The association between dermoscopic features and BRAF mutational status in cutaneous melanoma: Significance of the blue-white veil

Armengot‐Carbó, Miquel; Nagore, Eduardo; García-Casado, Zaida; Botella‐Estrada, Rafael

doi:10.1016/j.jaad.2017.12.064

Cited by 14 publications

(19 citation statements)

References 33 publications

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“…We found that the majority of dermoscopically similar multiple melanomas showed atypical network or regression structures as the prevalent criterion, in line with our previous findings . Recently, retrospective and prospective studies demonstrated that specific dermoscopic features of melanomas are associated with somatic BRAF mutational pattern, suggesting a potential influence of BRAF alterations on the dermoscopic appearance. However, we could not identify a specific dermoscopic prevalent criterion for concordant mutation‐positive or mutation‐negative similar melanomas, probably due to the low number of concordant cases.…”

Section: Discussionsupporting

confidence: 91%

“…BRAF mutational status has been associated with dermoscopic appearance of sporadic primary melanoma in a few studies . Two observational retrospective studies showed a correlation between BRAF mutations and the presence of “peppering,” irregular streaks and ulceration .…”

Section: Introductionmentioning

confidence: 99%

“…Two observational retrospective studies showed a correlation between BRAF mutations and the presence of “peppering,” irregular streaks and ulceration . In addition, Armengot‐Carbò et al recently found an association of younger age at diagnosis and dermoscopic blue‐white with BRAF mutation and developed a model based on these two features predicting with good accuracy the occurrence of BRAF mutational status. However, there is no knowledge about the association between dermoscopic aspects of multiple melanomas and BRAF mutational status …”

Section: Introductionmentioning

confidence: 99%

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Dermoscopic similarity is an independent predictor of BRAF mutational concordance in multiple melanomas

Moscarella

Pellegrini

Pampena

et al. 2019

Experimental Dermatology

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Background The association of clinical and dermoscopic features with BRAF mutational status has been poorly analysed in multiple primary melanomas (MPM). Objective To investigate whether concordance of BRAF mutational status is associated with dermoscopic similarity in multiple melanomas of the same patient. Methods Dermoscopic images and corresponding tissue sections of 124 melanomas from 62 patients with MPM were selected at four Italian Dermatology Departments. Similarity of dermoscopic appearance between multiple melanomas was evaluated according to the presence of the same prevalent dermoscopic feature. The BRAFV600 mutational status was analysed with allele‐specific TaqManTM assays or pyrosequencing. Spearman's correlation and univariate and multivariate regression analysis were used for statistical analysis. Results A similar dermoscopic appearance was identified in 38.7% (24/62) of patients with MPM and was correlated with older age at first diagnosis (rho: 0.26; P: 0.042) and occurrence on sun‐damaged skin (rho: 0.27; P: 0.037). The BRAFV600 mutation was detected in 39.5% (49/124) of the tumors and a concordant BRAF mutational status between melanomas in 33/62 (53.2%) MPM patients. Dermoscopically similar melanomas showed 5.7‐fold higher odds to be concordant for BRAF mutational status compared to dissimilar lesions (OR: 5.7; 95% CI 1.7‐19.5; P: 0.005). Conclusion Dermoscopic similarity of multiple melanomas represents an independent clinical predictor of a concordant BRAF mutational status in MPM patients.

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Section: Discussionsupporting

confidence: 91%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Dermoscopic similarity is an independent predictor of BRAF mutational concordance in multiple melanomas

Moscarella

Pellegrini

Pampena

et al. 2019

Experimental Dermatology

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“…Specific morphologic signatures associated with mutated BRAF have been described independently with dermoscopy 19 , reflectance confocal microscopy 20 , and histology 14, 21 . Histologic features include greater pagetoid scatter, intraepidermal nesting, epidermal thickening, better circumscription, larger rounder and more pigmented melanocytes, and less solar elastosis.…”

