AXINEO: AXIllary response to NEOadjuvant chemotherapy for breast cancer: can we predict response based on a biomarker panel?

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Franziska Fick, Florian Lenz, Verena-Wilbeth Sailer, Achim Rody, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7119537/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 18 Nov, 2025 Read the published version in Archives of Gynecology and Obstetrics → Version 1 posted 7 You are reading this latest preprint version Abstract Background Up to 60% of breast cancer patients achieve pathological complete response (pCR) and factors associated with breast-pCR have been extensively investigated. In patients with initially node-positive disease predicting axillary response to treatment remains challenging. Our study examines a biomarker panel assessed on core-biopsy lymph node metastatic tissue with the goal to establish predictive markers for nodal positive breast cancer. Material and Methods 40 women with core biopsy-proven node-positive breast cancer scheduled to receive neoadjuvant treatment at the certified Breast Cancer Center of the University Hospital Schleswig-Holstein Campus Lübeck were included. The expression of CAIX, PD-L1, TROP2, MSH2, MSH6, MLH1 and PMS2 as well as p53 mutation were assessed. Biomarkers were chosen based on their association with tumorigenesis and tumor progression. Statistical analysis was performed using SPSS 29. This investigator-initiated study was supported by a research grant from Gilead (Gilead Förderprogramm). Results Higher CAIX levels were associated with triple negative and Her2 positive receptor status (p = 0.003), Ki67 ≥ 50% in breast core biopsy (p = 0.005) as well as postmenopausal status (p = 0.007). P53 mutation was more frequent in G3 tumors (p = 0.025). All lymph node metastases were microsatellite stable (MSS). None of the markers could significantly predict pathological response (complete, breast or nodal). Conclusion Our study shows upregulated CAIX in lymph node metastasis frequently occurs in aggressive and highly proliferative tumors. However, none of the examined biomarkers could predict nodal response to therapy. Further research is necessary to better identify patients most likely to achieve nodal response through neoadjuvant chemotherapy. Figures Figure 1 Figure 2 Figure 3 Introduction Breast cancer (BC) is the most common malignancy in women worldwide ( 1 ). In Germany, one in five patients receive neoadjuvant chemotherapy (NACT) before definitive surgery ( 2 ). Depending on the subtype and extent of disease, NACT is able to eradicate all invasive tumor cells (pathological complete response = pCR) in up to 60% of patients with early BC and factors associated with breast-pCR have been extensively investigated. Regarding nodal response, recent data show that approximately 50–60% of patients initially cN + have no vital tumor cells in axillary lymph nodes following NACT ( 3 , 4 ). Importantly, axillary response to therapy guides treatment choices regarding surgical therapy of the axilla ( 5 – 10 ). Patients with cN+ → ycN0 conversion are recommended de-escalated procedures, such as targeted axillary dissection or sentinel node biopsy, while whose with persistently suspicious lymph nodes are usually offered axillary lymph node dissection, associated with increased risk of arm morbidity and lymph edema ( 11 – 15 ). However, predicting axillary response to treatment remains challenging, and imaging such as axillary ultrasound often fails to accurately detect axillary residual disease ( 16 ). Therefore, tools allowing for a reliable identification of patients most likely to reach axillary pCR are urgently needed. Beyond established predictive factors such as tumor size, number of positive lymph nodes, hormone receptor and Her2 status, grading and ki67, assessing tissue-based biomarkers may further improve response prediction. The present study aimed at examining a panel of biomarkers assessed on core-biopsy of lymph node metastatic tissue with the goal to establish predictive markers for treatment response to neoadjuvant chemotherapy in node-positive breast cancer. The following biomarkers were chosen based on their association with tumorigenesis and tumor progression: p53 expression status, TROP 2 (Tumor-associated calcium signal transducer 2), PD-L1 (Programmed Cell Death 1 Ligand 1), CAIX (Hypoxia-regulated carbonic anhydrase IX) and MSI (microsatellite instability). Methods We analysed core biopsy specimens of lymph node metastases of 40 female patients treated at the certified Breast Center at the University Hospital Schleswig-Holstein between 2018 and 2024. Patients were chosen retrospectively according to their nodal pCR (50% nodal pCR, 50% nodal non-pCR). We defined complete pCR as ypT0 and ypN0. They were selected retrospectively due to their postoperative pCR result. The study was supported by a research grant from Gilead ( Gilead Förderprogramm ). The study was aproved by the local ethical committee and only patients who consented to the use of their data and archived tissue were included. Immunohistochemistry and evaluation The expression of p53, CAIX, PD-L1, TROP2, MSH2, MSH6, MLH1 and PMS2 was assessed using immunohistochemistry on 4 µm-thin sections. A positive control was provided for each marker as listed below. Table 1 Targets and used antibodies antibody target name Dilution manufacturer positive control MLH1 MLH1 RTU* Ventana (Roche) colon MSH2 MSH2 RTU Ventana (Roche) colon MSH6 MSH6 RTU Ventana (Roche) colon PMS2 PMS2 RTU Ventana (Roche) colon p53 p53 RTU Ventana (Roche) tonsil CA IX Carbonic Anhydrase IX RTU Ventana (Roche) gastric mucosa TROP2 TROP2 1:500 abcam breast cancer PD-L1 PD-L1 1:50 Dako tonsil *RTU = Ready To Use The p53 staining result was interpreted as previously described in ovarian carcinomas ( 17 ) and was indicated as either mutational-type or wild-type. PD-L1 status was evaluated as the proportion of tumor cells with any membrane-bound staining reaction and was reported as TPS. Due to the lack of differentiation between tumor-associated immune cells and local immune cells of the lymph node tissue, the CPS was not further evaluated. The mismatch-repair proteins were considered intact/preserved if all tumor cells showed a consistent, strong nuclear staining. In contrast, a complete lack of nuclear staining was declared as a loss, indicating a mismatch-repair-deficiency. The stained slides of CAIX and TROP2 were scanned using Ventana DP200 (Roche) at 40x magnification. QuPath software (version 0.4.4) was used to visualize the staining for CAIX and TROP2. A pathologist manually marked the tumor cells and set the parameters for cell detection as well as thresholds for classification in negative (0), weakly (1+), moderately (2+) and strongly (3+) positive tumor cells. Subsequently the immunohistochemical expression was quantified by the software providing the H-score. The mean value of the H-Scores of each tumor sample was used for statistical analysis. Statistical analysis We used SPSS Version 29 for statistical analyses. First, the data was examined for the presence of a normal distribution. Depending on the result, the H-scores of the respective cohorts were compared using the Mann-Whitney and Kruskal-Wallis-tests (CAIX and PDL1), chi-squared test (P53) or the ANOVA (TROP2). The p53-status was reported for each tumor sample as mutation-type or wild-type. In analogy, the tumor samples were classified as showing an intact or lost staining for the mismatch-repair proteins. The frequencies of the respective type in the two cohorts resulted in nominal scaled data and were statistically analyzed using the chi-squared test. The significance level was set at p < 0.05. Primary endpoint was the correlation with therapy response, defined as pCR (complete, breast, nodal). Results Tumor biology and patients characteristics Median age at diagnosis was 53 years (SD 12.3, range: 28–77 years). 17 out of 40 (42.5%) patients were premenopausal, one (2,5%) perimenopausal, 22 (55%) postmenopausal at diagnosis. All tumors had at least a G2 grading, 75% were G3. Median tumor size was 27.7 mm (SD 17.3). One patient had an inflammatory breast cancer. Average number of suspicious lymph nodes at diagnosis was two (SD 1.2, range 1 to 5). The most common subtype, assessed on primary tumor, was triple negative breast cancer (TNBC) (10 patients, 25%), followed by HR positive Her2 negative (16; 40%) and Her2 positive (14; 35%). Among patients with Her2 positive disease, 8 had HR positive and 6 HR negative tumors. One patient presented with a bifocal cancer, with one lesion HR positive Her2 negative and the other Her2 positive. Neoadjuvant Chemotherapy (NACT) All 40 patients underwent neoadjuvant chemotherapy for nodal positive breast cancer diagnosis according to the tumor biology and current standard of care. 65.0% (26/40) completed the chemotherapy as recommended. The remaining 14 patients experienced major adverse events such as peripheral neuropathy, diarrhoea, haematological toxicity or acute kidney injury and either discontinued chemotherapy or underwent dose reduction. Surgical treatment 21 patients (52.5%) received a breast-conserving therapy and 19 had a mastectomy (47.5%). The most common axillary procedure was primary axillary lymph node dissection performed in 20 patients (50%), followed by a targeted axillary dissection (TAD) in 17 patients (42.5% %) and sentinel lymph node biopsy in three patients (7,5%). Out of 17 patients receiving TAD initially, four (23,5%) underwent completion axillary lymph node dissection. In summary, 24 patients received axillary dissection in total (20 primary and 4 patients secondary after TAD, 60%). All patients characteristics are shown in Table 2 . Table 2 Patients characteristics Median/Percentage Age 53 years (SD 12.5) Tumor size 27.7 mm (SD 17.3) Number of suspicious lymph nodes at diagnosis 2 Ki67 50% Completion of neoadjuvant chemotherapy as planned Yes No 65.0% (26/40) 35.0% (14/40) Breast surgery Breast-conserving surgery Mastectomy 52.5% (21/40) 47.5% (19/40) Final axillary surgery Sentinel node biopsy Targeted axillary dissection (TAD) Axillary lymph node dissection 7.5% (3/40) 32.5% (13/40) 60.0% (24/40) Biomarker analysis In this cohort, none of the tested markers on the lymph node specimen was correlated significantly with pathological response to chemotherapy (pCR, ypT0, ypN0). Only 13 out of 40 patients had a complete pCR (32.5%). One patient had only noninvasive tumor rest (ypTis) after surgery. The other 26 had invasive tumor rest in the breast (ypT1) and/or the lymph nodes (ypN+). The pCR rates (complete, breast, nodal) differed significantly between the different receptor status (complete pCR p < 0.001, breast p = 0.003, nodal p = 0.004, Fig. 3 . The lowest pCR rate was observed in HR positive Her2 negative breast cancers (complete pCR 0%, breast pCR 6.25%, nodal pCR 18.75%). In general more patients had nodal pCR (50%, n = 20) than breast pCR (37.5%, n = 15), see Fig. 3 . 