Gender and melanoma subtype-based prognostic implications of MUC16 and TTN co-occurrent mutations in melanoma: A retrospective multi-study analysis.

Background: Most primary cutaneous melanomas have pathogenesis driven by ultraviolet exposure and genetic mutations, whereas acral lentiginous melanoma (ALM) and metastatic melanoma are much less, if at all, linked with the former. Thus, we evaluated both ultraviolet related and non-ultraviolet related melanomas. Mutations in the MUC16 and TTN genes commonly occur concurrently in these melanoma patients, but their combined prognostic significance stratified by gender and cancer subtype remains unclear.

Methods: The cBioPortal database was queried for melanoma studies and returned 16 independent studies. Data from 2447 melanoma patients were utilized including those with ALM, cutaneous melanoma (CM), and melanoma of unknown primary (MUP). Patients were grouped based on the presence or absence of MUC16 and TTN mutations. Univariate Cox regression and Student's t-tests were used to analyze hazard ratios and total mutation count comparisons, respectively.

Results: TTN mutations, either alone or concurrently with MUC16 mutations, significantly correlated with worse prognosis overall, in both genders, and in CM patients. ALM patients with both mutations had better prognoses than CM patients, while ALM patients with neither mutation had worse prognosis than CM patients. For MUP patients, only MUC16 mutations correlated with worse prognosis. ALM patients with neither MUC16 nor TTN mutations had significantly more total mutations than MUP patients, followed by CM patients.

Conclusion: TTN mutations are a potential marker of poor prognosis in melanoma, which is amplified in the presence of concurrent MUC16 mutations. ALM patients with neither gene mutations had worse prognosis, suggesting a protective effect of having both MUC16 and TTN mutations. Only MUC16 mutations conferred a worse prognosis for MUP patients. Comprehensive genetic profiling in melanoma patients may facilitate personalized treatment strategies to optimize patient outcomes.