Section: Discussionmentioning

confidence: 99%

A Deep Learning Approach for Rapid Mutational Screening in Melanoma

Kim

Nomikou

Coudray³

et al. 2019

Preprint

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36DNA-based molecular assays for determining mutational status in melanomas are time-37 consuming and costly. As an alternative, we applied a deep convolutional neural network 38 (CNN) to histopathology images of tumors from 257 melanoma patients and developed a 39 fully automated model that first selects for tumor-rich areas (Area under the curve 40 AUC=0.98), and second, predicts for the presence of mutated BRAF or NRAS. Network 41 performance was enhanced on BRAF-mutated melanomas 1.0 mm (AUC=0.83) and on 42 non-ulcerated NRAS-mutated melanomas (AUC=0.92). Applying our models to 43 histological images of primary melanomas from The Cancer Genome Atlas database also 44 demonstrated improved performances on thinner BRAF-mutated melanomas and non-45 ulcerated NRAS-mutated melanomas. We propose that deep learning-based analysis of 46 histological images has the potential to become integrated into clinical decision making 47 for the rapid detection of mutations of interest in melanoma. 48 49 50 Mutations in the BRAF oncogene are found in 50-60% of all melanomas 1 , while NRAS 51 mutations comprise an additional 15-20%. With the development of targeted therapies 2, 52 3 , determining the mutational status of BRAF and NRAS has become an integral 53 component for the management of Stage III/IV melanomas. DNA molecular assays such 54 as Sanger sequencing, pyrosequencing, and next generation sequencing (NGS) are the 55 current gold standard to determine mutational status 4 . However, these methods are costly 56 and time-consuming. Immunohistochemistry, real-time polymerase chain reaction (PCR), 57 and automated platforms 5, 6, 7 are rapid and less expensive alternatives, but are limited to 58 screening for specific mutations, such as BRAF-V600E/K or NRAS-Q61R/L, and may 59 potentially fail to identify rare mutational variants in patients that might have otherwise 60 benefited from adjuvant targeted therapy.61 62 Deep Convolutional Neural Network (CNN) methods to predict mutational status have 63 been demonstrated in other solid tumors. CNNs utilize multiple layers of convolution 64 operations, pooling layers, and fully connected layers to perform classification of images 65 to classes of interest through identification of various image features often not directly 66 detectable by the human eye. Deep CNNs, which utilize non-linear learning algorithms, 67have been successful in manipulating and processing large data sets, particularly for 68 image analysis 8 . Using images from The Cancer Genome Atlas (TCGA), a collaborative 69 cancer genomics database 9 , our group has previously developed a machine learning 70 algorithm that can predict for 6 different genes, including EGFR and STK11, in lung 71 carcinoma 10 . In breast cancer, deep learning applied to tumor microarray images has 72 been shown to predict for ER status with an 84% accuracy 11 . 73 74 In this study, we adapt our previous deep learning algorithm to a different dataset 75 comprised of histopathology images of primary melanomas resected from patients 76 pros...

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“…In addition to the early detection of melanoma, the dermatoscopy provides some details about the presence of the BRAF mutation that has changed the therapeutical approach in recent years. It is reported that the presence of blue-white veil is highly associated with BRAF mutation (28). The appearance of blue-gray colored peppering is more common in the melanomas that showed MAPK (BRAF and NRAS) mutation (29).…”

Section: öZmentioning

confidence: 99%

The Role of Diagnostic Approaches to Determine the Treatment

Eskiocak¹,

Durdu²

2018

tdd

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The diagnosis of dermatological diseases requires cytological, dermatoscopic, histopathological examinations, some laboratory tests, and radiology imaging in addition to clinical examination. However, these tests are quite important, not only in time of diagnosis, but also in patient follow ups and determining the therapeutic approach. In this article, the diagnostic tests are reviewed that may help to dermatologists in detecting the treatment of dermatological diseases.

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The association between dermoscopic features and BRAF mutational status in cutaneous melanoma: Significance of the blue-white veil

Cited by 14 publications

References 33 publications

Dermoscopic similarity is an independent predictor of BRAF mutational concordance in multiple melanomas

Dermoscopic similarity is an independent predictor of BRAF mutational concordance in multiple melanomas

A Deep Learning Approach for Rapid Mutational Screening in Melanoma

The Role of Diagnostic Approaches to Determine the Treatment

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