Evolving-Pattern Analysis of Transient and Long-Term Biomarkers for Cancers: Hepatocellular Carcinoma as a Case

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• 作者：Yingying Wang ; Yunpeng Cai ; Yingbo Miao
• 关键词：Transient biomarker ; Long ; term biomarker ; Functional term ; HCC ; Cirrhosis ; microRNA
• 刊名：Interdisciplinary Sciences: Computational Life Sciences
• 出版年：2015
• 出版时间：December 2015
• 年：2015
• 卷：7
• 期：4
• 页码：414-422
• 全文大小：2,531 KB
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• 作者单位：Yingying Wang (1)
  Yunpeng Cai (1)
  Yingbo Miao (2)
  
  1. Research Center for Biomedical Information Technology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
  2. College of Pharmacy, Nankai University, Tianjin, China
  
• 刊物主题：Computer Appl. in Life Sciences; Computational Biology/Bioinformatics; Statistics for Life Sciences, Medicine, Health Sciences; Theoretical and Computational Chemistry; Theoretical, Mathematical and Computational Physics; Computational Science and Engineering;
• 出版者：International Association of Scientists in the Interdisciplinary Areas
• ISSN：1867-1462

文摘

Cancer is a complex disease arises from combinations of changes that occur over a period of time. With the development of bioinformatics, more and more biomarkers representing changes in cancers had been identified using gene expression profiles. However, biomarkers alone are quite limited in explaining the molecular processes occurred in the due process. In this paper, we develop an evolving-pattern analysis pipeline for in-depth studies of gene expression changes during different disease stages, choosing hepatocellular carcinoma (HCC) as a case. Enrichment analyses were performed on three levels: functional terms, validated genes, and regulation factors for all the biomarkers to find out their biological characters. Our results show that biomarkers with distinct evolving patterns exhibit quite different characteristics on functional and regulation levels. For the case of HCC, transient biomarkers are mostly annotated to metabolic processes, while long-term biomarkers are mostly annotated to regulation processes, with a larger number of enriched regulation factors. Furthermore, our pipeline reveals the important roles of microRNAs in various evolving patterns, which are known to be closely related to HCC. These results confirm that evolving-pattern analysis may provide a new sight for in-depth studies of biomarkers and diseases. Keywords Transient biomarker Long-term biomarker Functional term HCC Cirrhosis microRNA