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Background Population-wide screening for melanoma is not cost-effective, but genetic characterization could facilitate risk stratification and targeted screening. Common Melanocortin-1 receptor (MC1R) red hair colour (RHC) variants and Microphthalmia-associated transcription factor (MITF) E318K separately confer moderate melanoma susceptibility, but their interactive effects are relatively unexplored. Objectives To evaluate whether MC1R genotypes differentially affect melanoma risk in MITF E318K+ vs. E318K– individuals. Materials and methods Melanoma status (affected or unaffected) and genotype data (MC1R and MITF E318K) were collated from research cohorts (five Australian and two European). In addition, RHC genotypes from E318K+ individuals with and without melanoma were extracted from databases (The Cancer Genome Atlas and Medical Genome Research Bank, respectively). χ2 and logistic regression were used to evaluate RHC allele and genotype frequencies within E318K+/– cohorts depending on melanoma status. Replication analysis was conducted on 200 000 general-population exomes (UK Biobank). Results The cohort comprised 1165 MITF E318K– and 322 E318K+ individuals. In E318K– cases MC1R R and r alleles increased melanoma risk relative to wild type (wt), P < 0.001 for both. Similarly, each MC1R RHC genotype (R/R, R/r, R/wt, r/r and r/wt) increased melanoma risk relative to wt/wt (P < 0.001 for all). In E318K+ cases, R alleles increased melanoma risk relative to the wt allele [odds ratio (OR) 2.04 (95% confidence interval 1.67–2.49); P = 0.01], while the r allele risk was comparable with the wt allele [OR 0.78 (0.54–1.14) vs. 1.00, respectively]. E318K+ cases with the r/r genotype had a lower but not significant melanoma risk relative to wt/wt [OR 0.52 (0.20–1.38)]. Within the E318K+ cohort, R genotypes (R/R, R/r and R/wt) conferred a significantly higher risk compared with non-R genotypes (r/r, r/wt and wt/wt) (P < 0.001). UK Biobank data supported our findings that r did not increase melanoma risk in E318K+ individuals. Conclusions RHC alleles/genotypes modify melanoma risk differently in MITF E318K– and E318K+ individuals. Specifically, although all RHC alleles increase risk relative to wt in E318K– individuals, only MC1R R increases melanoma risk in E318K+ individuals. Importantly, in the E318K+ cohort the MC1R r allele risk is comparable with wt. These findings could inform counselling and management for MITF E318K+ individuals.

This cross-sectional survey identified risk factors for developing a second primary melanoma. Patients with melanoma who had characteristics such as male sex, older age, high naevus count, or melanoma on the trunk or upper limbs had a substantially higher risk of subsequent melanoma and should therefore be more intensively monitored.

Melanoma is a cancer of melanocytes, with multiple subtypes based on body site location. Cutaneous melanoma is associated with skin exposed to ultraviolet radiation; uveal melanoma occurs in the eyes; mucosal melanoma occurs in internal mucous membranes; and acral melanoma occurs on the palms, soles, and nail beds. Here, we present the largest whole-genome sequencing study of melanoma to date, with 570 tumors profiled, as well as methylation and RNA sequencing for subsets of tumors. Uveal melanoma is genomically distinct from other melanoma subtypes, harboring the lowest tumor mutation burden and with significantly mutated genes in the G-protein signaling pathway. Most cutaneous, acral, and mucosal melanomas share alterations in components of the MAPK, PI3K, p53, p16, and telomere pathways. However, the mechanism by which these pathways are activated or inactivated varies between melanoma subtypes. Additionally, we identify potential novel germline predisposition genes for some of the less common melanoma subtypes. Significance: This is the largest whole-genome analysis of melanoma to date, comprehensively comparing the genomics of the four major melanoma subtypes. This study highlights both similarities and differences between the subtypes, providing insights into the etiology and biology of melanoma. This article is highlighted in the In This Issue feature, p. 2711

