Whole-genome landscape of mucosal melanoma reveals diverse drivers and therapeutic targets

Knowledge of key drivers and therapeutic targets in mucosal melanoma is limited due to the paucity of comprehensive mutation data on this rare tumor type. To better understand the genomic landscape of mucosal melanoma, here we describe whole genome sequencing analysis of 67 tumors and validation of driver gene mutations by exome sequencing of 45 tumors. Tumors have a low point mutation burden and high numbers of structural variants, including recurrent structural rearrangements targeting TERT, CDK4 and MDM2. Significantly mutated genes are NRAS, BRAF, NF1, KIT, SF3B1, TP53, SPRED1, ATRX, HLA-A and CHD8. SF3B1 mutations occur more commonly in female genital and anorectal melanomas and CTNNB1 mutations implicate a role for WNT signaling defects in the genesis of some mucosal melanomas. TERT aberrations and ATRX mutations are associated with alterations in telomere length. Mutation profiles of the majority of mucosal melanomas suggest potential susceptibility to CDK4/6 and/or MEK inhibitors.

1. Despite the significantly larger sample size analysed in this manuscript, all the recurrently mutated genes and driver oncogenes, structural variants and rearrangements for mucosal melanoma were previously reported by the same authors (Hayward, et al. Nature 2017). Several other findings were also previously reported by Furney, et al. Journal of Pathology, 2013. It seems a larger sample size was still not sufficient to identify any new driver gene.
2. The discussion contains several hypotheses based on the presented genomic landscape of mucosal melanoma, however, these seem a bit superficial. For example, based on mutation profile, the authors suggest a potential susceptibility of mucosal melanoma to CDK4/6 inhibitors alone or in combination with MEK inhibitors or immunotherapy. The authors should provide experimental evidence for these therapy regimens.
3. The manuscript would be significantly improved if, in addition to the descriptions of the mutational profiles, these could be studied for their clinical/prognostic implications. Fig 3a and 3c suggest mucosal melanoma at nasal site doesn't have any BRAF mutation. Authors have not discussed such findings. Also, authors should perform a detailed investigation on whether different genetic background (Chinese vs Caucasian) has any impact on the genomic landscape of mucosal melanoma.

Reviewer #2 (Remarks to the Author):
This is an extension of a previous analysis of mucosal melanomas from some of the same authors, with a larger sample size that provided the opportunity to explore differences by body sites and other features. Although still a small study, and not original, it is the largest to date, given the rarity of this tumor subtype, and would be of interest to the melanoma and cancer research community.
I have several comments or questions. The abstract is misleading. Only 67 melanomas underwent whole genome sequencing and provided estimates of mutations, telomere length, copy number alterations and structural variants. The remaining 45 FFPE samples underwent whole exome sequencing and were used only as a validation for driver gene mutations.
Based on the data in Supplemental Table 1, only 28 tissue samples were primary melanomas, the remaining were recurrences, lymph nodes metastases or had unknown status. This is important and needs to be stated, because the mutations and structural variants identified may reflect the clones that allowed cell migration to other sites but not the full characteristics of the primary tumors. And the mutational signature analysis could also be different in primary vs. metastatic samples. An analysis stratifying the main results between primary and metastatic/recurrence sites would be important. For example, mutations/loss in BAP1 or ATRX have been associated with increased risk of metastasis across different cancer types. Were the samples carrying these mutations metastatic/recurrent mucosal melanomas?
It is known that sample purity based on histological assessment often poorly reflect the actual tumor content. What was the sample purity based on copy number alterations (and variant allele fraction in the case of copy neutral samples)? Apparent lack of specific driver mutations or other changes may be due to low sample purity. This is particularly important for the primary melanomas, which are likely to be very small and the samples may be contaminated by the surrounding tissue The finding of UV-related signature 7 in 6 samples is intriguing. Are these primary melanoma samples? I am wondering whether these melanomas that could have been driven by the accumulation of UV-related mutations show different patterns of driver genes or structural variants in comparison to the other mucosal melanomas. Can a description of these 6 vs the other samples be reported? This could suggest different patterns of tumor initiation between the two groups.
Still related to mutational signatures: the contribution of signature 1 was significantly more prevalent in melanoma from lower body sites than upper body sites. What was the estimated power to distinguish signatures based on the sample size of upper and lower body sites? What were the mutational signatures in the FFPE samples? What were the 'normal', reference samples for the FFPE tumor tissue?
Whole genome sequencing was carried out in three different centers. More details are needed to ascertain that the approaches, e.g., filtering process for mutation calling, were consistent across the centers.
Was the telomere length analysis adjusted for age? Also, the associations between TERT mutations and short telomeres, and ATRX mutations with longer telomere have already been reported and investigated in detail across multiple cancer types (Barthel, Nature Genetics 2017), thus they may not need to be reported in the abstract.
Except for four samples, all melanomas included in the WGS analysis were from China and Australia. Is there any difference between these melanomas arising from subjects with different pigmentation background (besides the body site distribution)?
The ascertainment of structural variants is known to be challenging as spurious rearrangements are common. Can at least a percentage of the SVs be validated in the lab? "Some evidence" of chromotripsis is reported. What was the evidence based on? As the analysis of chromotripsis in PCAWG shows (reported in BioRxiv), there are specific criteria and tests to define chromotripsis.
SPRED1 and NF1 were reported as almost mutually exclusive, since 11/13 mutations in SPRED1 were in NF wild type tumors. However, SPRED1 mutations were identified in 6 (based on WGS) and 1 (based on WES) tumors only. How many of these were NF1 wild type?