Literature DB >> 33837773

Genomic Risk Score for Melanoma in a Prospective Study of Older Individuals.

Andrew Bakshi1, Mabel Yan1, Moeen Riaz1, Galina Polekhina1, Suzanne G Orchard1, Jane Tiller1, Rory Wolfe1, Amit Joshi2, Yin Cao3, Aideen M McInerney-Leo4, Tatiane Yanes4, Monika Janda4,5, H Peter Soyer4, Anne E Cust6, Matthew H Law7,8, Peter Gibbs9, Catriona McLean9, Andrew T Chan2, John J McNeil1, Victoria J Mar1,10, Paul Lacaze1.   

Abstract

BACKGROUND: Recent genome-wide association meta-analysis for melanoma doubled the number of previously identified variants. We assessed the performance of an updated polygenic risk score (PRS) in a population of older individuals, where melanoma incidence and cumulative ultraviolet radiation exposure is greatest.
METHODS: We assessed a PRS for cutaneous melanoma comprising 55 variants in a prospective study of 12 712 individuals in the ASPirin in Reducing Events in the Elderly Trial. We evaluated incident melanomas diagnosed during the trial and prevalent melanomas diagnosed preenrolment (self-reported). Multivariable models examined associations between PRS as a continuous variable (per SD) and categorical (low-risk [0%-20%], medium-risk [21%-80%], high-risk [81%-100%] groups) with incident melanoma. Logistic regression examined the association between PRS and prevalent melanoma.
RESULTS: At baseline, mean participant age was 75 years; 55.0% were female, and 528 (4.2%) had prevalent melanomas. During follow-up (median = 4.7 years), 120 (1.0%) incident cutaneous melanomas occurred, 98 of which were in participants with no history. PRS was associated with incident melanoma (hazard ratio = 1.46 per SD, 95% confidence interval [CI] = 1.20 to 1.77) and prevalent melanoma (odds ratio [OR] = 1.55 per SD, 95% CI = 1.42 to 1.69). Participants in the highest-risk PRS group had increased risk compared with the low-risk group for incident melanoma (OR = 2.51, 95% CI = 1.28 to 4.92) and prevalent melanoma (OR = 3.66, 95% CI = 2.69 to 5.05). When stratifying by sex, only males had an association between the PRS and incident melanoma, whereas both sexes had an association between the PRS and prevalent melanoma.
CONCLUSIONS: A genomic risk score is associated with melanoma risk in older individuals and may contribute to targeted surveillance.
© The Author(s) 2021. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.

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Year:  2021        PMID: 33837773      PMCID: PMC8921762          DOI: 10.1093/jnci/djab076

Source DB:  PubMed          Journal:  J Natl Cancer Inst        ISSN: 0027-8874            Impact factor:   11.816


  37 in total

1.  Changing trends in the incidence of invasive melanoma in Victoria, 1985-2015.

Authors:  David J Curchin; Victoria R Harris; Christopher J McCormack; Saxon D Smith
Journal:  Med J Aust       Date:  2018-04-02       Impact factor: 7.738

2.  Prediction of Melanoma Risk in a Southern European Population Based on a Weighted Genetic Risk Score.

Authors:  Katerina P Kypreou; Irene Stefanaki; Kyriaki Antonopoulou; Fani Karagianni; Georgios Ntritsos; Alexios Zaras; Vasiliki Nikolaou; Iro Kalfa; Vasiliki Chasapi; Dorothea Polydorou; Helen Gogas; George M Spyrou; Lars Bertram; Christina M Lill; John P A Ioannidis; Christina Antoniou; Evangelos Evangelou; Alexander I Stratigos
Journal:  J Invest Dermatol       Date:  2015-12-14       Impact factor: 8.551

Review 3.  Genome-wide association studies and polygenic risk scores for skin cancer: clinically useful yet?

