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Open AccessArticle

Identifying Interaction Clusters for MiRNA and MRNA Pairs in TCGA Network

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Department of Mathematics and Computer Science, Indiana State University, Terre Haute, IN 47809, USA
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Department of Biology, Indiana State University, Terre Haute, IN 47809, USA
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Carmel High School, 520 E. Main St. Carmel, IN 46032, USA
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Seven Lakes High School, 9251 S Fry Rd, Katy, TX 77494, USA
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Department of Biostatistics, University of Michigan, Ann Arbor, MI 48109, USA
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Department of Internal Medicine, University of Michigan, Ann Arbor, MI 48109, USA
*
Author to whom correspondence should be addressed.
Genes 2019, 10(9), 702; https://doi.org/10.3390/genes10090702
Received: 14 August 2019 / Accepted: 6 September 2019 / Published: 11 September 2019
Existing methods often fail to recognize the conversions for the biological roles of the pairs of genes and microRNAs (miRNAs) between the tumor and normal samples. We have developed a novel cluster scoring method to identify messenger RNA (mRNA) and miRNA interaction pairs and clusters while considering tumor and normal samples jointly. Our method has identified 54 significant clusters for 15 cancer types selected from The Cancer Genome Atlas project. We also determined the shared clusters across tumor types and/or subtypes. In addition, we compared gene and miRNA overlap between lists identified in our liver hepatocellular carcinoma (LIHC) study and regulatory relationships reported from human and rat nonalcoholic fatty liver disease studies (NAFLD). Finally, we analyzed biological functions for the single significant cluster in LIHC and uncovered a significantly enriched pathway (phospholipase D signaling pathway) with six genes represented in the cluster, symbols: DGKQ, LPAR2, PDGFRB, PIK3R3, PTGFR and RAPGEF3.
Keywords: miRNA; mRNA; liver hepatocellular carcinoma; gene regulation; clustering algorithm; The Cancer Genome Atlas miRNA; mRNA; liver hepatocellular carcinoma; gene regulation; clustering algorithm; The Cancer Genome Atlas
MDPI and ACS Style

Dai, X.; Ding, L.; Liu, H.; Xu, Z.; Jiang, H.; Handelman, S.K.; Bai, Y. Identifying Interaction Clusters for MiRNA and MRNA Pairs in TCGA Network. Genes 2019, 10, 702.

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