Computational protocol: Risk of colorectal cancer for carriers of a germline mutation in POLE or POLD1

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Protocol publication

[…] We searched in PubMed for relevant studies published prior to October 2016 that reported pedigree and cancer data for families with germline POLE or POLD1 variants that were either novel or previously observed at population frequency of ≤0.002 according to the non-Finnish European population in the ExAC database, given recent evidence that shows low variant allele frequency is an important guide for determining disease causing variants. Variants identified from the literature were re-annotated, for consistency, via in silico methods using Annovar with default settings. We applied a criteria for predicting pathogenicity of missense variants in both genes as recommended by the American College of Medical Genetics and Genomics (ACMG), namely using (i) multiple commonly used in silico tools (SIFT, PolyPhen2, MutationTaster, CADD, GERP, REVEL, and M-CAP ( for references)) and (ii) a high level of consensus between multiple in silico tools for prediction of deleterious effect. For this study, we applied the recommended or default thresholds for prediction of deleteriousness for each of the seven in silico tools (see for thresholds). For each variant, the sum of in silico tools that reported the variant to be deleterious was calculated (maximum score of 7). A variant was considered to be likely pathogenic for this study where ≥4 out of 7 in silico tools predicted the variant to have a deleterious effect (). Families were excluded from the penetrance analysis if they were: (i) families of probands with variants not predicted to be pathogenic by <4 out of the 7 in silico tools used; (ii) discovery families that originally described the POLE c.1270C>G p.Leu424Val and POLD1 c.1433G>A p.Ser478Asn variants; (iii) families of carriers of de novo mutations; or (iv) uninformative due to missing information on sex or age at cancer diagnosis of probands. For those families included in the analysis, mutation carrier status, sex, cancer or polyp-affected status, age at cancer or polyp/polyposis diagnosis, last known age or death, and country of study of families were extracted, where possible, from identified studies.We searched for POLE or POLD1 mutation carrier families by genotyping 669 population-based probands diagnosed with CRC before 60 years of age from the Australasian Colorectal Cancer Family Registry (ACCFR), () for 17 rare germline variants within the exonuclease domains of the POLE and POLD1 genes ( and ). These 17 variants were selected based on multiple sources namely: 1) rare germline variants in the exonuclease domains of POLE and POLD1 reported in the ExAC database (≤0.002 allele frequency), 2) variants identified from our in-house whole genome and whole exome sequencing studies of 100 multiple-case CRC-affected families from the clinic-based recruitment arm of the Australasian Colorectal Cancer Family Registry (ACCFR) that were either rare or novel variants according to ExAC database (≤0.002 allele frequency), 3) were reported in the discovery paper by Palles et al, and 4) were predicted to be deleterious by ≥4 out of the 7 in silico tools.Using data from both published studies and the ACCFR, we estimated the hazard ratio (HR) and corresponding 95% confidence interval (CI) of CRC for mutation carriers compared with the general population (based on age, sex- and country-specific incidences) and the age-specific cumulative risks (penetrance), using a modified segregation analysis that incorporated data of all family members whether genotyped or not, and whether affected or not. We properly adjusted for ascertainment of families in which each pedigree’s data was conditioned on the proband’s genotype, cancer status and age at diagnosis (for population-based families) or on the proband’s genotype, and the cancer statuses and ages at diagnoses of all family members (for clinic-based families) to produce unbiased estimates (see details in ). All statistical tests were two-sided, and P-values less than 0.05 were considered statistically significant. […]

Pipeline specifications

Software tools ANNOVAR, PolyPhen, MutationTaster, M-CAP
Application WES analysis