Large-scale public data reuse to model immunotherapy response and resistance

Autor: Jingxin Fu, Karen Li, Wubing Zhang, Changxin Wan, Jing Zhang, Peng Jiang, X. Shirley Liu
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Zdroj: Genome Medicine, Vol 12, Iss 1, Pp 1-8 (2020)
Druh dokumentu: article
ISSN: 1756-994X
DOI: 10.1186/s13073-020-0721-z
Popis: Abstract Despite growing numbers of immune checkpoint blockade (ICB) trials with available omics data, it remains challenging to evaluate the robustness of ICB response and immune evasion mechanisms comprehensively. To address these challenges, we integrated large-scale omics data and biomarkers on published ICB trials, non-immunotherapy tumor profiles, and CRISPR screens on a web platform TIDE ( http://tide.dfci.harvard.edu ). We processed the omics data for over 33K samples in 188 tumor cohorts from public databases, 998 tumors from 12 ICB clinical studies, and eight CRISPR screens that identified gene modulators of the anticancer immune response. Integrating these data on the TIDE web platform with three interactive analysis modules, we demonstrate the utility of public data reuse in hypothesis generation, biomarker optimization, and patient stratification.
Databáze: Directory of Open Access Journals
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