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. KRAS 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.
IntroductionNon-small-cell lung cancer (NSCLC) is one of the main causes of death by cancer worldwide. With the rise of targeted therapies, the search for molecular abnormalities is becoming a crucial step in the management of lung cancer. Whole exome sequencing (WES) is developing rapidly and is now accessible in routine care. However, its value, compared to smaller gene panels, remains unclear.MethodsWe conducted a retrospective analysis of all 281 patients with lung carcinoma referred to the Molecular Tumor Board of the Georges-François Leclerc Cancer Center (CGFL) between March 2015 and January 2018. We compared the results of standard molecular testing with the results of WES performed on every patient.ResultsWES highlighted many more mutations than smaller panels (mutations were found in 82 genes, while smaller panels found, at the most, mutations in 12 genes). Most of these mutations were class III or IV according to the ESCAT classification. The exome sensitivity also showed limitations, notably a slightly lower efficiency for common mutations, including classical EGFR mutations.ConclusionSmall, targeted panels could be preferred over WES at the initial diagnosis of metastatic NSCLC. They are more sensitive for the identification of mutations on the most frequently mutated genes, such as ALK, BRAF, EGFR, ERBB2, KRAS or MET. Larger panels or WES could be useful at disease progression, to enlarge treatment possibilities by highlighting uncommon but potentially targetable mutations that are not covered by smaller, targeted panels.
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