarker subgroups (EFS, RFS, DMFS, OS and MSS). One patient that did not undergo surgery (\u003cem\u003en\u003c/em\u003e=1) was excluded from the subgroup-analysis of patients with RNA-sequencing data, DNA-sequencing data, PD-L1 expression and pathologic response available. A detailed overview is demonstrated in \u003cstrong\u003eExtended Data Fig. 10.\u0026nbsp;\u003c/strong\u003eSpearman’s correlation coefficient was estimated for pairs of biomarkers.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe reverse Kaplan-Meier method was used for estimating median follow-up time. The Kaplan-Meier method was used to generate EFS, RFS, DMFS, OS and MSS curves and to calculate the 5-year landmark survival estimates for the clinical cohort, also stratified by pathologic response and biomarker values. Overall comparisons in survival outcomes across the subgroups were tested using the log-rank test. Univariable Cox regression analyses were performed in forest plots, and relevant characteristics were further analyzed with multivariable Cox regression. Proportionality of hazards was assessed using Schoenfeld residual plots. Imputation of missing data by best- and worst-case scenarios was performed as sensitivity analysis, as well as using multivariate imputation by chained equations. No adjustments for multiplicity were performed. Statistical analyses were performed using R software (version 4.2.2).\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cu\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eRNA-sequencing and DNA-sequencing data generated during the study will be deposited in the European Genome-phenome Archive (EGA) for PRADO under the accession codes EGAS50000000268 (DNA) or\u0026nbsp;EGAS00001007601 (RNA). For OpACIN-neo under the accession codes EGAS00001004832 (DNA) or\u0026nbsp;EGAS00001004833 (RNA). To minimize the risk of patient re-identification, de-identified individual patient-level clinical data are available under restricted access. Upon scientifically sound request, data access can be obtained via the NKI\u0026rsquo;s scientific repository at [email protected], which will contact the corresponding author (C.U.B.). Data requests will be reviewed by the institutional review board of the NKI and will require the requesting researcher to sign a data access agreement with the NKI.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding Acknowledgement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to thank the patients and their families for participating in these trials.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe authors gratefully acknowledge the support of all colleagues from Melanoma Institute Australia, Royal Prince Alfred Hospital, Royal North Shore and Mater Hospital, University Medical Center Utrecht, Erasmus Medical Center, Leiden University Medical Center, University Medical Center Groningen and the Netherlands Cancer Institute; B. Schermers from Sirius Medical for providing magnetic seeds and a magnetic seed detector; S. Vanhoutvin for financial management; M.J. Gregorio, K. de Joode, A.M. van Eggermond, E.H.J. Tonk and J. Kingma-Veenstra for administrative support and data management; and A Evans and B Stegenga from Bristol Myers Squibb for scientific input and long-term support of our neoadjuvant immunotherapy efforts.\u003c/p\u003e\n\u003cp\u003eA.M.M. is supported by an NHRMC Investigator Grant. R.P.M.S. is supported by Melanoma Institute Australia. R.A.S. is supported by a National Health and Medical Research Council of Australia (NHMRC) Investigator Grant (2022/GNT2018514). G.V.L. is supported by an\u0026nbsp;NHMRC Investigator Grant and the University of Sydney Medical Foundation.\u0026nbsp;Financial support for the study was provided by Bristol-Myers Squibb.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eC.U.B. designed the trial and had written the protocol. The final amendment of the PRADO extension was written by \u0026nbsp;E.A.R. together with C.U.B. in 20th Workshop on \u0026lsquo;Methods in Clinical Cancer Research\u0026rsquo; (Zeist, Netherlands). A.C.J.v.A. and G.V.L. reviewed the trial protocol. I.L.M.R., A.M.M., R.P.M.S., J.M.V., W.v.H., E.A.R., E.K., A.A.M.v.d.V., K.P.M.S., H.E., G.A.P.H., J.A.v.d.H., D.J.G., A.J.W., J.M.L., W.M.C.K., C.Z., A.Bruining, A.A.M., T.E.P., K.F.S., S.Chong, A.S., J.B.A.G.H., A.v.A., G.V.L., and C.U.B. have included and treated patients, and collected clinical data. A.T.A., L.G.G.-O. and A.v.d.W. contributed to central and local data management. M.G. was a clinical\u0026nbsp;project manager of the trial. S.Cornelissen performed DNA and RNA isolations. A.Broeks coordinated and contributed to translational laboratory logistics and immunohistochemistry and molecular laboratory work. P.D. and J.R. performed the bioinformatics analysis. A.J.C., R.V.R., R.A.S. and B.v.d.W. reviewed and scored the pathology of all cases. L.L.H. and M.Y.L. performed the statistical analyses. L.L.H. and C.U.B. wrote the first draft of the manuscript. All authors interpreted the data, reviewed the manuscript and approved the final version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo author has received financial support for the work on this manuscript, and no medical writer was involved at any stage of the preparation of this manuscript. A.M.M. has served on advisory boards for BMS, MSD, Novartis, Roche, Pierre-Fabre and QBiotics. R.P.M.S. has received honoraria for advisory board participation from MSD and Clinical Laboratories Pty Ltd. W.J.v.H. has received speakers honorarium regeneron, Sanofi, MSD, Belpharma, novartis, reports an advisory role Belpharma and