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Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
Published on: May 17, 2019
Gene co-expression network approach for predicting prognostic microRNA biomarkers in different subtypes of breast
Masoumeh Adhami1, Habib MotieGhader2, Ali Akbar Haghdoost1
1Modeling in Health Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran.
Abstract:
New diagnostic miRNA biomarkers for different types of cancer have been studied extensively, particularly for breast cancer (BC), which is a leading cause of death among women and has many different subtypes. In the present study, a systems biology approach was used to find remarkable and novel miRNA biomarkers for five molecular subtypes of BC: luminal A, luminal B, ERBB2, basal-like and normal-like. The mRNA expression data from the five BC subtypes was used to reconstruct co-expression networks. The important mRNA-miRNA interactions were considered when reconstructing the bipartite networks from which the five bipartite sub-networks were reconstructed for further analysis. The novel biomarkers detected for each subtype are as follows: miRNAs 26b-5p and 124-3p for basal-like, 26b-5p, 124-3p and 5011-5p for ERBB2, 26b-5p and 5011-5p for LumA, 124-3p, 26b-5p and 7-5p for LumB and 26b-5p, 124-3p and 193b-3p for normal-like. The roles of the identified miRNAs in the occurrence or development of each subtype of BC remain unclear and should be investigated in future studies. In addition, the target genes of these miRNAs may be critical to the mechanisms underlying each subtype and should be analyzed as therapeutic targets in future studies.
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