Screening for cancer associated MiRNAs through co-gene, co-function and co-pathway analysis

  • Authors:

  • Xue Xiao;Dongguo Li;Lei Gao;Xia Li;Qianghu Wang;Shaojun Zhang;Zhicheng Liu

  • Affiliations:

  • School of Biomedical Engineering, Capital Medical University, Beijing 100069, China;School of Biomedical Engineering, Capital Medical University, Beijing 100069, China;School of Biomedical Engineering, Capital Medical University, Beijing 100069, China;School of Biomedical Engineering, Capital Medical University, Beijing 100069, China and College of Bioinformatics Science and Technology, and Bio-pharmaceutical Key Laboratory of Heilongjiang Prov ...;College of Bioinformatics Science and Technology, and Bio-pharmaceutical Key Laboratory of Heilongjiang Province and State, Harbin Medical University, Harbin, Heilongjiang 150086, China;College of Bioinformatics Science and Technology, and Bio-pharmaceutical Key Laboratory of Heilongjiang Province and State, Harbin Medical University, Harbin, Heilongjiang 150086, China;School of Biomedical Engineering, Capital Medical University, Beijing 100069, China

  • Venue:
  • Computers in Biology and Medicine
  • Year:
  • 2012

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Abstract

MicroRNAs (miRNAs) though present themselves as a group of non-coding small RNAs play critical roles in many biological and pathological processes. Among which the regulation of human cancer is one of the most excited potentiality. The goal of this study is to obtain miRNAs robustly associated with cancer by screening all of the possible miRNAs/cancer pairs in three consecutive steps. First, in co-gene analysis, gene set enrichment analysis is carried out for all miRNA/cancer pairs. Second, in co-function analysis, information theoretic similarity on GO is calculated for miRNA/cancer pairs screened from the former step. Third, in co-pathway analysis, pathway enrichment analysis is performed for miRNA/cancer pairs screened from the second step. In this study, we totally included 776 miRNAs and 25 cancer types. As a result, 94 miRNAs were identified with robust association with 17 types of cancer. Meanwhile, 83 pathways with relevance to both miRNAs and cancer were also singled out. This framework provides an effective way to narrow down miRNAs for cancer and to pinpoint corresponding pathways.