SeqOIA platform, an integrative and interactive approach to optimize personalized cancer treatment

SeqOIA platform, an integrative and interactive approach to optimize personalized cancer treatment | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Short Report SeqOIA platform, an integrative and interactive approach to optimize personalized cancer treatment Jelena Filipovic, Emma Anjorand, Laetitia Marisa, Eurydice Angeli, and 15 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6991185/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Here, we report the importance of integrative genomic analysis and combined therapies in precision medicine to achieve durable responses in patients with limited treatment options. We report here data from 27 patients with cancers in a situation of treatment failure. For each patient, Sequencing Omics Information Analysis (SeqOIA) platform performed integrative genomic analysis. SeqOIA-tailored treatment outperformed previous lines. Combined treatments showed greater clinical benefit ( P <0.01) and longer survival than monotherapies ( P =0.07). Biological sciences/Cancer Biological sciences/Computational biology and bioinformatics Health sciences/Oncology Figures Figure 1 Figure 2 Figure 3 Full Text Precision medicine is becoming increasingly accessible due to widespread adoption of high-speed molecular analyses 1 . However, the first trials of guided treatment-choice were disappointing 2 due to limited availability of therapeutic regimen and the restriction of profiling to mutational analyses. Since then, the number of available targeted therapies has increased considerably. Moreover, molecular analyses are becoming more integrative, taking into account epigenetic, transcriptomic and proteomic signatures of tumors. In France, the national program of “France-Medecine-Génomique-2025” (PFMG25) uses innovative integrative molecular analyses to offer personalized treatments to patients with rare cancers or with cancers in a treatment-failure situation 3 . From October 2020 to May 2024, a total of 1,049 patients were included in the PFMG25 program, including 73 patients from Avicenne Hospital. Data from 20 patients with hepatocellular carcinomas have been previously reported 4 . Among the remaining 53 patients, 27 received a Sequencing Omics Information Analysis (SeqOIA)-tailored treatments (P1‒P27, Supp.Fig.S1). The SeqOIA platform performed tumor and germline whole-genome sequencing, tumor whole-exome sequencing, and RNAseq on frozen samples from recent tumor biopsies (Supp.Methods). Radiological assessment of treatment response were done by 18Flurorodeoxyglucose-Positron Emission Tomography-Computed Tomography (18FDG-PET-CT) when feasible or computed tomography before treatment initiation, and after 3 and 6 months of treatment. PET-CT-specific parameters, including ∆SUVpeak, ∆MTV and ∆TLG were used to evaluate clinical benefit according to PERCIST criteria. For each patient, growth modulation index (GMI) was calculated (Supp.Methods). To confirm the presence of specific gene alterations at protein level, we performed complementary immunostainings using the same samples previously used for genomic analyses (Supp.Methods). The characteristics of the 27 patients and exclusion reasons are detailed in Supp.Table.S1. Twenty histological cancer types were represented (Supp.Table.S2). The mean tumor cellularity was 56.4%, and 48% of tumors exhibited normal ploidy. All tumors had a low tumor mutational burden and were stable for microsatellite instability. A total of 114 variants were identified, 53.5% were pathogenic, while 46.5% were of uncertain significance but potentially driver (Fig.1). These variants were clonal in 61% of cases, frequently involving TP53, PTEN, AKT1, KMT2D, KRAS, and PI3KCA genes. For PI3KCA mutations, 4 out of 5 corresponding tumors showed strong PI3KCA protein expression, in favor of activating variants (Supp.Fig.S2). Overall, 41% of tumors harbored at least one pathogenic alteration in the PI3KCA-AKT-mTOR pathway. Furthermore, mutations in DNA-repair genes and chromatin modulation genes were found in 29% and 55% of patients, respectively. A germ-line pathogenic mutation was identified in 4 patients (15%), in NF1 , FANCM , RAD51C , and MUTYH genes. Molecular signatures were determined based on mutations in coding and non-coding regions 5 . In particular, the SBS3 signature, indicative of defective homologous recombination DNA damage repair, was observed in only two tumors (Supp.Fig.S3). In contrast, 11 patients (40%) had an HRD score >42 (Fig.1), a classical “positivity” threshold 6,7 . For copy number variations, there were 160 copy gains, recurrent for MYC, NCOA2 , or PREX2 .Additionally, 131 homozygous deletions were found, frequently identified in tumor suppressor genes such as CDKN2A, CDKN2B or MTAP (Supplementary Fig.S4). At transcriptomic level, data was obtained for 18 patients (66%) (Supp.Table.S1). We specifically focused on immune and repair deficit signatures (Supp.Fig.S5). Nine patients had an overall overexpression of immune markers, including one patient (P12) with a hemangioendothelioma and a class E immune-high signature 8 . Ten patients had low expression of multiple repair deficit markers, with HRD positivity in five patients. PI3K-AKT-mTOR pathway activation was also observed in eight patients. Treatment decisions, frequently off-label (62.5%), were discussed in a dedicated multidisciplinary meeting. A total of thirty-two lines of treatment have been delivered, with 37.5% classified as ESCAT-I or II (standard-of-care or high proof level of efficacy) according to ESMO guidelines 9 (Table 1). The median treatment duration was 6 months (ranging from 3 to 24 months). For the 17 lines of treatment assessed using PET-CT, 68% of patients had a controlled disease, as evidenced by the ∆TLG composite marker (Supp.Fig.S6). In addition, the SeqOIA-tailored treatment was often superior to the previous line, with a GMI ³ 1.33 observed in 70% of patients (Fig.2A). Interestingly, median survival was not linked to ESCAT category of treatment (Fig.2B). Among the 11 patients with HRD positivity, two had a metabolic complete response using a PARP inhibitor-containing regimen; one was previously reported 10 . The other patient, P24, had lung metastases from uterine leiomyosarcoma with a homozygous deletion of BRCA2 . As a second line therapy, she received a combination of cisplatin and olaparib, resulting in a complete metabolic response after 6 months of treatment (Fig.3A). Due to the frequent alterations of the PI3K-AKT-mTOR pathway, 10 patients received an mTOR inhibitor-based therapy. For example, P16 had a metastatic low-grade neuroendocrine tumor with an ELK1::TFE3 fusion with a resulting TFE3 nuclear accumulation, leading to PI3K/AKT/mTOR pathway overexpression (Fig.3B). Considering the available data, P16 received a combined treatment of somatostatin analogs and everolimus with 13 month disease stabilization 11 . Considering all 32 lines of treatment, 69% were combined therapies, resulting in a significant increased clinical benefit (86% vs. 54%, P <0.01) and a trend toward increased survival compared to monotherapies (14.3 vs. 11.1 months, HR=0.77, P =0.07). For example, P13 had a lung metastatic cholangiocarcinoma with seven previous lines of treatment. We identified a c.35G>A p.(Gly12Asp) KRAS hotspot variant and a c.2519_2520delCCinsAA p.(Ala840Glu) JAK1 variant of unknown significance. This alteration corresponded to the substitution of a highly conserved alanine with a glutamate in the functional Protein Kinase I domain. Alanine being a small, non-polar and hydrophobic amino acid, while glutamate has a larger, rigid, negatively charged side chain, we hypothesized that this substitution would rigidify JAK1 protein in an open and active state 12 . Indeed, using AlphaMissense Pathogenicity Heatmap 13 , this substitution was associated with a high pathogenic score. Considering the cross-talk between the JAK/STAT and RAS/MEK pathways, P13 received a combined treatment of MEK and JAK1 inhibitors with an excellent partial (Fig.2C). Interestingly, five patients benefited from two SeqOIA-tailored treatment lines. P18 received a first-line androgen-receptor-targeting therapy and a second-line targeting the PI3KCA/AKT/mTOR and MEK pathways due to the presence of a pathogenic variant of AKT1 c.49G>A p.