Tumor γδ T-cell abundance is associated with favorable cancer treatment outcomes

Authors

Niu, X., Kundnani, D. L., Dicome, M., Tafoya, L., Song, L., Mamedov, M., Liu, X. S., Sahu, A. D.

Abstract

Purpose: Clinical response to immune checkpoint blockade (ICB) remains variable. We asked whether immune-cell populations in the tumor microenvironment (TME) are associated with benefit across treatments and tumor types. Experimental Design: We analyzed pretreatment bulk tumor RNA-seq from ICB cohorts and TCGA. Gene-level effects associated with ICB response or TCGA survival were projected onto Human Primary Cell Atlas profiles of 157 cell types. Cox and mixed-effects models accounted for cancer type, cohort, and therapy, as appropriate. After {gamma}{delta} T cells emerged as a leading population, we adjusted their associations for eight CD8 estimators and evaluated them using TRUST4-based TRG/TRD reconstruction and single-cell RNA-seq. Results: {gamma}{delta} T-cell programs were among the signatures consistently associated with ICB response and favorable TCGA survival. Across ICB cohorts, {gamma}{delta} T-cell abundance was associated with response (n=1,356; OR, 1.38; 95% CI, 1.23-1.56) and overall survival (n=1,074; HR, 0.82; 95% CI, 0.76-0.88), with associations persisting after CD8 adjustment. ICB-response-associated cell-type profiles were strongly concordant with chemotherapy response (r=0.92) and moderately concordant with radiation response (r=0.58); targeted and hormone therapy analyses were underpowered. TRUST4 reconstruction and single-cell RNA-seq provided orthogonal support for the {gamma}{delta} signal. Conclusions: Pretreatment {gamma}{delta} T-cell abundance was associated with favorable ICB outcomes and survival across cancers, while related cell-type programs extended to selected non-immunotherapy response settings. Although associative and context dependent, these findings support prospective evaluation of {gamma}{delta} T-cell abundance as a candidate tumor-immune biomarker.

Preprint server: bioRxiv
The authors list and abstract were imported from bioRxiv on 02 Sep 2026.

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