Exome-Based Genomic Markers Could Improve Prediction of Checkpoint Inhibitor Efficacy Independently of Tumor Type.
Fiche publication
Date publication
avril 2023
Journal
International journal of molecular sciences
Auteurs
Membres identifiés du Cancéropôle Est :
Dr BOIDOT Romain, Pr GHIRINGHELLI François, Mme TRUNTZER Caroline, Dr FAVIER Laure, Dr DERANGERE Valentin
Tous les auteurs :
Dalens L, Lecuelle J, Favier L, Fraisse C, Lagrange A, Kaderbhai C, Boidot R, Chevrier S, Mananet H, Derangère V, Truntzer C, Ghiringhelli F
Lien Pubmed
Résumé
Immune checkpoint inhibitors (ICIs) have improved the care of patients in multiple cancer types. However, PD-L1 status, high Tumor Mutational Burden (TMB), and mismatch repair deficiency are the only validated biomarkers of efficacy for ICIs. These markers remain imperfect, and new predictive markers represent an unmet medical need. Whole-exome sequencing was carried out on 154 metastatic or locally advanced cancers from different tumor types treated by immunotherapy. Clinical and genomic features were investigated using Cox regression models to explore their capacity to predict progression-free survival (PFS). The cohort was split into training and validation sets to assess validity of observations. Two predictive models were estimated using clinical and exome-derived variables, respectively. Stage at diagnosis, surgery before immunotherapy, number of lines before immunotherapy, pleuroperitoneal, bone or lung metastasis, and immune-related toxicity were selected to generate a clinical score. mutations, TMB, TCR clonality, and Shannon entropy were retained to generate an exome-derived score. The addition of the exome-derived score improved the prediction of prognosis compared with the clinical score alone. Exome-derived variables could be used to predict responses to ICI independently of tumor type and might be of value in improving patient selection for ICI therapy.
Mots clés
TCR, TMB, biomarkers, exome sequencing, immunotherapy
Référence
Int J Mol Sci. 2023 04 20;24(8):