A Pan-Cancer Comparative Analysis of The Cancer Genome Atlas Transcriptomic TIL-Immune Signatures

TL;DR

This study compares immune-related gene signatures across 33 cancer types to identify which ones best predict patient survival and disease progression.

Contribution

The study introduces a pan-cancer analysis of TIL-immune signatures, identifying those with consistent prognostic value across multiple cancer types.

Findings

Zhang CD8 TCS showed the highest accuracy in predicting overall survival and progression-free interval across cancers.

Six immune signatures showed consistent associations with survival and progression across multiple cancer types.

Prognostic performance of signatures varied by cancer type and germ cell origin.

Abstract

Efforts to understand the tumor microenvironment (TME) through basic science research and The Cancer Genome Atlas (TCGA) data analysis have led to the creation of unique immune transcriptomic signatures from tumor-infiltrating lymphocytes (TIL). However, no pan-cancer analysis has been conducted to compare the prognostic performance of these signatures using overall survival (OS) or progression-free interval (PFI) as endpoints. We compiled a library of 146 TIL-immune signatures and evaluated gene signature score correlation with OS and PFI for 9,961 available TCGA samples across 33 cancer types. Zhang CD8 TCS demonstrated higher accuracy in prognosticating both OS and PFI across the pan-cancer landscape, however, variability was seen across cancer types and germ cell origin. Cluster analysis compiled a group of six signatures (Oh.Cd8.MAIT, Grog.8KLRB1, Oh.TIL_CD4.GZMK, Grog.CD4.TCF7, Oh.CD8.RPL, Grog.CD4.RPL32) whose association with OS and PFI could potentially be conserved across multiple cancer types.

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