Background Immunotherapies have significantly improved the overall survival for patients with advanced melanoma. However, almost half of such patients either do not respond to the therapy or develop resistance to it, subjecting patients to ineffective treatments and unnecessary costs. Predictive biomarker testing can ensure that the patient receives the most effective therapy thereby reducing costs and toxicities. This study was conducted prior to and alongside a clinical validation study of routine predictive biomarker testing for patients with advanced melanoma to gain an insight into the factors associated with successful implementation of this intervention. Methods We conducted semi-structured interviews (n=25) with health professionals and patients guided by the EPIS (Exploration, Preparation, Implementation, and Sustainment) framework to understand enablers and barriers of implementation. Data analysis involved inductive and deductive thematic analysis using the Consolidated Framework for Implementation Research (CFIR). Results Health providers and patients consistently reported ‘clinical utility of predictive biomarker test’ as a major enabler, recognising that an effective test would assist in identifying likely non-responders and consequently avoid the side effects and other costs of ineffective treatment. Trust in data scientists, adaptability of the test platform, pre-existing organisational infrastructure, and supportive organisational implementation culture were also identified as factors that would support implementation. Lack of validated predictive biomarkers, resources and costs required to implement the test, and health providers’ knowledge, beliefs and concerns around the test were the principal factors that would impede implementation. Conclusion This study identifies factors influencing implementation of biomarkers as predictors of treatment response to immunotherapy for melanoma and potential strategies to overcome barriers impeding their transition from discovery to the clinic.

Tumor mutation burden (TMB) has been proposed as a key determinant of immunogenicity in several cancers, including melanoma. The evidence presented thus far, however, is often contradictory and based mostly on RNA-sequencing data for the quantification of immune cell phenotypes. Few studies have investigated TMB across acral, mucosal, and cutaneous melanoma subtypes, which are known to have different TMB. It is also unknown whether chromosomal structural mutations [structural variant (SV) mutations] contribute to the immunogenicity in acral and mucosal melanomas where such aberrations are common. We stained 151 cutaneous and 35 acral and mucosal melanoma patient samples using quantitative IHC and correlated immune infiltrate phenotypes with TMB and other genomic profiles. TMB and SVs did not correlate with the densities of CD8+ lymphocytes, CD103+ tumor-resident T cells (Trm), CD45RO+ cells, and other innate and adaptive immune cell subsets in cutaneous and acral/mucosal melanoma tumors, respectively, including in analyses restricted to the site of disease and in a validation cohort. In 43 patients with stage III treatment-naïve cutaneous melanoma, we found that the density of immune cells, particularly Trm, was significantly associated with patient survival, but not with TMB. Overall, TMB and chromosomal structural aberrations are not associated with protective antitumor immunity in treatment-naïve melanoma.

Supplementary Data from Comparative Genomics Provides Etiologic and Biological Insight into Melanoma Subtypes

Supplementary Figures 1-8 and Supplementary Tables 1-4

Legends for Supplementary Figures

Melanoma is a cancer of melanocytes, with multiple subtypes based on body site location. Cutaneous melanoma is associated with skin exposed to ultraviolet radiation; uveal melanoma occurs in the eyes; mucosal melanoma occurs in internal mucous membranes; and acral melanoma occurs on the palms, soles, and nail beds. Here, we present the largest whole-genome sequencing study of melanoma to date, with 570 tumors profiled, as well as methylation and RNA sequencing for subsets of tumors. Uveal melanoma is genomically distinct from other melanoma subtypes, harboring the lowest tumor mutation burden and with significantly mutated genes in the G-protein signaling pathway. Most cutaneous, acral, and mucosal melanomas share alterations in components of the MAPK, PI3K, p53, p16, and telomere pathways. However, the mechanism by which these pathways are activated or inactivated varies between melanoma subtypes. Additionally, we identify potential novel germline predisposition genes for some of the less common melanoma subtypes.Significance:This is the largest whole-genome analysis of melanoma to date, comprehensively comparing the genomics of the four major melanoma subtypes. This study highlights both similarities and differences between the subtypes, providing insights into the etiology and biology of melanoma.This article is highlighted in the In This Issue feature, p. 2711

Supplement 2 from Melanoma Prognosis: A REMARK-Based Systematic Review and Bioinformatic Analysis of Immunohistochemical and Gene Microarray Studies

Supplement 4 from Melanoma Prognosis: A REMARK-Based Systematic Review and Bioinformatic Analysis of Immunohistochemical and Gene Microarray Studies

PDF file - 381K, Results of Melanoma Specific Mutation Panel.

