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Table 1: samples included in the RNAseq analysis Figure 1: consort flow diagram Table 2: Comparison of patients' characteristics of the subset of patients included in the RNA-seq analysis and patients recruited in the DECISION study Figure 2: Progression-free survival of the subgroup of patients included in the RNA-seq analysis. Table 3: Pathways_GO_analysis Figure 3: Kaplan-Meyer curves of the three RNA expression groups regarding treatment group in DECISION trial. Figure 4: A,B,C: PFS in papillary, follicular and poorly differentiated histologies, respectively; D,E,F: OS in papillary, follicular and poorly differentiated histologies, respectively Figure 5: Overall survival (OS) analysis based on RNA expression profile from TCGA data of papillary thyroid cancer (Cell, 2014) Figure 6: Analyses based on 121 angiogenesisrelated genes

Several biomarkers have been suggested to have prognostic value in differentiated thyroid carcinomas (DTC) with no validation in the refractory setting, including all tumor subtypes. We aim to correlate RNA expression profiles with survival based on patients included in the DECISION trial. We obtained 247 samples from the 417 patients included in the DECISION study and performed RNAseq analysis (77 million paired-end reads for each sample on HiSeq2000). After quality control, 125 samples were included in the secondary analysis and mapped against the human reference genome (GRCh38) with STAR (v2.5.1b) using ENCODE parameter. Survival analysis was calculated using the Kaplan–Meier method and log-rank test was used for statistical comparison. In this post hoc analysis, we identified three groups of tumors based on their gene expression profile: BRAF-like, RAS-like, and non-BRAF-non-RAS-like (NoBRaL). No significant correlation with sorafenib responders was observed. However, we identified a statistically significant correlation between the RNA-expression profiles and progression-free survival. The BRAF-like profile had a significantly better outcome compared with RAS-like and NoBRaL (11.8, 6.2, and 5.5 months, respectively) [HR: 0.31, 95% confidence interval (CI), 0.17–0.60; P < 0.001 and HR: 0.36 (95% CI, 0.21–0.63); P < 0.001] and HR: 0.36 (95% CI, 0.21–0.63; P < 0.001) and maintained significance as an independent prognostic factor for overall survival in the multivariate analysis for papillary thyroid cancers. To our knowledge, this is the first comprehensive RNA-seq analysis of all histologic subtypes of DTC. The RNA expression profiles identified may suggest a new prognostic parameter to be considered before recommendation of systemic therapies or the design of stratification factors for future clinical trials.

Purpose:FGFR1 amplification (FGFR1amp) is recurrent in metastatic breast cancer (MBC) and is associated with resistance to endocrine therapy and CDK4/6 inhibitors (CDK4/6is). Multi-tyrosine kinase inhibitors (MTKIs) and selective pan-FGFR inhibitors (FGFRis) are being developed for FGFR1amp breast cancer. High-level FGFR amplification and protein expression by IHC have identified breast cancer responders to FGFRis or MTKIs, respectively.Experimental Design:Here, we used preclinical models and patient samples to identify predictive biomarkers to these drugs. We evaluated the antitumor activity of an FGFRi and an MTKI in a collection of 17 breast cancer patient–derived xenografts (PDXs) harboring amplification in FGFR1/2/3/4 and in 10 patients receiving either an FGFRi/MTKI. mRNA levels were measured on FFPE tumor samples using two commercial strategies. Proliferation and angiogenesis were evaluated by detecting Ki-67 and CD31 in viable areas by immunofluorescence.Results:High FGFR1–4 mRNA levels but not copy-number alteration (CNA) is associated with FGFRi response. Treatment with MTKIs showed higher response rates than with FGFRis (86% vs. 53%), regardless of the FGFR1–4 mRNA levels. FGFR-addicted PDXs exhibited an antiproliferative response to either FGFRis or MTKIs, and PDXs exclusively sensitive to MTKI exhibited an additional antiangiogenic response. Consistently, the clinical benefit of MTKIs was not associated with high FGFR1–4 mRNA levels and was observed in patients previously treated with antiangiogenic drugs.Conclusions:Tailored therapy with FGFRis in molecularly selected MBC based on high FGFR1–4 mRNA levels warrants prospective validation in patients with CDK4/6i-resistant luminal breast cancer and in patients with TNBC without targeted therapeutic options.