Authors:  M R Roberts; M M Asgari; A E Toland
Journal:  Br J Dermatol       Date:  2019-07-07       Impact factor: 9.302

4.  Development and external validation study of a melanoma risk prediction model incorporating clinically assessed naevi and solar lentigines.

Authors:  K Vuong; B K Armstrong; M Drummond; J L Hopper; J H Barrett; J R Davies; D T Bishop; J Newton-Bishop; J F Aitken; G G Giles; H Schmid; M A Jenkins; G J Mann; K McGeechan; A E Cust
Journal:  Br J Dermatol       Date:  2019-09-22       Impact factor: 9.302

5.  The validity of self-reported cancer in an Australian population study.

Authors:  Venurs Loh; Jessica Harding; Vira Koshkina; Elizabeth Barr; Jonathan Shaw; Dianna Magliano
Journal:  Aust N Z J Public Health       Date:  2014-02       Impact factor: 2.939

6.  Effect of Aspirin on Disability-free Survival in the Healthy Elderly.

Authors:  John J McNeil; Robyn L Woods; Mark R Nelson; Christopher M Reid; Brenda Kirpach; Rory Wolfe; Elsdon Storey; Raj C Shah; Jessica E Lockery; Andrew M Tonkin; Anne B Newman; Jeff D Williamson; Karen L Margolis; Michael E Ernst; Walter P Abhayaratna; Nigel Stocks; Sharyn M Fitzgerald; Suzanne G Orchard; Ruth E Trevaks; Lawrence J Beilin; Geoffrey A Donnan; Peter Gibbs; Colin I Johnston; Joanne Ryan; Barbara Radziszewska; Richard Grimm; Anne M Murray
Journal:  N Engl J Med       Date:  2018-09-16       Impact factor: 91.245

7.  pROC: an open-source package for R and S+ to analyze and compare ROC curves.

Authors:  Xavier Robin; Natacha Turck; Alexandre Hainard; Natalia Tiberti; Frédérique Lisacek; Jean-Charles Sanchez; Markus Müller
Journal:  BMC Bioinformatics       Date:  2011-03-17       Impact factor: 3.307

8.  Genome-wide association study identifies a new melanoma susceptibility locus at 1q21.3.

Authors:  Stuart Macgregor; Grant W Montgomery; Jimmy Z Liu; Zhen Zhen Zhao; Anjali K Henders; Mitchell Stark; Helen Schmid; Elizabeth A Holland; David L Duffy; Mingfeng Zhang; Jodie N Painter; Dale R Nyholt; Judith A Maskiell; Jodie Jetann; Megan Ferguson; Anne E Cust; Mark A Jenkins; David C Whiteman; Håkan Olsson; Susana Puig; Giovanna Bianchi-Scarrà; Johan Hansson; Florence Demenais; Maria Teresa Landi; Tadeusz Dębniak; Rona Mackie; Esther Azizi; Brigitte Bressac-de Paillerets; Alisa M Goldstein; Peter A Kanetsky; Nelleke A Gruis; David E Elder; Julia A Newton-Bishop; D Timothy Bishop; Mark M Iles; Per Helsing; Christopher I Amos; Qingyi Wei; Li-E Wang; Jeffrey E Lee; Abrar A Qureshi; Richard F Kefford; Graham G Giles; Bruce K Armstrong; Joanne F Aitken; Jiali Han; John L Hopper; Jeffrey M Trent; Kevin M Brown; Nicholas G Martin; Graham J Mann; Nicholas K Hayward
Journal:  Nat Genet       Date:  2011-10-09       Impact factor: 38.330

Review 9.  Cutaneous melanoma: From pathogenesis to therapy (Review).

Authors:  Giulia C Leonardi; Luca Falzone; Rossella Salemi; Antonino Zanghì; Demetrios A Spandidos; James A Mccubrey; Saverio Candido; Massimo Libra
Journal:  Int J Oncol       Date:  2018-02-27       Impact factor: 5.650

Review 10.  Risk prediction models for melanoma: a systematic review.

