Background: Mucosal and acral melanoma respond worse to immune checkpoint inhibitors (ICI) than cutaneous melanoma. MDM2/4 as well as EGFR amplifications are supposed to be associated with hyperprogression on ICI in diverse cancers. We therefore investigated the response of metastatic acral and mucosal melanoma to ICI in regard to MDM2/4 or EGFR amplifications and melanoma type. Methods: We conducted a query of our melanoma registry, looking for patients with metastatic acral or mucosal melanoma treated by ICI. Whole exome sequencing, FISH and immunohistochemistry on melanoma tissue could be performed on 45 of the total cohort of 51 patients. Data were correlated with patients’ responses to ICI and survival. Results: 22 out of 51 patients had hyperprogressive disease (an increase in tumor load of >50% at the first staging). Hyperprogression occurred more often in case of MDM2/4 or EGFR amplification or <1% PD-L1 positive tumor cells. Nevertheless, this association was not significant. Interestingly, the anorectal melanoma type and the presence of liver metastases were significantly associated with worse survival. Conclusions: So far, we found no reliable predictive marker for patients who develop hyperprogression on ICI, specifically with regard to MDM2/4 or EGFR amplifications. Nevertheless, patients with anorectal melanoma, liver metastases or melanoma with amplified MYC seem to have an increased risk of not benefitting from ICI.

The detection of somatic driver mutations by next-generation sequencing (NGS) is becoming increasingly important in the care of advanced melanoma patients. In our study, we evaluated the NGS results of 82 melanoma patients from clinical routine in 2017. Besides determining the tumor mutational burden (TMB) and annotation of all genetic driver alterations, we investigated their potential as a predictor for resistance to immune checkpoint inhibitors (ICI) and as a distinguishing feature between melanoma subtypes. Melanomas of unknown primary had a similar mutation pattern and TMB to cutaneous melanoma, which hints at its cutaneous origin. Besides the typical hotspot mutation in BRAF and NRAS, we frequently observed CDKN2A deletions. Acral and mucosal melanomas were dominated by CNV alterations affecting PDGFRA, KIT, CDK4, RICTOR, CCND2 and CHEK2. Uveal melanoma often had somatic SNVs in GNA11/Q and amplification of MYC in all cases. A significantly higher incidence of BRAF V600 mutations and EGFR amplifications, PTEN and TP53 deletions was found in patients with disease progression while on ICI. Thus, NGS might help to characterize melanoma subtypes more precisely and to identify possible resistance mechanisms to ICI therapy. Nevertheless, NGS based studies, including larger cohorts, are needed to support potential genetic ICI resistance mechanisms.

A growing number of druggable targets and national initiatives for precision oncology necessitate broad genomic profiling for many cancer patients. Whole exome sequencing (WES) offers unbiased analysis of the entire coding sequence, segmentation-based detection of copy number alterations (CNAs), and accurate determination of complex biomarkers including tumor mutational burden (TMB), homologous recombination repair deficiency (HRD), and microsatellite instability (MSI). To assess the inter-institution variability of clinical WES, we performed a comparative pilot study between German Centers of Personalized Medicine (ZPMs) from five participating institutions. Tumor and matched normal DNA from 30 patients were analyzed using custom sequencing protocols and bioinformatic pipelines. Calling of somatic variants was highly concordant with a positive percentage agreement (PPA) between 91 and 95% and a positive predictive value (PPV) between 82 and 95% compared with a three-institution consensus and full agreement for 16 of 17 druggable targets. Explanations for deviations included low VAF or coverage, differing annotations, and different filter protocols. CNAs showed overall agreement in 76% for the genomic sequence with high wet-lab variability. Complex biomarkers correlated strongly between institutions (HRD: 0.79–1, TMB: 0.97–0.99) and all institutions agreed on microsatellite instability. This study will contribute to the development of quality control frameworks for comprehensive genomic profiling and sheds light onto parameters that require stringent standardization.

