Journal article
A Multifactorial Likelihood Model for MMR Gene Variant Classification Incorporating Probabilities Based on Sequence Bioinformatics and Tumor Characteristics: A Report from the Colon Cancer Family Registry
BA Thompson, DE Goldgar, C Paterson, M Clendenning, R Walters, S Arnold, MT Parsons, WD Michael, S Gallinger, RW Haile, JL Hopper, MA Jenkins, L Lemarchand, NM Lindor, PA Newcomb, SN Thibodeau, JP Young, DD Buchanan, SV Tavtigian, AB Spurdle
Human Mutation | WILEY | Published : 2013
DOI: 10.1002/humu.22213
Abstract
Mismatch repair (MMR) gene sequence variants of uncertain clinical significance are often identified in suspected Lynch syndrome families, and this constitutes a challenge for both researchers and clinicians. Multifactorial likelihood model approaches provide a quantitative measure of MMR variant pathogenicity, but first require input of likelihood ratios (LRs) for different MMR variation-associated characteristics from appropriate, well-characterized reference datasets. Microsatellite instability (MSI) and somatic BRAF tumor data for unselected colorectal cancer probands of known pathogenic variant status were used to derive LRs for tumor characteristics using the Colon Cancer Family Regist..
View full abstractGrants
Awarded by National Cancer Institute
Funding Acknowledgements
Contract Grant sponsors: National Health and Medical Research Council (496616); Cancer Australia (1010859); NIH National Cancer Institute (RFA CA-95-011); Australasian Colorectal Cancer Family Registry (UO1 CA097735); USC Familial Colorectal Neoplasia Collaborative Group (UO1 CA074799); Mayo Clinic Cooperative Family Registry for Colon Cancer Studies (UO1 CA074800); Ontario Registry for Studies of Familial Colorectal Cancer (UO1 CA074783); Seattle Colorectal Cancer Family Registry (UO1 CA074794); University of Hawaii Colorectal Cancer Family Registry (UO1 CA074806); University of California, Irvine Informatics Center (U01 CA078296).We thank the many families in the Colon CFR who have participated in the research programs, and the Australian Red Cross Blood Services (ARCBS) donors who participated as healthy controls in this study. We are grateful to Rachel Morris and the staff at ARCBS for their assistance with the collection of risk factor information and blood samples, and Melanie Higgins, Kimberley Hinze, Felicity Lose, and members of the Molecular Cancer Epidemiology Laboratory for their assistance with collection and processing of blood samples. We also acknowledge Russell Bell for his assistance in the set up of the LOVD Website. B. A. T was awarded a Ph.D. scholarship from the Cancer Council Queensland. A. B. S. is an NHMRC Senior Research Fellow. This work was supported by the National Cancer Institute, National Institutes of Health under RFA#CA-95-011 and through cooperative agreements with members of the Colon CFR and P.I.s. The content of this manuscript does not necessarily reflect the views or policies of the National Cancer Institute or any of the collaborating centers in the CFRs, nor does mention of trade names, commercial products, or organizations imply endorsement by the US Government or the CFR. None of the authors have a conflict of interest.