(Glu17Lys), with AKT1 amplification (9 copies), theoretically associated with PI3KCA/mTOR pathway activation, and a bi-allelic deletion of MAP2K4 , suggesting sensitivity to MEK inhibitors 14 . P18 achieved a cumulative 15.5-month of additional disease control (Supp. Fig.S7). Finally, of the 32 treatment lines, 40% were guided by transcriptomic analyses, including a MET inhibitor for two patients. P27 had a progressive metastatic head and neck cancer and a MET gene amplification (9 copies) with MET mRNA overexpression (98 th percentile). The patient achieved a durable partial response with cabozantinib monotherapy. In this real-life case series, 50% of patients received a tailored treatment based on genomic analyses, as reported in similar pan-cancer real-life practices 15,16 . The integrative approach, not limited to mutational studies, combined with interpretive data analysis, and enabling a higher identification rate of actionable targets, is the originality of our series. In contrast, therapies supported by multiple data sources, including transcriptomics, are more likely to result in successful treatments 16 . Furthermore, we extended mutational analysis to variants of unknown significance whose imputability in carcinogenesis was strongly suspected. For at least two of these variants, on FANCM and on JAK1 , our interactive multidisciplinary approach substantiated their pathogenicity, enabling the administration of effective therapeutics that the patients would not have otherwise received. The functional value of most variants identified in whole-genome analyses will undoubtedly represent a considerable challenge in the coming decades. Overall, the clinical benefit observed in our series is significant; with a median progression-free survival being six months longer than that previously reported 16 . This can be explained by the integrative data analysis, and the use of combined treatments that fully consider molecular heterogeneity. Combined therapies represented 69% of treatment lines in our study, compared to less than 20% in other studies 16 . There are still some concerns: i) the significant financial burden of this approach, as personalized strategies often involve the use of novel therapies outside official authorization, which is considered an obstacle for many physicians 17 . A medico-economic evaluation is currently underway for the PFMG2025 program; ii) the biological heterogeneity of metastatic disease is usually assessed using a single metastatic sample. Analyzing several metastases by pooling samples in a single analysis could help limit the costs 18 . However, ethical and technological issues remain to perform multiple sampling, particularly when it has to be repeated overtime; iii) for toxicity management, particularly when using combination therapies, interactive multidisciplinary care with pharmacists is essential to identify potential drug interactions; iv) finally, it can be noted that imaging evaluation criteria are equivocal for this type of advanced pathology, with a significant metastatic tumor burden and often long evolution favoring molecular heterogeneity. Metastatic disease should no longer be considered as a single biological entity, but rather as a combination of several biological diseases. "Dissociated" responses, which often lead to treatment modification based on classic progression criteria, warrant a reevaluation using radiological and clinical composite criteria, including quality of life. In conclusion, our real-life, monocentric experience of interactive multidisciplinary care based on integrative genomic analyses in metastatic pan-cancer patients highlights the clinical benefit of using combined personalized therapies. Declarations The authors declare no potential conflicts of interest. This study was approved by the local ethical committee. Data availability statement All data generated or analysed during this study are included in this published article and its supplementary information files. Authors’ contributions Conception and design: JF, GB, DH Development of methodology: GB, DH Acquisition of data: All authors Analyses and interpretation of data: JF, EA, LM, MS, HB, KL, GF, JLC, PLP, GB, DH Drafting, review: JF, JC, PLP, GB, DH Revision of the manuscript: All authors Material support: PLP, GB Administrative and technical: PLP, GB Study supervision: GB, DH Acknowledgments This research received no external funding but was fully supported by the PFMG2025. 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Table Table 1: Molecular alterations and genomics-guided treatment PatientID N° of lines before genomics-guided treatment Molecular alteration Genomics-guided treatment ESCAT class Drug schedule Best response Response duration (months) P1 6 NF1 biallelic loss (mutation + LOH) MEK inhibitor IA (low-grade serous ovarian carcinoma with MAPK pathway activation) trametinib (2 mg/g then following drug monitoring 3 mg/d) SD 15 P1 7 NF1 biallelic loss (mutation + LOH) + immune transcriptomic signature MEK inhibitor + anti-PD1 antibody IA, IIIA trametinib (3 mg/d) + pembrolizumab (200 mg/3w) PD <3 P2 2 biallelic NF1 inactivation (germ-line mutation +LOH) + High HRD score MEK inhibitor + CDDP IV (MEKi) IIIA (PARPi) trametinib (2 mg/d) + CDDP (40 mg/m 2 /w) SD 4 P3 4 SF3B1 mutation + homozygous deletion of CHEK2 + high HRD score PARPi IV (SF3B1) IC (HRD score) olaparib (300 mg bid) PD <3 P4 6 ERBB2 amplification (7 copies) + ERBB3 amplification (7 copies) + ERBB2/ERBB3 mRNA overexpression + High HRD score (mutation XRCC1 , biallelic inactivation) Anti-HER2 antibody + CCDP IB-III (anti-HER2) IA (CDDP) Trastuzumab (6 mg/kg/3w) + CDDP (30 mg/m 2 /w) + afatinib (20 mg/d) PR 10 P4 7 ERBB2/ERBB3 mRNA overexpression Anti-ER2/HER3 TKI + docetaxel IV (afatinib) afatinib (40 mg/d) + docetaxel (75 mg/m 2 /3w) PR 6 P5 1 FANCM biallelic loss + high HRD score PARPi maintenance IIIA olaparib (300 mg bid) CR 14 P5 2 FANCM biallelic loss + high HRD score PARPi + CDDP + RT followed with PAPRi maintenance IIIA olaparib (100 mg bid then 300 mg bid) + CDDP (40 mg/m 2 /w) CR 31 P6 2 CTNNB mutation and PI3KCA mutation + transcriptomic activation of PI3KCA/AKT/mTOR pathway mTOR inhibitor + anti-aromatase III everolimus (10 mg/d then 12,5 mg/d) + letrozole 2.5 mg/d SD 8 P7 2 FGFR3-TACC3 fusion FGFR3 inhibitor + RT on residual localizations IA erdafitinib (8 mg/d decreased to 6 mg/d for severe toxicities) PR Not reached (>23) P8 6 Cyclin D1 amplification (15 copies) CDK4 inhibitor III palbociclib (125 mg/d continuously) PD <3 P8 7 RAD50 mutation, biallelic inactivation, high HRD score + immune transcriptomic signature PARPi + CDDP + anti-PD1 antibody IIIA (PARPi) olaparib (100 mg bid) + CDDP (40 mg/m 2 /w) + pembrolizumab (200 mg/3w) PR 6 P9 3 PTEN mutation + PI3KCA mutation mTOR inhibitor + CDDP + anti-PD1 antibody II everolimus (10 mg/d) + CDDP (30mg/m 2 /w) + pembrolizumab (200 mg/3w) PD <3 P10 4 MET mRNA overexpression + high HRD score (low RAD51C expression) MET inhibitor + PARPi + stereotactic RT IIIA (PARPi) IIIA (MET inhibitor) cabozantinib (60 mg/d) + olaparib (200 mg bid) SD 12 P11 2 SFPQ::TFE3 fusion mTOR inhibitor IIIA everolimus (10 mg/d) PD <3 P12 2 High-immune E transcriptomic signature Anti-PD1 IIB pembrolizumab (200 mg/3w) PD <3 P13 7 KRAS mutation + JAK1 mutation (with LOH) MEK inhibitor + JAK1 inhibitor IV (MEKi) IV (JAKi) trametinib (2 mg/d) + filgetinib (200 mg/d) PR 9 P14 2 High HRD score (genomic and transcriptional + low ATM/BAP1/RAD51 mRNA expression) PARPi + CDDP IIIA niraparib (300 mg/d) + CDDP (40 mg/m 2 /w) PR 5 (then loss of follow-up) P15 3 High HRD score (genomic and transcriptional + low ATR/ATRX mRNA expression) PARPi + CDDP IIIA olaparib (100 mg/d then 200mg/d because of under exposure) + CDDP (30 mg/m 2 /w) PR 4.5 (brain progression) P16 2 ELK1::TFE3 fusion + PI3K/AKT/mTOR pathway activation (mRNA overexpression) mTOR inhibitor + somatostatin analogous IIIB everolimus (10 mg/d) + octreotide (100 ug/4w) SD 13 P17 2 PI3KCA mutation p.