Authors:  Juliet A Usher-Smith; Jon Emery; Angelos P Kassianos; Fiona M Walter
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2014-06-03       Impact factor: 4.254

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  6 in total

1.  Using the Prediction Model Risk of Bias Assessment Tool (PROBAST) to Evaluate Melanoma Prediction Studies.

Authors:  Isabelle Kaiser; Sonja Mathes; Annette B Pfahlberg; Wolfgang Uter; Carola Berking; Markus V Heppt; Theresa Steeb; Katharina Diehl; Olaf Gefeller
Journal:  Cancers (Basel)       Date:  2022-06-20       Impact factor: 6.575

2.  Aspirin and the Risk of Colorectal Cancer According to Genetic Susceptibility among Older Individuals.

Authors:  Andrew Bakshi; Yin Cao; Paul Lacaze; Andrew T Chan; Suzanne G Orchard; Prudence R Carr; Amit D Joshi; Alisa K Manning; Daniel D Buchanan; Asad Umar; Ingrid M Winship; Peter Gibbs; John R Zalcberg; Finlay Macrae; John J McNeil
Journal:  Cancer Prev Res (Phila)       Date:  2022-07-05

3.  A Polygenic Risk Score Predicts Incident Prostate Cancer Risk in Older Men but Does Not Select for Clinically Significant Disease.

Authors:  Andrew Bakshi; Moeen Riaz; Suzanne G Orchard; Prudence R Carr; Amit D Joshi; Yin Cao; Richard Rebello; Tú Nguyen-Dumont; Melissa C Southey; Jeremy L Millar; Lucy Gately; Peter Gibbs; Leslie G Ford; Howard L Parnes; Andrew T Chan; John J McNeil; Paul Lacaze
Journal:  Cancers (Basel)       Date:  2021-11-19       Impact factor: 6.639

4.  Reporting Quality of Studies Developing and Validating Melanoma Prediction Models: An Assessment Based on the TRIPOD Statement.

Authors:  Isabelle Kaiser; Katharina Diehl; Markus V Heppt; Sonja Mathes; Annette B Pfahlberg; Theresa Steeb; Wolfgang Uter; Olaf Gefeller
Journal:  Healthcare (Basel)       Date:  2022-01-26

5.  Independent evaluation of melanoma polygenic risk scores in UK and Australian prospective cohorts.

Authors:  Julia Steinberg; Mark M Iles; Jin Yee Lee; Xiaochuan Wang; Matthew H Law; Amelia K Smit; Tu Nguyen-Dumont; Graham G Giles; Melissa C Southey; Roger L Milne; Graham J Mann; D Timothy Bishop; Robert J MacInnis; Anne E Cust
Journal:  Br J Dermatol       Date:  2022-03-31       Impact factor: 11.113

Review 6.  Value of PET imaging for radiation therapy.

Authors:  Constantin Lapa; Ursula Nestle; Nathalie L Albert; Christian Baues; Ambros Beer; Andreas Buck; Volker Budach; Rebecca Bütof; Stephanie E Combs; Thorsten Derlin; Matthias Eiber; Wolfgang P Fendler; Christian Furth; Cihan Gani; Eleni Gkika; Anca-L Grosu; Christoph Henkenberens; Harun Ilhan; Steffen Löck; Simone Marnitz-Schulze; Matthias Miederer; Michael Mix; Nils H Nicolay; Maximilian Niyazi; Christoph Pöttgen; Claus M Rödel; Imke Schatka; Sarah M Schwarzenboeck; Andrei S Todica; Wolfgang Weber; Simone Wegen; Thomas Wiegel; Constantinos Zamboglou; Daniel Zips; Klaus Zöphel; Sebastian Zschaeck; Daniela Thorwarth; Esther G C Troost
Journal:  Strahlenther Onkol       Date:  2021-07-14       Impact factor: 3.621

  6 in total

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