PDF file - 270K, Mutation List used in confirmation phase.

Supplement 1 from Melanoma Prognosis: A REMARK-Based Systematic Review and Bioinformatic Analysis of Immunohistochemical and Gene Microarray Studies

XLS file - 50K, Confirmation panel assay design.

Despite intensive research efforts, within-stage survival rates for melanoma vary widely. Pursuit of molecular biomarkers with improved prognostic significance over clinicohistological measures has produced extensive literature. Reviews have synthesized these data, but none have systematically partitioned high-quality studies from the remainder across different molecular methods nor examined system properties of that output. Databases were searched for studies analyzing protein expression by immunohistochemistry (n = 617, extending the only systematic review to date by 102 studies) or for gene expression microarray studies (n = 45) in melanoma in relation to outcome. REMARK-derived criteria were applied to identify high-quality studies. Biomarkers and pathways were functionally assessed by using gene ontology software. Most manuscripts did not meet REMARK-based criteria, an ongoing trend that can impede translational research. Across REMARK-compliant literature, 41 proteins were significantly associated with outcome. Multimarker tests consistently emerged among the most promising potential biomarkers, indicating a need to continue assessing candidates in that composite setting. Twenty-one canonical pathways were populated by outcome-related proteins but not by those that failed to show such an association; we propose that this set of pathways warrants closer investigation to understand drivers of poor outcome in melanoma. Two-gene expression microarray studies met REMARK-based criteria reflecting a genuine paucity of literature in the area. The 254 outcome-related genes were examined for correspondences with the systematically identified protein signature. This analysis highlighted proliferating cell nuclear antigen and survivin as priorities for further examination as biomarkers in melanoma prognosis, and illustrated ongoing need to integrate alternative approaches to biomarker discovery in melanoma translational research. Mol Cancer Ther; 10(8); 1520–8. ©2011 AACR.

Supplementary Data from Loss-of-Function Fibroblast Growth Factor Receptor-2 Mutations in Melanoma

Supplement 3 from Melanoma Prognosis: A REMARK-Based Systematic Review and Bioinformatic Analysis of Immunohistochemical and Gene Microarray Studies

Supplement 5 from Melanoma Prognosis: A REMARK-Based Systematic Review and Bioinformatic Analysis of Immunohistochemical and Gene Microarray Studies

Previous studies suggest that polygenic risk scores (PRSs) may improve melanoma risk stratification. However, there has been limited independent validation of PRS-based risk prediction, particularly assessment of calibration (comparing predicted to observed risks).To evaluate PRS-based melanoma risk prediction in prospective UK and Australian cohorts with European ancestry.We analysed invasive melanoma incidence in the UK Biobank (UKB; n = 395 647, 1651 cases) and a case-cohort nested within the Melbourne Collaborative Cohort Study (MCCS, Australia; n = 4765, 303 cases). Three PRSs were evaluated: 68 single-nucleotide polymorphisms (SNPs) at 54 loci from a 2020 meta-analysis (PRS68), 50 SNPs significant in the 2020 meta-analysis excluding UKB (PRS50) and 45 SNPs at 21 loci known in 2018 (PRS45). Ten-year melanoma risks were calculated from population-level cancer registry data by age group and sex, with and without PRS adjustment.Predicted absolute melanoma risks based on age and sex alone underestimated melanoma incidence in the UKB [ratio of expected/observed cases: E/O = 0·65, 95% confidence interval (CI) 0·62-0·68] and MCCS (E/O = 0·63, 95% CI 0·56-0·72). For UKB, calibration was improved by PRS adjustment, with PRS50-adjusted risks E/O = 0·91, 95% CI 0·87-0·95. The discriminative ability for PRS68- and PRS50-adjusted absolute risks was higher than for risks based on age and sex alone (Δ area under the curve 0·07-0·10, P 0·0001), and higher than for PRS45-adjusted risks (Δ area under the curve 0·02-0·04, P 0·001).A PRS derived from a larger, more diverse meta-analysis improves risk prediction compared with an earlier PRS, and might help tailor melanoma prevention and early detection strategies to different risk levels. Recalibration of absolute risks may be necessary for application to specific populations.

