Pan-cancer landscape of T-cell exhaustion heterogeneity within the tumor microenvironment revealed a progressive roadmap of hierarchical dysfunction associated with prognosis and therapeutic efficacy

Abstract

BACKGROUND: T cells form the major component of anti-tumor immunity. A deeper understanding of T cell exhaustion (TEX) heterogeneity within the tumor microenvironment (TME) is key to overcoming TEX and improving checkpoint blockade immunotherapies in the clinical setting. METHODS: We conducted a comprehensive pan-cancer analysis of TEX subsets from 9564 tumor samples across 30 bulk solid cancer types. Pan-cancer TEX subtypes were identified using literature-derived hierarchical TEX-specific developmental pathway signatures. The potential multi-omics and clinical features involved in TEX heterogeneity were determined. FINDINGS: Our study yielded a dynamic, progressive roadmap and a hierarchical dysfunction landscape regarding TEX within the TME. In total, we identified five pan-cancer TEX subtypes, revealing tissue/cancer type-specific TEX patterns in low immunogenic tumors. By contrast, highly immunogenic tumors tend to harbor high frequencies of progenitor TEX subsets. In addition, the TEX profile also revealed distinct prognoses, intrinsic molecular subtype distribution, immune microenvironment and multi-omics features among the cancers. Network analysis identified four previously unknown TEX-associated cancer genes (tolloid-like 1, myosin heavy chain 111, P2Y receptor family member 8 and protein kinase D2), the possible association with anti-PD-1 immunotherapy response was validated using a single-cell dataset. Finally, a machine learning-based gene signature was developed to model the hierarchical TEX stages, verified in single-cell and immunotherapy patient cohorts. INTERPRETATION: Our study provided a TEX-derived system that can be applied for the immune subtyping of cancers and may have implications for the further optimization of personalized cancer immunotherapy. FUNDING: This study was supported by the National Natural Science Foundation of China (Grant No. 62072341 and 61973240). The funders had no roles in study design, data collection and analysis, decision to publish, or preparation of the manuscript.