Estimating CDKN2A carrier probability and personalizing cancer risk assessments in hereditary melanoma using melaPRO

Wenyi Wang, Kristin B. Niendorf, Devanshi Patel, Amanda Blackford, Fabio Marroni, Arthur J. Sober, Giovanni Parmigiani, Hensin Tsao

Research output: Contribution to journalArticlepeer-review

25 Scopus citations

Abstract

Personalized cancer risk assessment remains an essential imperative in postgenomic cancer medicine. In hereditary melanoma, germline CDKN2A mutations have been reproducibly identified in melanoma-prone kindreds worldwide. However, genetic risk counseling for hereditary melanoma remains clinically challenging. To address this challenge, we developed and validated MelaPRO, an algorithm that provides germline CDKN2A mutation probabilities and melanoma risk to individuals from melanoma-prone families. MelaPRO builds on comprehensive genetic information, and uses Mendelian modeling to provide fine resolution and high accuracy. In an independent validation of 195 individuals from 167 families, MelaPRO exhibited good discrimination with a concordance index (C) of 0.86 [95% confidence intervals (95% CI), 0.75-0.97] and good calibration, with no significant difference between observed and predicted carriers (26; 95% CI, 20-35, as compared with 22 observed). In cross-validation, MelaPRO outperformed the existing predictive model MELPREDICT (C, 0.82; 95% CI, 0.61-0.93), with a difference of 0.05 (95% CI, 0.007-0.17). MelaPRO is a clinically accessible tool that can effectively provide personalized risk counseling for all members of hereditary melanoma families.

Original languageEnglish (US)
Pages (from-to)552-559
Number of pages8
JournalCancer Research
Volume70
Issue number2
DOIs
StatePublished - Jan 15 2010

Fingerprint Dive into the research topics of 'Estimating CDKN2A carrier probability and personalizing cancer risk assessments in hereditary melanoma using melaPRO'. Together they form a unique fingerprint.

Cite this