The Melanocortin 1 receptor and its influence on naevi and melanoma in dark‐skinned phenotypes

Smith, David John Mackay

doi:10.1111/ajd.12982

Cited by 3 publications

(3 citation statements)

References 49 publications

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“…Additionally, it is known that various high, moderate, and low‐risk germline polymorphisms and candidate single nucleotide polymorphisms (SNPs) influence the susceptibility and prognosis in cutaneous melanoma 23 . It is thought that melanocortin 1 receptor variants may have an effect on both melanoma development and the number and morphology of nevi regardless of phenotype 24 . Recent studies have shown that low‐penetrance melanoma susceptibility genes or SNPs and MITF E318K variants are not only indicators of high melanoma risk, but they also influence nevus count 25 .…”

Section: Discussionmentioning

confidence: 99%

“…23 It is thought that melanocortin 1 receptor variants may have an effect on both melanoma development and the number and morphology of nevi regardless of phenotype. 24 Recent studies have shown that low-penetrance melanoma susceptibility genes or SNPs and MITF E318K variants are not only indicators of high melanoma risk, but they also influence nevus count. 25 Based on this information, we argue that there is a strong correlation between melanoma and nevus count, not because melanoma arises on a preexisting nevus but because they share a common genetic basis.…”

Section: Discussionmentioning

confidence: 99%

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Comparison of phenotypic features in patients with single vs multiple primary cutaneous melanomas: a prospective single‐center study

et al. 2022

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Background There is sparse data regarding total body nevus count (TBNC), nevus count in specific locations, phenotypic factors, anthropometric indices, sunburn, and the relation to multiple primary cutaneous melanomas (MPCM) development. We aim to compare these variables in a cohort of patients diagnosed with single primary melanoma (SPM) and MPCM with histologic diagnoses of melanoma in situ, superficial spreading, and nodular melanoma in our clinic.Methods Prospective observational studies for the evaluation of nevus counts in biopsyproven melanoma patients from 2017 to 2020 at Ankara University were conducted. Age, gender, family history of melanoma, increased sun exposure, nonmelanoma skin cancers (NMSC), height, sunburn history, TBNC, and nevi count in specific anatomical locations were evaluated by multivariate logistic regression analysis.Results A total number of 156 patients consisting of 22 MPCM and 134 SPM were included. Mean TBNC for SPM vs MPCM patients were 96.87 (SD AE 124.71) vs 247.00 (SD AE 261.58), respectively (P < 0.0001). TBNC was correlated to the left arm, trunk, lower extremity, and head and neck nevus counts but not with the right arm nevus count.Multiple regression analysis showed that having more than 10 nevi on the head and neck area is associated with MPCM (OR, 3.882 [95% CI, 1.084-13.899]). TBNC and nevus count in specific locations were found to be significantly higher in MPCM. ConclusionThe risk of MPCM was associated with having ≥10 nevi on the head and neck.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Comparison of phenotypic features in patients with single vs multiple primary cutaneous melanomas: a prospective single‐center study

et al. 2022

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“…This is most strongly expressed in the red hair phenotype with its extreme sensitivity to UV exposure 21 . It has been shown that in the Australia approximately 50% of the population carry at least one of these dysfunctional MC1R genes making sun exposure pattern choices and protective measures vital to maintaining good health 22 . Both MC1R and ET-1 influence localisation of XPA, in nuclear and chromatin fractions, on UV exposure.…”

Section: Dna Damage Response In Melanocytesmentioning

confidence: 99%

Circadian rhythms: influence on skin cancer and exposure paradigms

Smith

2022

MRAJ

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Approximately 10% of genes oscillate according to a circadian clock. Even though cells are capable of independent oscillation there is a master controller in the brain, the suprachiasmatic nucleus (SCN), that provides a coordinated response throughout the body, influenced by daily and seasonal patterns of light and heat. These genes have widely varied functions but are significantly influential in DNA damage repair, the cell cycle, cellular proliferation and apoptosis, as well as metabolic function. Normal circadian rhythms are essential for the body’s natural defence against disease and cancer. Deregulation may enhance the capacity for carcinogenesis in the skin and the influence of the circadian clock helps explain two of the anomalies of melanoma exposure patterns: A higher incidence amongst indoor as opposed to outdoor workers and on intermittently as opposed chronically exposed skin.

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m5C-Related Signatures for Predicting Prognosis in Cutaneous Melanoma with Machine Learning

Huang

Zhang

et al. 2021

Journal of Oncology

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Background. Cutaneous melanoma (CM) is one of the most life-threatening primary skin cancers and is prone to distant metastases. A widespread presence of posttranscriptional modification of RNA, 5-methylcytosine (m5C), has been observed in human cancers. However, the potential mechanism of the tumorigenesis and prognosis in CM by dysregulated m5C-related regulators is obscure. Methods. We use comprehensive bioinformatics analyses to explore the expression of m5C regulators in CM, the prognostic implications of the m5C regulators, the frequency of the copy number variant (CNV), and somatic mutations in m5C regulators. Additionally, the CM patients were divided into three clusters for better predicting clinical features and outcomes via consensus clustering of m5C regulators. Then, the risk score was established via Lasso Cox regression analysis. Next, the prognosis value and clinical characteristics of m5C-related signatures were further explored. Then, machine learning was used to recognize the outstanding m5C regulators to risk score. Finally, the expression level and clinical value of USUN6 were analyzed via the tissue microarray (TMA) cohort. Results. We found that m5C regulators were dysregulated in CM, with a high frequency of somatic mutations and CNV alterations of the m5C regulatory gene in CM. Furthermore, 16 m5C-related proteins interacted with each other frequently, and we divided CM patients into three clusters to better predicting clinical features and outcomes. Then, five m5C regulators were selected as a risk score based on the LASSO model. The XGBoost algorithm recognized that NOP2 and NSUN6 were the most significant risk score contributors. Immunohistochemistry has verified that low expression of USUN6 was closely correlated with CM progression. Conclusion. The m5C-related signatures can be used as new prognostic biomarkers and therapeutic targets for CM, and NSUN6 might play a vital role in tumorigenesis and malignant progression.

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The Melanocortin 1 receptor and its influence on naevi and melanoma in dark‐skinned phenotypes

Cited by 3 publications

References 49 publications

Comparison of phenotypic features in patients with single vs multiple primary cutaneous melanomas: a prospective single‐center study

Comparison of phenotypic features in patients with single vs multiple primary cutaneous melanomas: a prospective single‐center study

Circadian rhythms: influence on skin cancer and exposure paradigms

m5C-Related Signatures for Predicting Prognosis in Cutaneous Melanoma with Machine Learning

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