In silico Analysis of Combinatorial microRNA Activity Reveals Target Genes and Pathways Associated with Breast Cancer Metastasis

Abstract Aberrant microRNA activity has been reported in many diseases, and studies often find numerous microRNAs concurrently dysregulated. Most target genes have binding sites for multiple microRNAs, and mounting evidence indicates that it is important to consider their combinatorial effect on tar...

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Main Authors: Alan A. Dombkowski, Zakia Sultana, Douglas B. Craig, Hasan Jamil
Format: Article
Language:English
Published: SAGE Publishing 2011-01-01
Series:Cancer Informatics
Online Access:https://doi.org/10.4137/CIN.S6631
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author Alan A. Dombkowski
Zakia Sultana
Douglas B. Craig
Hasan Jamil
author_facet Alan A. Dombkowski
Zakia Sultana
Douglas B. Craig
Hasan Jamil
author_sort Alan A. Dombkowski
collection DOAJ
description Abstract Aberrant microRNA activity has been reported in many diseases, and studies often find numerous microRNAs concurrently dysregulated. Most target genes have binding sites for multiple microRNAs, and mounting evidence indicates that it is important to consider their combinatorial effect on target gene repression. A recent study associated the coincident loss of expression of six microRNAs with metastatic potential in breast cancer. Here, we used a new computational method, miR-AT!, to investigate combinatorial activity among this group of microRNAs. We found that the set of transcripts having multiple target sites for these microRNAs was significantly enriched with genes involved in cellular processes commonly perturbed in metastatic tumors: cell cycle regulation, cytoskeleton organization, and cell adhesion. Network analysis revealed numerous target genes upstream of cyclin D1 and c-Myc, indicating that the collective loss of the six microRNAs may have a focal effect on these two key regulatory nodes. A number of genes previously implicated in cancer metastasis are among the predicted combinatorial targets, including TGFB1, ARPC3, and RANKL. In summary, our analysis reveals extensive combinatorial interactions that have notable implications for their potential role in breast cancer metastasis and in therapeutic development.
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spelling doaj.art-5ab701c1bfb34a028427e8bc60c9b0472022-12-21T17:14:19ZengSAGE PublishingCancer Informatics1176-93512011-01-011010.4137/CIN.S6631In silico Analysis of Combinatorial microRNA Activity Reveals Target Genes and Pathways Associated with Breast Cancer MetastasisAlan A. Dombkowski0Zakia Sultana1Douglas B. Craig2Hasan Jamil3Division of Clinical Pharmacology and Toxicology, Department of Pediatrics, Wayne State University School of Medicine, Detroit, MI, USA.Department of Computer Science, Wayne State University, Detroit, MI, USA.Division of Clinical Pharmacology and Toxicology, Department of Pediatrics, Wayne State University School of Medicine, Detroit, MI, USA.Department of Computer Science, Wayne State University, Detroit, MI, USA.Abstract Aberrant microRNA activity has been reported in many diseases, and studies often find numerous microRNAs concurrently dysregulated. Most target genes have binding sites for multiple microRNAs, and mounting evidence indicates that it is important to consider their combinatorial effect on target gene repression. A recent study associated the coincident loss of expression of six microRNAs with metastatic potential in breast cancer. Here, we used a new computational method, miR-AT!, to investigate combinatorial activity among this group of microRNAs. We found that the set of transcripts having multiple target sites for these microRNAs was significantly enriched with genes involved in cellular processes commonly perturbed in metastatic tumors: cell cycle regulation, cytoskeleton organization, and cell adhesion. Network analysis revealed numerous target genes upstream of cyclin D1 and c-Myc, indicating that the collective loss of the six microRNAs may have a focal effect on these two key regulatory nodes. A number of genes previously implicated in cancer metastasis are among the predicted combinatorial targets, including TGFB1, ARPC3, and RANKL. In summary, our analysis reveals extensive combinatorial interactions that have notable implications for their potential role in breast cancer metastasis and in therapeutic development.https://doi.org/10.4137/CIN.S6631
spellingShingle Alan A. Dombkowski
Zakia Sultana
Douglas B. Craig
Hasan Jamil
In silico Analysis of Combinatorial microRNA Activity Reveals Target Genes and Pathways Associated with Breast Cancer Metastasis
Cancer Informatics
title In silico Analysis of Combinatorial microRNA Activity Reveals Target Genes and Pathways Associated with Breast Cancer Metastasis
title_full In silico Analysis of Combinatorial microRNA Activity Reveals Target Genes and Pathways Associated with Breast Cancer Metastasis
title_fullStr In silico Analysis of Combinatorial microRNA Activity Reveals Target Genes and Pathways Associated with Breast Cancer Metastasis
title_full_unstemmed In silico Analysis of Combinatorial microRNA Activity Reveals Target Genes and Pathways Associated with Breast Cancer Metastasis
title_short In silico Analysis of Combinatorial microRNA Activity Reveals Target Genes and Pathways Associated with Breast Cancer Metastasis
title_sort in silico analysis of combinatorial microrna activity reveals target genes and pathways associated with breast cancer metastasis
url https://doi.org/10.4137/CIN.S6631
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AT douglasbcraig insilicoanalysisofcombinatorialmicrornaactivityrevealstargetgenesandpathwaysassociatedwithbreastcancermetastasis
AT hasanjamil insilicoanalysisofcombinatorialmicrornaactivityrevealstargetgenesandpathwaysassociatedwithbreastcancermetastasis