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Integrative Pan-Cancer Genomic and Transcriptomic Analyses of Refractory Metastatic Cancer

癌症 转录组 计算生物学 耐火材料(行星科学) 癌症研究 生物信息学 生物 遗传学 基因 基因表达 天体生物学
作者
Yoann Pradat,Julien Viot,Andrey A. Yurchenko,Konstantin Gunbin,Luigi Cerbone,Marc Deloger,Guillaume Grisay,Loïc Verlingue,Véronique Scott,Ismaël Padioleau,Leonardo Panunzi,Stefan Michiels,Antoine Hollebecque,Gérôme Jules-Clément,Laura Mezquita,Antoine Lainé,Yohann Loriot,Benjamin Besse,Luc Friboulet,Fabrice André
出处
期刊:Cancer Discovery [American Association for Cancer Research]
卷期号:13 (5): 1116-1143 被引量:25
标识
DOI:10.1158/2159-8290.cd-22-0966
摘要

Abstract Metastatic relapse after treatment is the leading cause of cancer mortality, and known resistance mechanisms are missing for most treatments administered to patients. To bridge this gap, we analyze a pan-cancer cohort (META-PRISM) of 1,031 refractory metastatic tumors profiled via whole-exome and transcriptome sequencing. META-PRISM tumors, particularly prostate, bladder, and pancreatic types, displayed the most transformed genomes compared with primary untreated tumors. Standard-of-care resistance biomarkers were identified only in lung and colon cancers—9.6% of META-PRISM tumors, indicating that too few resistance mechanisms have received clinical validation. In contrast, we verified the enrichment of multiple investigational and hypothetical resistance mechanisms in treated compared with nontreated patients, thereby confirming their putative role in treatment resistance. Additionally, we demonstrated that molecular markers improve 6-month survival prediction, particularly in patients with advanced breast cancer. Our analysis establishes the utility of the META-PRISM cohort for investigating resistance mechanisms and performing predictive analyses in cancer. Significance: This study highlights the paucity of standard-of-care markers that explain treatment resistance and the promise of investigational and hypothetical markers awaiting further validation. It also demonstrates the utility of molecular profiling in advanced-stage cancers, particularly breast cancer, to improve the survival prediction and assess eligibility to phase I clinical trials. This article is highlighted in the In This Issue feature, p. 1027
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