What question did this study set out to answer?

This research aims to identify biomarkers that correlate with treatment response in patients receiving PD-(L)1 immunotherapy.

May 29, 2026

T-cell stem-like memory cells as a novel biomarker to identify patients with sustained disease control during treatment with PD-(L)1 immunotherapy.

Key Points

This research aims to identify biomarkers that correlate with treatment response in patients receiving PD-(L)1 immunotherapy.
Analyzed peripheral blood from 151 metastatic patients receiving various PD-(L)1 therapies.
Evaluated CD4 and CD8 T-cell populations using multiparameter flow cytometry and computed stem-like-to-effector ratios.
Utilized Mann–Whitney U tests and Cox models for analyzing disease control rates and time to disease control loss.
Among 151 patients, 89 achieved disease control while 62 experienced progression.
Disease control linked to higher frequencies of stem-like and naive T-cells (p<0.05) and increased stem-like-to-effector ratios (SCM/CM p<0.001).
Cox models indicated significant associations (HR range 1.7–4.8, all p<0.05) related to T-cell profiles and treatment outcomes.

Abstract

2578 Background: Reliable, clinically easily testable biomarkers to monitor the benefit of treatment with immune checkpoint inhibitors (ICI) remain limited. We performed comprehensive analysis of markers defining differentiation and functional status of different populations of peripheral blood T-cell in order to identify biomarkers associates to treatment response in treated patients. Methods: Peripheral blood was analyzed from metastatic patients receiving PD-(L)1–based therapy: anti–PD-(L)1 monotherapy (n=102), combination therapies (n=35), or chemo-immunotherapy (n=14). Sampling time on therapy was heterogeneous, recorded, and included in sensitivity analyses. All patients provided informed consent under IRB approval. A variety of CD4 andCD8 cell populations (naive, stem-like memory SCM, central memory CM, effector memory EM, EMRA/TEMRA). were analyzed using -standardized multiparameter flow cytometry. Pre-specified stem-like–to–effector balance ratios were computed within CD4 and CD8 (SCM/CM and SCM/EM; SCM/EMRA exploratory). Markers analysis included CD45RA, CCR7, CD95, TCF1/TCF7, TOX, TIGIT, and Ki-67). Clinical benefit was assessed by disease control rate (DCR=CR+PR+SD) versus progressive disease ( PD). Biomarkers were analyzed using Mann–Whitney U tests and clustered using unsupervised 1D k-means. Time-to-event analyses used univariable Cox models for time to disease control loss (DCL), defined from ICI initiation to first PD (or discontinuation for progression). Results: Among 151 patients, DCR n=89 and PD n=62, disease control was characterized by a stem-like/early memory blood T-cell profile. DCR showed higher CD4 and CD8 naive and SCM frequencies (p1 favorable), significant associations were observed across subsets, ratio, and marker features (HR range 1.7–4.8; all p<0.05), with the strongest effects for stem-like–to–effector cell ratios and differentiated subset metrics. Associations were observed across PD-(L)1–based regimens. Conclusions: Stem-like memory CD4 and CD8 T cells represent a new marker associated with efficacious response to ICI and DCR while a dominant effector/terminal differentiation profile to DCL and PD. These findings underscore the importance of immune monitoring to identify patients at risk of early loss of treatment benefit and disease progression and to guide treatment modifications.

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