Correlation between PD-L1 gene expression (RNAseq) and PD-L1 immunohistochemistry score (r2 = 0.711, p = 3.33E-09). Green diamonds = PD-L1 negative by immunohistochemistry; Empty diamonds = PD-L1 positive by immunohistochemistry.

A copy of a booklet communicating personalised risk of melanoma.

Supplementary Figure 1 - PDF file 91K, Schematic diagram of experimental procedure and bioinformatic analysis

Supplementary Table S1. Probability ratios (95% CI) for disagreement between self-reported and clinically-measured hair, eye and skin color phenotype.

Background: Communication of personalized melanoma genomic risk information may improve melanoma prevention behaviors.Methods: We evaluated the feasibility and acceptability of communicating personalized genomic risk of melanoma to the public and its preliminary impact on behaviors and psychosocial outcomes. One hundred eighteen people aged 22 to 69 years provided a saliva sample and were randomized to the control (nonpersonalized educational materials) or intervention (personalized booklet presenting melanoma genomic risk as absolute and relative risks and a risk category based on variants in 21 genes, telephone-based genetic counseling, and nonpersonalized educational materials). Intention-to-treat analyses overall and by-risk category were conducted using ANCOVA adjusted for baseline values.Results: Consent to participate was 41%, 99% were successfully genotyped, and 92% completed 3-month follow-up. Intervention participants reported high satisfaction with the personalized booklet (mean = 8.6, SD = 1.6; on a 0–10 scale) and genetic counseling (mean = 8.1, SD = 2.2). No significant behavioral effects at 3-month follow-up were identified between intervention and control groups overall: objectively measured standard erythemal doses per day [−16%; 95% confidence interval (CI), −43% to 24%] and sun protection index (0.05; 95% CI, −0.07 to 0.18). There was increased confidence identifying melanoma at 3 months (0.40; 95% CI, 0.10–0.69). Stratified by risk category, effect sizes for intentional tanning and some individual sun protection items appeared stronger for the average-risk group. There were no appreciable group differences in skin cancer–related worry or psychologic distress.Conclusions: Our results demonstrate feasibility and acceptability of providing personalized genomic risk of melanoma to the public.Impact: Genomic risk information has potential as a melanoma prevention strategy. Cancer Epidemiol Biomarkers Prev; 26(2); 212–21. ©2016 AACR.

Supplementary file (clean version) including Supplementary text on Materials and Methods, and the following tables: Supplementary Table 1. Genomic variants included in the genomic risk estimates and their published associations with melanoma. Supplementary Table 2. Sun Protection Index: Individual items. Supplementary Table 3. Preliminary effect of the intervention on resource use and costs at 3-months.

Supplementary tables 1, 3 and 4 - XLSX file 31K, 1. Performance summary of exome sequencing and capture kit used for each sample 3. List of genes for each melanoma subtype 4. List of potential actionable mutations in BRAF/NRAS wild-type tumors

Supplementary Figure S1: The 30 body sites for which separate counts of melanocytic nevi were made.