Supplementary Figure 1. FGFR1-4 DNA CN, mRNA levels and ROC curves analysis. A) Waterfall plot representing the best antitumor response of FGFRi in 24 patients from 8 different cancer types treated at VHIO. FGFR1/2 amplification status and high FGFR1-4 mRNA levels are indicated in the underneath panel. B) Copy number (CN) values of FGFR1-4 by MSK-IMPACT in the FGFR/FGFamp PDX collection and categorized analysis in PDXs harboring CN amplification (CN>4), according to the response to rogaratinib (responders (SD and PR) and non-responders (PD)). C) Evaluation of FGFR1/4 CN ratio by FISH ratio (the dashed line indicates the CN ratio>2.2 that is considered amplified) and categorized analysis according to the response to rogaratinib. D) Correlation analysis between the CN values (X-axis) and mRNA levels (Y-axis) of FGFR1-4 obtained from MSK-IMPACT or nCounter, respectively. Pearson correlation coefficient (r2) is shown. E) Categorized analysis of FGFR1-4 mRNA composite biomarker according to the response to rogaratinib, obtained from HTG or qPCR data. Statistical test: Mann-Whitney U test. ROC curve analysis the FGFR1-4 mRNA composite biomarker, obtained from HTG or qPCR (AUC=0.89, both).

Supplementary Figure 2. FGFR1-3 protein expression in BC PDXs models. A) Western blot (WB) analysis of FGFR1 and FGFR3 protein expression in PDX models; CAL120 cells were used as positive control for FGFR1 expression. B) Clinical evolution of a refractory metastatic triple negative breast cancer (mTNBC) patient -Pt306-, whose primary tumor harbored a high-level FGFR2amp (CN 21.8) and co-amplification of 11q13 (CN 7.0), assessed by FISH. Pt achieved disease stabilization (SD) lasting 8 months: reduction in lung target lesions (TL, red arrow) and overall decrease in other lung non-target lesions (NTL, red circle). Primary tumor biopsy was available for further molecular characterization with IHC FGFR2. C) IHC images of FGFR2 in PDX models and the primary tumor Bx from Pt306, according to the model/patient response to FGFRi (PD or SD). D) Correlation analysis of FGFR1/2/3 mRNA levels vs. protein levels by WB for FGFR1/3 or IHC for FGFR2. FGFR1/3 were quantified with ImageJ (normalized by tubulin levels) and FGFR2 with QuPath and ImageJ. Statistical test: Pearson correlation coefficient (r2) is shown.

Purpose:FGFR1 amplification (FGFR1amp) is recurrent in metastatic breast cancer (MBC) and is associated with resistance to endocrine therapy and CDK4/6 inhibitors (CDK4/6is). Multi-tyrosine kinase inhibitors (MTKIs) and selective pan-FGFR inhibitors (FGFRis) are being developed for FGFR1amp breast cancer. High-level FGFR amplification and protein expression by IHC have identified breast cancer responders to FGFRis or MTKIs, respectively.Experimental Design:Here, we used preclinical models and patient samples to identify predictive biomarkers to these drugs. We evaluated the antitumor activity of an FGFRi and an MTKI in a collection of 17 breast cancer patient–derived xenografts (PDXs) harboring amplification in FGFR1/2/3/4 and in 10 patients receiving either an FGFRi/MTKI. mRNA levels were measured on FFPE tumor samples using two commercial strategies. Proliferation and angiogenesis were evaluated by detecting Ki-67 and CD31 in viable areas by immunofluorescence.Results:High FGFR1–4 mRNA levels but not copy-number alteration (CNA) is associated with FGFRi response. Treatment with MTKIs showed higher response rates than with FGFRis (86% vs. 53%), regardless of the FGFR1–4 mRNA levels. FGFR-addicted PDXs exhibited an antiproliferative response to either FGFRis or MTKIs, and PDXs exclusively sensitive to MTKI exhibited an additional antiangiogenic response. Consistently, the clinical benefit of MTKIs was not associated with high FGFR1–4 mRNA levels and was observed in patients previously treated with antiangiogenic drugs.Conclusions:Tailored therapy with FGFRis in molecularly selected MBC based on high FGFR1–4 mRNA levels warrants prospective validation in patients with CDK4/6i-resistant luminal breast cancer and in patients with TNBC without targeted therapeutic options.