(H1047R) + transcriptomic PI3KCA/AKT/mTOR pathway activation mTOR inhibitor IIA everolimus (10 mg/d) CR Not reached (>14) P18 3 AR amplification (10 copies) + AR protein overexpression + SPOP mutation with LOH AR antagonist + paclitaxel + bevacizumab IIB abiraterone acetate (500 mg bid) + paclitaxel + bevacizumab PR 9 P18 4 AKT1 mutation + AKT1 amplification (9 copies) + biallelic loss of MAP2K4 MEK inhibitor + mTOR inhibitor IV (MEKi) trametinib (2 mg/d) + everolimus (10 mg/d) PR 6,5 (interruption for severe toxicity) P19 2 PTEN biallelic loss (mutation + LOH) + PI3KCA mutation mTOR inhibitor + capecitabin IIA everolimus (10 mg/d) + capecitabin (1000 mg/m2 bid 14d/3w) PR <3 (early interruption for severe toxicity) P20 2 ARID1A biallelic inactivation (two mutations) + PI3KCA mutation EZH2 inhibitor + mTOR inhibitor + carboplatin IV (EZH2i) III (mTORi) Tazemetostat (800 mg bid) + everolimus (10 mg/d) SD 5 P21 4 High HRD score PARPi IIIA olaparib (300 mg bid) PR 5 P22 2 FGFR2 mutation pan-FGFR inhibitor IC pemigatinib (13.5mg/d 2w on and 1w off) SD 10 P23 4 KRAS mutation p.(G12D) + AKT1 mutation MEK inhibitor + mTOR inhibitor IV (MEKi) IV (mTOR inhibitor) trametinib (2mg/d then 1mg/d) + everolimus (10mg/d then 5mg/d for toxicities and over-exposure) PR 7.5 (interruption for toxicity) P24 1 High HRD score + BRCA2 biallelic deletion PARPi + CDDP IIA olaparib (100 then 200 mg bid for under exposure) + CDDP (30 mg/m 2 /w) PR Not reached (>10) P25 4 PTEN biallelic inactivation mTOR inhibitor IIA everolimus (10 mg/d then 5 mg/d for toxicity and over-exposure) PD <3 P26 3 High HRD score, SBS3 signature, methylation BRCA1 promotor and low mRNA BRCA1 expression + immune signature PARPi + dose-dense EC regimen IC/IIA olaparib (100 mg bid) + epirubicine (75 mg/m 2 /2w) + cyclophosphamide (1200 mg/m 2 /2w) PD 8) ID: identity; ESCAT: ESMO Scale for Clinical Actionability of molecular Targets; P: Patient; LOH: Loss Of Heterozygosity; SD: Stable Disease; d: day; PD: Progressive Disease; HRD: Homologous Recombination Deficiency; CDDP: cisplatin; PARPi: Poly (ADP-Ribose) Polymérase inhibitors; w: weekly; bid: bi-daily; PR: Partial Response; TKI: Tyrosine Kinase Inhibitors; CR: Complete Response; RT: Radiotherapy; AR: Androgen Receptor; EC: Epirubicin-Cyclophosphamide. Additional Declarations No competing interests reported. Supplementary Files suppmaterialandmethods.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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Hamdan","email":"data:image/png;base64,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","orcid":"","institution":"Hôpital La Porte Verte","correspondingAuthor":true,"prefix":"","firstName":"Diaddin","middleName":"","lastName":"Hamdan","suffix":""}],"badges":[],"createdAt":"2025-06-27 11:28:19","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6991185/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6991185/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":87700450,"identity":"1515c226-b1bb-4d88-971c-39983f4d90d2","added_by":"auto","created_at":"2025-07-28 07:17:49","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":114478,"visible":true,"origin":"","legend":"\u003cp\u003eTumor cell fraction, ploidy, tumor mutational burden (TMB), microsatellite stability status (MSI), and homologous recombination deficiency (HRD) for the 27 patients with the gene variants detected by SeqOIA gene analysis. The variants illustrated are the pathologic variants and the predicted driver. They are classified according to their clonal or subclonal status and the loss of heterozygosity (LOH) or amplification.\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6991185/v1/2dbbf3ab1d765be623eadc79.jpg"},{"id":87702380,"identity":"8841a2d7-ec92-44be-a56f-48a4d143b12d","added_by":"auto","created_at":"2025-07-28 07:33:49","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":149725,"visible":true,"origin":"","legend":"\u003cp\u003ePanel A illustrates the total duration of response for each of the 27 patients and the calculated Growth Modulation Index with a cutoff of 1.33 for treatment efficacy. The SeqOIA-tailored treatment is often superior to the previous therapeutic line, with a Growth Modulation Index ³ 1.33 for 70% of the patients.\u003c/p\u003e\n\u003cp\u003ePanel B shows the survival curves according to ESCAT categories of treatment (I/II \u003cem\u003evs.\u003c/em\u003eIII/IV), and to the type of treatment (combined \u003cem\u003evs\u003c/em\u003e. monotherapies).\u003c/p\u003e\n\u003cp\u003ePanel C illustrates the treatment history and genomic analysis of P13: he has a\u003cem\u003e KRAS\u003c/em\u003e hotspot mutation \u003cem\u003ec.35G\u0026gt;A p.(Gly12Asp)\u003c/em\u003e, and one variant of unknown significance, predicted driver in \u003cem\u003eJAK1\u003c/em\u003e gene \u003cem\u003ec.2519_2520delCCinsAA p.(Ala840Glu)\u003c/em\u003e. The \u003cem\u003eJAK1\u003c/em\u003e gene \u003cem\u003ec.2519_2520delCCinsAA p.(Ala840Glu)\u003c/em\u003ecorresponding to an alanine to glutamine substitution in the functional domain protein kinase I. This alanine at the position 840 is highly conserved among species. The alanine has a smaller non-polar side chain while the glutamate side chain is longer, negatively-charged and more rigid. This blocks JAK1 and keeps it in an open active position. The AlphaMissense Pathogenicity heatmap analysis of the AlphaFold Protein Structure Database attributes to this amino-acid substitution a high pathogenicity score of 0.765. There is a cross-talk between \u003cem\u003eJAK/STAT\u003c/em\u003e and \u003cem\u003eKRAS/MEK\u003c/em\u003e pathways that can lead to the overall activation of the MEK pathway. This might explain the benefit of the combination of MEK inhibitor and JAK1 inhibitor in P16 with an excellent partial response after 6 months of treatment.\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6991185/v1/a07d8012dcb762db959f26f7.jpg"},{"id":87700455,"identity":"a27646a4-bf6c-4390-a815-76b1302de988","added_by":"auto","created_at":"2025-07-28 07:17:49","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":133619,"visible":true,"origin":"","legend":"\u003cp\u003ePanel A: The history of P24 treated for a uterine leiomyosarcoma with lung metastasis with high score of 74 (upper panel). Genomic analysis revealed a typical HRD chromosomal profile characterized by various gains and deletions including a bi-allelic homozygous deletion of BRCA2 (middle panel). Based on recommendations from the SeqOIA gene analysis, she was treated with cisplatin and olaparib resulting in a complete metabolic response after 6 months of treatment (lower panel).\u003c/p\u003e\n\u003cp\u003ePanel B illustrates the history of P16 treated for a low-grade neuroendocrine tumor of the gut with lung metastases (upper panel), and a characteristic Xp11.2 translocation with an ELK1::TFE3 fusion leading to TFE3 nucleus accumulation. The middle panel illustrates a strong TFE3 nuclear staining of cancer cells. Transcriptomic analysis revealed an overexpression of the PIK3/AKT/mTOR pathway (lower panel) that justified the use of a treatment combing somatostatin analogous and everolimus. PET: Positron Emission Tomography; PD: Progressive Disease; SD: Stable Disease.\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6991185/v1/c82a0edeb86ca99af6b77080.jpg"},{"id":91903506,"identity":"0eec46fb-7cd0-414f-975d-c8ba984bc09d","added_by":"auto","created_at":"2025-09-22 22:54:14","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1104782,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6991185/v1/25df348c-e2c3-40f7-8547-89f2a17175a7.pdf"},{"id":87702381,"identity":"2e507e8f-2d1a-47cb-8cfd-faf2066e3591","added_by":"auto","created_at":"2025-07-28 07:33:50","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":2010385,"visible":true,"origin":"","legend":"","description":"","filename":"suppmaterialandmethods.docx","url":"https://assets-eu.researchsquare.com/files/rs-6991185/v1/f9856bee601cdc7f2810f685.