A multicentre study of naevus-associated melanoma vs. de novo melanoma, tumour thickness and body site differences.

BACKGROUND: Whether melanoma in histological contiguity with a naevus [naevus-associated melanoma (NAM)] is distinctly different from melanoma arising de novo remains unclear. OBJECTIVES: To determine whether the characteristics of de novo melanoma differ from NAM and are not due to naevus obliteration in thicker tumours. METHODS: We conducted a multicentre retrospective study of de novo melanoma and NAM in seven referral centres in Europe, Australia and the USA between 2006 and 2015. RESULTS: In a total of 9474 localized melanomas, de novo melanoma was associated with thicker tumours and body site differences compared with NAM. In the subset of T1 melanomas (n = 5307), similar body site differences were found in multivariate analysis by body site. When compared with NAM, de novo melanoma was more likely to affect older individuals (≥ 70 years) when located on the head/neck [odds ratio (OR) 4·65, 95% confidence interval (CI) 2·55-8·46], the trunk (OR 1·82, 95% CI 1·40-2·36) or the upper extremity (OR 1·69, 95% CI 1·14-2·50), was more likely to affect female patients when located on the lower extremities (OR 1·36, 95% CI 1·03-1·80), and was more likely to be of the nodular melanoma subtype (OR 2·23, 95% CI 1·14-4·35) when located on the trunk. De novo melanoma was less likely to have regression present compared with NAM. CONCLUSIONS: Clinicopathological and body site differences between de novo melanoma and NAM support the divergent pathway model of development. These differences were also found in thin melanomas, suggesting that de novo melanomas are different from NAM and their differences are not due to the obliteration of naevus remnants in thicker tumours.

Histopathological features of complete pathological response predict recurrence-free survival following neoadjuvant targeted therapy for metastatic melanoma.

BACKGROUND: Recent clinical trials demonstrated the safety and efficacy of neoadjuvant dabrafenib and trametinib (DT) among patients with surgically resectable clinical stage III BRAFV600E/K mutant melanoma. Although patients achieving a complete pathological response (pCR) exhibited superior recurrence-free survival (RFS) versus those who did not, 30% of pCR patients relapsed. We sought to identify whether histopathological features of the pathological response further delineated risk of relapse. METHODS: Surgical resection specimens from DT-treated patients in two phase 2 clinical trials were reviewed. Histopathological features, including relative amounts of viable tumour, necrosis, melanosis, and fibrosis (hyalinized or immature/proliferative) were assessed for associations with patient outcomes. RESULTS: Fifty-nine patients underwent surgical resection following neoadjuvant DT. Patients achieving pCR (49%) had longer RFS compared with patients who did not (P = 0.005). Patients whose treated tumour showed any hyalinized fibrosis had longer RFS versus those without (P = 0.014), whereas necrosis (P = 0.012) and/or immature/proliferative fibrosis (P = 0.026) correlated with shorter RFS. Multivariable analyses showed absence of pCR or presence of immature fibrosis independently predicted shorter RFS. Among pCR patients, mature/hyalinized-type fibrosis correlated with improved RFS (P = 0.035). CONCLUSIONS: The extent and composition of the pathological response following neoadjuvant DT in BRAFV600E/K mutant melanoma correlates with RFS, including pCR patients. These findings support the need for detailed histological analysis of specimens collected after neoadjuvant therapy.

A risk prediction model for the development of subsequent primary melanoma in a population-based cohort.