Supplementary Table S2 HTG OBP panel raw data

Supplementary Figure Legends

Supplementary Figure 5. Relative expression levels of lucitanib-specific RTK targets and ligands in PDX and patient tumors. A) mRNA expression levels of 2544 genes detected by HTG in Pt325 samples (Pre-tt versus On-tt). Highlighted are some differentially expressed genes between both samples, including FGFR1. Data is log-2 transformed. B) and C) Relative mRNA levels of lucitanib-specific RTK targets or cognate ligands in PDX and patient tumors from the MTKI/FGFRi-treated patient cohort from Figure 3D, respectively.

Supplementary Table S1 PDXs subtype, genotype and drug efficacy data

Several biomarkers have been suggested to have prognostic value in differentiated thyroid carcinomas (DTC) with no validation in the refractory setting, including all tumor subtypes. We aim to correlate RNA expression profiles with survival based on patients included in the DECISION trial. We obtained 247 samples from the 417 patients included in the DECISION study and performed RNAseq analysis (77 million paired-end reads for each sample on HiSeq2000). After quality control, 125 samples were included in the secondary analysis and mapped against the human reference genome (GRCh38) with STAR (v2.5.1b) using ENCODE parameter. Survival analysis was calculated using the Kaplan–Meier method and log-rank test was used for statistical comparison. In this post hoc analysis, we identified three groups of tumors based on their gene expression profile: BRAF-like, RAS-like, and non-BRAF-non-RAS-like (NoBRaL). No significant correlation with sorafenib responders was observed. However, we identified a statistically significant correlation between the RNA-expression profiles and progression-free survival. The BRAF-like profile had a significantly better outcome compared with RAS-like and NoBRaL (11.8, 6.2, and 5.5 months, respectively) [HR: 0.31, 95% confidence interval (CI), 0.17–0.60; P < 0.001 and HR: 0.36 (95% CI, 0.21–0.63); P < 0.001] and HR: 0.36 (95% CI, 0.21–0.63; P < 0.001) and maintained significance as an independent prognostic factor for overall survival in the multivariate analysis for papillary thyroid cancers. To our knowledge, this is the first comprehensive RNA-seq analysis of all histologic subtypes of DTC. The RNA expression profiles identified may suggest a new prognostic parameter to be considered before recommendation of systemic therapies or the design of stratification factors for future clinical trials.

Here, we used preclinical models and patient samples to identify predictive biomarkers to these drugs. We evaluated the antitumor activity of an FGFRi and an MTKI in a collection of 17 breast cancer patient-derived xenografts (PDXs) harboring amplification inHighTailored therapy with FGFRis in molecularly selected MBC based on high

Oncologia de precisió; Assaigs clínics; Preselecció molecular Oncología de precisión; Ensayos clínicos; Preselección molecular Precision oncology; Clinical Trials; Molecular prescreening Most academic precision oncology programs have been designed to facilitate enrollment of patients in early clinical trials with matched targeted agents. Over the last decade, major changes were seen both in the targetable molecular alteration landscape and in drug development trends. In this article, we describe how the Vall d’Hebron Institute of Oncology molecular prescreening program adapted to a dynamic model of biomarker-drug codevelopment. We started with a tumor-agnostic hotspot mutation panel plus in situ hybridization and immunohistochemistry of selected markers and subsequently transitioned to tumor-specific amplicon-based next-generation sequencing (NGS) tests together with custom copy number, fusion, and outlier gene expression panels. All assays are optimized for archived formalin-fixed paraffin-embedded tumor tissues without matched germline sequencing. In parallel, biomarker-matched trials evolved from a scenario of few targets and large populations (such as PI3K inhibitors in PIK3CA mutants) to a complex situation with many targets and small populations (such as multiple targetable fusion events). Recruitment rates in clinical trials with mandatory biomarkers decreased over the last 3 years. Molecular tumor board meetings proved critical to guide oncologists on emerging biomarkers for clinical testing and interpretation of NGS results. The substantial increase of immunotherapy trials had a major impact in target prioritization and guided clinical implementation of new markers, such as tumor mutational burden, with larger exon-based NGS assays and gene expression signatures to capture microenvironment infiltration patterns. This new multiomics era of precision oncology is expected to increase the opportunities for early clinical trial matching.

