GZMK expression within activated intratumoral T-cell subsets reflects differentiation efficiency and predicts response to cancer immunotherapy

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Authors: Cem M. Sievers, Tiangen Chang, Yvette L. Robbins, Jay Friedman, Marco Craveiro, Xinping Yang, Christopher J. Silvin, Jason M. Redman, Patrick Soon‐Shiong, Wiem Lassoued, Martha Quezado, Wojciech Mydlarz
+5 more Nancy P. Judd, Jeffrey Schlom, James Gulley, Eytan Ruppin, Clint T. Allen
Cited by: 1
References: 68

Abstract

Abstract Neoadjuvant immunotherapies (NITs) have demonstrated clinical benefit in head and neck carcinoma and other cancers by enhancing T cell-mediated anti-tumor immunity. However, disease recurrence remains a major challenge in a significant proportion of patients. Characterization of T cell dynamics underlying NIT outcomes may lead to improved treatment strategies. Here, we identify baseline intratumoral T cell differentiation efficiency as a predictor of response to NIT. Clonal analysis of tumor-emergent T cells post-treatment revealed granzyme K ( GZMK) expression within differentiated subsets as a marker of recent differentiation. Efficient pre-treatment differentiation of GZMK + progenitor T cells toward activated effectors predicts increased treatment-induced tumor regression. Consistently, pre-treatment tumor-infiltrating T cell clones predominantly adopt either exhausted, tissue-resident memory-like, or peripherally enriched GZMK + progenitor states, implicating impaired intratumoral differentiation in limited anti-tumor immunity at baseline. Together, our findings demonstrate that GZMK + T cell profiles reflect baseline anti-tumor immunocompetence and offer a clinically actionable biomarker for predicting immunotherapy response. NCT04247282, ClinicalTrails.gov, registered 1/30/2020 and NCT03429036, ClinicalTrails.gov, registered 11/06/2020.

Fields of Study & Subjects

Cancer Immunotherapy and Biomarkers CAR-T cell therapy research Immunotherapy and Immune Responses

Publication details

Journal / source
npj Precision Oncology
Publisher
Springer Science and Business Media LLC
Volume
10
Issue
1
Publication date
18 April 2026
Language
EN