Dataset Information

Using Somatic Mutations from Tumors to Classify Variants in Mismatch Repair Genes.

ABSTRACT: Present guidelines for classification of constitutional variants do not incorporate inferences from mutations seen in tumors, even when these are associated with a specific molecular phenotype. When somatic mutations and constitutional mutations lead to the same molecular phenotype, as for the mismatch repair genes, information from somatic mutations may enable interpretation of previously unclassified variants. To test this idea, we first estimated likelihoods that somatic variants in MLH1, MSH2, MSH6, and PMS2 drive microsatellite instability and characteristic IHC staining patterns by calculating likelihoods of high versus low normalized variant read fractions of 153 mutations known to be pathogenic versus those of 760 intronic passenger mutations from 174 paired tumor-normal samples. Mutations that explained the tumor mismatch repair phenotype had likelihood ratio for high variant read fraction of 1.56 (95% CI 1.42-1.71) at sites with no loss of heterozygosity and of 26.5 (95% CI 13.2-53.0) at sites with loss of heterozygosity. Next, we applied these ratios to 165 missense, synonymous, and splice variants observed in tumors, combining in a Bayesian analysis the likelihood ratio corresponding with the adjusted variant read fraction with pretest probabilities derived from published analyses and public databases. We suggest classifications for 86 of 165 variants: 7 benign, 31 likely benign, 22 likely pathogenic, and 26 pathogenic. These results illustrate that for mismatch repair genes, characterization of tumor mutations permits tumor mutation data to inform constitutional variant classification. We suggest modifications to incorporate molecular phenotype in future variant classification guidelines.

SUBMITTER: Shirts BH

PROVIDER: S-EPMC6035155 | biostudies-literature | 2018 Jul

REPOSITORIES: biostudies-literature

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Using Somatic Mutations from Tumors to Classify Variants in Mismatch Repair Genes.

Shirts Brian H BH Konnick Eric Q EQ Upham Sarah S Walsh Tom T Ranola John Michael O JMO Jacobson Angela L AL King Mary-Claire MC Pearlman Rachel R Hampel Heather H Pritchard Colin C CC

American journal of human genetics 20180607 1

Present guidelines for classification of constitutional variants do not incorporate inferences from mutations seen in tumors, even when these are associated with a specific molecular phenotype. When somatic mutations and constitutional mutations lead to the same molecular phenotype, as for the mismatch repair genes, information from somatic mutations may enable interpretation of previously unclassified variants. To test this idea, we first estimated likelihoods that somatic variants in MLH1, MSH ...[more]

PMID: 29887214

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Project description:Background & aimsSome colorectal and endometrial tumors with microsatellite instability not attributable to MLH1 hypermethylation or germline mutations contain 2 or more somatic mutations in genes encoding mismatch repair (MMR) proteins. We sought to define the molecular phenotype of this newly recognized tumor subtype.MethodsFrom 2 prospective studies of the efficacy of screening for Lynch syndrome, we identified patients with colorectal and endometrial tumors who had 2 or more somatic (but not germline) mutations in genes encoding MMR proteins (double somatic). We determined the frequencies of tumor mutations in PIK3CA, BRAF, KRAS, NRAS, and PTEN by targeted next-generation sequencing and used logistic-regression models to compare them with those from patients with Lynch syndrome, MLH1-hypermethylated, or microsatellite-stable tumors. We validated our findings using independent data sets from The Cancer Genome Atlas.ResultsAmong colorectal cancer cases, we found that 14 of 21 (67%) patients with double somatic tumors also had PIK3CA mutations, compared with 4 of 18 (22%) tumors from patients with Lynch syndrome, 2 of 10 (20%) tumors with MLH1 hypermethylation, and 12 of 78 (15%) tumors with microsatellite stability (P < .0001 for patients with double somatic tumors vs other subgroups). Mutations in PIK3CA were detected in all 13 patients with double somatic endometrial cancers (P = .04 compared with other subgroups). We did not detect BRAF mutations in patients with double somatic colorectal tumors or Lynch syndrome. We found highly similar results in a validation cohort from The Cancer Genome Atlas (113 patients with colorectal tumors, 178 endometrial tumors); 100% of double somatic cases had a somatic mutation in PIK3CA (P < .0001 compared with other subgroups).ConclusionsMost patients with colorectal or endometrial tumors with 2 or more somatic (but not germline) mutations in MMR proteins also have mutations in PIK3CA; mutations in PIK3CA are detected at substantially higher frequencies in these double somatic tumors than in other microsatellite-instability subgroups. PIK3CA mutation status might be used to identify a specific group of colorectal tumors, and to select treatment or determine prognosis.

Project description:Gastrointestinal stromal tumors (GISTs) are rare but treatable soft tissue sarcomas. Nearly all GISTs have somatic mutations in either the KIT or PDGFRA gene, but there are no known inherited genetic risk factors. We assessed the relationship between KIT/PDGFRA mutations and select deletions or single nucleotide polymorphisms (SNPs) in 279 participants from a clinical trial of adjuvant imatinib mesylate. Given previous evidence that certain susceptibility loci and carcinogens are associated with characteristic mutations, or "signatures" in other cancers, we hypothesized that the characteristic somatic mutations in the KIT and PDGFRA genes in GIST tumors may similarly be mutational signatures that are causally linked to specific mutagens or susceptibility loci. As previous epidemiologic studies suggest environmental risk factors such as dioxin and radiation exposure may be linked to sarcomas, we chose 208 variants in 39 candidate genes related to DNA repair and dioxin metabolism or response. We calculated adjusted odds ratios (ORs) and 95% confidence intervals (CIs) for the association between each variant and 7 categories of tumor mutation using logistic regression. We also evaluated gene-level effects using the sequence kernel association test (SKAT). Although none of the association p-values were statistically significant after adjustment for multiple comparisons, SNPs in CYP1B1 were strongly associated with KIT exon 11 codon 557-8 deletions (OR = 1.9, 95% CI: 1.3-2.9 for rs2855658 and OR = 1.8, 95% CI: 1.2-2.7 for rs1056836) and wild type GISTs (OR = 2.7, 95% CI: 1.5-4.8 for rs1800440 and OR = 0.5, 95% CI: 0.3-0.9 for rs1056836). CYP1B1 was also associated with these mutations categories in the SKAT analysis (p = 0.002 and p = 0.003, respectively). Other potential risk variants included GSTM1, RAD23B and ERCC2. This preliminary analysis of inherited genetic risk factors for GIST offers some clues about the disease's genetic origins and provides a starting point for future candidate gene or gene-environment research.

Dataset Information

Using Somatic Mutations from Tumors to Classify Variants in Mismatch Repair Genes.

Publications

Using Somatic Mutations from Tumors to Classify Variants in Mismatch Repair Genes.

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