Exome analysis reveals genomic markers associated with better efficacy of Nivolumab in lung cancer patients
Corentin Richard1, Jean David Fumet1, Caroline Truntzer1, Sandy Chevrier1, Francois Ghiringhelli1, Romain Boidot1 1CentreGeorges-François Leclerc, Dijon, France Hypothesis: Anti PD-1 are approved for non-small cell lung cancer after failure of first line chemotherapy. However, only a quarter of patients benefits from this therapy. Methods: We studied 81 lung cancer patients treated in second or third line by Nivolumab in which we performed somatic and constitutional exome analysis. Using bioinformatics analysis, we studied either tumor related characteristics (chromosomal instability, aneuploidy, tumor clonality, mutational signature, tumor mutation burden per coding MB, neoepitope, activation of WNT, AKT, and MAPK pathways, mutations in DNA repair pathways) or immunological characteristics (frequency of intratumoral T cell clones, antigen presentation and Type I IFN mutation pathways). Results: We examined a total of 85 variables, including 9 clinical parameters and 76 parameters derived from exome analyses. High non-synonymous mutational tumor burden per coding MB, high level of neoepitopes, presence of mutational signatures 1A and 1B from Alexandrov et al., mutations in DNA repair pathways and presence of a low number of T cell clones are associated with better OS and PFS. Using a stepwise algorithm and BIC criterion, we selected 10 exome parameters in addition to 6 clinical variables that are associated with PFS and OS. In fact, the composite biological variable constructed with these selected variables was strongly associated with PFS and could discriminate patients with good or poor PFS (median PFS of 1.8 months versus 6.0 months p=2.83e-5) with an AUC of 0.967 (specificity of 100% and sensibility of 89%). This composite variable is currently being validated on two other cohorts of 37 patients treated with pembrolizumab, and 15 patients treated with nivolumab. Conclusions: This work underlines the capacity of exome analysis to provide the most accurate prediction of survival under anti-PD1 therapy in lung cancer patients.
Credits: None available.
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