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"SeqOIA platform, an integrative and interactive approach to optimize personalized cancer treatment","fulltext":[{"header":"Full Text","content":"\u003cp\u003ePrecision medicine is becoming increasingly accessible due to widespread adoption of high-speed molecular analyses\u003csup\u003e1\u003c/sup\u003e. However, the first trials of guided treatment-choice were disappointing\u003csup\u003e2\u003c/sup\u003e due to limited availability of therapeutic regimen and the restriction of profiling to mutational analyses. Since then, the number of available targeted therapies has increased considerably. Moreover, molecular analyses are becoming more integrative, taking into account epigenetic, transcriptomic and proteomic signatures of tumors. In France, the national program of “France-Medecine-Génomique-2025” (PFMG25) uses innovative integrative molecular analyses to offer personalized treatments to patients with rare cancers or with cancers in a treatment-failure situation \u003csup\u003e3\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eFrom October 2020 to May 2024, a total of 1,049 patients were included in the PFMG25 program, including 73 patients from Avicenne Hospital. Data from 20 patients with hepatocellular carcinomas have been previously reported\u003csup\u003e4\u003c/sup\u003e. Among the remaining 53 patients, 27 received a Sequencing Omics Information Analysis (SeqOIA)-tailored treatments (P1‒P27, Supp.Fig.S1). The SeqOIA platform performed tumor and germline whole-genome sequencing, tumor whole-exome sequencing, and RNAseq on frozen samples from recent tumor biopsies (Supp.Methods).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eRadiological assessment of treatment response were done by 18Flurorodeoxyglucose-Positron Emission Tomography-Computed Tomography (18FDG-PET-CT) when feasible or computed tomography before treatment initiation, and after 3 and 6 months of treatment. PET-CT-specific parameters, including ∆SUVpeak, ∆MTV and ∆TLG were used to evaluate clinical benefit according to PERCIST criteria. For each patient, growth modulation index (GMI) was calculated (Supp.Methods).\u003c/p\u003e\n\u003cp\u003eTo confirm the presence of specific gene alterations at protein level, we performed complementary immunostainings using the same samples previously used for genomic analyses (Supp.Methods).\u003c/p\u003e\n\u003cp\u003eThe characteristics of the 27 patients and exclusion reasons are detailed in Supp.Table.S1. Twenty histological cancer types were represented (Supp.Table.S2).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe mean tumor cellularity was 56.4%, and 48% of tumors exhibited normal ploidy. All tumors had a low tumor mutational burden and were stable for microsatellite instability.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eA total of 114 variants were identified, 53.5% were pathogenic, while 46.5% were of uncertain significance but potentially driver (Fig.1). \u0026nbsp;These variants were clonal in 61% of cases,\u0026nbsp;frequently involving \u003cem\u003eTP53, PTEN, AKT1, KMT2D, KRAS,\u0026nbsp;\u003c/em\u003eand\u003cem\u003e\u0026nbsp;PI3KCA\u003c/em\u003e genes. For \u003cem\u003ePI3KCA\u003c/em\u003e mutations, 4 out of 5 corresponding tumors showed strong PI3KCA protein expression, in favor of activating variants (Supp.Fig.S2). Overall, 41% of tumors harbored at least one pathogenic alteration in the \u003cem\u003ePI3KCA-AKT-mTOR\u003c/em\u003e pathway. Furthermore, mutations in DNA-repair genes and chromatin modulation genes were found in 29% and 55% of patients, respectively.\u003c/p\u003e\n\u003cp\u003eA germ-line pathogenic mutation was identified in 4 patients (15%), in \u003cem\u003eNF1\u003c/em\u003e, \u003cem\u003eFANCM\u003c/em\u003e, \u003cem\u003eRAD51C\u003c/em\u003e, and \u003cem\u003eMUTYH\u003c/em\u003e genes.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMolecular signatures were determined based on mutations in coding and non-coding regions\u003csup\u003e5\u003c/sup\u003e. In particular, the SBS3 signature, indicative of defective homologous recombination DNA damage repair, was observed in only two tumors (Supp.Fig.S3). In contrast, 11 patients (40%) had an HRD score \u0026gt;42 (Fig.1), a classical “positivity” threshold \u003csup\u003e6,7\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eFor copy number variations, there were 160 copy gains, recurrent for \u003cem\u003eMYC, NCOA2\u003c/em\u003e, or \u003cem\u003ePREX2\u003c/em\u003e.Additionally, 131 homozygous deletions were found, frequently identified in tumor suppressor genes such as \u003cem\u003eCDKN2A, CDKN2B\u003c/em\u003e or \u003cem\u003eMTAP\u003c/em\u003e (Supplementary Fig.S4).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAt transcriptomic level, data was obtained for 18 patients (66%) (Supp.Table.S1). We specifically focused on immune and repair deficit signatures (Supp.Fig.S5). Nine patients had an overall overexpression of immune markers, including one patient (P12) with a hemangioendothelioma and a class E immune-high signature\u003csup\u003e8\u003c/sup\u003e. Ten patients had low expression of multiple repair deficit markers, with HRD positivity in five patients. \u003cem\u003ePI3K-AKT-mTOR\u003c/em\u003e pathway activation was also observed in eight patients.\u003c/p\u003e\n\u003cp\u003eTreatment decisions, frequently off-label (62.5%), were discussed in a dedicated multidisciplinary meeting. A total of thirty-two lines of treatment have been delivered, with 37.5% classified as ESCAT-I or II (standard-of-care or high proof level of efficacy) according to ESMO guidelines\u003csup\u003e9\u003c/sup\u003e (Table 1). The median treatment duration was 6 months (ranging from 3 to 24 months). For the 17 lines of treatment assessed using PET-CT, 68% of patients had a controlled disease, as evidenced by the ∆TLG composite marker (Supp.Fig.S6). In addition, the SeqOIA-tailored treatment was often superior to the previous line, with a GMI\u0026nbsp;³\u0026nbsp;1.33 observed in 70% of patients (Fig.2A). Interestingly, median survival was not linked to ESCAT category of treatment (Fig.2B).\u003c/p\u003e\n\u003cp\u003eAmong the 11 patients with HRD positivity, two had a metabolic complete response using a PARP inhibitor-containing regimen; one was previously reported \u003csup\u003e10\u003c/sup\u003e. The other patient, P24, had lung metastases from uterine leiomyosarcoma with a homozygous deletion of \u003cem\u003eBRCA2\u003c/em\u003e. As a second line therapy, she received a combination of cisplatin and olaparib, resulting in a complete metabolic response after 6 months of treatment (Fig.3A).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDue to the frequent alterations of the PI3K-AKT-mTOR pathway, 10 patients received an mTOR inhibitor-based therapy. For example, P16 had a metastatic low-grade neuroendocrine tumor with an \u003cem\u003eELK1::TFE3\u003c/em\u003e fusion with a resulting TFE3 nuclear accumulation, leading to \u003cem\u003ePI3K/AKT/mTOR\u003c/em\u003e pathway overexpression (Fig.3B). Considering the available data, P16 received a combined treatment of somatostatin analogs and everolimus with 13 month disease stabilization\u003csup\u003e11\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eConsidering all 32 lines of treatment, 69% were combined therapies, resulting in a significant increased clinical benefit (86% \u003cem\u003evs.\u003c/em\u003e 54%, \u003cem\u003eP\u003c/em\u003e\u0026lt;0.01) and a trend toward increased survival compared to monotherapies (14.3 \u003cem\u003evs.\u003c/em\u003e 11.1 months, HR=0.77, \u003cem\u003eP\u003c/em\u003e=0.07). For example, P13 had a lung metastatic cholangiocarcinoma with seven previous lines of treatment. We identified a \u003cem\u003ec.35G\u0026gt;A p.(Gly12Asp)\u003c/em\u003e \u003cem\u003eKRAS\u003c/em\u003e hotspot variant and a \u003cem\u003ec.2519_2520delCCinsAA p.