Analysis of PD1, LAG3, TIGIT, and TIM3 expression in human lung adenocarcinoma reveals a 25-gene signature predicting immunotherapy response

Immune checkpoint inhibitors (ICIs) have advanced the treatment of non-small cell lung cancer (NSCLC). This study evaluates the predictive value of CD8<sup>+</sup> T cell exhaustion in patients with lung adenocarcinoma treated with ICIs. By analyzing tumor samples from 166 patients through multiplex immunofluorescence, we quantify tumor-infiltrating lymphocytes (TILs) expressing exhaustion markers programmed cell death-1 (PD1), lymphocyte activation gene 3 (LAG3), T cell immunoreceptor with Ig and ITIM domains (TIGIT), and T cell immunoglobulin and mucin domain 3 (TIM3). Their co-expression is associated with ICI resistance, irrespective of programmed cell death ligand-1 (PD-L1) status. We also identify a 25-gene signature indicative of CD8<sup>+</sup> T cell exhaustion with high predictive accuracy for ICI response. Validated using several datasets from various clinical trials, this signature accurately predicts ICI responsiveness. Our findings highlight T cell exhaustion's significance in lung adenocarcinoma responses to ICIs and suggest the 25-gene signature as a potential universal biomarker to reinforce precision medicine. This was registered under Clinical Trial registration number NCT02534649.

Authors

Institutions

Publication Details

Journal
Cell Reports Medicine
Published
2024-11-25
DOI
https://doi.org/10.1016/j.xcrm.2024.101831
Citations
24
Primary Topic
Cancer Immunotherapy and Biomarkers
Type
article
Field-Weighted Citation Impact
6.78

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Analysis of PD1, LAG3, TIGIT, and TIM3 expression in human lung adenocarcinoma reveals a 25-gene signature predicting immunotherapy response

Diego Teyssonneau, Florent Peyraud, Sylvestre Le Moulec, Alban Bessede et al.
24 citations
Cell Reports Medicine
Cancer Immunotherapy and Biomarkers
6.78
article

Analysis of PD1, LAG3, TIGIT, and TIM3 expression in human lung adenocarcinoma reveals a 25-gene signature predicting immunotherapy response

Diego Teyssonneau, Florent Peyraud, Sylvestre Le Moulec, Alban Bessede, Lucile Vanhersecke, Coriolan Lebreton, Bérengère Dadone‐Montaudié, Laïla Belcaid, Jean-Philippe Guégan, Oren Lara, Lola‐Jade Palmieri, Laura Leroy, Thomas Grellety, Maxime Brunet, Guilhem Roubaud, Ikbel Achour, Mathilde Cabart, Christophe Rey, Ezogelin Oflazoglu Gruyters, Ophélie Odin, Emma Clot, Sophie Cousin, Antoine Italiano
article en
24 citations

Abstract

Immune checkpoint inhibitors (ICIs) have advanced the treatment of non-small cell lung cancer (NSCLC). This study evaluates the predictive value of CD8<sup>+</sup> T cell exhaustion in patients with lung adenocarcinoma treated with ICIs. By analyzing tumor samples from 166 patients through multiplex immunofluorescence, we quantify tumor-infiltrating lymphocytes (TILs) expressing exhaustion markers programmed cell death-1 (PD1), lymphocyte activation gene 3 (LAG3), T cell immunoreceptor with Ig and ITIM domains (TIGIT), and T cell immunoglobulin and mucin domain 3 (TIM3). Their co-expression is associated with ICI resistance, irrespective of programmed cell death ligand-1 (PD-L1) status. We also identify a 25-gene signature indicative of CD8<sup>+</sup> T cell exhaustion with high predictive accuracy for ICI response. Validated using several datasets from various clinical trials, this signature accurately predicts ICI responsiveness. Our findings highlight T cell exhaustion's significance in lung adenocarcinoma responses to ICIs and suggest the 25-gene signature as a potential universal biomarker to reinforce precision medicine. This was registered under Clinical Trial registration number NCT02534649.

Cell Reports MedicineVol. 5(12)
University of Copenhagen (DK), Centre Hospitalier Universitaire de Nice (FR), AstraZeneca (Singapore) (SG), Centre Hospitalier de la Côte Basque (FR), AstraZeneca (Switzerland) (CH), Institut Bergonié (FR)
AstraZeneca, Roche, Conseil Régional Aquitaine
Good health and well-being
Openalex Percentile: Top 2%
Cancer Immunotherapy and Biomarkers
6.78
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.