Unveiling the molecular landscape and clinically relevant molecular heterogeneity of mucosal melanoma of the head and neck region.

AIMS

Mucosal melanoma of the head and neck (MM-H&N) is an aggressive disease known for its frequent residual tumours/relapses (RT/R) at the surgical site, as well as eventual metastases. Our understanding of the MM-H&N mutational landscape, together with the correlation of specific mutations with clinical-pathological features, is significantly less comprehensive compared to that of cutaneous melanoma. Additionally, the mutational status of consecutive samples collected from single patients has not been investigated, which limits our ability to characterise the prognosis and treatment options for this patient subset.

METHODS AND RESULTS

A total of 53 MM-H&N specimens from 27 patients were analysed using a laboratory-developed multigene next-generation sequencing (NGS) panel. Among these, material from 46 of 53 (86.8%) samples and from 25 of 27 patients (92.6%) was suitable for NGS. The most frequently detected mutations were found in the RAS genes family, specifically KRAS and NRAS (seven of 46, 15.2%), as well as TP53, KIT and BRAF (each in three of 46, 6.5%); 25 of 46 (54.3%) samples exhibited a wild-type (WT) status. A statistically significant association between BRAF/RAS mutations and mucosal lentiginous histology (P = 0.041) was observed. Additionally, four of 11 (36.4%) patients with consecutive specimens, with no pre-/intersurgery systemic therapies administered and all having at least two evaluable NGS results, demonstrated molecular heterogeneity in the analysed samples.

CONCLUSIONS

MM-H&N shows a significant percentage of WT cases and a limited number of targetable mutations, predominantly involving BRAF/RAS mutations, the latter of which are associated with mucosal lentiginous histology. A subset of patients with consecutive samples demonstrates discordant molecular results, indicating that NGS of all samples may be necessary to determine the most appropriate therapeutic approach.