(Ala840Glu)\u003c/em\u003e \u003cem\u003eJAK1\u003c/em\u003e variant of unknown significance. This alteration corresponded to the substitution of a highly conserved alanine with a glutamate in the functional Protein Kinase I domain. Alanine being a small, non-polar and hydrophobic amino acid, while glutamate has a larger, rigid, negatively charged side chain, we hypothesized that this substitution would rigidify JAK1 protein in an open and active state\u003csup\u003e12\u003c/sup\u003e. Indeed, using AlphaMissense Pathogenicity Heatmap\u003csup\u003e13\u003c/sup\u003e, this substitution was associated with a high pathogenic score. Considering the cross-talk between the JAK/STAT and RAS/MEK pathways, P13 received a combined treatment of MEK and JAK1 inhibitors with an excellent partial (Fig.2C).\u003c/p\u003e\n\u003cp\u003eInterestingly, five patients benefited from two SeqOIA-tailored treatment lines. P18 received a first-line androgen-receptor-targeting therapy and a second-line targeting the PI3KCA/AKT/mTOR and MEK pathways due to the presence of a pathogenic variant of \u003cem\u003eAKT1\u003c/em\u003e c.49G\u0026gt;A p.(Glu17Lys), with \u003cem\u003eAKT1\u003c/em\u003e amplification (9 copies), theoretically associated with PI3KCA/mTOR pathway activation, and a bi-allelic deletion of \u003cem\u003eMAP2K4\u003c/em\u003e, suggesting sensitivity to MEK inhibitors\u003csup\u003e14\u003c/sup\u003e. P18 achieved a cumulative 15.5-month of additional disease control (Supp. Fig.S7).\u003c/p\u003e\n\u003cp\u003eFinally, of the 32 treatment lines, 40% were guided by transcriptomic analyses, including a MET inhibitor for two patients. P27 had a progressive metastatic head and neck cancer and a \u003cem\u003eMET\u003c/em\u003e gene amplification (9 copies) with \u003cem\u003eMET\u0026nbsp;\u003c/em\u003emRNA overexpression (98\u003csup\u003eth\u003c/sup\u003e percentile). The patient achieved a durable partial response with cabozantinib monotherapy.\u003c/p\u003e\n\u003cp\u003eIn this real-life case series, 50% of patients received a tailored treatment based on genomic analyses, as reported in similar pan-cancer real-life practices\u003csup\u003e15,16\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe integrative approach, not limited to mutational studies, combined with interpretive data analysis, and enabling a higher identification rate of actionable targets, is the originality of our series.\u003c/p\u003e\n\u003cp\u003eIn contrast, therapies supported by multiple data sources, including transcriptomics, are more likely to result in successful treatments\u003csup\u003e16\u003c/sup\u003e. \u0026nbsp;Furthermore, we extended mutational analysis to variants of unknown significance whose imputability in carcinogenesis was strongly suspected. For at least two of these variants, on \u003cem\u003eFANCM\u003c/em\u003e and on \u003cem\u003eJAK1\u003c/em\u003e, our interactive multidisciplinary approach substantiated their pathogenicity, enabling the administration of effective therapeutics that the patients would not have otherwise received. The functional value of most variants identified in whole-genome analyses will undoubtedly represent a considerable challenge in the coming decades.\u003c/p\u003e\n\u003cp\u003eOverall, the clinical benefit observed in our series is significant; with a median progression-free survival being six months longer than that previously reported\u003csup\u003e16\u003c/sup\u003e. This can be explained by the integrative data analysis, and the use of combined treatments that fully consider molecular heterogeneity. Combined therapies represented 69% of treatment lines in our study, compared to less than 20% in other studies\u003csup\u003e16\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eThere are still some concerns: i) the significant financial burden of this approach, as personalized strategies often involve the use of novel therapies outside official authorization, which is considered an obstacle for many physicians\u003csup\u003e17\u003c/sup\u003e. A medico-economic evaluation is currently underway for the PFMG2025 program; ii) the biological heterogeneity of metastatic disease is usually assessed using a single metastatic sample. Analyzing several metastases by pooling samples in a single analysis could help limit the costs\u003csup\u003e18\u003c/sup\u003e. However, ethical and technological issues remain to perform multiple sampling, particularly when it has to be repeated overtime; iii) for toxicity management, particularly when using combination therapies, interactive multidisciplinary care with pharmacists is essential to identify potential drug interactions; iv) finally, it can be noted that imaging evaluation criteria are equivocal for this type of advanced pathology, with a significant metastatic tumor burden and often long evolution favoring molecular heterogeneity. Metastatic disease should no longer be considered as a single biological entity, but rather as a combination of several biological diseases. \"Dissociated\" responses, which often lead to treatment modification based on classic progression criteria, warrant a reevaluation using radiological and clinical composite criteria, including quality of life.\u003c/p\u003e\n\u003cp\u003eIn conclusion, our real-life, monocentric experience of interactive multidisciplinary care based on integrative genomic analyses in metastatic pan-cancer patients highlights the clinical benefit of using combined personalized therapies.\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eThe authors declare no potential conflicts of interest.\u003c/p\u003e\n\u003cp\u003eThis study was approved by the local ethical committee.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data generated or analysed during this study are included in this published article and its supplementary information files.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors’ contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConception and design: JF, GB, DH\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDevelopment of methodology: GB, DH\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAcquisition of data: All authors\u003c/p\u003e\n\u003cp\u003eAnalyses and interpretation of data: JF, EA, LM, MS, HB, KL, GF, JLC, PLP, GB, DH\u003c/p\u003e\n\u003cp\u003eDrafting, review: JF, JC, PLP, GB, DH\u003c/p\u003e\n\u003cp\u003eRevision of the manuscript: All authors\u003c/p\u003e\n\u003cp\u003eMaterial support: PLP, GB\u003c/p\u003e\n\u003cp\u003eAdministrative and technical: PLP, GB\u003c/p\u003e\n\u003cp\u003eStudy supervision: GB, DH\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research received no external funding but was fully supported by the PFMG2025.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eMateo J, Steuten L, Aftimos P, et al. Delivering precision oncology to patients with cancer. \u003cem\u003eNat Med. \u003c/em\u003e2022;28(4):658-665.\u003c/li\u003e\n\u003cli\u003eLe Tourneau C, Delord JP, Goncalves A, et al. Molecularly targeted therapy based on tumour molecular profiling versus conventional therapy for advanced cancer (SHIVA): a multicentre, open-label, proof-of-concept, randomised, controlled phase 2 trial. \u003cem\u003eLancet Oncol. \u003c/em\u003e2015;16(13):1324-1334.\u003c/li\u003e\n\u003cli\u003econtributors P. PFMG2025-integrating genomic medicine into the national healthcare system in France. \u003cem\u003eLancet Reg Health Eur. \u003c/em\u003e2025;50:101183.\u003c/li\u003e\n\u003cli\u003eLimousin W, Laurent-Puig P, Ziol M, et al. Molecular-based targeted therapies in patients with hepatocellular carcinoma and hepato-cholangiocarcinoma refractory to atezolizumab/bevacizumab. \u003cem\u003eJ Hepatol. \u003c/em\u003e2023;79(6):1450-1458.\u003c/li\u003e\n\u003cli\u003eAlexandrov LB, Kim J, Haradhvala NJ, et al. The repertoire of mutational signatures in human cancer. \u003cem\u003eNature. \u003c/em\u003e2020;578(7793):94-101.\u003c/li\u003e\n\u003cli\u003eRay-Coquard I, Pautier P, Pignata S, et al. Olaparib plus Bevacizumab as First-Line Maintenance in Ovarian Cancer. \u003cem\u003eN Engl J Med. \u003c/em\u003e2019;381(25):2416-2428.