In silico analysis of combinatorial microRNA activity reveals target genes and pathways associated with breast cancer metastasis

Alan A. Dombkowski, Kazi Zakia Sultana, Douglas B. Craig, Hasan Jamil

Research output: Contribution to journalArticleResearchpeer-review

12 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)13-29
Number of pages17
JournalCancer Informatics
Volume10
DOIs
StatePublished - 28 Mar 2011

Fingerprint

MicroRNAs
Computer Simulation
Breast Neoplasms
Neoplasm Metastasis
Genes
bcl-1 Genes
Cytoskeleton
Cell Adhesion
Neoplasms
Cell Cycle
Binding Sites

Keywords

  • Bioinformatics
  • Cancer
  • Computational
  • Metastasis
  • microRNA

Cite this

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title = "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 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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In silico analysis of combinatorial microRNA activity reveals target genes and pathways associated with breast cancer metastasis. / Dombkowski, Alan A.; Sultana, Kazi Zakia; Craig, Douglas B.; Jamil, Hasan.

In: Cancer Informatics, Vol. 10, 28.03.2011, p. 13-29.

Research output: Contribution to journalArticleResearchpeer-review

TY - JOUR

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AB - 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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