Whole-genome sequencing identifies recurrent mutations in hepatocellular carcinoma
Zhengyan Kan,Hancheng Zheng,Xiao Liu,Shuyu Li,Thomas D. Barber,Zhuolin Gong,Huan Gao,Ke Hao,Melinda D. Willard,Jiangchun Xu,Robert Hauptschein,Paul A. Rejto,Julio Fernandez,Guan Wang,Qinghui Zhang,Bo Wang,Ronghua Chen,Jian Wang,Nikki P. Lee,Wei Zhou,Zhao Lin,Zhiyu Peng,Kang Yi,Shengpei Chen,Lin Li,Xiaomei Fan,Jie Yang,Rui Ye,Jia Ju,Kai Wang,Heather Estrella,Shibing Deng,Ping Wei,Ming Qiu,Isabella H. Wulur,Jiangang Liu,Mariam Ehsani,Chunsheng Zhang,Andrey Loboda,Wing-Kin Sung,Wing-Kin Sung,Amit Aggarwal,Ronnie T.P. Poon,Sheung Tat Fan,Jun Wang,James S. Hardwick,James S. Hardwick,Christoph Reinhard,Hongyue Dai,Yingrui Li,John M. Luk,John M. Luk,John M. Luk,Mao Mao,Mao Mao +54 more
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TLDR
Findings from a whole-genome sequencing study of 88 matched HCC tumor/normal pairs, 81 of which are Hepatitis B virus (HBV) positive, find beta-catenin to be the mostrequently mutated oncogene and TP53 the most frequently mutated tumor suppressor.Abstract:
Hepatocellular carcinoma (HCC) is one of the most deadly cancers worldwide and has no effective treatment, yet the molecular basis of hepatocarcinogenesis remains largely unknown. Here we report findings from a whole-genome sequencing (WGS) study of 88 matched HCC tumor/normal pairs, 81 of which are Hepatitis B virus (HBV) positive, seeking to identify genetically altered genes and pathways implicated in HBV-associated HCC. We find beta-catenin to be the most frequently mutated oncogene (15.9%) and TP53 the most frequently mutated tumor suppressor (35.2%). The Wnt/beta-catenin and JAK/STAT pathways, altered in 62.5% and 45.5% of cases, respectively, are likely to act as two major oncogenic drivers in HCC. This study also identifies several prevalent and potentially actionable mutations, including activating mutations of Janus kinase 1 (JAK1), in 9.1% of patients and provides a path toward therapeutic intervention of the disease.read more
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Patterns of Somatic Mutation in Human Cancer Genomes
TL;DR: In this paper, the coding exons of the family of 518 protein kinases were sequenced in 210 cancers of diverse histological types to explore the nature of the information that will be derived from cancer genome sequencing.
Integrative Genomics Viewer
James T. Robinson,Helga Thorvaldsdottir,Wendy Winckler,Mitchell Guttman,Eric S. Lander,Eric S. Lander,Gad Getz,Jill P. Mesirov +7 more
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Targeting the IL-6/JAK/STAT3 signalling axis in cancer.
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Exome sequencing of hepatocellular carcinomas identifies new mutational signatures and potential therapeutic targets
Kornelius Schulze,Sandrine Imbeaud,Eric Letouzé,Ludmil B. Alexandrov,Ludmil B. Alexandrov,Julien Calderaro,Sandra Rebouissou,Gabrielle Couchy,Clément Meiller,Jayendra Shinde,Frédéric Soysouvanh,Anna Line Calatayud,Roser Pinyol,Laura Pelletier,Charles Balabaud,Alexis Laurent,Jean-Frédéric Blanc,Vincenzo Mazzaferro,Fabien Calvo,Augusto Villanueva,Jean-Charles Nault,Paulette Bioulac-Sage,Michael R. Stratton,Josep M. Llovet,Josep M. Llovet,Jessica Zucman-Rossi +25 more
TL;DR: Exome sequencing analysis of 243 liver tumors identified mutational signatures associated with specific risk factors, mainly combined alcohol and tobacco consumption and exposure to aflatoxin B1, and defined the extensive landscape of altered genes and pathways in HCC.
Journal ArticleDOI
Landscape of Infiltrating T Cells in Liver Cancer Revealed by Single-Cell Sequencing
Chunhong Zheng,Liangtao Zheng,Jae-Kwang Yoo,Huahu Guo,Yuanyuan Zhang,Guo Xinyi,Boxi Kang,Ruozhen Hu,Julie Y. Huang,Qiming Zhang,Zhouzerui Liu,Minghui Dong,Xueda Hu,Wenjun Ouyang,Jirun Peng,Jirun Peng,Zemin Zhang +16 more
TL;DR: Deep single-cell RNA sequencing on 5,063 single T cells isolated from peripheral blood, tumor, and adjacent normal tissues from six hepatocellular carcinoma patients enables us to identify 11 T cell subsets based on their molecular and functional properties and delineate their developmental trajectory.
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TL;DR: In this article, the authors present an approach for efficient and intuitive visualization tools able to scale to very large data sets and to flexibly integrate multiple data types, including clinical data.
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