Introduction: Gene alterations in NOTCH signaling pathway have a prevalence ranging from Methods: From Jan/2017 to Dec/2018, 1,697 patients (pts) had their FFPE tumor samples (either primary or metastasis) analyzed for mutations (mut) using a custom developed Amplicon-Seq panel of 59 cancer-related genes (including NOTCH1 [hotspots 5% exon coverage] and NOTCH4 [hotspots 3% exon coverage]) that was run in Illumina MiSeq (v1). Additionally, 502 samples were analyzed for Copy Number Alterations (CNA) using a panel of 44 genes (including NOTCH1-4) using NanoString nCounter (copy number between 4-6 copies were validated by FISH). From Jun/2018 to Jun/2019 an expanded NOTCH Amplicon-Seq panel v2 (including additional exons in NOTCH1 plus NOTCH2 and NOTCH3 hotspots regions) replaced the prior v1 panel and 618 samples were sequenced. Results: Colorectal cancer (CRC) (n= 404 [24%]; n=241 [39 %]) and breast cancer (BC) (n=283 [17%]; n= 194 [31%]) were the most frequent tumor types for v1 and v2 panel cohorts, respectively. NOTCH1-4 mut were detected in 11 cases (0.64%). The highest rate of NOTCH pathway alterations (NOTCH1-4 mut plus CN gain or loss) was detected in BC (n=14 [7.7%]) with a clear enrichment in triple negative subtype. Higher prevalence of NOTCH1-4 mut was detected using expanded v2 panel, with 17 NOTCH1-4 mut cases (2.75%). Head & neck (H&N) (n=3 [5%]); BC (n=6 [3%]); and CRC (n=6 [2.5%]) were most common tumors. From all NOTCH1-4 gene mut detected, 8 were known actionable oncogenic driver mut and 9 were variants of unknown significance. When comparing our latest v2 results with GENIE database (mostly large NGS panels with exon capture), we found a similar prevalence in NOTCH1-4 mut in BC and CRC, but lower prevalence was seen in H&N, biliary and gastric tumors. We enrolled 4 pt in clinical trials with NOTCH inhibitors (3 NOTCH1 actionable mut pt (0.48%), 1 NOTCH3 actionable mut pt (0.16%). Conclusion: Institutional efforts to increase coverage of NOTCH pathway genes improved the detection of actionable NOTCH1-4 mut. Differences in prevalence as compared to GENIE dataset may be attributed to the small number of samples tested with our v2 panel and larger panels covering all exons of NOTCH1-4 genes in GENIE cohort. Therefore, we keep evolving our NOTCH prescreening program for clinical trial enrichment. Citation Format: Analía Azaro, Susana Aguilar, Zighereda Ogbah, Omar Saavedra, María Vieito, Ignacio Matos, Irene Braña, Enriqueta Felip, Joan Carles, Lorena Fariñas, Elena Elez, Teresa Macarulla, Cristina Saura, Rodrigo Dienstmann, Elena Garralda, Ana Vivancos. Adapting a molecular prescreening program to detect notch pathway alterations in the context of early drug development [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2953.

