A polymorphism in IRF4 affects human pigmentation through a tyrosinase-dependent MITF/TFAP2A pathway.

Sequence polymorphisms linked to human diseases and phenotypes in genome-wide association studies often affect noncoding regions. A SNP within an intron of the gene encoding Interferon Regulatory Factor 4 (IRF4), a transcription factor with no known role in melanocyte biology, is strongly associated with sensitivity of skin to sun exposure, freckles, blue eyes, and brown hair color. Here, we demonstrate that this SNP lies within an enhancer of IRF4 transcription in melanocytes. The allele associated with this pigmentation phenotype impairs binding of the TFAP2A transcription factor that, together with the melanocyte master regulator MITF, regulates activity of the enhancer. Assays in zebrafish and mice reveal that IRF4 cooperates with MITF to activate expression of Tyrosinase (TYR), an essential enzyme in melanin synthesis. Our findings provide a clear example of a noncoding polymorphism that affects a phenotype by modulating a developmental gene regulatory network.

Enhancing predictions of patient conveyance using emergency call handler free text notes for unconscious and fainting incidents reported to the London Ambulance Service.

OBJECTIVE: Pre-hospital emergency medical services use clinical decision support systems (CDSS) to triage calls. Call handlers often supplement this by making free text notes covering key incident information. We investigate whether machine learning approaches using features from such free text notes can improve prediction of unconscious patients who require conveyance. MATERIALS AND METHODS: We analysed a subset of all London Ambulance Service calls that were triaged through the Medical Priority Dispatch System (MPDS) as involving an unconscious or fainting patient in 2018. We use and compare two machine learning algorithms: random forest (RF) and gradient boosting machine (GBM). For each incident, we predict whether the patient will be conveyed to a hospital emergency department or equivalent using as features 1) the MPDS code, 2) the free text notes and 3) the two together. We evaluate model performance using the area under the curve (AUC) metric. Given the imbalance of outcomes (patient conveyed 71 %, not conveyed 29 %), we also consider sensitivity and specificity. RESULTS: Using only the MPDS code resulted in an AUC of 0.57. Using the text notes gave an improved AUC score of 0.63 and combining the two gave an AUC score of 0.64 (scores were similar for RF and GBM). GBM models scored better on sensitivity (0.93 vs 0.62 for RF in the combined model), but specificity was lower (0.17 vs. 0.56 for RF in the combined model). CONCLUSIONS: Using information contained in the free text notes made by call handlers in combination with MPDS improves prediction of unconscious and fainting patients requiring conveyance to a hospital emergency department (or equivalent) when compared with machine learning models using MPDS codes only. This suggests there is some useful information in unstructured data captured by emergency call handlers that complements MPDS codes. Quantifying this gain can help inform emergency medical service policy when evaluating the decision to expand or augment existing CDSS.

Endometrial tumour BRAF mutations and MLH1 promoter methylation as predictors of germline mismatch repair gene mutation status: a literature review.

Colorectal cancer (CRC) that displays high microsatellite instability (MSI-H) can be caused by either germline mutations in mismatch repair (MMR) genes, or non-inherited transcriptional silencing of the MLH1 promoter. A correlation between MLH1 promoter methylation, specifically the 'C' region, and BRAF V600E status has been reported in CRC studies. Germline MMR mutations also greatly increase risk of endometrial cancer (EC), but no systematic review has been undertaken to determine if these tumour markers may be useful predictors of MMR mutation status in EC patients. Endometrial cancer cohorts meeting review inclusion criteria encompassed 2675 tumours from 20 studies for BRAF V600E, and 447 tumours from 11 studies for MLH1 methylation testing. BRAF V600E mutations were reported in 4/2675 (0.1%) endometrial tumours of unknown MMR mutation status, and there were 7/823 (0.9%) total sequence variants in exon 11 and 27/1012 (2.7%) in exon 15. Promoter MLH1 methylation was not observed in tumours from 32 MLH1 mutation carriers, or for 13 MSH2 or MSH6 mutation carriers. MMR mutation-negative individuals with tumour MLH1 and PMS2 IHC loss displayed MLH1 methylation in 48/51 (94%) of tumours. We have also detailed specific examples that show the importance of MLH1 promoter region, assay design, and quantification of methylation. This review shows that BRAF mutations occurs so infrequently in endometrial tumours they can be discounted as a useful marker for predicting MMR-negative mutation status, and further studies of endometrial cohorts with known MMR mutation status are necessary to quantify the utility of tumour MLH1 promoter methylation as a marker of negative germline MMR mutation status in EC patients.

Tumor mismatch repair immunohistochemistry and DNA MLH1 methylation testing of patients with endometrial cancer diagnosed at age younger than 60 years optimizes triage for population-level germline mismatch repair gene mutation testing.

PURPOSE: Clinicopathologic data from a population-based endometrial cancer cohort, unselected for age or family history, were analyzed to determine the optimal scheme for identification of patients with germline mismatch repair (MMR) gene mutations. PATIENTS AND METHODS: Endometrial cancers from 702 patients recruited into the Australian National Endometrial Cancer Study (ANECS) were tested for MMR protein expression using immunohistochemistry (IHC) and for MLH1 gene promoter methylation in MLH1-deficient cases. MMR mutation testing was performed on germline DNA of patients with MMR-protein deficient tumors. Prediction of germline mutation status was compared for combinations of tumor characteristics, age at diagnosis, and various clinical criteria (Amsterdam, Bethesda, Society of Gynecologic Oncology, ANECS). RESULTS: Tumor MMR-protein deficiency was detected in 170 (24%) of 702 cases. Germline testing of 158 MMR-deficient cases identified 22 truncating mutations (3% of all cases) and four unclassified variants. Tumor MLH1 methylation was detected in 99 (89%) of 111 cases demonstrating MLH1/PMS2 IHC loss; all were germline MLH1 mutation negative. A combination of MMR IHC plus MLH1 methylation testing in women younger than 60 years of age at diagnosis provided the highest positive predictive value for the identification of mutation carriers at 46% versus ≤ 41% for any other criteria considered. CONCLUSION: Population-level identification of patients with MMR mutation-positive endometrial cancer is optimized by stepwise testing for tumor MMR IHC loss in patients younger than 60 years, tumor MLH1 methylation in individuals with MLH1 IHC loss, and germline mutations in patients exhibiting loss of MSH6, MSH2, or PMS2 or loss of MLH1/PMS2 with absence of MLH1 methylation.