\u003c/li\u003e\n\u003cli\u003eVergote I, Gonzalez-Martin A, Ray-Coquard I, et al. European experts consensus: BRCA/homologous recombination deficiency testing in first-line ovarian cancer. \u003cem\u003eAnn Oncol. \u003c/em\u003e2022;33(3):276-287.\u003c/li\u003e\n\u003cli\u003ePetitprez F, de Reynies A, Keung EZ, et al. B cells are associated with survival and immunotherapy response in sarcoma. \u003cem\u003eNature. \u003c/em\u003e2020;577(7791):556-560.\u003c/li\u003e\n\u003cli\u003eMateo J, Chakravarty D, Dienstmann R, et al. A framework to rank genomic alterations as targets for cancer precision medicine: the ESMO Scale for Clinical Actionability of molecular Targets (ESCAT). \u003cem\u003eAnn Oncol. \u003c/em\u003e2018;29(9):1895-1902.\u003c/li\u003e\n\u003cli\u003eHamdan D, Marisa L, Tlemsani C, et al. Olaparib in the Setting of Radiotherapy-Associated Sarcoma: What Can Precision Medicine Offer For Rare Cancers? \u003cem\u003eJCO Precis Oncol. \u003c/em\u003e2023;7:e2200582.\u003c/li\u003e\n\u003cli\u003eDamayanti NP, Budka JA, Khella HWZ, et al. Therapeutic Targeting of TFE3/IRS-1/PI3K/mTOR Axis in Translocation Renal Cell Carcinoma. \u003cem\u003eClin Cancer Res. \u003c/em\u003e2018;24(23):5977-5989.\u003c/li\u003e\n\u003cli\u003eLupardus PJ, Skiniotis G, Rice AJ, et al. Structural snapshots of full-length Jak1, a transmembrane gp130/IL-6/IL-6Ralpha cytokine receptor complex, and the receptor-Jak1 holocomplex. \u003cem\u003eStructure. \u003c/em\u003e2011;19(1):45-55.\u003c/li\u003e\n\u003cli\u003eCheng J, Novati G, Pan J, et al. Accurate proteome-wide missense variant effect prediction with AlphaMissense. \u003cem\u003eScience. \u003c/em\u003e2023;381(6664):eadg7492.\u003c/li\u003e\n\u003cli\u003eXue Z, Vis DJ, Bruna A, et al. MAP3K1 and MAP2K4 mutations are associated with sensitivity to MEK inhibitors in multiple cancer models. \u003cem\u003eCell Res. \u003c/em\u003e2018;28(7):719-729.\u003c/li\u003e\n\u003cli\u003eKim R, Kim S, Oh BB, et al. Clinical application of whole-genome sequencing of solid tumors for precision oncology. \u003cem\u003eExp Mol Med. \u003c/em\u003e2024;56(8):1856-1868.\u003c/li\u003e\n\u003cli\u003ePleasance E, Bohm A, Williamson LM, et al. Whole-genome and transcriptome analysis enhances precision cancer treatment options. \u003cem\u003eAnn Oncol. \u003c/em\u003e2022;33(9):939-949.\u003c/li\u003e\n\u003cli\u003eHorgan D, Ciliberto G, Conte P, et al. Bringing Greater Accuracy to Europe\u0026apos;s Healthcare Systems: The Unexploited Potential of Biomarker Testing in Oncology. \u003cem\u003eBiomed Hub. \u003c/em\u003e2020;5(3):182-223.\u003c/li\u003e\n\u003cli\u003eLitchfield K, Reading JL, Puttick C, et al. Meta-analysis of tumor- and T cell-intrinsic mechanisms of sensitization to checkpoint inhibition. \u003cem\u003eCell. \u003c/em\u003e2021;184(3):596-614 e514.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Table","content":"\u003cp\u003eTable 1: Molecular alterations and genomics-guided treatment\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePatientID\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eN\u0026deg; of lines before genomics-guided treatment\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMolecular alteration\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGenomics-guided treatment\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eESCAT class\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDrug schedule\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBest response\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eResponse duration (months)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003eP1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cem\u003eNF1\u003c/em\u003e biallelic loss (mutation + LOH)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eMEK inhibitor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eIA (low-grade serous ovarian carcinoma with MAPK pathway activation)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003etrametinib (2 mg/g then following drug monitoring 3 mg/d)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003eSD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003eP1\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cem\u003eNF1\u0026nbsp;\u003c/em\u003ebiallelic loss (mutation + LOH) + immune transcriptomic signature\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eMEK inhibitor + anti-PD1 antibody\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eIA, IIIA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003etrametinib (3 mg/d) + pembrolizumab (200 mg/3w)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003ePD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026lt;3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003eP2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003ebiallelic\u003cem\u003e\u0026nbsp;NF1\u003c/em\u003e inactivation (germ-line mutation +LOH) + High HRD score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eMEK inhibitor + CDDP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eIV (MEKi)\u003c/p\u003e\n \u003cp\u003eIIIA (PARPi)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003etrametinib (2 mg/d) + CDDP (40 mg/m\u003csup\u003e2\u003c/sup\u003e/w)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003eSD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003eP3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cem\u003eSF3B1\u003c/em\u003e mutation + homozygous deletion of \u003cem\u003eCHEK2\u0026nbsp;\u003c/em\u003e+ high HRD score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003ePARPi\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eIV (SF3B1)\u003c/p\u003e\n \u003cp\u003eIC (HRD score)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003eolaparib (300 mg bid)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003ePD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026lt;3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003eP4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cem\u003eERBB2\u003c/em\u003e amplification (7 copies) + \u003cem\u003eERBB3\u003c/em\u003e amplification (7 copies) + \u003cem\u003eERBB2/ERBB3\u003c/em\u003e mRNA overexpression + High HRD score (mutation\u003cem\u003e\u0026nbsp;XRCC1\u003c/em\u003e, biallelic inactivation)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eAnti-HER2 antibody + CCDP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eIB-III (anti-HER2)\u003c/p\u003e\n \u003cp\u003eIA (CDDP)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003eTrastuzumab (6 mg/kg/3w) + CDDP (30 mg/m\u003csup\u003e2\u003c/sup\u003e/w) + afatinib (20 mg/d)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003ePR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003eP4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cem\u003eERBB2/ERBB3\u003c/em\u003e mRNA overexpression\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eAnti-ER2/HER3 TKI + docetaxel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eIV (afatinib)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003eafatinib (40 mg/d) + docetaxel (75 mg/m\u003csup\u003e2\u003c/sup\u003e/3w)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003ePR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003eP5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cem\u003eFANCM\u003c/em\u003e biallelic loss + high HRD score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003ePARPi maintenance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eIIIA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003eolaparib (300 mg bid)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003eCR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003eP5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cem\u003eFANCM\u003c/em\u003e biallelic loss + high HRD score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003ePARPi + CDDP + RT followed with PAPRi maintenance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eIIIA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003eolaparib (100 mg bid then 300 mg bid) + CDDP (40 