Melanoma risk prediction using a multilocus genetic risk score in the Women's Health Initiative cohort

Cho, Hyunje G.; Ransohoff, Katherine J.; Hedlin, Haley; Assimes, Themistocles L.; Han, Jiali; Stefanick, Marcia L.; Tang, Jean Y.; Sarin, Kavita Y.

doi:10.1016/j.jaad.2018.02.052

Cited by 22 publications

(18 citation statements)

References 14 publications

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“…Conversely, in our study we observed a significant NRI that was driven by improvements in specificity and sensitivity, particularly specificity. The Women’s Health Initiative cohort recently showed a 2-fold increased risk of melanoma for the highest versus lowest tertile of genetic risk score comprising 21 SNPs ( Cho et al., 2018 ), compared with a 3-fold difference in our studies. They had limited information on phenotypic risk factors ( Cho et al., 2018 ).…”

Section: Discussioncontrasting

confidence: 57%

“…The Women’s Health Initiative cohort recently showed a 2-fold increased risk of melanoma for the highest versus lowest tertile of genetic risk score comprising 21 SNPs ( Cho et al., 2018 ), compared with a 3-fold difference in our studies. They had limited information on phenotypic risk factors ( Cho et al., 2018 ). We observed a larger improvement to risk prediction based on ORs from the study datasets, but this is likely due to model overfitting ( Wray et al., 2013 ).…”

Section: Discussioncontrasting

confidence: 57%

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Assessing the Incremental Contribution of Common Genomic Variants to Melanoma Risk Prediction in Two Population-Based Studies

Drummond

Kanetsky

Goldstein

et al. 2018

Journal of Investigative Dermatology

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It is unclear to what degree genomic and traditional (phenotypic and environmental) risk factors overlap in their prediction of melanoma risk. We evaluated the incremental contribution of common genomic variants (in pigmentation, nevus, and other pathways) and their overlap with traditional risk factors, using data from two population-based case-control studies from Australia (n = 1,035) and the United Kingdom (n = 1,460) that used the same questionnaires. Polygenic risk scores were derived from 21 gene regions associated with melanoma and odds ratios from published meta-analyses. Logistic regression models were adjusted for age, sex, center, and ancestry. Adding the polygenic risk score to a model with traditional risk factors increased the area under the receiver operating characteristic curve (AUC) by 2.3% (P = 0.003) for Australia and by 2.8% (P = 0.002) for Leeds. Gene variants in the pigmentation pathway, particularly MC1R, were responsible for most of the incremental improvement. In a cross-tabulation of polygenic by traditional tertile risk scores, 59% (Australia) and 49% (Leeds) of participants were categorized in the same (concordant) tertile. Of participants with low traditional risk, 9% (Australia) and 21% (Leeds) had high polygenic risk. Testing of genomic variants can identify people who are susceptible to melanoma despite not having a traditional phenotypic risk profile.

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Section: Discussioncontrasting

confidence: 57%

Section: Discussioncontrasting

confidence: 57%

Assessing the Incremental Contribution of Common Genomic Variants to Melanoma Risk Prediction in Two Population-Based Studies

Drummond

Kanetsky

Goldstein

et al. 2018

Journal of Investigative Dermatology

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“…Postmenopausal women with the highest PRS tertile had increased melanoma prevalence (OR 1·91, 95% CI 1·50–2·42) and incidence (hazard ratio 1·89, 95% CI 1·42–2·52), compared with the lowest tertile. Small improvements in risk prediction were observed [AUC increase of 0·075 (prevalent), 0·068 (incident)] …”

Section: Resultsmentioning

confidence: 99%

Genome‐wide association studies and polygenic risk scores for skin cancer: clinically useful yet?

