Genomic Profiling of Extensive Stage Small-Cell Lung Cancer Patients Identifies Molecular Factors Associated with Survival.

Abstract

Objective: Extensive stage Small-Cell Lung Cancer (ES-SCLC) is the most lethal lung cancer, and the addition of immunotherapy conferred a slight survival benefit for patients. Extensive molecular profiling of patients treated with chemotherapy (CT) or chemotherapy plus immunotherapy (CT+IO) would be able to identify molecular factors associated with patients' survival.

Material and methods: In this retrospective study, 99 ES-SCLC patients were considered. Of the 79 includible patients, 42 received CT (median age 71 y/o, I-IIIQ: 65-76), and 37 received CT+IO (median age 71 y/o, I-IIIQ 66-75). The FoundationOne CDx assay was performed on patients' tumor tissues.

Results: The most mutated genes were TP53 (99%), RB1 (78%), PTEN (23%) and MLL2 (20%), with no significant differences between the treatment groups. As a continuous variable, Tumor Mutation Burden (TMB) had an effect on patients' progression-free survival (PFS) by type of treatment (HR 1.81 (95%, CI: 0.99-3.31) and HR 0.84 (95%, CI: 0.56-1.26) for patients treated with CT and CT+IO, respectively). TMB was also computed and dichotomized using two different cut-offs: considering cut-offs of 10 mut/Mb and >16 mut/Mb, 45 patients (57%) and 68 patients (86.1%) had a low TMB, respectively. A high TMB (cut-off 10 mut/Mb) predicted worse PFS in patients treated with CT (p=0.046); even though not statistically significant, a high TMB (cut-off 16 mut/Mb) predicted a better survival in patients treated with CT+IO. Moreover, at univariate analysis, MLL2 mutations were associated with better prognosis in the overall case series (HR_PFS = 0.51, 95% CI: 0.28-0.94), and overall survival (HR_OS = 0.52, 95% CI: 0.28-0.97).

Conclusion: In ES-SCLC, TMB is associated with worse survival in patients treated with CT alone, and with better survival in patients treated with CT+IO, whether considered as a continuous or a dichotomized variable, at different cut-offs. Alterations in epigenetic factors are also associated to better patient prognosis.