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PURPOSE: Immune checkpoint inhibition (ICI) shows benefits in adjuvant (AT) and neoadjuvant (NAT) melanoma treatments. However, ICI frequently induces severe immune-related adverse events (irAEs). Unlike metastatic disease, where irAEs are a clinical trade-off for treatment that improves survival, the toxicity burden from ICI in AT is a substantial clinical problem urging for irAE-predictive biomarkers. EXPERIMENTAL DESIGN: We assessed post-surgical, pre-ICI treatment peripheral CD4+ and CD8+ T cells from clinical trial patients (CheckMate-915) treated with AT nivolumab (NIVO, n=130) or ipilimumab/nivolumab (COMBO, n=82). Performing RNA-seq differential gene expression analysis we tested baseline differences associated with severe (grade 3-5) irAEs and constructed an irAE-predictive model using LASSO-regularized logistic regression. RESULTS: The analysis of predicted protein-protein interactions among differentially expressed genes (DEGs) in peripheral CD4+ cells revealed significant enrichment of the spleen tyrosine kinase (SYK) pathway, associated with severe irAEs in COMBO-treated patients. This gene-expression signature predicted severe-irAE COMBO patients (chi-square p-value=0.001) with 73% accuracy and was independent of disease recurrence (p=0.79). The irAE-predictive model incorporating this gene-expression signature demonstrated 82% accuracy (chi-square p-value=8.91E-06). CONCLUSIONS: We identified baseline gene-expression differences in key immune pathways of peripheral blood T cells from COMBO-treated patients with grade 3-5 irAEs, and defined a SYK-related gene signature correctly identifying ~60% of COMBO-treated patients with grade 3-5 irAE. This finding aligns with our previous work linking anti-CTLA-4 irAEs with a germline variant associated with high SYK expression. This gene signature may serve as a baseline biomarker of severe grade 3-5 irAE risk, which is especially important in AT.
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Background: The high mortality of cutaneous melanoma (CM) is partly due to unpredictable patterns of disease progression in patients with early-stage lesions. The reliable prediction of advanced disease risk from early-stage CM, is an urgent clinical need, especially given the recent expansion of immune checkpoint inhibitor therapy to the adjuvant setting. In our study, we comprehensively investigated the role of germline variants as CM prognostic markers. Methods: We performed a genome-wide association analysis in two independent cohorts of N=551 (discovery), and N=550 (validation) early-stage immunotherapy-naïve melanoma patients. A multivariable Cox proportional hazard regression model was used to identify associations with overall survival in the discovery group, followed by a validation analysis. Transcriptomic profiling and survival analysis were used to elucidate the biological relevance of candidate genes associated with CM progression. Results: We found two independent associations of germline variants with melanoma prognosis. The alternate alleles of these two SNPs were both associated with an increased risk of death [rs60970102 in MELK: HR=3.14 (2.05-4.81), p=1.48×10-7; and rs77480547 in SH3BP4: HR=3.02 (2.02-4.52), p=7.58×10-8, both in the pooled cohort]. The addition of the combined risk alleles (CRA) of the identified variants into the prognostic model improved the predictive power, as opposed to a model of clinical covariates alone. Conclusions: Our study provides suggestive evidence of novel melanoma germline prognostic markers, implicating two candidate genes: an oncogene MELK and a tumor suppressor SH3BP4, both previously suggested to affect CM progression. Pending further validation, these findings suggest that the genetic factors may improve the prognostic stratification of high-risk early-stage CM patients, and propose putative biological insights for potential therapeutic investigation of these targets to prevent aggressive outcome from early-stage melanoma.