We analysed whole-genome sequences of 560 breast cancers to advance understanding of the driver mutations conferring clonal advantage and the mutational processes generating somatic mutations. We found that 93 protein-coding cancer genes carried probable driver mutations. Some non-coding regions exhibited high mutation frequencies, but most have distinctive structural features probably causing elevated mutation rates and do not contain driver mutations. Mutational signature analysis was extended to genome rearrangements and revealed twelve base substitution and six rearrangement signatures. Three rearrangement signatures, characterized by tandem duplications or deletions, appear associated with defective homologous-recombination-based DNA repair: one with deficient BRCA1 function, another with deficient BRCA1 or BRCA2 function, the cause of the third is unknown. This analysis of all classes of somatic mutation across exons, introns and intergenic regions highlights the repertoire of cancer genes and mutational processes operating, and progresses towards a comprehensive account of the somatic genetic basis of breast cancer.

Hepatic resection is the most curative treatment option for early‐stage hepatocellular carcinoma, but is associated with a high recurrence rate, which exceeds 50% at 5 years after surgery. Understanding the genetic basis of hepatocellular carcinoma at surgically curable stages may enable the identification of new molecular biomarkers that accurately identify patients in need of additional early therapeutic interventions. Whole exome sequencing and copy number analysis was performed on 231 hepatocellular carcinomas (72% with hepatitis B viral infection) that were classified as early‐stage hepatocellular carcinomas, candidates for surgical resection. Recurrent mutations were validated by Sanger sequencing. Unsupervised genomic analyses identified an association between specific genetic aberrations and postoperative clinical outcomes. Recurrent somatic mutations were identified in nine genes, including TP53, CTNNB1, AXIN1, RPS6KA3, and RB1. Recurrent homozygous deletions in FAM123A, RB1, and CDKN2A, and high‐copy amplifications in MYC, RSPO2, CCND1, and FGF19 were detected. Pathway analyses of these genes revealed aberrations in the p53, Wnt, PIK3/Ras, cell cycle, and chromatin remodeling pathways. RB1 mutations were significantly associated with cancer‐specific and recurrence‐free survival after resection (multivariate P = 0.038 and P = 0.012, respectively). FGF19 amplifications, known to activate Wnt signaling, were mutually exclusive with CTNNB1 and AXIN1 mutations, and significantly associated with cirrhosis (P = 0.017). Conclusion: RB1 mutations can be used as a prognostic molecular biomarker for resectable hepatocellular carcinoma. Further study is required to investigate the potential role of FGF19 amplification in driving hepatocarcinogenesis in patients with liver cirrhosis and to investigate the potential of anti‐FGF19 treatment in these patients. (Hepatology 2014;60:1971–1981)

We present the first Korean individual genome sequence (SJK) and analysis results. The diploid genome of a Korean male was sequenced to 28.95-fold redundancy using the Illumina paired-end sequencing method. SJK covered 99.9% of the NCBI human reference genome. We identified 420,083 novel single nucleotide polymorphisms (SNPs) that are not in the dbSNP database. Despite a close similarity, significant differences were observed between the Chinese genome (YH), the only other Asian genome available, and SJK: (1) 39.87% (1,371,239 out of 3,439,107) SNPs were SJK-specific (49.51% against Venter's, 46.94% against Watson's, and 44.17% against the Yoruba genomes); (2) 99.5% (22,495 out of 22,605) of short indels (< 4 bp) discovered on the same loci had the same size and type as YH; and (3) 11.3% (331 out of 2920) deletion structural variants were SJK-specific. Even after attempting to map unmapped reads of SJK to unanchored NCBI scaffolds, HGSV, and available personal genomes, there were still 5.77% SJK reads that could not be mapped. All these findings indicate that the overall genetic differences among individuals from closely related ethnic groups may be significant. Hence, constructing reference genomes for minor socio-ethnic groups will be useful for massive individual genome sequencing.

Accurate and physiologically meaningful biomarkers for human aging are key to assessing antiaging therapies. Given ethnic differences in health, diet, lifestyle, behavior, environmental exposures, and even average rate of biological aging, it stands to reason that aging clocks trained on datasets obtained from specific ethnic populations are more likely to account for these potential confounding factors, resulting in an enhanced capacity to predict chronological age and quantify biological age. Here, we present a deep learning-based hematological aging clock modeled using the large combined dataset of Canadian, South Korean, and Eastern European population blood samples that show increased predictive accuracy in individual populations compared to population specific hematologic aging clocks. The performance of models was also evaluated on publicly available samples of the American population from the National Health and Nutrition Examination Survey (NHANES). In addition, we explored the association between age predicted by both population specific and combined hematological clocks and all-cause mortality. Overall, this study suggests (a) the population specificity of aging patterns and (b) hematologic clocks predicts all-cause mortality. The proposed models were added to the freely-available Aging.AI system expanding the range of tools for analysis of human aging.