BACKGROUND: Guidelines for follow-up of patients with melanoma are based on limited evidence. OBJECTIVES: To guide skin surveillance, we developed a risk prediction model for subsequent primary melanomas, using demographic, phenotypical, histopathological, sun exposure and genomic risk factors. METHODS: Using Cox regression frailty models, we analysed data for 2613 primary melanomas from 1266 patients recruited to the population-based Genes, Environment and Melanoma study in New South Wales, Australia, with a median of 14 years' follow-up via the cancer registry. Discrimination and calibration were assessed. RESULTS: The median time to diagnosis of a subsequent primary melanoma decreased with each new primary melanoma. The final model included 12 risk factors. Harrell's C-statistic was 0·73 [95% confidence interval (CI) 0·68-0·77], 0·65 (95% CI 0·62-0·68) and 0·65 (95% CI 0·61-0·69) for predicting second, third and fourth primary melanomas, respectively. The risk of a subsequent primary melanoma was 4·75 times higher (95% CI 3·87-5·82) for the highest vs. the lowest quintile of the risk score. The mean absolute risk of a subsequent primary melanoma within 5 years was 8·0 ± SD 4.1% after the first primary melanoma, and 46·8 ± 15·0% after the second, but varied substantially by risk score. CONCLUSIONS: The risk of developing a subsequent primary melanoma varies considerably between individuals and is particularly high for those with two or more primary melanomas. The risk prediction model and its associated nomograms enable estimation of the absolute risk of subsequent primary melanoma, on the basis of on an individual's risk factors, and can be used to tailor surveillance intensity, communicate risk and provide patient education. What's already known about this topic? Current guidelines for the frequency and length of follow-up to detect new primary melanomas in patients with one or more previous primary melanomas are based on limited evidence. People with one or more primary melanomas have, on average, a higher risk of developing another primary invasive melanoma, compared with the general population, but an accurate way of estimating individual risk is needed. What does this study add? We provide a comprehensive risk prediction model for subsequent primary melanomas, using data from 1266 participants with melanoma (2613 primary melanomas), over a median 14 years' follow-up. The model includes 12 risk factors comprising demographic, phenotypical, histopathological and genomic factors, and sun exposure. It enables estimation of the absolute risk of subsequent primary melanomas, and can be used to tailor surveillance intensity, communicate individual risk and provide patient education.

Gut microbiome modulates response to anti-PD-1 immunotherapy in melanoma patients.

Preclinical mouse models suggest that the gut microbiome modulates tumor response to checkpoint blockade immunotherapy; however, this has not been well-characterized in human cancer patients. Here we examined the oral and gut microbiome of melanoma patients undergoing anti-programmed cell death 1 protein (PD-1) immunotherapy (n = 112). Significant differences were observed in the diversity and composition of the patient gut microbiome of responders versus nonresponders. Analysis of patient fecal microbiome samples (n = 43, 30 responders, 13 nonresponders) showed significantly higher alpha diversity (P < 0.01) and relative abundance of bacteria of the Ruminococcaceae family (P < 0.01) in responding patients. Metagenomic studies revealed functional differences in gut bacteria in responders, including enrichment of anabolic pathways. Immune profiling suggested enhanced systemic and antitumor immunity in responding patients with a favorable gut microbiome as well as in germ-free mice receiving fecal transplants from responding patients. Together, these data have important implications for the treatment of melanoma patients with immune checkpoint inhibitors.

Correlation of BRAF and NRAS mutation status with outcome, site of distant metastasis and response to chemotherapy in metastatic melanoma.

BACKGROUND: The prognostic significance of BRAF and NRAS mutations in metastatic melanoma patients remains uncertain, with several studies reporting conflicting results, often biased by the inclusion of patients treated with BRAF and MEK (MAPK) inhibitors. We therefore interrogated a historical cohort of patients free of the confounding influence of MAPK inhibitor therapy. METHODS: Patients with available archival tissue first diagnosed with metastatic melanoma between 2002 and 2006 were analysed. Mutational analysis was performed using the OncoCarta Panel. Patient characteristics, treatment outcome and survival were correlated with BRAF/NRAS mutation status. RESULTS: In 193 patients, 92 (48%) melanomas were BRAF-mutant, 39 (20%) were NRAS-mutant and 62 (32%) were wild-type for BRAF/NRAS mutations (wt). There was no difference in response to chemotherapy based on mutation status (35-37%). The distant disease-free interval (DDFI) was significantly shorter in patients with wt melanoma (27.9 months vs 35.1 for BRAF and 49.1 for NRAS) although this was not significant in multivariate analysis. Survival from stage IV melanoma diagnosis was not significantly different based on mutation status. The DDFI was significantly shorter in patients with BRAF(V600K/R) versus BRAF(V600E) melanoma in univariate and multivariate analyses. CONCLUSIONS: BRAF and NRAS mutation status does not influence survival in metastatic melanoma.