Background: Immune checkpoint inhibitors (ICIs) have demonstrated significantly improved clinical efficacy in a minority of patients with advanced melanoma, whereas non-responders potentially suffer from severe side effects and delays in other treatment options. Predicting the response to anti-PD1 treatment in melanoma remains a challenge because the current FDA-approved gold standard, the nonsynonymous tumor mutation burden (nsTMB), offers limited accuracy. Methods: In this study, we developed a multi-omics-based machine learning model that integrates genomic and transcriptomic biomarkers to predict the response to anti-PD1 treatment in patients with advanced melanoma. We employed least absolute shrinkage and selection operator (LASSO) regression with 49 biomarkers extracted from tumor–normal whole-exome and RNA sequencing as input features. The performance of the multi-omics AI model was thoroughly compared to that of nsTMB alone and to models that use only genomic or transcriptomic biomarkers. Results: We used publicly available DNA and RNA-seq datasets of melanoma patients for the training and validation of our model, forming a meta-cohort of 449 patients for which the outcome was recorded as a RECIST score. The model substantially improved the prediction of anti-PD1 outcomes compared to nsTMB alone, with an ROC AUC of 0.7 in the training set and an ROC AUC of 0.64 in the test set. Using SHAP values, we demonstrated the explainability of the model’s predictions on a per-sample basis. Conclusions: We demonstrated that models using only RNA-seq or multi-omics biomarkers outperformed nsTMB in predicting the response of melanoma patients to ICI. Furthermore, our machine learning approach improves clinical usability by providing explanations of its predictions on a per-patient basis. Our findings underscore the utility of multi-omics data for selecting patients for treatment with anti-PD1 drugs. However, to train clinical-grade AI models for routine applications, prospective studies collecting larger melanoma cohorts with consistent application of exome and RNA sequencing are required.

Genomic characterisation has led to an improved understanding of adult melanoma. However, the aetiology of melanoma in children is still unclear and identifying the correct diagnosis and therapeutic strategies remains challenging. Exome sequencing of matched tumour-normal pairs from 26 paediatric patients was performed to study the mutational spectrum of melanomas. The cohort was grouped into different categories: spitzoid melanoma (SM), conventional melanoma (CM), and other melanomas (OT). In all patients with CM (n = 10) germline variants associated with melanoma were found in low to moderate melanoma risk genes: in 8 patients MC1R variants, in 2 patients variants in MITF, PTEN and BRCA2. Somatic BRAF mutations were detected in 60% of CMs, homozygous deletions of CDKN2A in 20%, TERTp mutations in 30%. In the SM group (n = 12), 5 patients carried at least one MC1R variant; somatic BRAF mutations were detected in 8.3%, fusions in 25% of the cases. No SM showed a homozygous CDKN2A deletion nor a TERTp mutation. In 81.8% of the CM/SM cases the UV damage signatures SBS7 and/or DBS1 were detected. The patient with melanoma arising in giant congenital nevus (CNM) demonstrated the characteristic NRAS Q61K mutation. UV-radiation and MC1R germline variants are risk factors in the development of conventional and spitzoid paediatric melanomas. Paediatric CMs share genomic similarities with adult CMs while the SMs differ genetically from the CM group. Consistent genetic characterization of all paediatric melanomas will potentially lead to better subtype differentiation, treatment, and prevention in the future. Found in Acknowledgement.

MAD2L1BP -encoded p31 ^comet mediates Trip13-dependent disassembly of Mad2- and Rev7-containing complexes and, through this antagonism, promotes timely spindle assembly checkpoint (SAC) silencing, faithful chromosome segregation, insulin signaling, and homology-directed repair (HDR) of DNA double-strand breaks. We identified a homozygous MAD2L1BP nonsense variant, R253*, in 2 siblings with microcephaly, epileptic encephalopathy, and juvenile granulosa cell tumors of ovary and testis. Patient-derived cells exhibited high-grade mosaic variegated aneuploidy, slowed-down proliferation, and instability of truncated p31 ^comet mRNA and protein. Corresponding recombinant p31 ^comet was defective in Trip13, Mad2, and Rev7 binding and unable to support SAC silencing or HDR. Furthermore, C-terminal truncation abrogated an identified interaction of p31 ^comet with tp53. Another homozygous truncation, R227*, detected in an early-deceased patient with low-level aneuploidy, severe epileptic encephalopathy, and frequent blood glucose elevations, likely corresponds to complete loss of function, as in Mad2l1bp ^–/– mice. Thus, human mutations of p31 ^comet are linked to aneuploidy and tumor predisposition.