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s41588-024-01785-9.pdf

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Mutation rates varied across the different cancer types with cuta-<lb/>neous melanoma having the highest single nucleotide variant mutation <lb/>count and meningioma the lowest (Extended Data Fig. 2). A total of 945 <lb/>samples, notably colorectal and uterine cancers, were hypermutated, <lb/>either as result of defective mismatch repair (dMMR) or POLE mutation. <lb/>Invasive ductal carcinoma of the breast had the highest power for driver <lb/>gene detection (&gt;90% power for a mutation rate of at least 2% higher <lb/>than background) and large cell lung cancer had the lowest power (Fig. 2 <lb/>and Supplementary Table 4). Compared with the recent Pan-Cancer <lb/>Analysis of Whole Genomes analysis 12 , the 100kGP cohort was better <lb/>powered to identify a driver mutation for 19 cancers, notably for breast, <lb/>colorectal, esophageal and uterine cancer, lung adenocarcinoma and <lb/>bladder transitional cell carcinoma where the sample sizes were more <lb/>than tenfold higher. <lb/>Spectrum of cancer driver genes <lb/>Across all cancer types we identified 770 unique tumor-driver gene <lb/>pairs corresponding to 330 unique candidate cancer driver genes <lb/>(Fig. 3, Extended Data Fig. 3 and Supplementary Table 5). When <lb/>

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vision of precision oncology through WGS to National Health Service <lb/>(NHS) patients as part of their routine care 11 . <lb/>Here, we report an analysis of WGS data on 10,478 patients span-<lb/>ning 35 cancer types recruited to the 100kGP (Fig. 1a). Across all cancer <lb/>types we identify 330 candidate driver genes, including 74 which are <lb/>new to any cancer. We relate these to their actionability both in terms <lb/>of currently approved therapeutic agents and through computational <lb/>chemogenomic analysis to predict candidacy for future clinical trials. <lb/>Results <lb/>We analysed 10,478 cancer genomes spanning 35 different cancer types <lb/>(Fig. 1b and Supplementary Tables 1 and 2). While broadly reflecting <lb/>the spectrum and frequencies of cancers diagnosed in the UK popula-<lb/>tion, there were differences, with an over-representation of colorectal <lb/>and kidney cancers and a paucity of prostate and pancreatic cancers <lb/>(Extended Data Fig. 1). Additionally, for the main cancer types, the <lb/>patients recruited to 100kGP tended to be younger and had earlier <lb/>stage tumors compared to patients in the general UK population (Sup-<lb/>plementary Table 3). <lb/>

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