24 out of 40 (60%) patients underwent germline genetic testing at the certified Center for Familial Breast and Ovarian Cancer (FBREK). Out of these, six (25% of all tested patients and 15% of the total cohort) were mutational carriers (1 x BRCA1, 3 x BRCA2, 1 x CHEK2, 1 x PTEN). No significant differences in the tested markers were shown between germline mutation carriers and non-carriers Table 3 Biomarker panel assessed on the core-biopsy lymph node metastatic tissue and correlation of markers and clinical-pathological factors (p-values < 0.05 are shown in bold); since all specimens were microsatellite stable, MSI status was not included in the table. Total (n) TROP 2 TROP2 high* P53 mutation PD-L1 PD-L1 ≥ 1% CAIX CAIX high* Total number of analysed patients (n) 40 39 39 Median: 171.0 40 38 38 39 39 Median: 0.025 pCR 1) Yes No p-value 13 27 12 27 0.571 6 (50%) 14 (51.9%) 0.915 9 (69.2%) 15 (55.6%) 0.408 0.756 1 (8.3%) 8 (30.8%) 0.130 0.070 8 (66.7%) 12 (44.4%) 0.200 Breast pCR 2) Yes No p-value 15 25 14 25 0.315 8 (57.1%) 12 (48%) 0.584 10 (66.7%) 14 (56%) 0.505 0.790 2 (14.3%) 7 (29.2%) 0.298 0.251 9 (64.3%) 11 (44%) 0.224 Nodal pCR Yes No p-value 20 20 19 20 0.562 9 (47.4%) 11 (55%) 0.634 14 (70%) 10 (50%) 0.197 0.752 4 (22.2%) 5 (25%) 0.841 0.166 12 (63.2%) 8 (40%) 0.148 Age ≥ 53 years < 53 years p-value 20 20 19 20 0.506 9 (47.4%) 11 (55%) 0.421 13 (65%) 11 (55%) 0.519 0.057 7 (36.8%) 2 (10.5%) 0.056 0.033 14 (73.7%) 6 (30%) 0.006 Grading 3) G2 G3 p-value 10 30 10 29 0.078 3 (30.0%) 17 (56.7%) 0.118 3 (30%) 21 (70%) 0.025 0.336 1 (11.1%) 8 (27.6%) 0.310 0.272 3 (30%) 17 (58.6%) 0.118 Ki67 3) ≥ 50% < 50% p-value 20 20 20 19 0.288 10 (50%) 10 (52.6%) 0.869 15 (75%) 9 (45%) 0.053 0.775 6 (33.3%) 3 (15%) 0.184 0.235 12 (60%) 8 (42.1%) 0.264 Subtype NST Other p-value 36 4 35 4 0.905 17 (48.6%) 1 (50%) 0.998 20 (57.1%) 3 (75%) 0.787 ----- 9 (26,5%) 0 0.331 37 2 0.021 15 (42.9%) 3 (75%) 0.197 Menopausal Status Pre/perimenopausal Postmenopausal p-value 18 22 18 21 0.903 9 (50%) 11 (52.4%) 0.882 10 (55.6%) 14 (45.5%) 0.604 0.130 2 (11.1%) 7 (33.3%) 0.120 0.028 5 (27.8%) 15 (71.4%) 0.007 Receptor status HR + HER2- HER2 positive Triple-negative p-value 16 14 10 16 13 10 0.415 7 (43.8%) 6 (46.2%) 7 (70%) 0.386 6 (37.5%) 10 (71.4%) 8 (80%) 0.055 0.247 2 (13.3%) 3 (21.4%) 4 (44.4%) 0.215 0.263 3 (18.8%) 9 (69.2%) 8 (80%) 0.003 Germline mutation 4) Yes No No data/not tested p-value 6 16 18 6 15 18 0.592 3 (50%) 7 (46.7%) 10 (55.6%) 0.877 3 (50%) 4 (25%) 9 (50%) 0.287 0.925 1 (20%) 4 (25%) 4 (23.5%) 0.974 0.305 3 (50%) 6 (40%) 11 (61.1%) 0.481 * defined as expression level above median 1) defined as ypT0 ypN0 2) defined as ypT0 3) breast biopsy 4) Germline mutation tested with the German Consortium for Familial Breast and Ovarian Cancer panel TROP2 TROP2 expression (H-Score) was analyzed in 39 patients with an average of 177.85, median 171.0, with a standard deviation (SD) of 59.21; range 1.4 to 290.0. There were no significant differences shown for the TROP2 H-Score and the different parameters tested, see Table 3 . TROP2-high was defined as TROP2 expression level above the median of 171.0. There were no significant associations with other factors or response to treatment. There was no correlation between high CAIX expression (define as levels above median) and high TROP2 score (p = 0.634). 11/20 patients (55%) were both TROP2 and CAIX high, 10/19 (52.6%) had both biomarkers at a level lower than the median. P53 The p53 protein-expression was described binary (mutated/wildtype). The tumors of 24 patients (60%) showed a p53 mutational-type-expression and 16 (40%) showed p53 wildtype-expression. P53 mutation was significantly more frequent in G3 tumors (p = 0.025). 14 out of 20 patients (70.0%) with axillary pCR had a p53 mutation in the lymph node tissue, compared to 10 out of 20 (50.0%) with axillary non-pCR. There were no other significant results found. With regard to receptor status, HR + Her2 negative tumors showed p53 mutations in 37.5% (n = 6) of cases, whereas Her2 positive and triple negative tumors had p53 mutations in 71.4% (n = 10) and 80% (n = 8), respectively (p = 0.055). PD-L1 PD-L1 status could be analyzed in 38 patients. The average value was 1.46% with a range from 0 to 10% and a standard deviation of 1.92%. No differences were found for PD-L1 in between subgroups. Older patients were numerically more likely to have PD-L1 ≥ 1% in lymph node metastasis than younger patients (p = 0.057). CAIX CAIX expression was 6.106 in average, median 0.025, with a standard deviation (SD) of 15.96; range 0.0 to 69.15. Higher CAIX levels assessed in the lymph node core-biopsy were associated with triple negative and Her2 positive receptor status (p = 0.003), Ki67 ≥ 50% (assessed in breast core biopsy, p = 0.005) as well as postmenopausal status (p = 0.007). We grouped patients with CAIX above median as CAIX high. 63.2% of patients who achieved nodal pCR had above-median CAIX expression (CAIX high) levels, compared to 40% among patients with non-pCR (p = 0.148). 80% (n = 8) of the triple negative breast cancers had a CAIX expression levels above median e.g. CAIX high (p = 0.003), compared to 69.2% of the Her2 + subtype (n = 9) and 18.8% (n = 3) of the HR + Her2- group. We found significantly higher CAIX expressions in older and postmenopausal patients. The median for postmenopausal women was 0.670, respective 0.035 for pre/perimenopausal patients (p = 0.028). Matching this result CAIX expression levels were also higher in patients ≥ 53 years old (average 6.303 vs. 5.919; SD 16.29 vs. 16.06; p = 0.033). 14 patients older than 52 years (73.7%) versus 6 patients aged 52 or younger (30%) were in the CAIX high group (p = 0.006). MSI All tumors were microsatellite stable (testing was performed with MSH2, MSH6, MLH1 and PMS2 immunohistochemistry), so no further analysis could be made. Discussion To the best of our knowledge, this is the first comprehensive biomarker analysis of lymph node metastatic tissue in patients receiving neoadjuvant chemotherapy. The biomarkers were chosen based on their association with tumorigenesis and tumor progression. As expected, in the present analysis more patients in the nodal pCR group had triple-negative and HER2-positive tumors, compared to patients with nodal non-pCR. This goes along with research findings of the meta-analysis from 2020 which showed pCR rates to be lower in HR positive breast cancers ( 18 ). Hypoxia-regulated carbonic anhydrase IX (CAIX) is a hypoxia inducible molecular marker. The majority of studies suggest that CAIX can serve as a biomarker and therapeutic target in different tumor types. ( 19 , 20 ) CAIX can promote tumorigenesis and is associated with a more aggressive phenotype of cancer cells ( 21 ). Ong et al. analyzed specimens of more than 300 TNBC patients and found out that increased CAIX protein levels are independently associated with poor survival ( 22 , 23 ). Interestingly, in our study, 80% of patients with triple negative breast cancers had a CAIX expression in lymph node metastasis above median (CAIX high), compared to 69.2% of the Her2 + subtype and 18.8% of the HR + Her2-negative group (p = 0.003). This is in accordance with previous studies, which reported a significantly higher expression of CAIX in triple negative breast cancer ( 22 ). Furthermore, overexpression of CAIX protein in TNBC is associated with a BRCA1 mutant signature and loss of BRCA1 function ( 23 ). As there was only one patient with BRCA1 mutation in our study, further analyses were not possible. The correlation between CAIX and BRCA1 mutation, clearly associated with triple-negative subptype, should be investigated in future studies. One critical aspect that is worth noting in this context is the relatively high inter-observer variability of CAIX expression and its dependance on the quality of biopsies ( 24 ). Techniques to standardize histopathological assessment and lower inter-observer variability still need to be optimized in order to make the marker more comparable. Currently, research on CAIX fluoroscopy in single-photon emission computerized tomography (SPECT), positron emission tomography (PET), and near-infrared fluorescence imaging (NIRF) is ongoing. Hypothetically, these imaging modalities could be used in nodal positive breast cancer patients to determine CAIX expression in the future ( 25 ). Regarding potential therapeutic consequences, CAIX-based agents like the CAIX-specific monoclonal antibody girentuximab have been evaluated in a phase III clinical trials in high-risk renal cell carcinoma ( 26 ). Currently, no studies in breast cancer patients are available. Implementation of CAIX-based treatment could potentially enable new therapeutic strategies for high-risk breast cancer patients (e.g., triple negative, Ki67 ≥ 50%). In the present study, we show higher TROP2 expression in lymph node metastasis in patients with TNBC. TROP2 is a membrane protein involved in tumor progression by actively interacting with several key signaling pathways associated with cancer development and plays an important role in tumor growth, invasion, treatment resistance and metastasis. TROP2-targeted drugs are available such as sacituzumab govitecan ( 27 ). Further, high TROP2 expression correlates with poorer response and drug resistance ( 28 , 29 ). Previous studies have shown TROP2 expression to be heterogeneous among breast cancer subtypes ( 30 , 31 ), with higher expression in triple negative breast cancer. However, in contrast to our study, these analyses were performed on breast specimens ( 30 , 31 ). In our study, more patients with nodal pCR had p53 mutations in their lymph nodes (70% vs. 50%, p = 0.197) with further investigation in larger cohorts needed. P53 mutations were also more common in case of aggressive tumors (such as G3). We could also observe a potential difference in receptor status for p53-mutations. Accordingly, HR + Her2-negative cases showed p53 mutations in the lymph node in 37.5%, whereas Her2-positive and triple-negative patients showed p53 mutations in 71.4% and 80%, respectively (p = 0.055). P53, as a transcription factor, plays an important regulatory role in the multitude of cellular processes. Genotoxic stress leads to activation of p53 to facilitate DNA repair, cell cycle arrest, and apoptosis. P53 has been shown to be an important biomarker in endometrial cancer but is not one of the standard markers in breast cancer ( 32 ), although it is the most frequently mutated gene in breast cancers (up to 30%, subtype depending). The evidence on the prognostic value of p53 is not conclusive and seems to depend on hormonal status and prior treatment ( 33 ). MSI is an established marker for various tumors such as colorectal and endometrial cancer and is frequently used as a predictive factor for immune checkpoint inhibitor therapy ( 34 ). In breast cancer, however, the prevalence of microsatellite instability is low (1.8% or less) ( 35 – 37 ). This is in line with our study. All lymph node metastatic