The response to anti–PD-1 and anti–LAG-3 checkpoint blockade is associated with regulatory T cell reprogramming

Immune checkpoint blockade (ICB) has revolutionized cancer treatment; however, many patients develop therapeutic resistance. We previously identified and validated a pretreatment peripheral blood biomarker, characterized by a high frequency of LAG-3<sup>+</sup> lymphocytes, that predicts resistance in patients receiving anti-PD-1 (aPD-1) ICB. To better understand the mechanism of aPD-1 resistance, we identified murine tumor models with a high LAG-3<sup>+</sup> lymphocyte frequency (LAG-3<sup>hi</sup>), which were resistant to aPD-1 therapy, and LAG-3<sup>lo</sup> murine tumor models that were aPD-1 sensitive, recapitulating the predictive biomarker we previously described in patients. LAG-3<sup>hi</sup> tumor-bearing mice were sensitive to aPD-1 + anti-LAG-3 (aLAG-3) therapy, and this benefit was CD8<sup>+</sup> T cell dependent. The efficacy of combination therapy was enhanced in LAG-3<sup>hi</sup> (but not LAG-3<sup>lo</sup>) mice with depletion of CD4<sup>+</sup> T cells. Furthermore, responses to aPD-1 + aLAG-3 correlated with regulatory T cell (T<sub>reg</sub>) phenotypic plasticity in LAG-3<sup>hi</sup> mice, suggesting a specific role for T<sub>regs</sub> in response to aPD-1 + aLAG-3 treatment. Using T<sub>reg</sub> fate-tracking <i>Foxp3<sup>GFP-Cre-ERT2</sup></i> × ROSA<sup>YFP</sup> reporter mice, we demonstrated that expanded populations of unstable T<sub>regs</sub> correlated with improved response to combination therapy in LAG-3<sup>hi</sup> mice. Complementing these preclinical data, an increased proportion of unstable T<sub>regs</sub> also correlated with higher response rate and improved survival after aPD-1 + aLAG-3 therapy in a cohort of patients with metastatic melanoma (<i>n</i> = 117). These data indicate that T<sub>reg</sub> phenotypic plasticity affects aPD-1 + aLAG-3 responsiveness, which may represent a biomarker to aid patient selection and a rational therapeutic target for a subset of PD-1-refractory patients.

Authors

Institutions

Publication Details

Journal
Science Translational Medicine
Published
2025-04-09
DOI
https://doi.org/10.1126/scitranslmed.adk3702
Citations
10
Primary Topic
Cancer Immunotherapy and Biomarkers
Type
article
Field-Weighted Citation Impact
10.45
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The response to anti–PD-1 and anti–LAG-3 checkpoint blockade is associated with regulatory T cell reprogramming

Melissa J. Kasiewicz, William L. Redmond, Jasme Lee, Grace Helen McGee et al.
10 citations
Science Translational Medicine
Cancer Immunotherapy and Biomarkers
10.45
article

The response to anti–PD-1 and anti–LAG-3 checkpoint blockade is associated with regulatory T cell reprogramming

Melissa J. Kasiewicz, William L. Redmond, Jasme Lee, Grace Helen McGee, Margaret K. Callahan, Annah S. Rolig, Johanna K. Kaufmann, Niranjan Yanamandra, James Smothers, Elizabeth R. Sturgill, Xiyu Peng, Ronglai Shen, William L. Miller, Matthew Adamow, Nisha Holay, Sue Griffin, Yoshinobu Koguchi, Courtney Mick
article en
10 citations

Abstract

Immune checkpoint blockade (ICB) has revolutionized cancer treatment; however, many patients develop therapeutic resistance. We previously identified and validated a pretreatment peripheral blood biomarker, characterized by a high frequency of LAG-3<sup>+</sup> lymphocytes, that predicts resistance in patients receiving anti-PD-1 (aPD-1) ICB. To better understand the mechanism of aPD-1 resistance, we identified murine tumor models with a high LAG-3<sup>+</sup> lymphocyte frequency (LAG-3<sup>hi</sup>), which were resistant to aPD-1 therapy, and LAG-3<sup>lo</sup> murine tumor models that were aPD-1 sensitive, recapitulating the predictive biomarker we previously described in patients. LAG-3<sup>hi</sup> tumor-bearing mice were sensitive to aPD-1 + anti-LAG-3 (aLAG-3) therapy, and this benefit was CD8<sup>+</sup> T cell dependent. The efficacy of combination therapy was enhanced in LAG-3<sup>hi</sup> (but not LAG-3<sup>lo</sup>) mice with depletion of CD4<sup>+</sup> T cells. Furthermore, responses to aPD-1 + aLAG-3 correlated with regulatory T cell (T<sub>reg</sub>) phenotypic plasticity in LAG-3<sup>hi</sup> mice, suggesting a specific role for T<sub>regs</sub> in response to aPD-1 + aLAG-3 treatment. Using T<sub>reg</sub> fate-tracking <i>Foxp3<sup>GFP-Cre-ERT2</sup></i> × ROSA<sup>YFP</sup> reporter mice, we demonstrated that expanded populations of unstable T<sub>regs</sub> correlated with improved response to combination therapy in LAG-3<sup>hi</sup> mice. Complementing these preclinical data, an increased proportion of unstable T<sub>regs</sub> also correlated with higher response rate and improved survival after aPD-1 + aLAG-3 therapy in a cohort of patients with metastatic melanoma (<i>n</i> = 117). These data indicate that T<sub>reg</sub> phenotypic plasticity affects aPD-1 + aLAG-3 responsiveness, which may represent a biomarker to aid patient selection and a rational therapeutic target for a subset of PD-1-refractory patients.

Science Translational MedicineVol. 17(793)
Biogen (United States) (US), Memorial Sloan Kettering Cancer Center (US), University of Connecticut (US), Providence Portland Medical Center (US), GlaxoSmithKline (United States) (US)
Good health and well-being
Openalex Percentile: Top 2%
Cancer Immunotherapy and Biomarkers
10.45
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.