Insights for precision oncology from the integration of genomic and clinical data of 13,880 tumors from the 100,000 Genomes Cancer Programme.

The Cancer Programme of the 100,000 Genomes Project was an initiative to provide whole-genome sequencing (WGS) for patients with cancer, evaluating opportunities for precision cancer care within the UK National Healthcare System (NHS). Genomics England, alongside NHS England, analyzed WGS data from 13,880 solid tumors spanning 33 cancer types, integrating genomic data with real-world treatment and outcome data, within a secure Research Environment. Incidence of somatic mutations in genes recommended for standard-of-care testing varied across cancer types. For instance, in glioblastoma multiforme, small variants were present in 94% of cases and copy number aberrations in at least one gene in 58% of cases, while sarcoma demonstrated the highest occurrence of actionable structural variants (13%). Homologous recombination deficiency was identified in 40% of high-grade serous ovarian cancer cases with 30% linked to pathogenic germline variants, highlighting the value of combined somatic and germline analysis. The linkage of WGS and longitudinal life course clinical data allowed the assessment of treatment outcomes for patients stratified according to pangenomic markers. Our findings demonstrate the utility of linking genomic and real-world clinical data to enable survival analysis to identify cancer genes that affect prognosis and advance our understanding of how cancer genomics impacts patient outcomes.

Habitual coffee intake and risk for nonalcoholic fatty liver disease: a two-sample Mendelian randomization study.

PURPOSE: Epidemiological studies support a protective role of habitual coffee and caffeine consumption against the risk of non-alcoholic fatty liver disease (NAFLD). We aimed to investigate the causal relationship between coffee intake and the risk of NAFLD. METHODS: We performed a two-sample Mendelian randomization (MR) analysis using SNPs associated with habitual coffee intake in a published genome-wide association study (GWAS) as genetic instruments and summary-level data from a published GWAS of NAFLD (1122 cases and 399,900 healthy controls) in the UK Biobank. The causal relationship was estimated with the inverse weighted method using a 4-SNP and 6-SNP instrument based on the single largest non-UK Biobank GWAS (n = 91,462) and meta-analysis (n = 121,524) of GWAS data on habitual coffee intake, respectively. To maximize power, we also used up to 77 SNPs associated with coffee intake at a liberal significance level (p ≤ 1e-4) as instruments. RESULTS: We observed a non-significant trend towards a causal protective effect of coffee intake on NAFLD based upon either the 4-SNP (OR: 0.76; 95% CI 0.51, 1.14, p = 0.19) or 6-SNP genetic instruments (OR: 0.77; 95% CI 0.48, 1.25, p = 0.29). The result also remains non-significant when using the more liberal 77-SNP instrument. CONCLUSION: Our findings do not support a causal relationship between coffee intake and NAFLD risk. However, despite the largest-to-date sample size, the power of this study may be limited by the non-specificity and moderate effect size of the genetic alleles on coffee intake.