specimens analyzed were microsatellite stable. Nevertheless, MSH2, MSH6, MLH1 and PMS2 are part of extended germline testing in BC patients using the TruRisk©-Panel at German Centers for Familial Breast and Ovarian Cancer which currently includes ATM, BRCA1, BRCA2, BRIP1, CDH1, CHEK2, EPCAM, MLH1, MSH2, MSH6, PALB2, PMS2, PTEN, RAD51C, RAD51D, STK11, TP53 ( 38 ). One limitation of our study is the moderate number of patients (n = 40). Some of the initially planned assays such as PIK3CA somatic mutational analysis were not possible because of the limited amount of core-biopsy tissue specimen available. As the tests were conducted on lymph node metastatic core biopsies, we also cannot exclude intratumoral heterogeneity. This applies, for example, to PD-L1-status, for which high variability in expression within the same tumor has also been demonstrated in breast cancer ( 39 ). Because of the retrospective selection of patients according to their nodal response there might be a selection bias. Further studies should focus on CAIX expression and TP53 mutational status as well as possibly further potential biomarkers to improve the selection of patients most likely to achieve axillary response. Summary Among the biomarkers analyzed, numerical differences in the expression levels of CAIX and tissue mutational status of P53 were observed between patients with nodal pCR and non-pCR. Our study shows that upregulation of hypoxemia marker CAIX in the lymph node metastatic tissue before start of systemic therapy is significantly associated with a more aggressive tumor subtype. Further research is necessary to better identify patients most likely to achieve nodal response after neoadjuvant treatment, and thus best eligible for surgical de-escalation, e.g., targeted axillary dissection or sentinel node biopsy alone instead of full axillary lymph node dissection. Declarations Competing Interests Franziska Fick received lecture honoraria from Novartis and travel expenses from Astra Zeneca and Novartis.Nikolas Tauber received honoraria for lectures and participation in advisory boards: Novartis, ExactSciences, Thieme, PRAEGNANT, if-kongress, Aurikamed. Support for atttending meetings from Astra Zeneca, DGGG e.V., if-kongress, Aurikamed. Achim Rody recieved lecture honoraria from Roche, Daiichi Sankyo, Astra Zeneca, Pfizer, Novartis, Celgen, Novartis, ExactSciences, MSD, Pierre Fabre, Lilly, Seagen, TargosAdvisory Boards: Roche, Daiichi Sankyo, Astra Zeneca, Pfizer, Celgen, Eisai, Novartis, MSD, Hexal, Amgen, ExactSciences, Pierre FabreMaggie Banys-Paluchowski is Associate Editor of Archives of Gynecology and Obstetrics and the European Journal of Surgical Oncology. Honoraria for lectures and participation in advisory boards: Roche, Novartis, Pfizer, pfm, Eli Lilly, Onkowissen, Seagen, AstraZeneca, Eisai, Amgen, Samsung, Canon, MSD, GSK, Daiichi Sankyo, Gilead, Sirius Medical, Syantra, resitu, Pierre Fabre, ExactSciences. Study support: Damp Stiftung, AWOgyn, AGO-B, Claudia von Schilling Breast Cancer Research Foundation, Ehmann Stiftung, EndoMag, Mammotome, MeritMedical, Sirius Medical, Gilead, Hologic, ExactSciences. Travel expenses: Eli Lilly, ExactSciences, Pierre Fabre, Pfizer, Daiichi Sankyo, Roche.All oher authors declare that they have no financial interests. Author Contribution Franziska Fick (F.F.) and Florian Lenz (F.L.) contributed equally to this manuscript.Franziska Hemptenmacher (F.H.) und Maggie Banys-Paluchowski (M.B-P.) contributed equally to this manuscript. References Łukasiewicz S, Czeczelewski M, Forma A, Baj J, Sitarz R, Stanisławek A. 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Arbeitsgemeinschaft Gynäkologische Onkologie Recommendations for the Diagnosis and Treatment of Patients with Early Breast Cancer: Update 2023. Breast Care (Basel) 2023; 18(4):289–305. Tauber N, Amann N, Dannehl D, Deutsch TM, Dimpfl M, Fasching P et al. Therapy of early breast cancer: current status and perspectives. Arch Gynecol Obstet 2025. Banys-Paluchowski M, Gruber IV, Hartkopf A, Paluchowski P, Krawczyk N, Marx M et al. Axillary ultrasound for prediction of response to neoadjuvant therapy in the context of surgical strategies to axillary dissection in primary breast cancer: a systematic review of the current literature. Arch Gynecol Obstet 2020; 301(2):341–53. Köbel M, Kang EY. The Many Uses of p53 Immunohistochemistry in Gynecological Pathology: Proceedings of the ISGyP Companion Society Session at the 2020 USCAP Annual9 Meeting. Int J Gynecol Pathol 2021; 40(1):32–40. Spring LM, Fell G, Arfe A, Sharma C, Greenup R, Reynolds KL et al. Pathologic Complete Response after Neoadjuvant Chemotherapy and Impact on Breast Cancer Recurrence and Survival: A Comprehensive Meta-analysis. Clin Cancer Res 2020; 26(12):2838–48. Pastorek J, Pastorekova S. Hypoxia-induced carbonic anhydrase IX as a target for cancer therapy: from biology to clinical use. Semin Cancer Biol 2015; 31:52–64. Tan EY, Yan M, Campo L, Han C, Takano E, Turley H et al. The key hypoxia regulated gene CAIX is upregulated in basal-like breast tumours and is associated with resistance to chemotherapy. Br J Cancer 2009; 100(2):405–11. Lock FE, McDonald PC, Lou Y, Serrano I, Chafe SC, Ostlund C et al. Targeting carbonic anhydrase IX depletes breast cancer stem cells within the hypoxic niche. Oncogene 2013; 32(44):5210–9. Ong CHC, Lee DY, Lee B, Li H, Lim JCT, Lim JX et al. Hypoxia-regulated carbonic anhydrase IX (CAIX) protein is an independent prognostic indicator in triple negative breast cancer. Breast Cancer Res 2022; 24(1):38. Shamis SAK, Edwards J, McMillan DC. The relationship between carbonic anhydrase IX (CAIX) and patient survival in breast cancer: systematic review and meta-analysis. Diagn Pathol 2023; 18(1):46. Iakovlev VV, Pintilie M, Morrison A, Fyles AW, Hill RP, Hedley DW. Effect of distributional heterogeneity on the analysis of tumor hypoxia based on carbonic anhydrase IX. Lab Invest 2007; 87(12):1206–17. Chen K-T, Seimbille Y. New Developments in Carbonic Anhydrase IX-Targeted Fluorescence and Nuclear Imaging Agents. Int J Mol Sci 2022; 23(11). McDonald PC, Chafe SC, Supuran CT, Dedhar S. Cancer Therapeutic Targeting of Hypoxia Induced Carbonic Anhydrase IX: From Bench to Bedside. Cancers (Basel) 2022; 14(14). Bardia A, Hurvitz SA, Tolaney SM, Loirat D, Punie K, Oliveira M et al. Sacituzumab Govitecan in Metastatic Triple-Negative Breast Cancer. N Engl J Med 2021; 384(16):1529–41. Hientz K, Mohr A, Bhakta-Guha D, Efferth T. The role of p53 in cancer drug resistance and targeted chemotherapy. Oncotarget 2017; 8(5):8921–46. Shvartsur A, Bonavida B. Trop2 and its overexpression in cancers: regulation and clinical/therapeutic implications. Genes Cancer 2015; 6(3–4):84–105. Aslan M, Hsu E-C, Garcia-Marques FJ, Bermudez A, Liu S, Shen M et al. Oncogene-mediated metabolic gene signature predicts breast cancer outcome. NPJ Breast Cancer 2021; 7(1):141. Zhao W, Kuai X, Zhou X, Jia L, Wang J, Yang X et al. Trop2 is a potential biomarker for the promotion of EMT in human breast cancer. Oncol Rep 2018; 40(2):759–66. Vergote I, Matias-Guiu X. New FIGO 2023 endometrial cancer staging validation. Welcome to the first molecular classifiers and new pathological variables! Eur J Cancer 2023; 193:113318. Ungerleider NA, Rao SG, Shahbandi A, Yee D, Niu T, Frey WD et al. Breast cancer survival predicted by TP53 mutation status differs markedly depending on treatment. Breast Cancer Res 2018; 20(1):115. Le DT, Durham JN, Smith KN, Wang H, Bartlett BR, Aulakh LK et al. Mismatch repair deficiency predicts response of solid tumors to PD-1 blockade. Science 2017; 357(6349):409–13. Bonneville R, Krook MA, Kautto EA, Miya J, Wing MR, Chen H-Z et al. Landscape of Microsatellite Instability Across 39 Cancer Types. JCO Precis Oncol 2017; 2017. Cortes-Ciriano I, Lee S, Park W-Y, Kim T-M, Park PJ. A molecular portrait of microsatellite instability across multiple cancers. Nat Commun 2017; 8:15180. Klouch KZ, Stern M-H, Trabelsi-Grati O, Kiavue N, Cabel L, Silveira AB et al. Microsatellite instability detection in breast cancer using drop-off droplet digital PCR. Oncogene 2022; 41(49):5289–97. Kaleta T, Vesper AS, Rahner N, Loosen K, Cierna B, Ruhl D et al. Next-Gen-Sequencing basierte Multi-Genanalyse (TruRisk™-Genpanel) beim familiären Brust- und Eierstockkrebs. Geburtshilfe Frauenheilkd 2016; 76(10). Dill EA, Gru AA, Atkins KA, Friedman LA, Moore ME, Bullock TN et al. PD-L1 Expression and Intratumoral Heterogeneity Across Breast Cancer Subtypes and Stages: An Assessment of 245 Primary and 40 Metastatic Tumors. Am J Surg Pathol 2017; 41(3):334–42. Additional Declarations Competing interest reported. Franziska Fick received lecture honoraria from Novartis and travel expenses from Astra Zeneca and Novartis. Nikolas Tauber received honoraria for lectures and participation in advisory boards: Novartis, ExactSciences, Thieme, PRAEGNANT, if-kongress, Aurikamed. Support for atttending meetings from Astra Zeneca, DGGG e.V., if-kongress, Aurikamed. Achim Rody recieved lecture honoraria from Roche, Daiichi Sankyo, Astra Zeneca, Pfizer, Novartis, Celgen, Novartis, ExactSciences, MSD, Pierre Fabre, Lilly, Seagen, Targos Advisory Boards: Roche, Daiichi Sankyo, Astra Zeneca, Pfizer, Celgen, Eisai, Novartis, MSD, Hexal, Amgen, ExactSciences, Pierre Fabre Maggie Banys-Paluchowski is Associate Editor of Archives of Gynecology and Obstetrics and the European Journal of Surgical Oncology. Honoraria for lectures and participation in advisory boards: Roche, Novartis, Pfizer, pfm, Eli Lilly, Onkowissen, Seagen, AstraZeneca, Eisai, Amgen, Samsung, Canon, MSD, GSK, Daiichi Sankyo, Gilead, Sirius Medical, Syantra, resitu, Pierre Fabre, ExactSciences. Study support: Damp Stiftung, AWOgyn, AGO-B, Claudia von Schilling Breast Cancer Research Foundation, Ehmann Stiftung, EndoMag, Mammotome, MeritMedical, Sirius Medical, Gilead, Hologic, ExactSciences. Travel expenses: Eli Lilly, ExactSciences, Pierre Fabre, Pfizer, Daiichi Sankyo, Roche. All oher authors declare that they have no financial interests. Cite Share Download PDF Status: Published Journal Publication published 18 Nov, 2025 Read the published version in Archives of Gynecology and Obstetrics → Version 1 posted Editorial decision: Revision requested 08 Aug, 2025 Reviews received at journal 07 Aug, 2025 Reviewers agreed at journal 07 Aug, 2025 Reviewers invited by journal 05 Aug, 2025 Editor assigned by journal 17 Jul, 2025 Submission checks completed at journal 15 Jul, 2025 First submitted to journal 14 Jul, 2025 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. 