Surveillance for treatment failure of lentigo maligna with dermoscopy and in vivo confocal microscopy: new descriptors.

BACKGROUND: Nonsurgical treatment (radiotherapy, imiquimod) is increasingly employed for the management of lentigo maligna (LM). While the diagnosis of LM remains difficult, the detection of treatment failure is even more challenging. OBJECTIVES: To describe the sensitivity and specificity for the diagnosis of LM of individual features and methods using dermoscopy and in vivo reflectance confocal microscopy (RCM) to aid in the detection of treatment failure of LM following nonsurgical treatment. METHODS: A retrospective study of dermoscopy and RCM images (blinded to the correlation with pathology) in patients with biopsy-confirmed LM who were undergoing nonsurgical treatment in two referral institutions - one in Sydney, Australia, and the other in Barcelona, Spain. Ninety-eight patients were treated nonsurgically for LM during the period 2006-2012. Thirty-one patients had abnormal dermoscopy or RCM evaluation, and had a biopsy that identified LM recurrence in 15 patients and nonmelanoma diagnoses in 16 patients (one Bowen disease, 15 solar changes). RESULTS: The diagnosis of treatment failure was difficult with dermoscopy, with a sensitivity of 80% and specificity of 56%, even with the interpretation of an expert. The best criterion was asymmetric hyperpigmented follicular openings, but this was present in only 47% of treatment failure LM. Isolated, very fine brown dots ('dust' appearance) correlated highly with the diagnosis of treatment failure LM (73% sensitivity and 88% specificity) and with pagetoid cells seen with RCM. The LM score, comprising six criteria, had a specificity of 94% and sensitivity of 100%. CONCLUSIONS: These methods and descriptors should help to manage the diagnosis of treatment failure.

BRAF(V600E) protein expression and outcome from BRAF inhibitor treatment in BRAF(V600E) metastatic melanoma.

BACKGROUND: To examine the association between level and patterns of baseline intra-tumoural BRAF(V600E) protein expression and clinical outcome of BRAF(V600E) melanoma patients treated with selective BRAF inhibitors. METHODS: Fifty-eight BRAF(V600E) metastatic melanoma patients treated with dabrafenib or vemurafenib on clinical trials had pre-treatment tumour BRAF(V600E) protein expression immunohistochemically (IHC) assessed using the BRAF V600E mutant-specific antibody VE1. Sections were examined for staining intensity (score 1-3) and percentage of immunoreactive tumour cells, and from this an immunoreactive score (IRS) was derived (intensity × per cent positive/10). The presence of intra-tumoural heterogeneity for BRAF(V600E) protein expression was also assessed. BRAF(V600E) expression was correlated with RECIST response, time to best response (TTBR), progression-free survival (PFS) and overall survival (OS). RESULTS: Expression was generally high (median IRS 28 (range 5-30)) and homogeneous (78%). Expression of mutated protein BRAF(V600E) as measured by intensity, per cent immunoreactive cells, or IRS did not correlate with RECIST response, TTBR, PFS or OS, including on multivariate analysis. Heterogeneity of staining was seen in 22% of cases and did not correlate with outcome. CONCLUSION: In the current study population, IHC-measured pre-treatment BRAF(V600E) protein expression does not predict response or outcome to BRAF inhibitor therapy in BRAF(V600E) metastatic melanoma patients.