Background Despite favorable clinical and pathological prognostic factors, some patients (pts) with siNENs have impaired survival. In this study, we aimed to identify distinct RNA expression and splicing profiles (EP and SP, respectively) to correlate with prognosis. Methods Paraffin-embedded tumor samples of 48 pts with metastatic grade 1/2 siNENs were analyzed for RNAseq. We generated on average 66 million paired-end reads for each sample on HiSeq2500 (Illumina). RNAseq reads were mapped against the human reference genome (hg19) with Tophat (v2.0.14) and quantified using Cufflinks tools suite for expression analysis. As for splicing, SUPPA2 software was used to detect and quantify the splicing isoforms. 41 samples had sufficient quality to be included in the analysis. We used multivariate Cox proportional models to study the association between clinical variables and EP, SP and overall survival (OS). Poor outcome was defined as death within the first 3 years from advanced stage diagnosis. Results 9348 transcripts for unique genes were quantified and over 160000 splicing isoforms were examined. A gene signature of 329 transcripts was defined by a two-way statistical analysis between short- and long-term survivors. A pathway enrichment analysis showed a dysregulation in the poor prognosis group on the mTOR and the Toll-like pathways. The EP signature was shown to be an independent prognostic variable for OS (HR 0.05, 95% CI 0.005-0.51, p = 0.011 in multivariate analysis). The analysis of splicing revealed that 90 isoforms were differentially expressed, including those from ELOA and C14orf178 genes, which were associated with aggressiveness. Conclusions Different RNA-clusters, different deregulated pathways, and selective splicing alterations were identified for those pts with advanced siNENs with poor prognosis. To our knowledge, this is the first time that Toll-like pathway is involved in the pathogenesis of siNENs and that variants of ELOA and C14orf178 are linked to this pathology. These results may open the future option for a better management and new actionable pathways in this setting. Legal entity responsible for the study GETNE (Spanish Taskforce for Neuroendocrine and Endocrine Tumors). Funding GETNE. Disclosure J. Capdevila: Advisory / Consultancy, Speaker Bureau / Expert testimony: Bayer, Sanofi, Eisai, Ipsen, Pfizer, Novartis, Advanced Accelerator Applications, Merck; Leadership role, Research grant / Funding (institution): Astrazeneca, Eisai; Travel / Accommodation / Expenses: Ipsen, Eisai. J. Hernando: Speaker Bureau / Expert testimony: Eisai, Ipsen, Angelini, Roche; Travel / Accommodation / Expenses: Adacap, Novartis, Ipsen, Roche, Astrazeneca, Eisai. All other authors have declared no conflicts of interest.

Background Mutations in the CDKN2A and CDK4 genes predispose to melanoma. From three case-control studies of cutaneous melanoma, we estimated the prevalence and predictors of these mutations for people from regions with widely differing latitudes and melanoma incidence. Methods Population-based cases and controls from the United Kingdom (1586 cases, 499 controls) and Australia (596 early-onset cases, 476 controls), and a hospital-based series from Spain (747 cases, 109 controls), were screened for variants in all exons of CDKN2A and the p16INK4A binding domain of CDK4. Results The prevalence of mutations for people with melanoma was similar across regions: 2.3%, 2.5% and 2.0% for Australia, Spain and the United Kingdom respectively. The strongest predictors of carrying a mutation were having multiple primaries (odds ratio (OR) = 5.4, 95% confidence interval (CI: 2.5, 11.6) for 2 primaries and OR = 32.4 (95% CI: 14.7, 71.2) for 3 or more compared with 1 primary only); and family history (OR = 3.8; 95% CI:1.89, 7.5) for 1 affected first- or second-degree relative and OR = 23.2 (95% CI: 11.3, 47.6) for 2 or more compared with no affected relatives). Only 1.1% of melanoma cases with neither a family history nor multiple primaries had mutations. Conclusions There is a low probability (

We report the association of an inherited variant located upstream of the poly(adenosine diphosphate-ribose) polymerase 1 (PARP1) gene (rs2249844), with survival in 11 BioGenoMEL melanoma cohorts. The gene encodes a protein involved in a number of cellular processes including single-strand DNA repair. Survival analysis was conducted for each cohort using proportional hazards regression adjusting for factors known to be associated with survival. Survival was measured as overall survival (OS) and, where available, melanoma-specific survival (MSS). Results were combined using random effects meta-analysis. Evidence for a role of the PARP1 protein in melanoma ulceration and survival was investigated by testing gene expression levels taken from formalin-fixed paraffin-embedded tumors. A significant association was seen for inheritance of the rarer variant of PARP1, rs2249844 with OS (hazard ratio (HR) = 1.16 per allele, 95\% confidence interval (CI) 1.04-1.28, p = 0.005, eleven cohorts) and MSS (HR = 1.20 per allele, 95\% CI 1.01-1.39, p = 0.03, eight cohorts). We report bioinformatic data supportive of a functional effect for rs2249844. Higher levels of PARP1 gene expression in tumors were shown to be associated with tumor ulceration and poorer OS. What's New? Although staging systems predict outcome fairly well for melanoma, survival still varies among individual patients. In this meta-analysis, the authors found that inheritance of a rare genetic variant of PARP1 was associated with improved survival of melanoma patients. Increased expression of PARP1 has been associated with poorer outcome, and depletion of PARP1 may reduce both melanoma growth and angiogenesis. The identification of this and other germline variants that affect survival may help to identify key biological pathways active in host/tumor interactions, which may lead to the discovery of new therapeutic targets for treating advanced melanoma. \copyright 2014 UICC. Published by Wiley Periodicals, Inc. on behalf of UICC.