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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-7119537","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":497710291,"identity":"87b0baf6-5f3b-4d27-b55e-0597501f343d","order_by":0,"name":"Franziska Fick","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+klEQVRIiWNgGAWjYBAC+wMg0gAIGRgfHGA4YMMgwcDDAEI4gQEDXAuzAVBLGrFaGCBaGBgOHCZCi/ThZw9/FNQZ8zcwMx74ceZ84sz+swcY3lTg8QtfmrmBhMFhM4kDzAwHe27cTpwtkZfAOOcMHlt4GMwkDAyA3j7AD3TVh9uJ8yR4DJh52/BpYf8mkWBQZyMPtAWo5VziPP4zQC3/8GnhAbrJgNnMAKzlxoHE2Qw5QC0NeLWUSTYYHDY2PAzyy5lk45kzcgwOzjmG12HbJH/8qTOcd7yZ+cOPY3ayM86fMXzwpga3FgRgRmIfIEbDKBgFo2AUjALcAABW0VB9MVBu6wAAAABJRU5ErkJggg==","orcid":"","institution":"University Hospital Schleswig-Holstein","correspondingAuthor":true,"prefix":"","firstName":"Franziska","middleName":"","lastName":"Fick","suffix":""},{"id":497710294,"identity":"6a63a621-3f50-49d9-8e9a-133f5d58648f","order_by":1,"name":"Florian Lenz","email":"","orcid":"","institution":"University Hospital Schleswig-Holstein","correspondingAuthor":false,"prefix":"","firstName":"Florian","middleName":"","lastName":"Lenz","suffix":""},{"id":497710296,"identity":"1d4e8db8-16e5-476f-a8bf-9f2915263853","order_by":2,"name":"Verena-Wilbeth Sailer","email":"","orcid":"","institution":"University Hospital Schleswig-Holstein","correspondingAuthor":false,"prefix":"","firstName":"Verena-Wilbeth","middleName":"","lastName":"Sailer","suffix":""},{"id":497710299,"identity":"317d9f8b-ca0e-450f-bb6b-bff58f4aedaf","order_by":3,"name":"Achim Rody","email":"","orcid":"","institution":"University Hospital Schleswig-Holstein","correspondingAuthor":false,"prefix":"","firstName":"Achim","middleName":"","lastName":"Rody","suffix":""},{"id":497710300,"identity":"54f51dce-dd3d-4b3a-9e16-58e3b8ee39b9","order_by":4,"name":"Nikolas Tauber","email":"","orcid":"","institution":"University Hospital Schleswig-Holstein","correspondingAuthor":false,"prefix":"","firstName":"Nikolas","middleName":"","lastName":"Tauber","suffix":""},{"id":497710301,"identity":"64b43383-a726-44e9-8615-b83d2fe51663","order_by":5,"name":"Kerstin Muras","email":"","orcid":"","institution":"University Hospital Schleswig-Holstein","correspondingAuthor":false,"prefix":"","firstName":"Kerstin","middleName":"","lastName":"Muras","suffix":""},{"id":497710302,"identity":"86c90084-d2af-4a4d-a408-54bc5dfd79f2","order_by":6,"name":"Natalia Krawczyk","email":"","orcid":"","institution":"Düsseldorf University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Natalia","middleName":"","lastName":"Krawczyk","suffix":""},{"id":497710303,"identity":"2393f7c9-932f-461e-b42b-ad3b430c5b20","order_by":7,"name":"Julika Ribbat-Idel","email":"","orcid":"","institution":"University Hospital Schleswig-Holstein","correspondingAuthor":false,"prefix":"","firstName":"Julika","middleName":"","lastName":"Ribbat-Idel","suffix":""},{"id":497710304,"identity":"bc5689c5-8a69-4b2f-b9c4-fc847aa32e35","order_by":8,"name":"Franziska Hemptenmacher","email":"","orcid":"","institution":"University Hospital Schleswig-Holstein","correspondingAuthor":false,"prefix":"","firstName":"Franziska","middleName":"","lastName":"Hemptenmacher","suffix":""},{"id":497710305,"identity":"bd445d3c-831b-49ce-bb66-30f938323ad8","order_by":9,"name":"Maggie Banys-Paluchowski","email":"","orcid":"","institution":"University Hospital Schleswig-Holstein","correspondingAuthor":false,"prefix":"","firstName":"Maggie","middleName":"","lastName":"Banys-Paluchowski","suffix":""}],"badges":[],"createdAt":"2025-07-14 09:38:30","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7119537/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7119537/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s00404-025-08209-x","type":"published","date":"2025-11-18T15:57:32+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":88948680,"identity":"b042e87e-3fc7-4d81-8926-6b6ce69b030f","added_by":"auto","created_at":"2025-08-13 05:35:04","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":23070,"visible":true,"origin":"","legend":"\u003cp\u003eReceptor status of included patients.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7119537/v1/e2fa69a9e3e1762560bde4d0.png"},{"id":88948681,"identity":"45bbc027-4e21-4a2f-b0d9-56d7082ef8bf","added_by":"auto","created_at":"2025-08-13 05:35:04","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":42622,"visible":true,"origin":"","legend":"\u003cp\u003epCR rates (complete, breast, nodal).\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7119537/v1/3ec0040d3b26b5b21ec3dda9.png"},{"id":88950055,"identity":"49d9f355-63a4-4b34-8d3a-9da33054236c","added_by":"auto","created_at":"2025-08-13 05:43:04","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":40340,"visible":true,"origin":"","legend":"\u003cp\u003epCR rates according to receptor status of the tumor\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7119537/v1/f010a9a79af60eb5a24a4e39.png"},{"id":96650088,"identity":"ebd4c38b-053e-4e52-87c4-8b901fb28b77","added_by":"auto","created_at":"2025-11-24 16:06:57","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1153914,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7119537/v1/38346101-6b24-490d-97cf-99a2e7348b97.pdf"}],"financialInterests":"Competing interest reported. Franziska Fick received lecture honoraria from Novartis and travel expenses from Astra Zeneca and Novartis.\n\nNikolas Tauber received honoraria for lectures and participation in advisory boards: Novartis, ExactSciences, Thieme, PRAEGNANT, if-kongress, Aurikamed. Support for atttending meetings from Astra Zeneca, DGGG e.V., if-kongress, Aurikamed. \n\nAchim Rody recieved lecture honoraria from Roche, Daiichi Sankyo, Astra Zeneca, Pfizer, Novartis, Celgen, Novartis, ExactSciences, MSD, Pierre Fabre, Lilly, Seagen, Targos\nAdvisory Boards: Roche, Daiichi Sankyo, Astra Zeneca, Pfizer, Celgen, Eisai, Novartis, MSD, Hexal, Amgen, ExactSciences, Pierre Fabre\n\nMaggie Banys-Paluchowski is Associate Editor of Archives of Gynecology and Obstetrics and the European Journal of Surgical Oncology. Honoraria for lectures and participation in advisory boards: Roche, Novartis, Pfizer, pfm, Eli Lilly, Onkowissen, Seagen, AstraZeneca, Eisai, Amgen, Samsung, Canon, MSD, GSK, Daiichi Sankyo, Gilead, Sirius Medical, Syantra, resitu, Pierre Fabre, ExactSciences. Study support: Damp Stiftung, AWOgyn, AGO-B, Claudia von Schilling Breast Cancer Research Foundation, Ehmann Stiftung, EndoMag, Mammotome, MeritMedical, Sirius Medical, Gilead, Hologic, ExactSciences. Travel expenses: Eli Lilly, ExactSciences, Pierre Fabre, Pfizer, Daiichi Sankyo, Roche.\n\nAll oher authors declare that they have no financial interests.","formattedTitle":"AXINEO: AXIllary response to NEOadjuvant chemotherapy for breast cancer: can we predict response based on a biomarker panel?","fulltext":[{"header":"Introduction","content":"\u003cp\u003eBreast cancer (BC) is the most common malignancy in women worldwide (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). In Germany, one in five patients receive neoadjuvant chemotherapy (NACT) before definitive surgery (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Depending on the subtype and extent of disease, NACT is able to eradicate all invasive tumor cells (pathological complete response = pCR) in up to 60% of patients with early BC and factors associated with breast-pCR have been extensively investigated. Regarding nodal response, recent data show that approximately 50–60% of patients initially cN + have no vital tumor cells in axillary lymph nodes following NACT (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Importantly, axillary response to therapy guides treatment choices regarding surgical therapy of the axilla (\u003cspan additionalcitationids=\"CR6 CR7 CR8 CR9\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e–\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Patients with cN+ → ycN0 conversion are recommended de-escalated procedures, such as targeted axillary dissection or sentinel node biopsy, while whose with persistently suspicious lymph nodes are usually offered axillary lymph node dissection, associated with increased risk of arm morbidity and lymph edema (\u003cspan additionalcitationids=\"CR12 CR13 CR14\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e–\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). However, predicting axillary response to treatment remains challenging, and imaging such as axillary ultrasound often fails to accurately detect axillary residual disease (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Therefore, tools allowing for a reliable identification of patients most likely to reach axillary pCR are urgently needed.\u003c/p\u003e\u003cp\u003eBeyond established predictive factors such as tumor size, number of positive lymph nodes, hormone receptor and Her2 status, grading and ki67, assessing tissue-based biomarkers may further improve response prediction.\u003c/p\u003e\u003cp\u003eThe present study aimed at examining a panel of biomarkers assessed on core-biopsy of lymph node metastatic tissue with the goal to establish predictive markers for treatment response to neoadjuvant chemotherapy in node-positive breast cancer. The following biomarkers were chosen based on their association with tumorigenesis and tumor progression: p53 expression status, TROP 2 (Tumor-associated calcium signal transducer 2), PD-L1 (Programmed Cell Death 1 Ligand 1), CAIX (Hypoxia-regulated carbonic anhydrase IX) and MSI (microsatellite instability).\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eWe analysed core biopsy specimens of lymph node metastases of 40 female patients treated at the certified Breast Center at the University Hospital Schleswig-Holstein between 2018 and 2024. Patients were chosen retrospectively according to their nodal pCR (50% nodal pCR, 50% nodal non-pCR). We defined complete pCR as ypT0 and ypN0. They were selected retrospectively due to their postoperative pCR result. The study was supported by a research grant from Gilead (\u003cem\u003eGilead Förderprogramm\u003c/em\u003e). The study was aproved by the local ethical committee and only patients who consented to the use of their data and archived tissue were included.\u003c/p\u003e\u003cp\u003eImmunohistochemistry and evaluation\u003c/p\u003e\u003cp\u003eThe expression of p53, CAIX, PD-L1, TROP2, MSH2, MSH6, MLH1 and PMS2 was assessed using immunohistochemistry on 4 µm-thin sections. A positive control was provided for each marker as listed below.