mg/m\u003csup\u003e2\u003c/sup\u003e/w)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003eCR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003eP6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cem\u003eCTNNB\u003c/em\u003e mutation and \u003cem\u003ePI3KCA\u0026nbsp;\u003c/em\u003emutation + transcriptomic activation of \u003cem\u003ePI3KCA/AKT/mTOR\u003c/em\u003e pathway\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003emTOR inhibitor + anti-aromatase\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eIII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003eeverolimus (10 mg/d then 12,5 mg/d) \u0026nbsp;+ letrozole 2.5 mg/d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003eSD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003eP7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cem\u003eFGFR3-TACC3\u003c/em\u003e fusion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eFGFR3 inhibitor + RT on residual localizations\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eIA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003eerdafitinib (8 mg/d decreased to 6 mg/d for severe toxicities)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003ePR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003eNot reached (\u0026gt;23)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003eP8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cem\u003eCyclin D1\u003c/em\u003e amplification (15 copies)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eCDK4 inhibitor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eIII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003epalbociclib (125 mg/d continuously)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003ePD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026lt;3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003eP8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cem\u003eRAD50\u003c/em\u003e mutation, biallelic inactivation, high HRD score\u003c/p\u003e\n \u003cp\u003e+ immune transcriptomic signature\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003ePARPi + CDDP + anti-PD1 antibody\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eIIIA (PARPi)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003eolaparib (100 mg bid) + CDDP (40 mg/m\u003csup\u003e2\u003c/sup\u003e/w) + pembrolizumab (200 mg/3w)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003ePR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003eP9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cem\u003ePTEN\u0026nbsp;\u003c/em\u003emutation + \u003cem\u003ePI3KCA\u003c/em\u003e mutation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003emTOR inhibitor + CDDP + anti-PD1 antibody\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003eeverolimus (10 mg/d) + CDDP (30mg/m\u003csup\u003e2\u003c/sup\u003e/w) + pembrolizumab (200 mg/3w)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003ePD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026lt;3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003eP10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cem\u003eMET\u003c/em\u003e mRNA overexpression + high HRD score (low \u003cem\u003eRAD51C\u003c/em\u003e expression)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eMET inhibitor + PARPi + stereotactic RT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eIIIA (PARPi)\u003c/p\u003e\n \u003cp\u003eIIIA (MET inhibitor)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003ecabozantinib (60 mg/d) + olaparib (200 mg bid)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003eSD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003eP11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cem\u003eSFPQ::TFE3\u003c/em\u003e fusion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003emTOR inhibitor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eIIIA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003eeverolimus (10 mg/d)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003ePD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026lt;3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003eP12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eHigh-immune E transcriptomic signature\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eAnti-PD1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eIIB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003epembrolizumab (200 mg/3w)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003ePD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026lt;3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003eP13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cem\u003eKRAS\u003c/em\u003e mutation + \u003cem\u003eJAK1\u003c/em\u003e mutation (with LOH)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eMEK inhibitor + JAK1 inhibitor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eIV (MEKi)\u003c/p\u003e\n \u003cp\u003eIV (JAKi)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003etrametinib (2 mg/d) + filgetinib (200 mg/d)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003ePR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003eP14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eHigh HRD score (genomic and transcriptional + low \u003cem\u003eATM/BAP1/RAD51\u0026nbsp;\u003c/em\u003emRNA expression)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003ePARPi + CDDP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eIIIA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003eniraparib (300 mg/d) + CDDP (40 mg/m\u003csup\u003e2\u003c/sup\u003e/w)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003ePR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e5 (then loss of follow-up)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003eP15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eHigh HRD score (genomic and transcriptional + low \u003cem\u003eATR/ATRX\u003c/em\u003e mRNA expression)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003ePARPi + CDDP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eIIIA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003eolaparib (100 mg/d then 200mg/d because of under exposure) + CDDP (30 mg/m\u003csup\u003e2\u003c/sup\u003e/w)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003ePR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e4.5 (brain progression)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003eP16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cem\u003eELK1::TFE3\u003c/em\u003e fusion + PI3K/AKT/mTOR pathway activation (mRNA overexpression)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003emTOR inhibitor + somatostatin analogous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eIIIB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003eeverolimus (10 mg/d) + octreotide (100 ug/4w)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003eSD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003eP17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cem\u003ePI3KCA\u003c/em\u003e mutation p.