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

By Jingxin Fu, Karen Li, Wubing Zhang, Changxin Wan, Jing Zhang, Peng Jiang, X. S. Liu. Genome Medicine, 2020

905 citations recorded by the source corpus.

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.

Subfields: Cancer Research, Molecular Biology, Oncology

View Paper: https://www.semanticscholar.org/paper/d853849b8b1eff9264c7f67e9ccb6a37a6f734ed

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In Molecular Biology

Zexian Zeng

Citations in the corpus

TIMER2.0 for analysis of tumor-infiltrating immune cells (2020, background): “Gene expression-based approaches have been developed to predict survival and therapy response (32,34,35).”
JMJD8 Is an M2 Macrophage Biomarker, and It Associates With DNA Damage Repair to Facilitate Stemness Maintenance, Chemoresistance, and Immunosuppression in Pan-Cancer (2022, methodology): “(E) The table of correlations between JMJD8 methylation level and CTL-related factors was retrieved from the Methylation module of TIDE web tool, the third column means CTL correlation, and the fourth column refers to CTL dysfunction z-score of the interaction term.”