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eTargets and used antibodies\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eantibody target\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003ename\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDilution\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003emanufacturer\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003epositive control\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMLH1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMLH1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRTU*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eVentana (Roche)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ecolon\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMSH2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMSH2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRTU\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eVentana (Roche)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ecolon\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMSH6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMSH6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRTU\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eVentana (Roche)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ecolon\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePMS2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePMS2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRTU\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eVentana (Roche)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ecolon\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ep53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ep53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRTU\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eVentana (Roche)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003etonsil\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCA IX\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCarbonic Anhydrase IX\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRTU\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eVentana (Roche)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003egastric mucosa\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTROP2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTROP2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1:500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eabcam\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ebreast cancer\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePD-L1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePD-L1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1:50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eDako\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003etonsil\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e*RTU = Ready To Use\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe p53 staining result was interpreted as previously described in ovarian carcinomas (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e) and was indicated as either mutational-type or wild-type.\u003c/p\u003e\u003cp\u003ePD-L1 status was evaluated as the proportion of tumor cells with any membrane-bound staining reaction and was reported as TPS. Due to the lack of differentiation between tumor-associated immune cells and local immune cells of the lymph node tissue, the CPS was not further evaluated.\u003c/p\u003e\u003cp\u003eThe mismatch-repair proteins were considered intact/preserved if all tumor cells showed a consistent, strong nuclear staining. In contrast, a complete lack of nuclear staining was declared as a loss, indicating a mismatch-repair-deficiency.\u003c/p\u003e\u003cp\u003eThe stained slides of CAIX and TROP2 were scanned using Ventana DP200 (Roche) at 40x magnification. QuPath software (version 0.4.4) was used to visualize the staining for CAIX and TROP2. A pathologist manually marked the tumor cells and set the parameters for cell detection as well as thresholds for classification in negative (0), weakly (1+), moderately (2+) and strongly (3+) positive tumor cells. Subsequently the immunohistochemical expression was quantified by the software providing the H-score. The mean value of the H-Scores of each tumor sample was used for statistical analysis.\u003c/p\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eWe used SPSS Version 29 for statistical analyses. First, the data was examined for the presence of a normal distribution. Depending on the result, the H-scores of the respective cohorts were compared using the Mann-Whitney and Kruskal-Wallis-tests (CAIX and PDL1), chi-squared test (P53) or the ANOVA (TROP2). The p53-status was reported for each tumor sample as mutation-type or wild-type. In analogy, the tumor samples were classified as showing an intact or lost staining for the mismatch-repair proteins. The frequencies of the respective type in the two cohorts resulted in nominal scaled data and were statistically analyzed using the chi-squared test. The significance level was set at \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05. Primary endpoint was the correlation with therapy response, defined as pCR (complete, breast, nodal).\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eTumor biology and patients characteristics\u003c/p\u003e\n\u003cp\u003eMedian age at diagnosis was 53 years (SD 12.3, range: 28\u0026ndash;77 years). 17 out of 40 (42.5%) patients were premenopausal, one (2,5%) perimenopausal, 22 (55%) postmenopausal at diagnosis. All tumors had at least a G2 grading, 75% were G3. Median tumor size was 27.7 mm (SD 17.3). One patient had an inflammatory breast cancer. Average number of suspicious lymph nodes at diagnosis was two (SD 1.2, range 1 to 5).\u003c/p\u003e\n\u003cp\u003eThe most common subtype, assessed on primary tumor, was triple negative breast cancer (TNBC) (10 patients, 25%), followed by HR positive Her2 negative (16; 40%) and Her2 positive (14; 35%). Among patients with Her2 positive disease, 8 had HR positive and 6 HR negative tumors. One patient presented with a bifocal cancer, with one lesion HR positive Her2 negative and the other Her2 positive.\u003c/p\u003e\n\u003cp\u003eNeoadjuvant Chemotherapy (NACT)\u003c/p\u003e\n\u003cp\u003eAll 40 patients underwent neoadjuvant chemotherapy for nodal positive breast cancer diagnosis according to the tumor biology and current standard of care. 65.0% (26/40) completed the chemotherapy as recommended. The remaining 14 patients experienced major adverse events such as peripheral neuropathy, diarrhoea, haematological toxicity or acute kidney injury and either discontinued chemotherapy or underwent dose reduction.\u003c/p\u003e\n\u003cp\u003eSurgical treatment\u003c/p\u003e\n\u003cp\u003e21 patients (52.5%) received a breast-conserving therapy and 19 had a mastectomy (47.5%). The most common axillary procedure was primary axillary lymph node dissection performed in 20 patients (50%), followed by a targeted axillary dissection (TAD) in 17 patients (42.5% %) and sentinel lymph node biopsy in three patients (7,5%). Out of 17 patients receiving TAD initially, four (23,5%) underwent completion axillary lymph node dissection. In summary, 24 patients received axillary dissection in total (20 primary and 4 patients secondary after TAD, 60%). All patients characteristics are shown in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab2\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003ePatients characteristics\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eMedian/Percentage\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e53 years (SD 12.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eTumor size\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e27.7 mm (SD 17.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eNumber of suspicious lymph nodes at diagnosis\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eKi67\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e50%\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eCompletion of neoadjuvant chemotherapy as planned\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eYes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNo\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e65.0% (26/40)\u003c/p\u003e\n\u003cp\u003e35.0% (14/40)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eBreast surgery\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBreast-conserving surgery\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMastectomy\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e52.5% (21/40)\u003c/p\u003e\n\u003cp\u003e47.5% (19/40)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eFinal axillary surgery\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSentinel node biopsy\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTargeted axillary dissection (TAD)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAxillary lymph node dissection\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e7.5% (3/40)\u003c/p\u003e\n\u003cp\u003e32.5% (13/40)\u003c/p\u003e\n\u003cp\u003e60.0% (24/40)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eBiomarker analysis\u003c/p\u003e\n\u003cp\u003eIn this cohort, none of the tested markers on the lymph node specimen was correlated significantly with pathological response to chemotherapy (pCR, ypT0, ypN0). Only 13 out of 40 patients had a complete pCR (32.5%). One patient had only noninvasive tumor rest (ypTis) after surgery. The other 26 had invasive tumor rest in the breast (ypT1) and/or the lymph nodes (ypN+).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe pCR rates (complete, breast, nodal) differed significantly between the different receptor status (complete pCR p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, breast p\u0026thinsp;=\u0026thinsp;0.003, nodal p\u0026thinsp;=\u0026thinsp;0.004, Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e. The lowest pCR rate was observed in HR positive Her2 negative breast cancers (complete pCR 0%, breast pCR 6.25%, nodal pCR 18.75%). In general more patients had nodal pCR (50%, n\u0026thinsp;=\u0026thinsp;20) than breast pCR (37.5%, n\u0026thinsp;=\u0026thinsp;15), see Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e24 out of 40 (60%) patients underwent germline genetic testing at the certified Center for Familial Breast and Ovarian Cancer (FBREK). Out of these, six (25% of all tested patients and 15% of the total cohort) were mutational carriers (1 x BRCA1, 3 x BRCA2, 1 x CHEK2, 1 x PTEN). No significant differences in the tested markers were shown between germline mutation carriers and non-carriers\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003cdiv class=\"colspec\" align=\"char\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003ctable id=\"Tab3\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eBiomarker panel assessed on the core-biopsy lymph node metastatic tissue and correlation of markers and clinical-pathological factors (p-values\u0026thinsp;\u0026lt;\u0026thinsp;0.05 are shown in bold); since all specimens were microsatellite stable, MSI status was not included in the table.\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eTotal (n)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eTROP 2\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eTROP2 high*\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eP53 mutation\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003ePD-L1\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003ePD-L1\u0026thinsp;\u0026ge;\u0026thinsp;1%\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eCAIX\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eCAIX high*\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eTotal number of analysed patients (n)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e40\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e39\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e39\u003c/p\u003e\n\u003cp\u003eMedian: 171.