Deciphering immune predictors of immunotherapy response: A multiomics approach at the pan-cancer level.
basic_science · Level V
Where this comes from
- Record sourced from PubMed, PMID 40054456.
- Also identified by DOI 10.1016/j.xcrm.2025.101992 and PMC identifier 12047473.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
Abstract
Immune checkpoint blockade (ICB) therapy has transformed cancer treatment, yet many patients fail to respond. Employing single-cell multiomics, we unveil T cell dynamics influencing ICB response across 480 pan-cancer and 27 normal tissue samples. We identify four immunotherapy response-associated T cells (IRATs) linked to responsiveness or resistance and analyze their pseudotemporal patterns, regulatory mechanisms, and T cell receptor clonal expansion profiles specific to each response. Notably, transforming growth factor β1 (TGF-β1)+ CD4<sup>+</sup> and Temra CD8<sup>+</sup> T cells negatively correlate with therapy response, in stark contrast to the positive response associated with CXCL13+ CD4<sup>+</sup> and CD8<sup>+</sup> T cells. Validation with a cohort of 23 colorectal cancer (CRC) samples confirms the significant impact of TGF-β1+ CD4<sup>+</sup> and CXCL13+ CD4<sup>+</sup> and CD8<sup>+</sup> T cells on ICB efficacy. Our study highlights the effectiveness of single-cell multiomics in pinpointing immune markers predictive of immunotherapy outcomes, providing an important resource for crafting targeted immunotherapies for successful ICB treatment across cancers.
Medical subject headings
- Immunotherapy
- Neoplasms