Metabolism‐associated molecular classification of hepatocellular carcinoma. Issue 4 (29th January 2020)
- Record Type:
- Journal Article
- Title:
- Metabolism‐associated molecular classification of hepatocellular carcinoma. Issue 4 (29th January 2020)
- Main Title:
- Metabolism‐associated molecular classification of hepatocellular carcinoma
- Authors:
- Yang, Chen
Huang, Xiaowen
Liu, Zhicheng
Qin, Wenxin
Wang, Cun - Abstract:
- Abstract : Hepatocellular carcinoma (HCC) is a disease with unique management complexity because it displays high heterogeneity of molecular phenotypes. We herein aimed to characterize the molecular features of HCC by the development of a classification system that was based on the gene expression profile of metabolic genes. Integrative analysis was performed with a metadata set featuring 371 and 231 HCC human samples from the Cancer Genome Atlas and the International Cancer Genome Consortium, respectively. All samples were linked with clinical information. RNA sequencing data of 2752 previously characterized metabolism‐related genes were used for non‐negative matrix factorization clustering, and three subclasses of HCC (C1, C2, and C3) were identified. We then analyzed the metadata set for metabolic signatures, prognostic value, transcriptome features, immune infiltration, clinical characteristics, and drug sensitivity of subclasses, and compared the resulting subclasses with previously published classifications. Subclass C1 displayed high metabolic activity, low α‐fetoprotein (AFP) expression, and good prognosis. Subclass C2 was associated with low metabolic activities and displayed high expression of immune checkpoint genes, demonstrating drug sensitivity toward cytotoxic T‐lymphocyte‐associated protein‐4 inhibitors and the receptor tyrosine kinase inhibitor cabozantinib. Subclass C3 displayed intermediate metabolic activity, high AFP expression level, and bad prognosis.Abstract : Hepatocellular carcinoma (HCC) is a disease with unique management complexity because it displays high heterogeneity of molecular phenotypes. We herein aimed to characterize the molecular features of HCC by the development of a classification system that was based on the gene expression profile of metabolic genes. Integrative analysis was performed with a metadata set featuring 371 and 231 HCC human samples from the Cancer Genome Atlas and the International Cancer Genome Consortium, respectively. All samples were linked with clinical information. RNA sequencing data of 2752 previously characterized metabolism‐related genes were used for non‐negative matrix factorization clustering, and three subclasses of HCC (C1, C2, and C3) were identified. We then analyzed the metadata set for metabolic signatures, prognostic value, transcriptome features, immune infiltration, clinical characteristics, and drug sensitivity of subclasses, and compared the resulting subclasses with previously published classifications. Subclass C1 displayed high metabolic activity, low α‐fetoprotein (AFP) expression, and good prognosis. Subclass C2 was associated with low metabolic activities and displayed high expression of immune checkpoint genes, demonstrating drug sensitivity toward cytotoxic T‐lymphocyte‐associated protein‐4 inhibitors and the receptor tyrosine kinase inhibitor cabozantinib. Subclass C3 displayed intermediate metabolic activity, high AFP expression level, and bad prognosis. Finally, a 90‐gene classifier was generated to enable HCC classification. This study establishes a new HCC classification based on the gene expression profiles of metabolic genes, thereby furthering the understanding of the genetic diversity of human HCC. Abstract : Based on the gene expression profile of metabolic genes, patients with hepatocellular carcinoma (HCC) were divided into three subclasses: C1, C2, and C3. Each subclass had a different prognosis, clinicopathological characteristics, molecular characteristics, and potential therapies. Besides, this classification was associated with previously reported HCC molecular subclasses, including Boyault's classification, Chiang's classification, Hoshida's classification, Désert's classification, and the Cancer Genome Atlas's classification. … (more)
- Is Part Of:
- Molecular oncology. Volume 14:Issue 4(2020)
- Journal:
- Molecular oncology
- Issue:
- Volume 14:Issue 4(2020)
- Issue Display:
- Volume 14, Issue 4 (2020)
- Year:
- 2020
- Volume:
- 14
- Issue:
- 4
- Issue Sort Value:
- 2020-0014-0004-0000
- Page Start:
- 896
- Page End:
- 913
- Publication Date:
- 2020-01-29
- Subjects:
- classification -- hepatocellular carcinoma -- immune signatures -- metabolic genes
Cancer -- Molecular aspects -- Periodicals
616.994005 - Journal URLs:
- http://www.journals.elsevier.com/molecular-oncology/ ↗
http://febs.onlinelibrary.wiley.com/hub/journal/10.1002/(ISSN)1878-0261/issues/ ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1002/1878-0261.12639 ↗
- Languages:
- English
- ISSNs:
- 1574-7891
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5900.817993
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 13152.xml