Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related death worldwide. We sequenced and analyzed the whole genomes of 27 HCCs, 25 of which were associated with hepatitis B or C virus infections, including two sets of multicentric tumors. Although no common somatic mutations were identified in the multicentric tumor pairs, their whole-genome substitution patterns were similar, suggesting that these tumors developed from independent mutations, although their shared etiological backgrounds may have strongly influenced their somatic mutation patterns. Statistical and functional analyses yielded a list of recurrently mutated genes. Multiple chromatin regulators, including ARID1A, ARID1B, ARID2, MLL and MLL3, were mutated in ∼50% of the tumors. Hepatitis B virus genome integration in the TERT locus was frequently observed in a high clonal proportion. Our whole-genome sequencing analysis of HCCs identified the influence of etiological background on somatic mutation patterns and subsequent carcinogenesis, as well as recurrent mutations in chromatin regulators in HCCs.

We present redshift evolution of galaxy effective radius r e obtained from the Hubble Space Telescope (HST) samples of ∼ 190, 000 galaxies at z = 0 − 10. Our HST samples consist of 176, 152 photo-z galaxies at z = 0 − 6 from the 3D-HST+CANDELS catalogue and 10, 454 Lyman break galaxies (LBGs) at z = 4 − 10 identified in CANDELS, HUDF09/12, and HFF parallel fields, providing the largest data set to date for galaxy size evolution studies. We derive r e with the same technique over the wide-redshift range of z = 0 − 10, evaluating the optical-to-UV morphological K-correction and the selection bias of photo-z galaxies+LBGs as well as the cosmological surface brightness dimming effect. We find that r e values at a given luminosity significantly decrease towards high-z, regardless of statistics choices (e.g. r e ∝ (1 + z) −1.10±0.06 for median). For star-forming galaxies, there is no evolution of the power-law slope of the size-luminosity relation and the median Sérsic index (n ∼ 1.5). Moreover, the r e -distribution is well represented by log-normal functions whose standard deviation σ ln re does not show significant evolution within the range of σ ln re ∼ 0.45 − 0.75. We calculate the stellar-to-halo size ratio from our r e measurements and the dark-matter halo masses estimated from the abundance matching study, and obtain a nearly constant value of r e /r vir = 1.0 − 3.5% at z = 0 − 8. The combination of the r e -distribution shape+standard deviation, the constant r e /r vir , and n ∼ 1.5 suggests a picture that typical high-z star-forming galaxies have disk-like stellar components in a sense of dynamics and morphology over cosmic time of z ∼ 0 − 6. If high-z star-forming galaxies are truly dominated by disks, the r e /r vir value and the disk formation model indicate that the specific angular momentum of the disk normalized by the host halo is j d /m d ≃ 0.5 − 1. These are statistical results for galaxies' major stellar components, and the detailed study of clumpy sub-components is presented in the paper II.

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Liver cancer, which is most often associated with virus infection, is prevalent worldwide, and its underlying etiology and genomic structure are heterogeneous. Here we provide a whole-genome landscape of somatic alterations in 300 liver cancers from Japanese individuals. Our comprehensive analysis identified point mutations, structural variations (STVs), and virus integrations, in noncoding and coding regions. We discovered mutational signatures related to liver carcinogenesis and recurrently mutated coding and noncoding regions, such as long intergenic noncoding RNA genes (NEAT1 and MALAT1), promoters, CTCF-binding sites, and regulatory regions. STV analysis found a significant association with replication timing and identified known (CDKN2A, CCND1, APC, and TERT) and new (ASH1L, NCOR1, and MACROD2) cancer-related genes that were recurrently affected by STVs, leading to altered expression. These results emphasize the value of whole-genome sequencing analysis in discovering cancer driver mutations and understanding comprehensive molecular profiles of liver cancer, especially with regard to STVs and noncoding mutations.