Purpose: Understanding why some melanomas test negative for PD-L1 by IHC may have implications for the application of anti-PD-1 therapies in melanoma management. This study sought to determine somatic mutation and gene expression patterns associated with tumor cell PD-L1 expression, or lack thereof, in stage III metastatic melanoma to better define therapeutically relevant patient subgroups.Experimental Design: IHC for PD-L1 was assessed in 52 American Joint Committee on Cancer stage III melanoma lymph node specimens and compared with specimen-matched comprehensive clinicopathologic, genomic, and transcriptomic data.Results: PD-L1–negative status was associated with lower nonsynonymous mutation (NSM) burden (P = 0.017) and worse melanoma-specific survival [HR = 0.28 (0.12–0.66), P = 0.002] in stage III melanoma. Gene set enrichment analysis identified an immune-related gene expression signature in PD-L1–positive tumors. There was a marked increase in cytotoxic T-cell and macrophage-specific genes in PD-L1–positive melanomas. CD8Ahigh gene expression was associated with better melanoma-specific survival [HR = 0.2 (0.05–0.87), P = 0.017] and restricted to PD-L1–positive stage III specimens. NF1 mutations were restricted to PD-L1–positive tumors (P = 0.041).Conclusions: Tumor negative PD-L1 status in stage III melanoma lymph node metastasis is a marker of worse patient survival and is associated with a poor immune response gene signature. Lower NSM levels were associated with PD-L1–negative status suggesting differences in somatic mutation profiles are a determinant of PD-L1–associated antitumor immunity in stage III melanoma. Clin Cancer Res; 22(15); 3915–23. ©2016 AACR.

Table S1 - Summary of Gene Set Enrichment Analysis (GSEA) results for pathways with FDR < 0.05.

Supplementary Table 2 - PDF file 16632K, Single nucleotide variants identified for each sample

Purpose: The mutation load in melanoma is generally high compared with other tumor types due to extensive UV damage. Translation of exome sequencing data into clinically relevant information is therefore challenging. This study sought to characterize mutations identified in primary cutaneous melanomas and correlate these with clinicopathologic features.Experimental Design: DNA was extracted from 34 fresh-frozen primary cutaneous melanomas and matched peripheral blood. Tumor histopathology was reviewed by two dermatopathologists. Exome sequencing was conducted and mutation rates were correlated with age, sex, tumor site, and histopathologic variables. Differences in mutations between categories of solar elastosis, pigmentation, and BRAF/NRAS mutational status were investigated.Results: The average mutation rate was 12 per megabase, similar to published results in metastases. The average mutation rate in severely sun damaged (SSD) skin was 21 per Mb compared with 3.8 per Mb in non-SSD skin (P = 0.001). BRAF/NRAS wild-type (WT) tumors had a higher average mutation rate compared with BRAF/NRAS–mutant tumors (27 vs. 5.6 mutations per Mb; P = 0.0001). Tandem CC>TT/GG>AA mutations comprised 70% of all dinucleotide substitutions and were more common in tumors arising in SSD skin (P = 0.0008) and in BRAF/NRAS WT tumors (P = 0.0007). Targetable and potentially targetable mutations in WT tumors, including NF1, KIT, and NOTCH1, were spread over various signaling pathways.Conclusion: Melanomas arising in SSD skin have higher mutation loads and contain a spectrum of molecular subtypes compared with BRAF- and NRAS-mutant tumors indicating multigene screening approaches and combination therapies may be required for management of these patients. Clin Cancer Res; 19(17); 4589–98. ©2013 AACR.

Description of additional methods and procedures used in the study. Also includes Supplementary References.

MCC Patient characteristics (S1); Extension cohort of MCCs (S2); List of genes represented on the targeted sequencing panel (S3); Performance metrics for targeted sequencing and low coverage WGS (S4); Validation of mutations by orthogonal genotyping methods (S5); Immunohistochemistry scores for MCCs (S6); SNV and Indels called from targeted sequencing (S7); Mutational burden with respect to copy number changes through low coverage whole genome sequencing (S8); Gene level copy-number from LC-WGS (S9); Copies and viral integration sites for MCV positive MCCs (S10); Drug sensitivity data for 3 MCC cell lines (S11).

Focal copy number alterations proximal to viral integrations in V+MCC.

