ArticleFrontiers in immunology2026
Systematic evaluation of MAIT and iNKT abundance as checkpoint blockade biomarkers.
Article in Frontiers in immunology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Introduction: MAIT and iNKT cells are unconventional T cell lineages that bridge innate and adaptive immunity and have been implicated in antitumor immune responses and immunotherapy outcomes. However, evidence to date has largely derived from individual studies of selected cancer types or specialized immune profiling cohorts. Whether MAIT and iNKT abundance provides reproducible clinical information across large, multi-cancer immune checkpoint blockade (ICB) cohorts remains insufficiently evaluated. Methods: We applied an AI-based TCRβ inference framework to estimate MAIT and iNKT relative abundance from bulk TCRβ repertoires in healthy controls, patients with cancer, and ICB-treated cohorts. The main dataset included 1,619 samples from 420 healthy controls and 595 patients across 13 cancer types; response analyses used a discovery cohort of 964 samples from 436 patients across 9 cancer types and an independent validation cohort of 361 samples from 81 patients across 5 cancer types. Results: TCRβ-inferred estimates showed that both MAIT and iNKT abundance were reduced in pretreatment cancer PBMCs compared with healthy controls, supporting systemic perturbation of unconventional T cells in cancer. Abundance estimates were also tissue dependent, with MAIT showing lower inferred abundance in tumor biopsies than in PBMCs. In ICB cohorts, baseline MAIT and iNKT estimates in PBMCs or tumors were insufficient to distinguish responders from non-responders. Although on-treatment tumor iNKT estimates showed a modest enrichment in responders in the discovery cohort, this pattern had limited standalone predictive value and was not reproduced as a robust biomarker in validation. Discusson: These findings indicate that MAIT/iNKT abundance captures cancer-associated and tissue dependent immune variation but has limited value alone for predicting ICB response, highlighting the need to incorporate functional state, spatial localization, and broader immune context.
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