has received a research grant from Amgen. E.K.A. has consultancy/advisory relationships with Delcath, Immunocore, and Lilly, and has received research grants unrelated to this paper from Bristol Myers Squibb, Delcath, Novartis, and Pierre-Fabre. These grants are unrelated to current work and are paid to the institute. A.A.M.v.d.V., received travel fees from Ipsen and consultancies fees (all paid to the institute) from BMS, MSD, Ipsen, Eisai, Pfizer, Novartis, Sanofi, Roche and Pierre Fabre. K.P.M.S. has consultancy/advisory relationships with Abbvie, Sairopa, has received research funding TigaTx, Bristol Myers Squibb, Philips, Genmab, Pierre Fabre, and has received honoraria from Bristol Myers Squibb (all paid to the institute). H.E. has received institutional research grants from SkyLineDx, BMS, Novartis and Pierre Fabre, speaker honorarium from Janssen, not personal speaker honorarium but to the hospital from BMS and Novartis, and served as expert board for Pierre Fabre and BMS. G.A.P.H consultancy/advisory relationships with Amgen, Bristol-Myers Squibb, Roche, MSD, Novartis, Sanofi, Pierre Fabre and has received research grants from Bristol-Myers Squibb, Seerave (all paid to the institute). S. Ch\u0026rsquo;ngreceives fees for professional services provided to MSD and SkylineDx. J.B.A.G.H. reports an advisory role for Achilles Therapeutics, AstraZeneca, BioNTech, Bristol-Myers Squibb, Immunocore, Instil Bio, Iovance Biotherapeutics, Ipsen, Molecular Partners, MSD Oncology, Neogene Therapeutics, Novartis, Roche/Genentech, Sanofi, Sāstra, Third Rock Ventures and T-Knife; has received research funding, paid to the institute, from Amgen, Asher Biotherapeutics, BioNTech, Bristol-Myers Squibb, MSD, Neon Therapeutics, Novartis; and is stockowner of Neogene Therapeutics and Sāstra. R.V.R. has received honoraria from Merck Sharp \u0026amp; Dohme. R.A.S. has received fees for professional services from SkylineDx BV, IO Biotech ApS, MetaOptima Technology Inc., F. Hoffmann-La Roche Ltd, Evaxion, Provectus Biopharmaceuticals Australia, Qbiotics, Novartis, Merck Sharp \u0026amp; Dohme, NeraCare, AMGEN Inc., Bristol-Myers Squibb, Myriad Genetics, GlaxoSmithKline. A.C.J.v.A. reports an advisory role in Amgen, Bristol-Myers Squibb, Daiichi Sankyo, Genmab, Menarini Silicon Biosystems, Merck Serono-Pfizer, MSD Merck, Neracare, Novartis, Pierre Fabre, Provectus, Replimune, Sanofi, Sirius Medical, SkylineDx, 4SC; has received research funding from Amgen, Merck Serono \u0026ndash; Pfizer, SkylineDx. G.V.L. is consultant advisor for Agenus, Amgen, Array Biopharma, AstraZeneca, Bayer HealthCare Pharmaceuticals Inc, BioNTech SE, Boehringer Ingelheim International GmbH, Bristol Myers Squibb, Evaxion Biotech A/S, Fortiva Biologics (USA) Inc, GI Innovation Inc, Hexal AG (Sandoz Company), Highlight Therapeutics S.L., IOBiotech, Immunocore Ireland Limited, Innovent Biologics USA Inc, Iovance Biotherapeutics Inc, Merck Sharpe \u0026amp; Dohme, Novartis Pharma AG, OncoSec Medical Australia, PHMR Limited, Pierre Fabre, Regeneron Pharmaceuticals, Scancell Limited, SkylineDX BV. C.U.B.reports he has received compensation for advisory roles from BMS, MSD, Roche, Novartis, GSK, AZ, Pfizer, Lilly, GenMab, Pierre Fabre, Third Rock Ventures, Senya, received research funding from BMS, Novartis, NanoString, 4SC and reports to be co-founder of Immagene BV. All compensations and funding for C.U.B. were paid to the institute, except for Third Rock Ventures and Immagene. The other authors declare no conflicts of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBlank, C.U.\u003cem\u003e, et al.\u003c/em\u003e Neoadjuvant Nivolumab and Ipilimumab in Resectable Stage III Melanoma. \u003cem\u003eThe New England journal of medicine\u003c/em\u003e (2024).\u003c/li\u003e\n\u003cli\u003ePatel, S.P.\u003cem\u003e, et al.\u003c/em\u003e Neoadjuvant-Adjuvant or Adjuvant-Only Pembrolizumab in Advanced Melanoma. \u003cem\u003eThe New England journal of medicine\u003c/em\u003e \u003cstrong\u003e388\u003c/strong\u003e, 813-823 (2023).\u003c/li\u003e\n\u003cli\u003eForde, P.M.\u003cem\u003e, et al.\u003c/em\u003e Neoadjuvant PD-1 Blockade in Resectable Lung Cancer. \u003cem\u003eThe New England journal of medicine\u003c/em\u003e (2018).\u003c/li\u003e\n\u003cli\u003eVos, J.L.\u003cem\u003e, et al.\u003c/em\u003e Neoadjuvant immunotherapy with nivolumab and ipilimumab induces major pathological responses in patients with head and neck squamous cell carcinoma. \u003cem\u003eNature communications\u003c/em\u003e \u003cstrong\u003e12\u003c/strong\u003e, 7348 (2021).\u003c/li\u003e\n\u003cli\u003eChalabi, M.\u003cem\u003e, et al.\u003c/em\u003e Neoadjuvant immunotherapy leads to pathological responses in MMR-proficient and MMR-deficient early-stage colon cancers. \u003cem\u003eNature medicine\u003c/em\u003e \u003cstrong\u003e26\u003c/strong\u003e, 566-576 (2020).\u003c/li\u003e\n\u003cli\u003evan Dijk, N.\u003cem\u003e, et al.\u003c/em\u003e Preoperative ipilimumab plus nivolumab in locoregionally advanced urothelial cancer: the NABUCCO trial. \u003cem\u003eNature medicine\u003c/em\u003e \u003cstrong\u003e26\u003c/strong\u003e, 1839-1844 (2020).\u003c/li\u003e\n\u003cli\u003eCascone, T.\u003cem\u003e, et al.\u003c/em\u003e Neoadjuvant chemotherapy plus nivolumab with or without ipilimumab in operable non-small cell lung cancer: the phase 2 platform NEOSTAR trial. \u003cem\u003eNature medicine\u003c/em\u003e \u003cstrong\u003e29\u003c/strong\u003e, 593-604 (2023).\u003c/li\u003e\n\u003cli\u003eSchmid, P.\u003cem\u003e, et al.