Merkel cell carcinoma (MCC) is an uncommon, but highly malignant, cutaneous tumor. Merkel cell polyoma virus (MCV) has been implicated in a majority of MCC tumors; however, viral-negative tumors have been reported to be more prevalent in some geographic regions subject to high sun exposure. While the impact of MCV and viral T-antigens on MCC development has been extensively investigated, little is known about the etiology of viral-negative tumors. We performed targeted capture and massively parallel DNA sequencing of 619 cancer genes to compare the gene mutations and copy number alterations in MCV-positive (n = 13) and -negative (n = 21) MCC tumors and cell lines. We found that MCV-positive tumors displayed very low mutation rates, but MCV-negative tumors exhibited a high mutation burden associated with a UV-induced DNA damage signature. All viral-negative tumors harbored mutations in RB1, TP53, and a high frequency of mutations in NOTCH1 and FAT1. Additional mutated or amplified cancer genes of potential clinical importance included PI3K (PIK3CA, AKT1, PIK3CG) and MAPK (HRAS, NF1) pathway members and the receptor tyrosine kinase FGFR2. Furthermore, looking ahead to potential therapeutic strategies encompassing immune checkpoint inhibitors such as anti-PD-L1, we also assessed the status of T-cell–infiltrating lymphocytes (TIL) and PD-L1 in MCC tumors. A subset of viral-negative tumors exhibited high TILs and PD-L1 expression, corresponding with the higher mutation load within these cancers. Taken together, this study provides new insights into the underlying biology of viral-negative MCC and paves the road for further investigation into new treatment opportunities. Cancer Res; 75(24); 5228–34. ©2015 AACR.

Overdiagnosis of early melanoma is a significant problem. Due to subtle unique and overlapping clinical and histological criteria between pigmented lesions and the risk of mortality from melanoma, some benign pigmented lesions are diagnosed as melanoma. Although histopathology is the gold standard to diagnose melanoma, there is a demand to find alternatives that are more accurate and cost-effective. In the current "omics" era, there is gaining interest in biomarkers to help diagnose melanoma early and to further understand the mechanisms driving tumor progression. Genomic investigations have attempted to differentiate malignant melanoma from benign pigmented lesions. However, genetic biomarkers of early melanoma diagnosis have not yet proven their value in the clinical setting. Protein biomarkers may be more promising since they directly influence tissue phenotype, a result of by-products of genomic mutations, posttranslational modifications and environmental factors. Uncovering relevant protein biomarkers could increase confidence in their use as diagnostic signatures. Currently, proteomic investigations of melanoma progression from pigmented lesions are limited. Studies have previously characterised the melanoma proteome from cultured cell lines and clinical samples such as serum and tissue. This has been useful in understanding how melanoma progresses into metastasis and development of resistance to adjuvant therapies. Currently, most studies focus on metastatic melanoma to find potential drug therapy targets, prognostic factors and markers of resistance. This paper reviews recent advancements in the genomics and proteomic fields and reports potential avenues, which could help identify and differentiate melanoma from benign pigmented lesions and prevent the progression of melanoma.

Purpose We evaluated the impact of personal melanoma genomic risk information on sun-related behaviors and psychological outcomes. Methods In this parallel group, open, randomized controlled trial, 1,025 Australians of European ancestry without melanoma and aged 18–69 years were recruited via the Medicare database (3% consent). Participants were randomized to the intervention (n = 513; saliva sample for genetic testing, personalized melanoma risk booklet based on a 40-variant polygenic risk score, telephone-based genetic counseling, educational booklet) or control (n = 512; educational booklet). Wrist-worn ultraviolet (UV) radiation dosimeters (10-day wear) and questionnaires were administered at baseline, 1 month postintervention, and 12 months postbaseline. Results At 12 months, 948 (92%) participants completed dosimetry and 973 (95%) the questionnaire. For the primary outcome, there was no effect of the genomic risk intervention on objectively measured UV exposure at 12 months, irrespective of traditional risk factors. For secondary outcomes at 12 months, the intervention reduced sunburns (risk ratio: 0.72, 95% confidence interval: 0.54–0.96), and increased skin examinations among women. Melanoma-related worry was reduced. There was no overall impact on general psychological distress. Conclusion Personalized genomic risk information did not influence sun exposure patterns but did improve some skin cancer prevention and early detection behaviors, suggesting it may be useful for precision prevention. There was no evidence of psychological harm.