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e40\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e38\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e38\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e39\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e39\u003c/p\u003e\n\u003cp\u003eMedian: 0.025\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003epCR\u003c/strong\u003e \u003csup\u003e\u003cstrong\u003e1)\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eYes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNo\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ep-value\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e13\u003c/p\u003e\n\u003cp\u003e27\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e12\u003c/p\u003e\n\u003cp\u003e27\u003c/p\u003e\n\u003cp\u003e0.571\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e6 (50%)\u003c/p\u003e\n\u003cp\u003e14 (51.9%)\u003c/p\u003e\n\u003cp\u003e0.915\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e9 (69.2%)\u003c/p\u003e\n\u003cp\u003e15 (55.6%)\u003c/p\u003e\n\u003cp\u003e0.408\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.756\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e1 (8.3%)\u003c/p\u003e\n\u003cp\u003e8 (30.8%)\u003c/p\u003e\n\u003cp\u003e0.130\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e0.070\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e8 (66.7%)\u003c/p\u003e\n\u003cp\u003e12 (44.4%)\u003c/p\u003e\n\u003cp\u003e0.200\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eBreast pCR\u003c/strong\u003e \u003csup\u003e\u003cstrong\u003e2)\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eYes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNo\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ep-value\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e15\u003c/p\u003e\n\u003cp\u003e25\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e14\u003c/p\u003e\n\u003cp\u003e25\u003c/p\u003e\n\u003cp\u003e0.315\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e8 (57.1%)\u003c/p\u003e\n\u003cp\u003e12 (48%)\u003c/p\u003e\n\u003cp\u003e0.584\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e10 (66.7%)\u003c/p\u003e\n\u003cp\u003e14 (56%)\u003c/p\u003e\n\u003cp\u003e0.505\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e0.790\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e2 (14.3%)\u003c/p\u003e\n\u003cp\u003e7 (29.2%)\u003c/p\u003e\n\u003cp\u003e0.298\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e0.251\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e9 (64.3%)\u003c/p\u003e\n\u003cp\u003e11 (44%)\u003c/p\u003e\n\u003cp\u003e0.224\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eNodal pCR\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eYes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNo\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ep-value\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e20\u003c/p\u003e\n\u003cp\u003e20\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e19\u003c/p\u003e\n\u003cp\u003e20\u003c/p\u003e\n\u003cp\u003e0.562\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e9 (47.4%)\u003c/p\u003e\n\u003cp\u003e11 (55%)\u003c/p\u003e\n\u003cp\u003e0.634\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e14 (70%)\u003c/p\u003e\n\u003cp\u003e10 (50%)\u003c/p\u003e\n\u003cp\u003e0.197\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e0.752\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e4 (22.2%)\u003c/p\u003e\n\u003cp\u003e5 (25%)\u003c/p\u003e\n\u003cp\u003e0.841\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e0.166\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e12 (63.2%)\u003c/p\u003e\n\u003cp\u003e8 (40%)\u003c/p\u003e\n\u003cp\u003e0.148\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026ge; 53 years\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt; 53 years\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ep-value\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e20\u003c/p\u003e\n\u003cp\u003e20\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e19\u003c/p\u003e\n\u003cp\u003e20\u003c/p\u003e\n\u003cp\u003e0.506\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e9 (47.4%)\u003c/p\u003e\n\u003cp\u003e11 (55%)\u003c/p\u003e\n\u003cp\u003e0.421\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e13 (65%)\u003c/p\u003e\n\u003cp\u003e11 (55%)\u003c/p\u003e\n\u003cp\u003e0.519\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e0.057\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e7 (36.8%)\u003c/p\u003e\n\u003cp\u003e2 (10.5%)\u003c/p\u003e\n\u003cp\u003e0.056\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e0.033\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e14 (73.7%)\u003c/p\u003e\n\u003cp\u003e6 (30%)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e0.006\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eGrading\u003c/strong\u003e \u003csup\u003e\u003cstrong\u003e3)\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eG2\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eG3\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ep-value\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e10\u003c/p\u003e\n\u003cp\u003e30\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e10\u003c/p\u003e\n\u003cp\u003e29\u003c/p\u003e\n\u003cp\u003e0.078\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e3 (30.0%)\u003c/p\u003e\n\u003cp\u003e17 (56.7%)\u003c/p\u003e\n\u003cp\u003e0.118\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e3 (30%)\u003c/p\u003e\n\u003cp\u003e21 (70%)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e0.025\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e0.336\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e1 (11.1%)\u003c/p\u003e\n\u003cp\u003e8 (27.6%)\u003c/p\u003e\n\u003cp\u003e0.310\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e0.272\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e3 (30%)\u003c/p\u003e\n\u003cp\u003e17 (58.6%)\u003c/p\u003e\n\u003cp\u003e0.118\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eKi67\u003c/strong\u003e \u003csup\u003e3)\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026ge;\u0026thinsp;50%\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;50%\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ep-value\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e20\u003c/p\u003e\n\u003cp\u003e20\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e20\u003c/p\u003e\n\u003cp\u003e19\u003c/p\u003e\n\u003cp\u003e0.288\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e10 (50%)\u003c/p\u003e\n\u003cp\u003e10 (52.6%)\u003c/p\u003e\n\u003cp\u003e0.869\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e15 (75%)\u003c/p\u003e\n\u003cp\u003e9 (45%)\u003c/p\u003e\n\u003cp\u003e0.053\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e0.775\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e6 (33.3%)\u003c/p\u003e\n\u003cp\u003e3 (15%)\u003c/p\u003e\n\u003cp\u003e0.184\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e0.235\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e12 (60%)\u003c/p\u003e\n\u003cp\u003e8 (42.1%)\u003c/p\u003e\n\u003cp\u003e0.264\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eSubtype\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNST\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOther\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ep-value\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e36\u003c/p\u003e\n\u003cp\u003e4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e35\u003c/p\u003e\n\u003cp\u003e4\u003c/p\u003e\n\u003cp\u003e0.905\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e17 (48.6%)\u003c/p\u003e\n\u003cp\u003e1 (50%)\u003c/p\u003e\n\u003cp\u003e0.998\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e20 (57.1%)\u003c/p\u003e\n\u003cp\u003e3 (75%)\u003c/p\u003e\n\u003cp\u003e0.787\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e-----\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e9 (26,5%)\u003c/p\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003cp\u003e0.331\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e37\u003c/p\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e0.021\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e15 (42.9%)\u003c/p\u003e\n\u003cp\u003e3 (75%)\u003c/p\u003e\n\u003cp\u003e0.197\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eMenopausal Status\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePre/perimenopausal\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePostmenopausal\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ep-value\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e18\u003c/p\u003e\n\u003cp\u003e22\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e18\u003c/p\u003e\n\u003cp\u003e21\u003c/p\u003e\n\u003cp\u003e0.903\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e9 (50%)\u003c/p\u003e\n\u003cp\u003e11 (52.4%)\u003c/p\u003e\n\u003cp\u003e0.882\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e10 (55.6%)\u003c/p\u003e\n\u003cp\u003e14 (45.5%)\u003c/p\u003e\n\u003cp\u003e0.604\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e0.130\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e2 (11.1%)\u003c/p\u003e\n\u003cp\u003e7 (33.3%)\u003c/p\u003e\n\u003cp\u003e0.120\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e0.028\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e5 (27.8%)\u003c/p\u003e\n\u003cp\u003e15 (71.4%)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e0.007\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eReceptor status\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHR\u0026thinsp;+\u0026thinsp;HER2-\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHER2 positive\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTriple-negative\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ep-value\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e16\u003c/p\u003e\n\u003cp\u003e14\u003c/p\u003e\n\u003cp\u003e10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e16\u003c/p\u003e\n\u003cp\u003e13\u003c/p\u003e\n\u003cp\u003e10\u003c/p\u003e\n\u003cp\u003e0.415\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e7 (43.8%)\u003c/p\u003e\n\u003cp\u003e6 (46.2%)\u003c/p\u003e\n\u003cp\u003e7 (70%)\u003c/p\u003e\n\u003cp\u003e0.386\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e6 (37.5%)\u003c/p\u003e\n\u003cp\u003e10 (71.4%)\u003c/p\u003e\n\u003cp\u003e8 (80%)\u003c/p\u003e\n\u003cp\u003e0.055\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e0.247\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e2 (13.3%)\u003c/p\u003e\n\u003cp\u003e3 (21.4%)\u003c/p\u003e\n\u003cp\u003e4 (44.4%)\u003c/p\u003e\n\u003cp\u003e0.215\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e0.263\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e3 (18.8%)\u003c/p\u003e\n\u003cp\u003e9 (69.2%)\u003c/p\u003e\n\u003cp\u003e8 (80%)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e0.003\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eGermline mutation\u003c/strong\u003e \u003csup\u003e\u003cstrong\u003e4)\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eYes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNo\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNo data/not tested\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ep-value\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e6\u003c/p\u003e\n\u003cp\u003e16\u003c/p\u003e\n\u003cp\u003e18\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e6\u003c/p\u003e\n\u003cp\u003e15\u003c/p\u003e\n\u003cp\u003e18\u003c/p\u003e\n\u003cp\u003e0.592\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e3 (50%)\u003c/p\u003e\n\u003cp\u003e7 (46.7%)\u003c/p\u003e\n\u003cp\u003e10 (55.6%)\u003c/p\u003e\n\u003cp\u003e0.877\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e3 (50%)\u003c/p\u003e\n\u003cp\u003e4 (25%)\u003c/p\u003e\n\u003cp\u003e9 (50%)\u003c/p\u003e\n\u003cp\u003e0.287\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e0.925\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e1 (20%)\u003c/p\u003e\n\u003cp\u003e4 (25%)\u003c/p\u003e\n\u003cp\u003e4 (23.5%)\u003c/p\u003e\n\u003cp\u003e0.974\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e0.305\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e3 (50%)\u003c/p\u003e\n\u003cp\u003e6 (40%)\u003c/p\u003e\n\u003cp\u003e11 (61.1%)\u003c/p\u003e\n\u003cp\u003e0.481\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003csup\u003e*\u003c/sup\u003e defined as expression level above median\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e1)\u003c/sup\u003e defined as ypT0 ypN0\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e2)\u003c/sup\u003e defined as ypT0\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e3)\u003c/sup\u003e breast biopsy\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e4)\u003c/sup\u003e Germline mutation tested with the German Consortium for Familial Breast and Ovarian Cancer panel\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eTROP2\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eTROP2 expression (H-Score) was analyzed in 39 patients with an average of 177.85, median 171.0, with a standard deviation (SD) of 59.21; range 1.4 to 290.0. There were no significant differences shown for the TROP2 H-Score and the different parameters tested, see Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e. TROP2-high was defined as TROP2 expression level above the median of 171.0. There were no significant associations with other factors or response to treatment.\u003c/p\u003e\n\u003cp\u003eThere was no correlation between high CAIX expression (define as levels above median) and high TROP2 score (p\u0026thinsp;=\u0026thinsp;0.634). 11/20 patients (55%) were both TROP2 and CAIX high, 10/19 (52.6%) had both biomarkers at a level lower than the median.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eP53\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe p53 protein-expression was described binary (mutated/wildtype). The tumors of 24 patients (60%) showed a p53 mutational-type-expression and 16 (40%) showed p53 wildtype-expression. P53 mutation was significantly more frequent in G3 tumors (p\u0026thinsp;=\u0026thinsp;0.025). 14 out of 20 patients (70.0%) with axillary pCR had a p53 mutation in the lymph node tissue, compared to 10 out of 20 (50.0%) with axillary non-pCR. There were no other significant results found.\u003c/p\u003e\n\u003cp\u003eWith regard to receptor status, HR\u0026thinsp;+\u0026thinsp;Her2 negative tumors showed p53 mutations in 37.5% (n\u0026thinsp;=\u0026thinsp;6) of cases, whereas Her2 positive and triple negative tumors had p53 mutations in 71.4% (n\u0026thinsp;=\u0026thinsp;10) and 80% (n\u0026thinsp;=\u0026thinsp;8), respectively (p\u0026thinsp;=\u0026thinsp;0.055).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ePD-L1\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003ePD-L1 status could be analyzed in 38 patients. The average value was 1.46% with a range from 0 to 10% and a standard deviation of 1.92%. No differences were found for PD-L1 in between subgroups. Older patients were numerically more likely to have PD-L1\u0026thinsp;\u0026ge;\u0026thinsp;1% in lymph node metastasis than younger patients (p\u0026thinsp;=\u0026thinsp;0.057).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eCAIX\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eCAIX expression was 6.106 in average, median 0.025, with a standard deviation (SD) of 15.96; range 0.0 to 69.15. Higher CAIX levels assessed in the lymph node core-biopsy were associated with triple negative and Her2 positive receptor status (p\u0026thinsp;=\u0026thinsp;0.003), Ki67\u0026thinsp;\u0026ge;\u0026thinsp;50% (assessed in breast core biopsy, p\u0026thinsp;=\u0026thinsp;0.005) as well as postmenopausal status (p\u0026thinsp;=\u0026thinsp;0.007).\u003c/p\u003e\n\u003cp\u003eWe grouped patients with CAIX above median as CAIX high. 63.2% of patients who achieved nodal pCR had above-median CAIX expression (CAIX high) levels, compared to 40% among patients with non-pCR (p\u0026thinsp;=\u0026thinsp;0.148). 80% (n\u0026thinsp;=\u0026thinsp;8) of the triple negative breast cancers had a CAIX expression levels above median e.g. CAIX high (p\u0026thinsp;=\u0026thinsp;0.003), compared to 69.2% of the Her2\u0026thinsp;+\u0026thinsp;subtype (n\u0026thinsp;=\u0026thinsp;9) and 18.8% (n\u0026thinsp;=\u0026thinsp;3) of the HR\u0026thinsp;+\u0026thinsp;Her2- group.\u003c/p\u003e\n\u003cp\u003eWe found significantly higher CAIX expressions in older and postmenopausal patients. The median for postmenopausal women was 0.670, respective 0.035 for pre/perimenopausal patients (p\u0026thinsp;=\u0026thinsp;0.028). Matching this result CAIX expression levels were also higher in patients\u0026thinsp;\u0026ge;\u0026thinsp;53 years old (average 6.303 vs. 5.919; SD 16.29 vs. 16.06; p\u0026thinsp;=\u0026thinsp;0.033). 14 patients older than 52 years (73.7%) versus 6 patients aged 52 or younger (30%) were in the CAIX high group (p\u0026thinsp;=\u0026thinsp;0.006).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eMSI\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eAll tumors were microsatellite stable (testing was performed with MSH2, MSH6, MLH1 and PMS2 immunohistochemistry), so no further analysis could be made.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eTo the best of our knowledge, this is the first comprehensive biomarker analysis of lymph node metastatic tissue in patients receiving neoadjuvant chemotherapy. The biomarkers were chosen based on their association with tumorigenesis and tumor progression.\u003c/p\u003e\u003cp\u003eAs expected, in the present analysis more patients in the nodal pCR group had triple-negative and HER2-positive tumors, compared to patients with nodal non-pCR. This goes along with research findings of the meta-analysis from 2020 which showed pCR rates to be lower in HR positive breast cancers (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eHypoxia-regulated carbonic anhydrase IX (CAIX) is a hypoxia inducible molecular marker. The majority of studies suggest that CAIX can serve as a biomarker and therapeutic target in different tumor types. (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e) CAIX can promote tumorigenesis and is associated with a more aggressive phenotype of cancer cells (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). Ong et al. analyzed specimens of more than 300 TNBC patients and found out that increased CAIX protein levels are independently associated with poor survival (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). Interestingly, in our study, 80% of patients with triple negative breast cancers had a CAIX expression in lymph node metastasis above median (CAIX high), compared to 69.2% of the Her2\u0026thinsp;+\u0026thinsp;subtype and 18.8% of the HR\u0026thinsp;+\u0026thinsp;Her2-negative group (p\u0026thinsp;=\u0026thinsp;0.003). This is in accordance with previous studies, which reported a significantly higher expression of CAIX in triple negative breast cancer (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). Furthermore, overexpression of CAIX protein in TNBC is associated with a BRCA1 mutant signature and loss of BRCA1 function (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). As there was only one patient with BRCA1 mutation in our study, further analyses were not possible. The correlation between CAIX and BRCA1 mutation, clearly associated with triple-negative subptype, should be investigated in future studies.\u003c/p\u003e\u003cp\u003eOne critical aspect that is worth noting in this context is the relatively high inter-observer variability of CAIX expression and its dependance on the quality of biopsies (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). Techniques to standardize histopathological assessment and lower inter-observer variability still need to be optimized in order to make the marker more comparable. Currently, research on CAIX fluoroscopy in single-photon emission computerized tomography (SPECT), positron emission tomography (PET), and near-infrared fluorescence imaging (NIRF) is ongoing. Hypothetically, these imaging modalities could be used in nodal positive breast cancer patients to determine CAIX expression in the future (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eRegarding potential therapeutic consequences, CAIX-based agents like the CAIX-specific monoclonal antibody girentuximab have been evaluated in a phase III clinical trials in high-risk renal cell carcinoma (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). Currently, no studies in breast cancer patients are available. Implementation of CAIX-based treatment could potentially enable new therapeutic strategies for high-risk breast cancer patients (e.g., triple negative, Ki67\u0026thinsp;\u0026ge;\u0026thinsp;50%).