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

  • Yingying Wang
  • Yunpeng CaiEmail author
  • Yingbo Miao
Original Research Article

Abstract

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 

Notes

Acknowledgments

This work was supported by National Natural Science Foundation of China (Grant No. 31200995), and the development funds for Key Laboratory in Shenzhen (Grant No. ZDSY20120617113021359) and the Shenzhen Innovation Fund for Advanced Talents (Grant No. KQCX20130628112914291).

Compliance with Ethical Standards

Conflict of interest

No financial competing interests.

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Copyright information

© International Association of Scientists in the Interdisciplinary Areas and Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  1. 1.Research Center for Biomedical Information Technology, Shenzhen Institutes of Advanced TechnologyChinese Academy of SciencesShenzhenChina
  2. 2.College of PharmacyNankai UniversityTianjinChina

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