A minimal gene set characterizes TIL specific for diverse tumor antigens across different cancer types

Area of Science:

• Immunology
• Oncology
• Bioinformatics

Background:

• Identifying tumor-specific T cells that drive immunotherapy responses is difficult.
• Mutation-associated neoantigen (MANA)-specific CD8+ tumor-infiltrating lymphocytes (TIL) show specific gene expression patterns (high CXCL13, CD39; low IL7R), but their functional role is unclear.

Purpose of the Study:

• To develop and validate an integrative tool to identify MANA-specific TIL.
• To assess the collective relevance of specific gene expression markers to T cell functionality in cancer.

Main Methods:

• Developed a "MANAscore" algorithm using weighted expression of CXCL13, CD39, and IL7R.
• Applied the algorithm to single-cell RNAseq data from lung cancer and melanoma.
• Validated the algorithm's performance against known neoantigen-specific CD8+ clones and other tumor antigen-specific TIL.

Main Results:

• The MANAscore algorithm accurately identifies validated neoantigen-specific CD8+ clones and TIL recognizing other tumor antigens.
• MANAscore identified TIL with a tissue-resident memory gene expression program.
• In anti-PD-1 treated lung tumors, MANAscore-identified putative tumor-reactive cells (pTRC) exhibited higher checkpoint and cytotoxicity gene expression.

Conclusions:

• MANAscore is a robust tool for enriching candidate tumor-specific T cells.
• The algorithm aids in understanding the functional programming of tumor-reactive TIL.
• MANAscore can identify TIL with distinct gene expression patterns in responding tumors, offering insights into immunotherapy efficacy.