Michael T. Parsons

This study investigates the use of microsatellite loci for estimating relatedness between individuals in wild, outbred, vertebrate populations. We measured allele frequencies at 20 unlinked, dinucleotide-repeat microsatellite loci in a population of wild mice (Mus musculus), and used these observed frequencies to generate the expected distributions of pairwise relatedness among full sib, half sib, and unrelated pairs of individuals, as would be estimated from the microsatellite data. In this population one should be able to discriminate between unrelated and full-sib dyads with at least 97% accuracy, and to discriminate half-sib pairs from unrelated pairs or from full-sib pairs with better than 80% accuracy. If one uses the criterion that parent-offspring pairs must share at least one allele per locus, then only 15% of full-sib pairs, 2% of half-sib pairs, and 0% of unrelated pairs in this population would qualify as potential parent-offspring pairs. We verified that the simulation results (which assume a random mating population in Hardy-Weinberg and linkage equilibrium) accurately predict results one would obtain from this population in real life by scoring laboratory-bred full- and half-sib families whose parents were wild-caught mice from the study population. We also investigated the effects of using different numbers of loci, or loci of different average heterozygosities (He), on misclassification frequencies. Both variables have strong effects on misclassification rate. For example, it requires almost twice as many loci of He = 0.62 to achieve the same accuracy as a given number of loci He = 0.75. Finally, we tested the ability of UPGMA clustering to identify family groups in our population. Clustering of allele matching scores among the offspring of four sets of independent maternal half sibships (four females, each mated to two different males) perfectly recovered the true family relationships.

Colorectal cancer (CRC) that demonstrates microsatellite instability (MSI) is caused by either germline mismatch repair (MMR) gene mutations, or 'sporadic' somatic tumour MLH1 promoter methylation. MLH1 promoter methylation is reportedly correlated with tumour BRAF V600E mutation status. No systematic review has been undertaken to assess the value of BRAF V600E mutation and MLH1 promoter methylation tumour markers as negative predictors of germline MMR mutation status. A literature review of CRC cohorts tested for MMR mutations, and tumour BRAF V600E mutation and/or MLH1 promoter methylation was conducted using PubMed. Studies were assessed for tumour features, stratified by tumour MMR status based on immunohistochemistry or MSI where possible. Pooled frequencies and 95% CIs were calculated using a random effects model. BRAF V600E results for 4562 tumours from 35 studies, and MLH1 promoter methylation results for 2975 tumours from 43 studies, were assessed. In 550 MMR mutation carriers, the BRAF V600E mutation frequency was 1.40% (95% CI 0.06% to 3%). In MMR mutation-negative cases, the BRAF V600E mutation frequency was 5.00% (95% CI 4% to 7%) in 1623 microsatellite stable (MSS) cases and 63.50% (95% CI 47% to 79%) in 332 cases demonstrating MLH1 methylation or MLH1 expression loss. MLH1 promoter methylation of the 'A region' was reported more frequently than the 'C region' in MSS CRCs (17% vs 0.06%, p<0.0001) and in MLH1 mutation carriers (42% vs 6%, p<0.0001), but not in MMR mutation-negative MSI-H CRCs (40% vs 47%, p=0.12). Methylation of the 'C region' was a predictor of MMR mutation-negative status in MSI-H CRC cases (47% vs 6% in MLH1 mutation carriers, p<0.0001). This review demonstrates that tumour BRAF V600E mutation, and MLH1 promoter 'C region' methylation specifically, are strong predictors of negative MMR mutation status. It is important to incorporate these features in multifactorial models aimed at predicting MMR mutation status.

The prevalence and spectrum of germline mutations in BRCA1 and BRCA2 have been reported in single populations, with the majority of reports focused on White in Europe and North America. The Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA) has assembled data on 18,435 families with BRCA1 mutations and 11,351 families with BRCA2 mutations ascertained from 69 centers in 49 countries on six continents. This study comprehensively describes the characteristics of the 1,650 unique BRCA1 and 1,731 unique BRCA2 deleterious (disease-associated) mutations identified in the CIMBA database. We observed substantial variation in mutation type and frequency by geographical region and race/ethnicity. In addition to known founder mutations, mutations of relatively high frequency were identified in specific racial/ethnic or geographic groups that may reflect founder mutations and which could be used in targeted (panel) first pass genotyping for specific populations. Knowledge of the population-specific mutational spectrum in BRCA1 and BRCA2 could inform efficient strategies for genetic testing and may justify a more broad-based oncogenetic testing in some populations.

Pathogenic variants in highly penetrant genes are useful for the diagnosis, therapy, and surveillance for hereditary breast cancer. Large-scale studies are needed to inform future testing and variant classification processes in Japanese. We performed a case-control association study for variants in coding regions of 11 hereditary breast cancer genes in 7051 unselected breast cancer patients and 11,241 female controls of Japanese ancestry. Here, we identify 244 germline pathogenic variants. Pathogenic variants are found in 5.7% of patients, ranging from 15% in women diagnosed <40 years to 3.2% in patients ≥80 years, with BRCA1/2, explaining two-thirds of pathogenic variants identified at all ages. BRCA1/2, PALB2, and TP53 are significant causative genes. Patients with pathogenic variants in BRCA1/2 or PTEN have significantly younger age at diagnosis. In conclusion, BRCA1/2, PALB2, and TP53 are the major hereditary breast cancer genes, irrespective of age at diagnosis, in Japanese women.