\u003c/em\u003e Pembrolizumab for Early Triple-Negative Breast Cancer. \u003cem\u003eThe New England journal of medicine\u003c/em\u003e \u003cstrong\u003e382\u003c/strong\u003e, 810-821 (2020).\u003c/li\u003e\n\u003cli\u003eLiu, J.\u003cem\u003e, et al.\u003c/em\u003e Improved Efficacy of Neoadjuvant Compared to Adjuvant Immunotherapy to Eradicate Metastatic Disease. \u003cem\u003eCancer discovery\u003c/em\u003e \u003cstrong\u003e6\u003c/strong\u003e, 1382-1399 (2016).\u003c/li\u003e\n\u003cli\u003eBlank, C.U.\u003cem\u003e, et al.\u003c/em\u003e Neoadjuvant versus adjuvant ipilimumab plus nivolumab in macroscopic stage III melanoma. \u003cem\u003eNature medicine\u003c/em\u003e \u003cstrong\u003e24\u003c/strong\u003e, 1655-1661 (2018).\u003c/li\u003e\n\u003cli\u003eHuang, A.C.\u003cem\u003e, et al.\u003c/em\u003e A single dose of neoadjuvant PD-1 blockade predicts clinical outcomes in resectable melanoma. \u003cem\u003eNature medicine\u003c/em\u003e \u003cstrong\u003e25\u003c/strong\u003e, 454-461 (2019).\u003c/li\u003e\n\u003cli\u003eAmaria, R.N.\u003cem\u003e, et al.\u003c/em\u003e Neoadjuvant immune checkpoint blockade in high-risk resectable melanoma. \u003cem\u003eNature medicine\u003c/em\u003e \u003cstrong\u003e24\u003c/strong\u003e, 1649-1654 (2018).\u003c/li\u003e\n\u003cli\u003eRozeman, E.A.\u003cem\u003e, et al.\u003c/em\u003e Identification of the optimal combination dosing schedule of neoadjuvant ipilimumab plus nivolumab in macroscopic stage III melanoma (OpACIN-neo): a multicentre, phase 2, randomised, controlled trial. \u003cem\u003eThe lancet oncology\u003c/em\u003e \u003cstrong\u003e20\u003c/strong\u003e, 948-960 (2019).\u003c/li\u003e\n\u003cli\u003eLucas, M.W.\u003cem\u003e, et al.\u003c/em\u003e LBA42 Distant metastasis-free survival of neoadjuvant nivolumab plus ipilimumab versus adjuvant nivolumab in resectable, macroscopic stage III melanoma: The NADINA trial. \u003cem\u003eAnnals of Oncology\u003c/em\u003e \u003cstrong\u003e35\u003c/strong\u003e, S1233-S1234 (2024).\u003c/li\u003e\n\u003cli\u003eCristescu, R.\u003cem\u003e, et al.\u003c/em\u003e Pan-tumor genomic biomarkers for PD-1 checkpoint blockade-based immunotherapy. \u003cem\u003eScience (New York, N.Y.)\u003c/em\u003e \u003cstrong\u003e362\u003c/strong\u003e, eaar3593 (2018).\u003c/li\u003e\n\u003cli\u003eRozeman, E.A.\u003cem\u003e, et al.\u003c/em\u003e Survival and biomarker analyses from the OpACIN-neo and OpACIN neoadjuvant immunotherapy trials in stage III melanoma. \u003cem\u003eNature medicine\u003c/em\u003e \u003cstrong\u003e27\u003c/strong\u003e, 256-263 (2021).\u003c/li\u003e\n\u003cli\u003eMenzies, A.M.\u003cem\u003e, et al.\u003c/em\u003e Pathological response and survival with neoadjuvant therapy in melanoma: a pooled analysis from the International Neoadjuvant Melanoma Consortium (INMC). \u003cstrong\u003e37\u003c/strong\u003e, 9503-9503 (2019).\u003c/li\u003e\n\u003cli\u003eReijers, I.L.M.\u003cem\u003e, et al.\u003c/em\u003e Impact of personalized response-directed surgery and adjuvant therapy on survival after neoadjuvant immunotherapy in stage III melanoma: Comparison of 3-year data from PRADO and OpACIN-neo. \u003cem\u003eEur J Cancer\u003c/em\u003e \u003cstrong\u003e214\u003c/strong\u003e, 115141 (2025).\u003c/li\u003e\n\u003cli\u003eVersluis, J.M.\u003cem\u003e, et al.\u003c/em\u003e Survival update of neoadjuvant ipilimumab plus nivolumab in macroscopic stage III melanoma in the OpACIN and OpACIN-neo trials. \u003cem\u003eAnn Oncol\u003c/em\u003e \u003cstrong\u003e34\u003c/strong\u003e, 420-430 (2023).\u003c/li\u003e\n\u003cli\u003eReijers, I.L.M.\u003cem\u003e, et al.\u003c/em\u003e Representativeness of the Index Lymph Node for Total Nodal Basin in Pathologic Response Assessment After Neoadjuvant Checkpoint Inhibitor Therapy in Patients With Stage III Melanoma. \u003cem\u003eJAMA Surg\u003c/em\u003e \u003cstrong\u003e157\u003c/strong\u003e, 335-342 (2022).\u003c/li\u003e\n\u003cli\u003eSchermers, B.\u003cem\u003e, et al.\u003c/em\u003e Surgical removal of the index node marked using magnetic seed localization to assess response to neoadjuvant immunotherapy in patients with stage III melanoma. \u003cem\u003eThe British journal of surgery\u003c/em\u003e \u003cstrong\u003e106\u003c/strong\u003e, 519-522 (2019).\u003c/li\u003e\n\u003cli\u003eReijers, I.L.M.\u003cem\u003e, et al.\u003c/em\u003e Personalized response-directed surgery and adjuvant therapy after neoadjuvant ipilimumab and nivolumab in high-risk stage III melanoma: the PRADO trial. \u003cem\u003eNature medicine\u003c/em\u003e \u003cstrong\u003e28\u003c/strong\u003e, 1178-1188 (2022).\u003c/li\u003e\n\u003cli\u003eLong, G.V.\u003cem\u003e, et al.\u003c/em\u003e LBA41 Long-term survival with neoadjuvant therapy in melanoma: Updated pooled analysis from the International Neoadjuvant Melanoma Consortium (INMC). \u003cem\u003eAnnals of Oncology\u003c/em\u003e \u003cstrong\u003e35\u003c/strong\u003e, S1232 (2024).\u003c/li\u003e\n\u003cli\u003eTetzlaff, M.T.\u003cem\u003e, et al.\u003c/em\u003e Pathological assessment of resection specimens after neoadjuvant therapy for metastatic melanoma. \u003cem\u003eAnn Oncol\u003c/em\u003e \u003cstrong\u003e29\u003c/strong\u003e, 1861-1868 (2018).\u003c/li\u003e\n\u003cli\u003eMenzies, A.M.\u003cem\u003e, et al.\u003c/em\u003e Pathological response and survival with neoadjuvant therapy in melanoma: a pooled analysis from the International Neoadjuvant Melanoma Consortium (INMC). \u003cem\u003eNature medicine\u003c/em\u003e \u003cstrong\u003e27\u003c/strong\u003e, 301-309 (2021).\u003c/li\u003e\n\u003cli\u003eWolchok, J.D.\u003cem\u003e, et al.