Roberts

Asgari

Toland³

2019

Br J Dermatol

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Summary Background Genome‐wide association studies (GWAS) have identified thousands of susceptibility variants, although most have been associated with small individual risk estimates that offer little predictive value. However, combining multiple variants into polygenic risk scores (PRS) may be more informative. Multiple studies have developed PRS composed of GWAS‐identified variants for cutaneous cancers. This review highlights data from these studies. Objectives To review published GWAS and PRS studies for melanoma, cutaneous squamous cell carcinoma (cSCC) and basal cell carcinoma (BCC), and discuss their potential clinical utility. Methods We searched PubMed and the National Human Genome Research Institute–European Bioinformatics Institute GWAS catalogue to identify relevant studies. Results Results from 21 GWAS (11 melanoma, 3 cSCC, 7 BCC) and 11 PRS studies are summarized. Six loci in pigmentation genes overlap between these three cancers (ASIP/RALY, IRF4, MC1R, OCA2, SLC45A2 and TYR). Additional loci overlap for cSCC/BCC and BCC/melanoma, but no other loci are shared between cSCC and melanoma. PRS for melanoma show roughly two‐to‐threefold increases in risk and modest improvements in risk prediction (2–7% increases). PRS are associated with twofold and threefold increases in risk of cSCC and BCC, respectively, with small improvements (2% increase) in predictive ability. Conclusions Existing data indicate that PRS may offer small, but potentially meaningful, improvements to risk prediction. Additional research is needed to clarify the potential utility of PRS in cutaneous carcinomas. Clinical translation will require well‐powered validation studies incorporating known risk factors to evaluate PRS as tools for screening. What's already known about this topic? Over 50 susceptibility loci for melanoma, basal cell carcinoma (BCC) and cutaneous squamous cell carcinoma (cSCC) have been identified in genome‐wide association studies (GWAS). Polygenic risk scores (PRS) using variants identified from GWAS have also been developed for melanoma, BCC and cSCC, and investigated with respect to clinical risk prediction. What does this study add? This review provides an overview of GWAS findings and the potential clinical utility of PRS for melanoma, BCC and cSCC.

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“…Melanoma of the skin is associated with multiple risk factors besides exposure to UV radiation (e.g., sun and tanning bed) and age, such as ethnicity (Caucasian population), history of blistering sunburns at young age, dysplastic nevi, family history, occupational chemicals’ exposure (e.g., arsenic), fair skin and hair (blonde or red hair) and immunosuppression [5]. A risk associated with male sex has been described, but postmenopausal women have shown different genetic patterns (polymorphisms), which increase the risk of developing melanoma by 1.9 times [6]. Nonetheless, melanoma of the skin can be prevented if the exposure to previous external factors, such as exposure to sun or tanning, is reduced.…”

Section: Risk Factors Biomarkers and Prevention Of Melanoma Of The Skinmentioning

confidence: 99%

Holistic view of patients with melanoma of the skin: how can health systems create value and achieve better clinical outcomes?

Redondo

Ribeiro

Lopes

et al. 2019

ecancer

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Patients with skin cancer should be treated in healthcare units that ensure holistic and multidisciplinary approaches. Current healthcare units, especially those dedicated to cancer care, must evolve to integrated patient-centred systems. The current review presents a holistic health services perspective towards managing patients with melanoma of the skin, based on a literature search. It includes a detailed discussion on how this could impact on the patient, his or her quality of life and on service providers. Data from a multidisciplinary integrated practice unit, specialised in skin cancer, were also discussed, namely, for outcomes measurements, access to innovative treatments, valuebased healthcare, patient centricity and use of integrated systems. Epidemiology data, including disease determinants and risk factors, play an important role in defining measures, resources and management of these integrated cancer units. To optimise effective care and improve survival outcomes, integrated cancer clinics should comprise, in a patient-centred way, innovative treatments and technologies, along with continuous training and creation of multidisciplinary units of healthcare professionals. Measurement of outcomes, such as clinical, quality of life and cost, is decisive in determining affordability and access to the best available state-of-the-art care. Besides, treatment of melanoma has significantly improved over recent years, but with increasing costs, which brings a challenging mission to guarantee access to treatment and quality care. Value-based healthcare allows the achievement of better health outcomes and higher quality services while reducing the costs associated with the full-care cycle. Therefore, current healthcare systems should develop in line with health institutions' organisation and culture, increasing adherence to best practices and create value.

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Melanoma risk prediction using a multilocus genetic risk score in the Women's Health Initiative cohort

Abstract: Higher genetic risk is associated with increased melanoma prevalence and incidence in postmenopausal women, but current genetic information may have a limited role in risk prediction when phenotypic information is available.

Cited by 22 publications

References 14 publications

Assessing the Incremental Contribution of Common Genomic Variants to Melanoma Risk Prediction in Two Population-Based Studies

Assessing the Incremental Contribution of Common Genomic Variants to Melanoma Risk Prediction in Two Population-Based Studies

Genome‐wide association studies and polygenic risk scores for skin cancer: clinically useful yet?

Holistic view of patients with melanoma of the skin: how can health systems create value and achieve better clinical outcomes?

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