Somatic mutation landscape reveals differential variability of cell-of-origin for primary liver cancer. Issue 2 (February 2020)
- Record Type:
- Journal Article
- Title:
- Somatic mutation landscape reveals differential variability of cell-of-origin for primary liver cancer. Issue 2 (February 2020)
- Main Title:
- Somatic mutation landscape reveals differential variability of cell-of-origin for primary liver cancer
- Authors:
- Ha, Kyungsik
Fujita, Masashi
Karlić, Rosa
Yang, Sungmin
Xue, Ruidong
Zhang, Chong
Bai, Fan
Zhang, Ning
Hoshida, Yujin
Polak, Paz
Nakagawa, Hidewaki
Kim, Hong-Gee
Lee, Hwajin - Abstract:
- 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. Abstract : Systems biology; Biocomputational method; Gene mutation; Genomics; Cancer research; Bioinformatics-basedAbstract: 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. Abstract : Systems biology; Biocomputational method; Gene mutation; Genomics; Cancer research; Bioinformatics-based prediction of cell-of-origin; Primary liver cancers; Integration of epigenome, Genome and single-cell RNA-Seq data. … (more)
- Is Part Of:
- Heliyon. Volume 6:Issue 2(2020)
- Journal:
- Heliyon
- Issue:
- Volume 6:Issue 2(2020)
- Issue Display:
- Volume 6, Issue 2 (2020)
- Year:
- 2020
- Volume:
- 6
- Issue:
- 2
- Issue Sort Value:
- 2020-0006-0002-0000
- Page Start:
- Page End:
- Publication Date:
- 2020-02
- Subjects:
- Systems biology -- Biocomputational method -- Gene mutation -- Genomics -- Cancer research -- Bioinformatics-based prediction of cell-of-origin -- Primary liver cancers -- Integration of epigenome -- Genome and single-cell RNA-Seq data
Research -- Periodicals
Medical sciences -- Periodicals
Natural history -- Periodicals
Social sciences -- Periodicals
Earth sciences -- Periodicals
Physical sciences -- Periodicals
507.2 - Journal URLs:
- http://www.sciencedirect.com/science/journal/24058440/ ↗
http://www.sciencedirect.com/ ↗ - DOI:
- 10.1016/j.heliyon.2020.e03350 ↗
- Languages:
- English
- ISSNs:
- 2405-8440
- Deposit Type:
- Legaldeposit
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- Available online (eLD content is only available in our Reading Rooms) ↗
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- British Library DSC - BLDSS-3PM
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