\u003c/em\u003e Final, 10-Year Outcomes with Nivolumab plus Ipilimumab in Advanced Melanoma. \u003cem\u003eNew England Journal of Medicine\u003c/em\u003e \u003cstrong\u003e392\u003c/strong\u003e, 11-22 (2025).\u003c/li\u003e\n\u003cli\u003eAscierto, P.A.\u003cem\u003e, et al.\u003c/em\u003e Ipilimumab 10 mg/kg versus ipilimumab 3 mg/kg in patients with unresectable or metastatic melanoma: a randomised, double-blind, multicentre, phase 3 trial. \u003cem\u003eThe lancet oncology\u003c/em\u003e \u003cstrong\u003e18\u003c/strong\u003e, 611-622 (2017).\u003c/li\u003e\n\u003cli\u003eAngka, L.\u003cem\u003e, et al.\u003c/em\u003e Natural Killer Cell IFN\u0026gamma; Secretion is Profoundly Suppressed Following Colorectal Cancer Surgery. \u003cem\u003eAnnals of surgical oncology\u003c/em\u003e \u003cstrong\u003e25\u003c/strong\u003e, 3747-3754 (2018).\u003c/li\u003e\n\u003cli\u003eLeaver, H.A., Craig, S.R., Yap, P.L. \u0026amp; Walker, W.S. Lymphocyte responses following open and minimally invasive thoracic surgery. \u003cem\u003eEur J Clin Invest\u003c/em\u003e \u003cstrong\u003e30\u003c/strong\u003e, 230-238 (2000).\u003c/li\u003e\n\u003cli\u003evan Not, O.J.\u003cem\u003e, et al.\u003c/em\u003e Association of Immune-Related Adverse Event Management With Survival in Patients With Advanced Melanoma. \u003cem\u003eJAMA Oncol\u003c/em\u003e \u003cstrong\u003e8\u003c/strong\u003e, 1794-1801 (2022).\u003c/li\u003e\n\u003cli\u003eVerheijden, R.J.\u003cem\u003e, et al.\u003c/em\u003e Corticosteroids for Immune-Related Adverse Events and Checkpoint Inhibitor Efficacy: Analysis of Six Clinical Trials. \u003cem\u003eJ Clin Oncol\u003c/em\u003e \u003cstrong\u003e42\u003c/strong\u003e, 3713-3724 (2024).\u003c/li\u003e\n\u003cli\u003eVerheijden, R.J.\u003cem\u003e, et al.\u003c/em\u003e Corticosteroids and other immunosuppressants for immune-related adverse events and checkpoint inhibitor effectiveness in melanoma. \u003cem\u003eEur J Cancer\u003c/em\u003e \u003cstrong\u003e207\u003c/strong\u003e, 114172 (2024).\u003c/li\u003e\n\u003cli\u003eNot, O.J.v.\u003cem\u003e, et al.\u003c/em\u003e \u0026lt;i\u0026gt;BRAF\u0026lt;/i\u0026gt; and \u0026lt;i\u0026gt;NRAS\u0026lt;/i\u0026gt; Mutation Status and Response to Checkpoint Inhibition in Advanced Melanoma. \u003cem\u003eJCO Precision Oncology\u003c/em\u003e, e2200018 (2022).\u003c/li\u003e\n\u003cli\u003eReijers, I.L.M.\u003cem\u003e, et al.\u003c/em\u003e IFN-gamma signature enables selection of neoadjuvant treatment in patients with stage III melanoma. \u003cem\u003eJ Exp Med\u003c/em\u003e \u003cstrong\u003e220\u003c/strong\u003e(2023).\u003c/li\u003e\n\u003cli\u003eAyers, M.\u003cem\u003e, et al.\u003c/em\u003e IFN-gamma-related mRNA profile predicts clinical response to PD-1 blockade. \u003cem\u003eThe Journal of clinical investigation\u003c/em\u003e \u003cstrong\u003e127\u003c/strong\u003e, 2930-2940 (2017).\u003c/li\u003e\n\u003cli\u003eJiang, H., Lei, R., Ding, S.W. \u0026amp; Zhu, S. Skewer: a fast and accurate adapter trimmer for next-generation sequencing paired-end reads. \u003cem\u003eBMC Bioinformatics\u003c/em\u003e \u003cstrong\u003e15\u003c/strong\u003e, 182 (2014).\u003c/li\u003e\n\u003cli\u003eDobin, A.\u003cem\u003e, et al.\u003c/em\u003e STAR: ultrafast universal RNA-seq aligner. \u003cem\u003eBioinformatics\u003c/em\u003e \u003cstrong\u003e29\u003c/strong\u003e, 15-21 (2013).\u003c/li\u003e\n\u003cli\u003ePutri, G.H., Anders, S., Pyl, P.T., Pimanda, J.E. \u0026amp; Zanini, F. Analysing high-throughput sequencing data in Python with HTSeq 2.0. \u003cem\u003eBioinformatics\u003c/em\u003e \u003cstrong\u003e38\u003c/strong\u003e, 2943-2945 (2022).\u003c/li\u003e\n\u003cli\u003eLove, M.I., Huber, W. \u0026amp; Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. \u003cem\u003eGenome biology\u003c/em\u003e \u003cstrong\u003e15\u003c/strong\u003e, 550 (2014).\u003c/li\u003e\n\u003cli\u003eEwels, P., Magnusson, M., Lundin, S. \u0026amp; K\u0026auml;ller, M. MultiQC: summarize analysis results for multiple tools and samples in a single report. \u003cem\u003eBioinformatics\u003c/em\u003e \u003cstrong\u003e32\u003c/strong\u003e, 3047-3048 (2016).\u003c/li\u003e\n\u003cli\u003eHanssen, F.\u003cem\u003e, et al.\u003c/em\u003e Scalable and efficient DNA sequencing analysis on different compute infrastructures aiding variant discovery. \u003cem\u003eNAR Genom Bioinform\u003c/em\u003e \u003cstrong\u003e6\u003c/strong\u003e, lqae031 (2024).\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Table","content":"\u003cp\u003e\u003cstrong\u003eTable 1. Characteristics for patients with or without recurrence observed at 5 years follow-up \u0026nbsp;\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"614\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 38.355%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.3909%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAll\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(\u003cem\u003en\u003c/em\u003e=99)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.7557%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRecurrence\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(\u003cem\u003en\u003c/em\u003e=27)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.4984%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo Recurrence* (\u003cem\u003en\u003c/em\u003e=72)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 100%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBaseline characteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 