\u003c/p\u003e\u003cp\u003eIn the present study, we show higher TROP2 expression in lymph node metastasis in patients with TNBC. TROP2 is a membrane protein involved in tumor progression by actively interacting with several key signaling pathways associated with cancer development and plays an important role in tumor growth, invasion, treatment resistance and metastasis. TROP2-targeted drugs are available such as sacituzumab govitecan (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). Further, high TROP2 expression correlates with poorer response and drug resistance (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). Previous studies have shown TROP2 expression to be heterogeneous among breast cancer subtypes (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e), with higher expression in triple negative breast cancer. However, in contrast to our study, these analyses were performed on breast specimens (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn our study, more patients with nodal pCR had p53 mutations in their lymph nodes (70% vs. 50%, p\u0026thinsp;=\u0026thinsp;0.197) with further investigation in larger cohorts needed. P53 mutations were also more common in case of aggressive tumors (such as G3). We could also observe a potential difference in receptor status for p53-mutations. Accordingly, HR\u0026thinsp;+\u0026thinsp;Her2-negative cases showed p53 mutations in the lymph node in 37.5%, whereas Her2-positive and triple-negative patients showed p53 mutations in 71.4% and 80%, respectively (p\u0026thinsp;=\u0026thinsp;0.055). P53, as a transcription factor, plays an important regulatory role in the multitude of cellular processes. Genotoxic stress leads to activation of p53 to facilitate DNA repair, cell cycle arrest, and apoptosis. P53 has been shown to be an important biomarker in endometrial cancer but is not one of the standard markers in breast cancer (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e), although it is the most frequently mutated gene in breast cancers (up to 30%, subtype depending). The evidence on the prognostic value of p53 is not conclusive and seems to depend on hormonal status and prior treatment (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eMSI is an established marker for various tumors such as colorectal and endometrial cancer and is frequently used as a predictive factor for immune checkpoint inhibitor therapy (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). In breast cancer, however, the prevalence of microsatellite instability is low (1.8% or less) (\u003cspan additionalcitationids=\"CR36\" citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e). This is in line with our study. All lymph node metastatic specimens analyzed were microsatellite stable. Nevertheless, MSH2, MSH6, MLH1 and PMS2 are part of extended germline testing in BC patients using the TruRisk\u0026copy;-Panel at German Centers for Familial Breast and Ovarian Cancer which currently includes ATM, BRCA1, BRCA2, BRIP1, CDH1, CHEK2, EPCAM, MLH1, MSH2, MSH6, PALB2, PMS2, PTEN, RAD51C, RAD51D, STK11, TP53 (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eOne limitation of our study is the moderate number of patients (n\u0026thinsp;=\u0026thinsp;40). Some of the initially planned assays such as PIK3CA somatic mutational analysis were not possible because of the limited amount of core-biopsy tissue specimen available. As the tests were conducted on lymph node metastatic core biopsies, we also cannot exclude intratumoral heterogeneity. This applies, for example, to PD-L1-status, for which high variability in expression within the same tumor has also been demonstrated in breast cancer (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eBecause of the retrospective selection of patients according to their nodal response there might be a selection bias.\u003c/p\u003e\u003cp\u003eFurther studies should focus on CAIX expression and TP53 mutational status as well as possibly further potential biomarkers to improve the selection of patients most likely to achieve axillary response.\u003c/p\u003e\u003cp\u003eSummary\u003c/p\u003e\u003cp\u003eAmong the biomarkers analyzed, numerical differences in the expression levels of CAIX and tissue mutational status of P53 were observed between patients with nodal pCR and non-pCR. Our study shows that upregulation of hypoxemia marker CAIX in the lymph node metastatic tissue before start of systemic therapy is significantly associated with a more aggressive tumor subtype. Further research is necessary to better identify patients most likely to achieve nodal response after neoadjuvant treatment, and thus best eligible for surgical de-escalation, e.g., targeted axillary dissection or sentinel node biopsy alone instead of full axillary lymph node dissection.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003cp\u003eFranziska Fick received lecture honoraria from Novartis and travel expenses from Astra Zeneca and Novartis.Nikolas Tauber received honoraria for lectures and participation in advisory boards: Novartis, ExactSciences, Thieme, PRAEGNANT, if-kongress, Aurikamed. Support for atttending meetings from Astra Zeneca, DGGG e.V., if-kongress, Aurikamed. Achim Rody recieved lecture honoraria from Roche, Daiichi Sankyo, Astra Zeneca, Pfizer, Novartis, Celgen, Novartis, ExactSciences, MSD, Pierre Fabre, Lilly, Seagen, TargosAdvisory Boards: Roche, Daiichi Sankyo, Astra Zeneca, Pfizer, Celgen, Eisai, Novartis, MSD, Hexal, Amgen, ExactSciences, Pierre FabreMaggie Banys-Paluchowski is Associate Editor of Archives of Gynecology and Obstetrics and the European Journal of Surgical Oncology. Honoraria for lectures and participation in advisory boards: Roche, Novartis, Pfizer, pfm, Eli Lilly, Onkowissen, Seagen, AstraZeneca, Eisai, Amgen, Samsung, Canon, MSD, GSK, Daiichi Sankyo, Gilead, Sirius Medical, Syantra, resitu, Pierre Fabre, ExactSciences. Study support: Damp Stiftung, AWOgyn, AGO-B, Claudia von Schilling Breast Cancer Research Foundation, Ehmann Stiftung, EndoMag, Mammotome, MeritMedical, Sirius Medical, Gilead, Hologic, ExactSciences. Travel expenses: Eli Lilly, ExactSciences, Pierre Fabre, Pfizer, Daiichi Sankyo, Roche.All oher authors declare that they have no financial interests.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eFranziska Fick (F.F.) and Florian Lenz (F.L.) contributed equally to this manuscript.Franziska Hemptenmacher (F.H.) und Maggie Banys-Paluchowski (M.B-P.) contributed equally to this manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eŁukasiewicz S, Czeczelewski M, Forma A, Baj J, Sitarz R, Stanisławek A. Breast Cancer-Epidemiology, Risk Factors, Classification, Prognostic Markers, and Current Treatment Strategies-An Updated Review. 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Next-Gen-Sequencing basierte Multi-Genanalyse (TruRisk\u0026trade;-Genpanel) beim famili\u0026auml;ren Brust- und Eierstockkrebs. Geburtshilfe Frauenheilkd 2016; 76(10).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDill EA, Gru AA, Atkins KA, Friedman LA, Moore ME, Bullock TN et al. PD-L1 Expression and Intratumoral Heterogeneity Across Breast Cancer Subtypes and Stages: An Assessment of 245 Primary and 40 Metastatic Tumors. Am J Surg Pathol 2017; 41(3):334\u0026ndash;42.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"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":"archives-of-gynecology-and-obstetrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"arch","sideBox":"Learn more about [Archives of Gynecology and Obstetrics](https://www.springer.com/journal/404)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/arch/default.aspx","title":"Archives of Gynecology and Obstetrics","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-7119537/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7119537/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eUp to 60% of breast cancer patients achieve pathological complete response (pCR) and factors associated with breast-pCR have been extensively investigated. In patients with initially node-positive disease predicting axillary response to treatment remains challenging. Our study examines a biomarker panel assessed on core-biopsy lymph node metastatic tissue with the goal to establish predictive markers for nodal positive breast cancer.\u003c/p\u003e\u003ch2\u003eMaterial and Methods\u003c/h2\u003e\u003cp\u003e40 women with core biopsy-proven node-positive breast cancer scheduled to receive neoadjuvant treatment at the certified Breast Cancer Center of the University Hospital Schleswig-Holstein Campus L\u0026uuml;beck were included. The expression of CAIX, PD-L1, TROP2, MSH2, MSH6, MLH1 and PMS2 as well as p53 mutation were assessed. Biomarkers were chosen based on their association with tumorigenesis and tumor progression. Statistical analysis was performed using SPSS 29. This investigator-initiated study was supported by a research grant from Gilead (Gilead F\u0026ouml;rderprogramm).\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eHigher CAIX levels were associated with triple negative and Her2 positive receptor status (p\u0026thinsp;=\u0026thinsp;0.003), Ki67\u0026thinsp;\u0026ge;\u0026thinsp;50% in breast core biopsy (p\u0026thinsp;=\u0026thinsp;0.005) as well as postmenopausal status (p\u0026thinsp;=\u0026thinsp;0.007). P53 mutation was more frequent in G3 tumors (p\u0026thinsp;=\u0026thinsp;0.025). All lymph node metastases were microsatellite stable (MSS). None of the markers could significantly predict pathological response (complete, breast or nodal).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eOur study shows upregulated CAIX in lymph node metastasis frequently occurs in aggressive and highly proliferative tumors. However, none of the examined biomarkers could predict nodal response to therapy. Further research is necessary to better identify patients most likely to achieve nodal response through neoadjuvant chemotherapy.\u003c/p\u003e","manuscriptTitle":"AXINEO: AXIllary response to NEOadjuvant chemotherapy for breast cancer: can we predict response based on a biomarker panel?","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-13 05:34:59","doi":"10.21203/rs.3.rs-7119537/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-08-08T12:40:24+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-07T18:46:05+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"227216259002536508777192008259441346331","date":"2025-08-07T17:34:48+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-08-05T14:29:31+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-07-17T10:26:09+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-07-15T09:54:32+00:00","index":"","fulltext":""},{"type":"submitted","content":"Archives of Gynecology and Obstetrics","date":"2025-07-14T09:36:02+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"archives-of-gynecology-and-obstetrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"arch","sideBox":"Learn more about [Archives of Gynecology and Obstetrics](https://www.springer.com/journal/404)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/arch/default.aspx","title":"Archives of Gynecology and Obstetrics","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"d07438b2-4c6c-43ba-a495-ea87977c512d","owner":[],"postedDate":"August 13th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-11-24T16:00:51+00:00","versionOfRecord":{"articleIdentity":"rs-7119537","link":"https://doi.org/10.1007/s00404-025-08209-x","journal":{"identity":"archives-of-gynecology-and-obstetrics","isVorOnly":false,"title":"Archives of Gynecology and Obstetrics"},"publishedOn":"2025-11-18 15:57:32","publishedOnDateReadable":"November 18th, 2025"},"versionCreatedAt":"2025-08-13 05:34:59","video":"","vorDoi":"10.1007/s00404-025-08209-x","vorDoiUrl":"https://doi.org/10.1007/s00404-025-08209-x","workflowStages":[]},"version":"v1","identity":"rs-7119537","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7119537","identity":"rs-7119537","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}