Genomic copy number burden distinguishes the diagnosis and prognosis of primary dermal melanoma

Background Primary dermal melanoma (PDM) is a subtype of melanoma with histological features indiscernible from non-epidermal metastatic cutaneous melanoma deposits, although patients with PDMs have more favourable outcomes compared to patients with dermal metastases. Despite the histological similarity, it is not known whether the mutational landscapes of PDMs and dermal metastases are also similar, or whether distinct mutational patterns might exist in PDMs. Objectives To identify genomic features that distinguish PDMs from non-epidermal cutaneous melanoma metastases, thereby enhancing the accuracy of clinical diagnosis and prognostication. Methods Cohorts of 20 PDMs and 23 non-epidermal cutaneous metastases were sequenced using the TSO500 panel. Genomic features distinguishing PDMs and metastases were identified using the regularised random forest model and feature engineering. Predictive biomarkers of patient event-free survival were identified using Lasso-Cox regression. Results Both PDM and non-epidermal cutaneous metastases cohorts harboured point mutations characteristic of melanomas of epidermal origin. Compared to PDMs, metastases exhibited distinct CNVs that led to gains of oncogenes and losses of tumour suppressor genes. Extreme focal amplifications were uniquely identified in cases of non-epidermal cutaneous metastases but were absent PDMs. Large-scale copy number variations (CNVs) and focal amplifications were identified as discriminative biomarkers between PDMs and metastases. A clinical diagnosis of PDM and an absence of BRAF CNVs collectively were associated with improved event-free survival after surgery compared to a clinical diagnosis of metastasis or of PDM with BRAF CNVs. Conclusion We found that CNVs were the strongest discriminative features between PDMs and non-epidermal cutaneous metastases, with large-scale and focal CNVs abundant in metastases but not in PDMs. Notably, integrating BRAF copy number analysis with standard clinical criteria for diagnosing PDMs improved risk stratification after surgery. These data highlight the ability of panel-based genomic sequencing that enables detection of CNVs to inform clinical management of melanoma.