Volume 11, Issue 7 (September 2017)
Qom Univ Med Sci J 2017, 11(7): 98-116 |
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Sadeghi M, Ganjalikhani M R, Ranjbar B. Co-Expression and Microrna Regulatory Network Integration in Metastatic Prostate Tumor Using Microarray Expression Data Analysis. Qom Univ Med Sci J 2017; 11 (7) :98-116
URL: http://journal.muq.ac.ir/article-1-434-en.html
URL: http://journal.muq.ac.ir/article-1-434-en.html
1- Tarbiat modares university
2- university of Isfahan
3- Tarbiat modares university ,ranjbarb@modares.ac.ir
2- university of Isfahan
3- Tarbiat modares university ,
Abstract: (5731 Views)
Background and objectives: Prostate cancer is one of the most prevalent cancer in men which shows high heterogeneity in genetic and pathological features. Elucidating the regulatory relationships between microRNAs and mRNAs can help to identification of gene regulatory patterns in metastatic prostate cancer.
Methods: In the present study prostate cancer patient’s expression data (gene and microRNA) was used to study gene interactions in metastatic prostate tumor. Weighted gene co-expression network have been implemented for gene clustering and finding gene modules correlation with biochemical recurrence free survival variable. Differentially expressed microRNA gene targets were obtained from experimentally validated and prediction based databases and alongside with gene and microRNA expression, Pearson correlations measurements were implemented to constructing microRNA regulatory network.
Results: Two significant modules were detected in co-expressed modules significant analysis for biochemical recurrence free variable. One of them involved in cell cycle regulation and cell proliferation pathways which are hallmark pathways of progressed cancers. Integration of gene co-expression network with microRNA regulation network shows, first: Micrornas target pathways which involved in the progression of prostate cancer to metastatic stage, and second: introduce several key factors including microRNA and genes.
Conclusion: Present study revealed more details on key functional components in prostate cancer development. These details may provide opportunities for the development of alternative therapeutic approaches.
Methods: In the present study prostate cancer patient’s expression data (gene and microRNA) was used to study gene interactions in metastatic prostate tumor. Weighted gene co-expression network have been implemented for gene clustering and finding gene modules correlation with biochemical recurrence free survival variable. Differentially expressed microRNA gene targets were obtained from experimentally validated and prediction based databases and alongside with gene and microRNA expression, Pearson correlations measurements were implemented to constructing microRNA regulatory network.
Results: Two significant modules were detected in co-expressed modules significant analysis for biochemical recurrence free variable. One of them involved in cell cycle regulation and cell proliferation pathways which are hallmark pathways of progressed cancers. Integration of gene co-expression network with microRNA regulation network shows, first: Micrornas target pathways which involved in the progression of prostate cancer to metastatic stage, and second: introduce several key factors including microRNA and genes.
Conclusion: Present study revealed more details on key functional components in prostate cancer development. These details may provide opportunities for the development of alternative therapeutic approaches.
Type of Study: Original Article |
Received: 2016/03/12 | Accepted: 2016/05/1 | Published: 2017/09/23
Received: 2016/03/12 | Accepted: 2016/05/1 | Published: 2017/09/23
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eISSN: 2008-1375
pISSN: 1735-7799
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