TIDE

TIDE models tumor immune dysfunction and exclusion to predict and analyze mechanisms of response and resistance to immune checkpoint blockade (ICB) using integrated large-scale omics and functional genomic data.

Key Features:

• Integration of omics data: Processes over 33,000 samples across 188 tumor cohorts, including 998 tumors from 12 ICB clinical studies and data from eight CRISPR screens that identified gene modulators of anticancer immune response.
• Analysis modules: Provides three analysis modules that support hypothesis generation, biomarker optimization, and patient stratification from integrated datasets.
• Biomarker and immune-evasion evaluation: Integrates biomarkers from ICB trials to evaluate immune evasion mechanisms and optimize biomarker identification across cohorts.

Scientific Applications:

• ICB response prediction: Models and predicts responses to anti-PD1 and anti-CTLA4 therapies using integrated omics and functional genomic data.
• Validation and scope: Validated across multiple melanoma datasets and a limited non-small cell lung cancer (NSCLC) dataset, with reported limitations for glioblastoma, renal cell carcinoma, and therapies beyond anti-PD1 and anti-CTLA4.

Methodology:

Integrates large-scale omics datasets from published ICB trials and non-immunotherapy tumor profiles (33,000+ samples, 188 tumor cohorts, 998 tumors from 12 ICB studies) together with eight CRISPR screens and ICB biomarkers to evaluate immune evasion mechanisms and optimize biomarker identification.