38.355%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eContinent\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e(%)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; Europe\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; Australia\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.3909%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 65 (66)\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 34 (34)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.7557%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 20 (74)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 7 (26)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.4984%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;45 (63)\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;27 (38)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 38.355%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge (median (IQR))\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.3909%;\"\u003e\n \u003cp\u003e58.0 [51.0- 69.5]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 24.7557%;\"\u003e\n \u003cp\u003e\u0026nbsp;54.0 [51.0, 69.5]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 21.4984%;\"\u003e\n \u003cp\u003e\u0026nbsp;60.0 [52.0, 69.3]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 38.355%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e(%)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; Men\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; Women\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.3909%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 65 (66)\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 34 (34)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.7557%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 16 (59)\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 11 (41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.4984%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;49 (68)\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;23 (32)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 38.355%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eT-stage (%)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp;T1-2\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp;T3-4\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp;Tx\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp;MUP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.3909%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 43 (43)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 41 (41)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 2 (2)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 13 (13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.7557%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 12 (44)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 11 (41)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 2 (7)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 2 (7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.4984%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 31 (43)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 30 (42)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 0 (0)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 11 (15)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 38.355%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eUlceration (%)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp;No\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp;Yes\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; Unknown\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.3909%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 58 (72) \u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 23 (28)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.7557%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 14 (64)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 8 (36)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.4984%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 44 (75)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 15 (25)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 38.355%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eBRAF-\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003emutation (%)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp;Wildtype\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;V600E/K\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003emutant\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp;Unknown\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.3909%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 52 (54)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 45 (46)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 2\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.7557%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 8 (30) \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 19 (70)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 0\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.4984%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 44 (63)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 26 (37)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 2\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 38.355%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLocation of the lymph node (%)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;Neck\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;Axilla\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;Groin\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.3909%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; 24 (24)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 39 (39) \u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 36 (36) \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.7557%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 4 (14)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 9 (33)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 14 (52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.4984%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 20 (28)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 30 (42)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 22 (31)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 38.355%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of positive lymph nodes on PET-CT\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e(%)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp;1\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp;\u0026gt;1-3\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp;\u0026gt;3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.3909%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 57 (58) \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 33 (33)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 9 (9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.7557%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 15 (56)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 9 (33)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 3 (11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.4984%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 42 (58)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 24 (33)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 6 (8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 38.355%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSum of diameter target lesions, mm (median, IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.3909%;\"\u003e\n \u003cp\u003e25.0 [18.0, 33.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 24.7557%;\"\u003e\n \u003cp\u003e26.0 [19.0, 31.5]\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 21.4984%;\"\u003e\n \u003cp\u003e23.5 [18.0, 34.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 38.355%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLDH (median [IQR])\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.3909%;\"\u003e\n \u003cp\u003e186.0 [163.0, 215.5]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 24.7557%;\"\u003e\n \u003cp\u003e192.0 [172.5, 206.5]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 21.4984%;\"\u003e\n \u003cp\u003e184.0 [161.5, 216.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 100%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eResponse\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 38.355%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePathologic response *(%)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; MPR\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; pPR\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; pNR\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; Distant metastasis\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; Not evaluable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.3909%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 60 (61)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 11 (11)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 21 (21)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 6 (6)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 1 (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.7557%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 6 (22)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 5 (19)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 10 (37)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 6 (22)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.4984%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 54 (75)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 6 (8)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 11 (15)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 0 (0)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 1 (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 100%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eToxicity\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 38.355%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGrade \u0026ge;3 irAE(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.3909%;\"\u003e\n \u003cp\u003e30 (30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 24.7557%;\"\u003e\n \u003cp\u003e9 (31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 21.4984%;\"\u003e\n \u003cp\u003e21 (30)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 38.355%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrednisone (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.3909%;\"\u003e\n \u003cp\u003e50 (51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 24.7557%;\"\u003e\n \u003cp\u003e16 (55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 21.4984%;\"\u003e\n \u003cp\u003e34 (49)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 38.355%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSecond line immunosuppressives (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.3909%;\"\u003e\n \u003cp\u003e11 (11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 24.7557%;\"\u003e\n \u003cp\u003e4 (14)\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 21.4984%;\"\u003e\n \u003cp\u003e7 (10)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 100%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSubsequent surgery/therapy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 38.355%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eILN (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.3909%;\"\u003e\n \u003cp\u003e94 (95)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 24.7557%;\"\u003e\n \u003cp\u003e24 (89)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 21.4984%;\"\u003e\n \u003cp\u003e70 (97)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 38.355%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTLND (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.3909%;\"\u003e\n \u003cp\u003e33 (33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 24.7557%;\"\u003e\n \u003cp\u003e16 (59)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 21.4984%;\"\u003e\n \u003cp\u003e17 (24)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 38.355%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAdjuvant (%)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; Nivolumab\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; BRAF + MEK inhibitors\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.3909%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 7 (7)\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 10 (10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.7557%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 3 (11)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 5 (19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.4984%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 4 (6)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 5 (7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 38.355%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRadiotherapy (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.3909%;\"\u003e\n \u003cp\u003e8 (8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 24.7557%;\"\u003e\n \u003cp\u003e5 (19)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 21.4984%;\"\u003e\n \u003cp\u003e3 (4)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 100%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBiomarkers\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 38.355%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIFN\u003c/strong\u003e\u003cstrong\u003eg\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;signature score (mean (SD))\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.3909%;\"\u003e\n \u003cp\u003e0.37 [-7.28, 7.65]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 24.7557%;\"\u003e\n \u003cp\u003e-1.84 [-9.75, 0.37]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 21.4984%;\"\u003e\n \u003cp\u003e2.08 [-4.17, 9.16]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 38.355%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIFN\u003c/strong\u003e\u003cstrong\u003eg\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;(%)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;L\u003c/strong\u003e\u003cstrong\u003eow\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;H\u003c/strong\u003e\u003cstrong\u003eigh\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eunknown\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.3909%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 41 (51)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 39 (49)\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.7557%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 19 (76)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 6 (24)\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.4984%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 22 (40)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 33 (60)\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 38.355%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of nonsynomous \u0026nbsp;mutations (mut/mb; median [IQR])\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.3909%;\"\u003e\n \u003cp\u003e9.12 [5.61, 17.73]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 24.7557%;\"\u003e\n \u003cp\u003e8.50 [4.56, 12.31]\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 21.4984%;\"\u003e\n \u003cp\u003e10.73 [6.80, 22.26]\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 38.355%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTMB labels (%)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eLow\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;H\u003c/strong\u003e\u003cstrong\u003eigh\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; unknown\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.3909%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 43 (57)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 32 (43)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.7557%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 19 (70)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 8 (30)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.4984%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 24 (50)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 24 (50)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 38.355%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePDL1 (%)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026lt;1% \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026ge;1%-\u0026lt;50%\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp;\u0026ge; 50%\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; unknown\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.3909%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 43 (57) \u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 26 (34) \u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 7 (9)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.7557%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 17 (85)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 3 (15)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 0 (0)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.4984%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 26 (46)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 23 (41)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 7 (13)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 16\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 38.355%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePDL1 (%)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp;\u0026lt;1% \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp;\u0026ge;1%\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; unknown\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.3909%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 43 (57)\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 33 (43)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.7557%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 17 (85)\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 3 (15)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.4984%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 26 (46)\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 30 (54)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 16\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eData are median (IQR) or n (%). Percentages may not sum up to 100 because of rounding. Percentages are derived of the patients per column with known parameters.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e*The patients that died from non-melanoma related cause, were included in the group of patients with \u0026ldquo;no recurrence\u0026rdquo; since these patients did not have any signs of recurrence before death.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIQR, interquartile range; MUP, melanoma of unknown primary; LDH, Lactate dehydrogenase; ILN, index lymph node; TLND, therapeutic lymph node dissection; MPR, major pathologic response; pPR, pathologic partial response; pNR, pathologic non-response; irAE, immune related adverse events; IFNg, interferon gamma gene signature; TMB, tumor mutational burden; PD-L1, Programmed Cell Death Ligand 1;\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Neoadjuvant therapy, adjuvant therapy, immune checkpoint blockade, immunotherapy, personalized therapy, melanoma","lastPublishedDoi":"10.21203/rs.3.rs-7090131/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7090131/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eNeoadjuvant ipilimumab plus nivolumab has become standard therapy for stage III melanoma based on the NADINA trial, though long-term data are lacking. In the phase 2 PRADO cohort of OpACIN-neo (NCT02977052), 99 patients with stage III macroscopic melanoma received this regimen.\u003c/p\u003e\n\u003cp\u003eWe report first-time 5-year survival data: 71% event-free survival, 74% relapse-free survival, 79% distant metastasis-free survival, and 86% overall survival. Ongoing grade 1-2 immune-related adverse events occurred in 69% of patients alive, predominantly vitiligo and hypothyroidism.\u003c/p\u003e\n\u003cp\u003eMajor pathologic response (MPR), high tumor mutational burden (TMB), high interferon-gamma signature (IFNg), and PD-L1 expression ≥1% were associated with favorable outcomes. Combined high TMB, IFNg, and PD-L1 expression yielded 100% MPR and 100% 5-year event-free survival, while triple low expression had only 18% MPR and 41% event-free survival.\u003c/p\u003e\n\u003cp\u003eOur findings demonstrate favorable long-term outcomes for patients with an MPR and identify TMB, IFNg, and PD-L1 as promising baseline biomarkers.\u003c/p\u003e","manuscriptTitle":"Long-term survival after neoadjuvant low-dose ipilimumab plus high-dose nivolumab in resectable stage III melanoma: the 5-year survival-update and biomarker analysis from the PRADO-trial","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-15 12:17:47","doi":"10.21203/rs.3.rs-7090131/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"nature-medicine","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"nm","sideBox":"Learn more about [Nature Medicine](http://www.nature.com/nm/)","snPcode":"","submissionUrl":"","title":"Nature Medicine","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature Research","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"60ae7ec6-a252-43f0-93cf-c0f85140bedc","owner":[],"postedDate":"July 15th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":51505212,"name":"Biological sciences/Cancer/Skin cancer/Melanoma"},{"id":51505213,"name":"Biological sciences/Cancer/Tumour biomarkers"},{"id":51505214,"name":"Biological sciences/Cancer/Cancer therapy/Cancer immunotherapy"}],"tags":[],"updatedAt":"2026-01-29T08:06:18+00:00","versionOfRecord":{"articleIdentity":"rs-7090131","link":"https://doi.org/10.1038/s41591-025-04158-9","journal":{"identity":"nature-medicine","isVorOnly":false,"title":"Nature Medicine"},"publishedOn":"2026-01-28 05:00:00","publishedOnDateReadable":"January 28th, 2026"},"versionCreatedAt":"2025-07-15 12:17:47","video":"","vorDoi":"10.1038/s41591-025-04158-9","vorDoiUrl":"https://doi.org/10.1038/s41591-025-04158-9","workflowStages":[]},"version":"v1","identity":"rs-7090131","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7090131","identity":"rs-7090131","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}