Correlation of tumour BRAF mutations and MLH1 methylation with germline mismatch repair (MMR) gene mutation status: a literature review assessing utility of tumour features for MMR variant classification.

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.