Limits...
Dysregulation of cell cycle related genes and microRNAs distinguish the low- from high-risk of prostate cancer.

Wen J, Li R, Wen X, Chou G, Lu J, Wang X, Jin Y - Diagn Pathol (2014)

Bottom Line: Besides, 12 microRNAs target transcripts were significantly overlapped with down-regulated transcripts in cluster 5 with none of them was found overlapped with up-regulated transcripts.Functional annotation showed that cell cycle was the most significant function.Our findings raise the possibility that genes related with cell cycle and dysregulated miRNA at diagnosis might have clinical utility in distinguishing low- from high-risk PCa patients.

View Article: PubMed Central - PubMed

ABSTRACT

Background: Prostate cancer (PCa) is a biologically heterogeneous disease with considerable variation in clinical aggressiveness. In this study, bioinformatics was used to detect the patterns of gene expression alterations of PCa patients.

Methods: The gene expression profile GSE21034 and GSE21036 were downloaded from Gene Expression Omnibus (GEO) database. Significantly changed mRNA transcripts and microRNAs were identified between subtypes with favorable (cluster 2) and unfavorable (cluster 5) prognosis by two-side unequal variances t test. MicroRNAs and their potential target genes were identified by TargetScan and miRTarBase, respectively. Besides, the overlapped genes between the target genes of microRNAs and mRNA transcripts were assessed by Fisher' exact test (one side). The functional annotation was performed by DAVID, followed by construction of protein-protein interaction (PPI) network.

Results: Compared to cluster 2, 1556 up-regulated and 1288 down-regulated transcripts were identified in cluster 5. Total 28 microRNAs were up-regulated and 30 microRNAs were down-regulated in cluster 5. Besides, 12 microRNAs target transcripts were significantly overlapped with down-regulated transcripts in cluster 5 with none of them was found overlapped with up-regulated transcripts. Functional annotation showed that cell cycle was the most significant function. In the PPI network, BRCA1, CDK1, TK1 and TRAF2 were hub protein of signature genes in cluster 5, and TGFBR1, SMAD2 and SMAD4 were hub proteins of signature gnens in cluster 2.

Conclusions: Our findings raise the possibility that genes related with cell cycle and dysregulated miRNA at diagnosis might have clinical utility in distinguishing low- from high-risk PCa patients.

Virtual slides: The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/13000_2014_156.

No MeSH data available.


Related in: MedlinePlus

Protein-protein interactions in cluster 5 signature genes. Yellow nodes are those interacted with androgen receptor. Protein-protein interactions were downloaded from database HINT which removes low-quality/erroneous interactions by both systematically and manually filtering.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
getmorefigures.php?uid=PMC4215008&req=5

Fig1: Protein-protein interactions in cluster 5 signature genes. Yellow nodes are those interacted with androgen receptor. Protein-protein interactions were downloaded from database HINT which removes low-quality/erroneous interactions by both systematically and manually filtering.

Mentions: The results of PPI network analysis showed that there were 46 nodes and 46 edges in cluster 5 (Figure 1). Meanwhile, total 27 nodes and 34 edges were in cluster 2 (Figure 2). Proteins with at least ten interactions were considered as hubs. The results revealed that BRCA1, CDK1, TK1 and TRAF2 were hub protein of signature genes in cluster 5, and TGFBR1, SMAD2 and SMAD4 were hub proteins of signature gnens in cluster 2.Figure 1


Dysregulation of cell cycle related genes and microRNAs distinguish the low- from high-risk of prostate cancer.

Wen J, Li R, Wen X, Chou G, Lu J, Wang X, Jin Y - Diagn Pathol (2014)

Protein-protein interactions in cluster 5 signature genes. Yellow nodes are those interacted with androgen receptor. Protein-protein interactions were downloaded from database HINT which removes low-quality/erroneous interactions by both systematically and manually filtering.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4215008&req=5

Fig1: Protein-protein interactions in cluster 5 signature genes. Yellow nodes are those interacted with androgen receptor. Protein-protein interactions were downloaded from database HINT which removes low-quality/erroneous interactions by both systematically and manually filtering.
Mentions: The results of PPI network analysis showed that there were 46 nodes and 46 edges in cluster 5 (Figure 1). Meanwhile, total 27 nodes and 34 edges were in cluster 2 (Figure 2). Proteins with at least ten interactions were considered as hubs. The results revealed that BRCA1, CDK1, TK1 and TRAF2 were hub protein of signature genes in cluster 5, and TGFBR1, SMAD2 and SMAD4 were hub proteins of signature gnens in cluster 2.Figure 1

Bottom Line: Besides, 12 microRNAs target transcripts were significantly overlapped with down-regulated transcripts in cluster 5 with none of them was found overlapped with up-regulated transcripts.Functional annotation showed that cell cycle was the most significant function.Our findings raise the possibility that genes related with cell cycle and dysregulated miRNA at diagnosis might have clinical utility in distinguishing low- from high-risk PCa patients.

View Article: PubMed Central - PubMed

ABSTRACT

Background: Prostate cancer (PCa) is a biologically heterogeneous disease with considerable variation in clinical aggressiveness. In this study, bioinformatics was used to detect the patterns of gene expression alterations of PCa patients.

Methods: The gene expression profile GSE21034 and GSE21036 were downloaded from Gene Expression Omnibus (GEO) database. Significantly changed mRNA transcripts and microRNAs were identified between subtypes with favorable (cluster 2) and unfavorable (cluster 5) prognosis by two-side unequal variances t test. MicroRNAs and their potential target genes were identified by TargetScan and miRTarBase, respectively. Besides, the overlapped genes between the target genes of microRNAs and mRNA transcripts were assessed by Fisher' exact test (one side). The functional annotation was performed by DAVID, followed by construction of protein-protein interaction (PPI) network.

Results: Compared to cluster 2, 1556 up-regulated and 1288 down-regulated transcripts were identified in cluster 5. Total 28 microRNAs were up-regulated and 30 microRNAs were down-regulated in cluster 5. Besides, 12 microRNAs target transcripts were significantly overlapped with down-regulated transcripts in cluster 5 with none of them was found overlapped with up-regulated transcripts. Functional annotation showed that cell cycle was the most significant function. In the PPI network, BRCA1, CDK1, TK1 and TRAF2 were hub protein of signature genes in cluster 5, and TGFBR1, SMAD2 and SMAD4 were hub proteins of signature gnens in cluster 2.

Conclusions: Our findings raise the possibility that genes related with cell cycle and dysregulated miRNA at diagnosis might have clinical utility in distinguishing low- from high-risk PCa patients.

Virtual slides: The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/13000_2014_156.

No MeSH data available.


Related in: MedlinePlus