For cancer patients, comorbid obstructive sleep apnea (OSA) poses additional risk to their surgical/anaesthetic outcomes, quality of life, and survival. However, OSA screening is not well-established in oncology settings. We tested two screening tools (STOP-Bang questionnaire [SBQ] and the at-home monitoring device, ApneaLink™Air), for predicting polysomnography (PSG) confirmed OSA in post-treatment cancer patients.Breast (n = 56), endometrial (n = 37) and melanoma patients (n = 50) were recruited from follow-up clinics at Westmead Hospital (Sydney, Australia). All underwent overnight PSG, 137 completed SBQ, and 99 completed ApneaLink™Air. Positive (PPV) and negative (NPV) predictive values for PSG-determined moderate-to-severe OSA and severe OSA, were calculated using an SBQ threshold ≥3 au and ApneaLink™Air apnoea-hypopnea index thresholds of ≥10, ≥15 and ≥30 events/h.Both SBQ and ApneaLink™Air had high NPVs (92.7% and 85.2%-95.6% respectively) for severe OSA, but NPVs were lower for moderate-to-severe OSA (69.1% and 59.1%-75.5%, respectively). PPV for both tools were relatively low (all73%). Combining both tools did not improve screening performance.These screening tools may help identify cancer patients without severe OSA, but both are limited in identifying those with moderate-to-severe or severe OSA. PSG remains optimal for adequately identifying and managing comorbid OSA in cancer patients.

Risk prediction models, which include a combination of risk factors, have been developed as a more accurate way of estimating risk and personalising preventive interventions. Many melanoma risk prediction models have been published but few have been independently validated.1 We aimed to externally validate 12 melanoma risk prediction models using the Australian Melanoma Family Study (AMFS), a population-based, case-control-family study comprising 629 incident first-primary melanoma cases, 240 population-based controls ascertained using the electoral roll (voting is compulsory) and 295 spouse or friend controls.2 Recruitment took place from 2001 to 2005 in the states of New South Wales, Queensland and Victoria.

Background The study aimed to estimate the prevalence of active or previous SARS‐CoV‐2 infection in asymptomatic adults admitted for elective surgery in Australian hospitals. This surveillance activity was established as part of the National Pandemic Health Intelligence Plan. Methods Participants (n = 3037) were recruited from 11 public and private hospitals in four states (NSW, Vic, SA and WA) between 2 June and 17 July 2020, with an overall 66% participation rate. Presence of SARS‐CoV‐2 viral RNA was assessed by Reverse Transcriptase ‐ Polymerase Chain Reaction (RT‐PCR) analysis of nasopharyngeal swabs taken after induction of anaesthesia. Presence of anti‐SARS‐CoV‐2 antibodies was assessed by analysis of serum collected at the same time using a novel dual‐antigen ELISA assay. Results No patient (0/3010) returned a positive RT‐PCR result. The Bayesian estimated prevalence of active infection of 0.02% (95% probability interval 0.00–0.11%), with the upper endpoint being 1 in 918. Positive serology (IgG) was observed in 15 of 2991 patients, with a strong positive in five of those individuals (Bayesian estimated seroprevalence 0.16%; 95% probability interval 0.00–0.47%). Conclusion These results confirm that during periods of low community prevalence of SARS‐CoV‐2 elective surgery patients without fever or respiratory symptoms had a very low prevalence of active SARS‐CoV‐2 infection., During the COVID 19 pandemic decisions regarding elective surgery cessation had significant impact on patients and practitioners. This study formed part of the National Pandemic Health Intelligence Plan, and finds that in areas where community transmission of SARS Cov‐2 is low, the risk of an asymptomatic patient undergoing elective surgery having SARS CoV‐2 is very low.