Several studies have demonstrated that different genetic profiles contribute to melanoma development and progression.To evaluate the existence of different molecular aberration patterns in melanoma associated with v-raf murine sarcoma viral oncogene homolog B1 (BRAF) or 9p21 locus alterations, eleven patient-derived melanoma cell lines were characterized. Multiplex ligation probe amplification (MLPA) was used to detect chromosomal alterations. Single- strand conformation analysis and sequencing were performed to study BRAF, neuroblastoma RAS viral (v-ras) oncogene homolog (NRAS), v-kit Hardy-Zuckerman 4 feline sarcoma viral oncogene homolog (c-KIT), melanocortin 1 receptor (alpha melanocyte stimulating hormone receptor) (MC1R), cyclin-dependent kinase inhibitor 2A (CDKN2A) and cyclin-dependent kinase 4 (CDK4) genes.BRAFV600E mutation was detected in 54% of cell lines. NRAS was mutated in one cell line also carrying multiple copies of NRAS. All cell lines with MC1R variants harboured BRAFV600E. Concurrent loss of MUTYH (1p33), gains of c-MYC (8q24) and of CDK6 (7q21) were found to be significantly associated in cell lines (45%) that harboured biallelic 9p21 deletions including CDKN2B-CDKN2A-MTAP.These data suggest the existence of a specific pattern of somatic alterations in genes that are involved in DNA repair (MUTYH) and in cell cycle regulation (c-MYC, CDK6, CDKN2A and CDKN2B). Interestingly, all MC1R variants were associated with BRAFV600E and all cell lines from visceral metastases harboured BRAFV600E.

Importance Sun damage is the most important environmental factor associated with malignant melanoma. To address the health threat, as well as the economic burden, primary prevention and early detection are crucial. Objective To test the efficacy of a topical sunscreen in the prevention of UV-induced effects in nevi. Design Prospective study of nevi protected by sunscreen vs a physical barrier. Setting and Patients Twenty-three nevi from 20 patients attending a referral hospital. Intervention Half of each nevus was protected by either a physical barrier or a sunscreen. Lesions were completely irradiated by a single dose of UV-B. Main Outcomes and Measures In vivo examination before and 7 days after irradiation and histopathologic-immunopathologic evaluation after excision on the seventh day. Results The most frequent clinical changes after UV radiation were pigmentation, scaling, and erythema; the most frequent dermoscopic changes were increased globules/dots, blurred network, regression, and dotted vessels. Both physical barrier– and sunscreen-protected areas showed some degree of these changes. More than 30% (7) of nevi did not show any change on clinical examination, and 18% (4) had no dermoscopic change. Immunohistopathologic differences between the halves of each nevus were demonstrable even when in vivo examination detected nothing. Parakeratotic scale, increased number and activation of superficial melanocytes, and keratinocyte proliferation were the most remarkable features. The only difference between both barriers was more enhanced melanocytic activation and regression features in the sunscreen group. No phenotypic features were found to predict a specific UV-B response. Conclusions and Relevance Both physical barriers and sunscreens can partially prevent UV-B effects on nevi. Subclinical UV radiation effects, not always associated with visible changes, can develop even after protection. Sunscreens are not quite as effective as physical barriers in the prevention of inflammatory UV-B–induced effects.