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Somatic mutation landscape reveals differential variability of cell-of-origin for primary liver cancer.


ABSTRACT: Primary liver tissue cancer types are renowned to display a consistent increase in global disease burden and mortality, thus needing more effective diagnostics and treatments. Yet, integrative research efforts to identify cell-of-origin for these cancers by utilizing human specimen data were poorly established. To this end, we analyzed previously published whole-genome sequencing data for 384 tumor and progenitor tissues along with 423 publicly available normal tissue epigenomic features and single cell RNA-seq data from human livers to assess correlation patterns and extended this information to conduct in-silico prediction of the cell-of-origin for primary liver cancer subtypes. Despite mixed histological features, the cell-of-origin for mixed hepatocellular carcinoma/intrahepatic cholangiocarcinoma subtype was predominantly predicted to be hepatocytic origin. Individual sample-level predictions also revealed hepatocytes as one of the major predicted cell-of-origin for intrahepatic cholangiocarcinoma, thus implying trans-differentiation process during cancer progression. Additional analyses on the whole genome sequencing data of hepatic progenitor cells suggest these cells may not be a direct cell-of-origin for liver cancers. These results provide novel insights on the nature and potential contributors of cell-of-origins for primary liver cancers.

SUBMITTER: Ha K 

PROVIDER: S-EPMC7016380 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

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Somatic mutation landscape reveals differential variability of cell-of-origin for primary liver cancer.

Ha Kyungsik K   Fujita Masashi M   Karlić Rosa R   Yang Sungmin S   Xue Ruidong R   Zhang Chong C   Bai Fan F   Zhang Ning N   Hoshida Yujin Y   Polak Paz P   Nakagawa Hidewaki H   Kim Hong-Gee HG   Lee Hwajin H  

Heliyon 20200211 2


Primary liver tissue cancer types are renowned to display a consistent increase in global disease burden and mortality, thus needing more effective diagnostics and treatments. Yet, integrative research efforts to identify cell-of-origin for these cancers by utilizing human specimen data were poorly established. To this end, we analyzed previously published whole-genome sequencing data for 384 tumor and progenitor tissues along with 423 publicly available normal tissue epigenomic features and sin  ...[more]

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