The association between naevi and melanoma in populations with different levels of sun exposure: a joint case-control study of melanoma in the UK and Australia.

Two case-control studies were set up to investigate the relationship between melanocytic naevi and risk of melanoma and to compare the naevus phenotype in two countries exposed to greatly different levels of sun exposure and different melanoma rates. In England 117 melanoma cases and 163 controls were recruited from the North-East Thames Region and 183 melanoma cases and 162 controls from New South Wales, Australia. Each subject underwent a whole-body naevus count performed by the same examiner in each country. Relative risks associated with melanocytic naevi in each country were calculated with comparison of naevus data in controls between Australia and England. Atypical naevi were strong risk factors for melanoma in both countries: the odds ratio (OR) for three or more atypical naevi was 4.6 (95% CI 2.0-10.7) in Australia compared with 51.7 (95% CI 6.5-408.4) in England. Common naevi were also significant risk factors in Australia and England with similar odds ratios in the two countries. Prevalence of atypical naevi was greater in Australian controls than in English controls: OR 9.7 (95% CI 1.2-81.7) for three or more atypical naevi in Australia compared with England. For young age groups, the median number of common naevi was greater in Australia than in the UK, whereas for older individuals this difference in naevi number between the two countries disappeared. The prevalence of naevi on non-sun-exposed sites in controls was not significantly different between the two countries. The atypical mole syndrome (AMS) phenotype was more prevalent in Australian controls (6%) than in English controls (2%). The results of this study support the role of sun exposure in the induction of atypical naevi in adults. There was a trend towards stronger risk factors associated with atypical naevi in England compared with Australia. The atypical mole syndrome, usually associated with a genetic susceptibility to melanoma, was more common in Australia than in England, suggesting genetic environmental interactions with the possibility of phenocopies induced by sunlight

A population-based analysis of germline BAP1 mutations in melanoma

Germline mutation of the BRCA1 associated protein-1 (BAP1) gene has been linked to uveal melanoma, mesothelioma, meningioma, renal cell carcinoma and basal cell carcinoma. Germline variants have also been found in familial cutaneous melanoma pedigrees, but their contribution to sporadic melanoma has not been fully assessed. We sequenced BAP1 in 1,977 melanoma cases and 754 controls and used deubiquitinase assays, a pedigree analysis, and a histopathological review to assess the consequences of the mutations found. Sequencing revealed 30 BAP1 variants in total, of which 27 were rare (ExAc allele frequency <0.002). Of the 27 rare variants, 22 were present in cases (18 missense, one splice acceptor, one frameshift and two near splice regions) and 5 in controls (all missense). A missense change (S98R) in a case that completely abolished BAP1 deubiquitinase activity was identified. Analysis of cancers in the pedigree of the proband carrying the S98R variant and in two other pedigrees carrying clear loss-of-function alleles showed the presence of BAP1-associated cancers such as renal cell carcinoma, mesothelioma and meningioma, but not uveal melanoma. Two of these three probands carrying BAP1 loss-of-function variants also had melanomas with histopathological features suggestive of a germline BAP1 mutation. The remaining cases with germline mutations, which were predominantly missense mutations, were associated with less typical pedigrees and tumours lacking a characteristic BAP1-associated histopathological appearances, but may still represent less penetrant variants. Germline BAP1 alleles defined as loss-of-function or predicted to be deleterious/damaging are rare in melanoma

MX 2 is a novel regulator of cell cycle in melanoma cells

MX2 protein is a dynamin‐like GTPase2 that has recently been identified as an interferon‐induced restriction factor of HIV‐1 and other primate lentiviruses. A single nucleotide polymorphism (SNP), rs45430, in an intron of the MX2 gene, was previously reported as a novel melanoma susceptibility locus in genome‐wide association studies. Functionally, however, it is still unclear whether and how MX2 contributes to melanoma susceptibility and tumorigenesis. Here, we show that MX2 is differentially expressed in melanoma tumors and cell lines, with most metastatic cell lines showing lower MX2 expression than primary melanoma cell lines and melanocytes. Furthermore, high expression of MX2 RNA in primary melanoma tumors is associated with better patient survival. Overexpression of MX2 reduces in vivo proliferation partially through inhibition of AKT activation, suggesting that it can act as a tumor suppressor in melanoma. However, we have also identified a subset of melanoma cell lines with high endogenous MX2 expression where downregulation of MX2 leads to reduced proliferation. In these cells, MX2 downregulation interfered with DNA replication and cell cycle processes. Collectively, our data for the first time show that MX2 is functionally involved in the regulation of melanoma proliferation but that its function is context‐dependent

Image analysis of cutaneous melanoma histology: a systematic review and meta-analysis

