Abstract
9567 Background: Recently, tumor mutation burden (TMB) has been shown to increase the presentation of neoantigens that stimulate immune tumor recognition, resulting in improved immunotherapy (IT) outcomes in melanoma and other cancers. As melanoma is highly immunogenic, here we tested whether TMB associates with immune recognition during tumor progression, hence impacting melanoma overall survival (OS), independently of IT treatment. Methods: We have generated somatic mutation data from 314 IT-naive metastatic melanomas from The Cancer Genome Atlas (TCGA). In the TCGA cohort, TMB has been calculated for 210 genes (200GS) previously established from TMB studies of anti-CTLA4 and anti-PD1/PD-L1 IT. For validation, we have sequenced exonic regions of 20 genes (20GS) with the highest TMB among 200GS in 89 IT-naive metastatic melanomas ascertained at New York University Langone Medical Center. The TMB was defined using total number of somatic, non-synonymous mutations in either 200GS (TCGA discovery) or 20GS (validation), respectively. For discovery and validation cohorts, OS from primary diagnosis of samples with high TMB was compared against low TMB, using thresholds established in previous studies. Results: We found that total TMB predicts better OS (p = 0.03, HR = 2.64) in TCGA melanomas. Restricting the analysis only to the established 200GS, this association became more significant in all patients (p = 0.01, HR = 2.67) as well as in patients without IT (p = 0.01, HR = 2.67). In the validation stage of 89 melanomas without prior IT treatment, a high TMB in a subset of 20GS accurately determined favorable OS (p = 0.02, HR = 2.69) and confirmed TCGA observations from the 200GS. Conclusions: Here we show, for the first time, that in addition to IT, high TMB predicts more favorable OS in patients that never received IT, potentially serving as a novel marker of prognosis of melanoma and likely other immunogenic tumors at early stages. In addition, our study suggests that TMB test can be robust when applied to only a small subset of genes that trigger significantly higher immunogenicity. This may also eventually assist with accurate sub-selection of early stage patients likely to respond to IT regimens.
Published Version
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