(H1047R) + transcriptomic \u003cem\u003ePI3KCA/AKT/mTOR\u003c/em\u003e pathway activation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003emTOR inhibitor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eIIA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003eeverolimus (10 mg/d)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003eCR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003eNot reached (\u0026gt;14)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003eP18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cem\u003eAR\u003c/em\u003e amplification (10 copies) + AR protein overexpression + \u003cem\u003eSPOP\u003c/em\u003e mutation with LOH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eAR antagonist + paclitaxel + bevacizumab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eIIB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003eabiraterone acetate (500 mg bid) + paclitaxel + bevacizumab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003ePR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003eP18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cem\u003eAKT1\u003c/em\u003e mutation + \u003cem\u003eAKT1\u0026nbsp;\u003c/em\u003eamplification (9 copies) + biallelic loss of \u003cem\u003eMAP2K4\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eMEK inhibitor + mTOR inhibitor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eIV (MEKi)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003etrametinib (2 mg/d) + everolimus (10 mg/d)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003ePR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e6,5 (interruption for severe toxicity)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003eP19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cem\u003ePTEN\u003c/em\u003e biallelic loss (mutation + LOH) + \u003cem\u003ePI3KCA\u0026nbsp;\u003c/em\u003emutation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003emTOR inhibitor + capecitabin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eIIA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003eeverolimus (10 mg/d) + capecitabin (1000 mg/m2 bid 14d/3w)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003ePR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026lt;3 (early interruption for severe toxicity)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003eP20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cem\u003eARID1A\u003c/em\u003e biallelic inactivation (two mutations) + \u003cem\u003ePI3KCA\u003c/em\u003e mutation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eEZH2 inhibitor + mTOR inhibitor + carboplatin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eIV (EZH2i)\u003c/p\u003e\n \u003cp\u003eIII (mTORi)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003eTazemetostat (800 mg bid) + everolimus (10 mg/d)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003eSD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003eP21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eHigh HRD score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003ePARPi\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eIIIA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003eolaparib (300 mg bid)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003ePR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003eP22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cem\u003eFGFR2\u003c/em\u003e mutation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003epan-FGFR inhibitor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eIC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003epemigatinib (13.5mg/d 2w on and 1w off)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003eSD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003eP23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cem\u003eKRAS\u0026nbsp;\u003c/em\u003emutation p.(G12D) + \u003cem\u003eAKT1\u0026nbsp;\u003c/em\u003emutation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eMEK inhibitor + mTOR inhibitor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eIV (MEKi)\u003c/p\u003e\n \u003cp\u003eIV (mTOR inhibitor)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003etrametinib (2mg/d then 1mg/d) + everolimus (10mg/d then 5mg/d for toxicities and over-exposure)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003ePR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e7.5 (interruption for toxicity)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003eP24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eHigh HRD score + \u003cem\u003eBRCA2\u003c/em\u003e biallelic deletion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003ePARPi + CDDP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eIIA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003eolaparib (100 then 200 mg bid for under exposure) + CDDP (30 mg/m\u003csup\u003e2\u003c/sup\u003e/w)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003ePR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003eNot reached (\u0026gt;10)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003eP25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cem\u003ePTEN\u003c/em\u003e biallelic inactivation\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003emTOR inhibitor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eIIA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003eeverolimus (10 mg/d then 5 mg/d for toxicity and over-exposure)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003ePD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026lt;3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003eP26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eHigh HRD score, SBS3 signature, methylation \u003cem\u003eBRCA1\u003c/em\u003e promotor and low mRNA \u003cem\u003eBRCA1\u003c/em\u003e expression + immune signature\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003ePARPi + dose-dense EC \u0026nbsp;regimen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eIC/IIA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003eolaparib (100 mg bid) + epirubicine (75 mg/m\u003csup\u003e2\u003c/sup\u003e/2w) + cyclophosphamide (1200 mg/m\u003csup\u003e2\u003c/sup\u003e/2w)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003ePD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026lt;3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003eP27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cem\u003eMET\u0026nbsp;\u003c/em\u003eamplification (9 copies) and mRNA overexpression\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eMET inhibitor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eIIIA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003eCabozantinib (60 mg/d then 40 mg/d for toxicities)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003ePR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003eNot reached (\u0026gt;8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eID: identity; ESCAT: ESMO Scale for Clinical Actionability of molecular Targets; P: Patient; LOH: Loss Of Heterozygosity; SD: Stable Disease; d: day; PD: Progressive Disease; HRD: Homologous Recombination Deficiency; CDDP: cisplatin; PARPi: Poly (ADP-Ribose) Polym\u0026eacute;rase inhibitors; w: weekly; bid: bi-daily; PR: Partial Response; TKI: Tyrosine Kinase Inhibitors; CR: Complete Response; RT: Radiotherapy; AR: Androgen Receptor; EC: Epirubicin-Cyclophosphamide.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-6991185/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6991185/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eHere, we report the importance of integrative genomic analysis and combined therapies in precision medicine to achieve durable responses in patients with limited treatment options.\u003c/p\u003e\n\u003cp\u003eWe report here data from 27 patients with cancers in a situation of treatment failure. For each patient, Sequencing Omics Information Analysis (SeqOIA) platform performed integrative genomic analysis. SeqOIA-tailored treatment outperformed previous lines. Combined treatments showed greater clinical benefit (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.01) and longer survival than monotherapies (\u003cem\u003eP\u003c/em\u003e=0.07).\u003c/p\u003e","manuscriptTitle":"SeqOIA platform, an integrative and interactive approach to optimize personalized cancer treatment","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-28 07:17:45","doi":"10.21203/rs.3.rs-6991185/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d72c729f-948e-49df-a12d-d981c9e9fafb","owner":[],"postedDate":"July 28th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":51947427,"name":"Biological sciences/Cancer"},{"id":51947428,"name":"Biological sciences/Computational biology and bioinformatics"},{"id":51947429,"name":"Health sciences/Oncology"}],"tags":[],"updatedAt":"2025-09-22T22:53:36+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-28 07:17:45","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6991185","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6991185","identity":"rs-6991185","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}