The current subjective histopathological assessment of cutaneous melanoma is challenging. The application of image analysis algorithms to histological images may facilitate improvements in workflow and prognostication. To date, several individual algorithms applied to melanoma histological images have been reported with variations in approach and reported accuracies. Histological digital images can be created using a camera mounted on a light microscope, or through whole slide image (WSI) generation using a whole slide scanner. Before any such tool could be integrated into clinical workflow, the accuracy of the technology should be carefully evaluated and summarised. Therefore, the objective of this review was to evaluate the accuracy of existing image analysis algorithms applied to digital histological images of cutaneous melanoma. Database searching of PubMed and Embase from inception to 11th March 2022 was conducted alongside citation checking and examining reports from organisations. All studies reporting accuracy of any image analysis applied to histological images of cutaneous melanoma, were included. The reference standard was any histological assessment of haematoxylin and eosin-stained slides and/or immunohistochemical staining. Citations were independently deduplicated and screened by two review authors and disagreements were resolved through discussion. The data was extracted concerning study demographics; type of image analysis; type of reference standard; conditions included and test statistics to construct 2 × 2 tables. Data was extracted in accordance with our protocol and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses-Diagnostic Test Accuracy (PRISMA-DTA) Statement. A bivariate random-effects meta-analysis was used to estimate summary sensitivities and specificities with 95% confidence intervals (CI). Assessment of methodological quality was conducted using a tailored version of the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. The primary outcome was the pooled sensitivity and specificity of image analysis applied to cutaneous melanoma histological images. Sixteen studies were included in the systematic review, representing 4,888 specimens. Six studies were included in the meta-analysis. The mean sensitivity and specificity of automated image analysis algorithms applied to melanoma histological images was 90% (CI 82%, 95%) and 92% (CI 79%, 97%), respectively. Based on limited and heterogeneous data, image analysis appears to offer high accuracy when applied to histological images of cutaneous melanoma. However, given the early exploratory nature of these studies, further development work is necessary to improve their performance

Weakly-supervised learning for image-based classification of primary melanomas into genomic immune subgroups

Determining early-stage prognostic markers and stratifying patients for effective treatment are two key challenges for improving outcomes for melanoma patients. Previous studies have used tumour transcriptome data to stratify patients into immune subgroups, which were associated with differential melanoma specific survival and potential treatment strategies. However, acquiring transcriptome data is a time-consuming and costly process. Moreover, it is not routinely used in the current clinical workflow. Here we attempt to overcome this by developing deep learning models to classify gigapixel H&E stained pathology slides, which are well established in clinical workflows, into these immune subgroups. Previous subtyping approaches have employed supervised learning which requires fully annotated data, or have only examined single genetic mutations in melanoma patients. We leverage a multiple-instance learning approach, which only requires slide-level labels and uses an attention mechanism to highlight regions of high importance to the classification. Moreover, we show that pathology-specific self-supervised models generate better representations compared to pathology-agnostic models for improving our model performance, achieving a mean AUC of 0.76 for classifying histopathology images as high or low immune subgroups. We anticipate that this method may allow us to find new biomarkers of high importance and could act as a tool for clinicians to infer the immune landscape of tumours and stratify patients, without needing to carry out additional expensive genetic tests

Study of the female sex survival advantage in melanoma—a focus on x-linked epigenetic regulators and immune responses in two cohorts

Background: Survival from melanoma is strongly related to patient sex, with females having a survival rate almost twice that of males. Many explanations have been proposed but have not withstood critical scrutiny. Prior analysis of different cancers with a sex bias has identified six X-linked genes that escape X chromosome inactivation in females and are, therefore, potentially involved in sex differences in survival. Four of the genes are well-known epigenetic regulators that are known to influence the expression of hundreds of other genes and signaling pathways in cancer. Methods: Survival and interaction analysis were performed on the skin cutaneous melanoma (SKCM) cohort in The Cancer Genome Atlas (TCGA), comparing high vs. low expression of KDM6A, ATRX, KDM5C, and DDX3X. The Leeds melanoma cohort (LMC) on 678 patients with primary melanoma was used as a validation cohort. Results: Analysis of TCGA data revealed that two of these genes—KDM6A and ATRX—were associated with improved survival from melanoma. Tumoral KDM6A was expressed at higher levels in females and was associated with inferred lymphoid infiltration into melanoma. Gene set analysis of high KDM6A showed strong associations with immune responses and downregulation of genes associated with Myc and other oncogenic pathways. The LMC analysis confirmed the prognostic significance of KDM6A and its interaction with EZH2 but also revealed the expression of KDM5C and DDX3X to be prognostically significant. The analysis also confirmed a partial correlation of KDM6A with immune tumor infiltrates. Conclusion: When considered together, the results from these two series are consistent with the involvement of X-linked epigenetic regulators in the improved survival of females from melanoma. The identification of gene signatures associated with their expression presents insights into the development of new treatment initiatives but provides a basis for exploration in future studies