TY - JOUR
T1 - Gene networks and microRNAs implicated in aggressive prostate cancer
AU - Wang, Liang
AU - Tang, Hui
AU - Thayanithy, Venugopal
AU - Subramanian, Subbaya
AU - Oberg, Ann L.
AU - Cunningham, Julie M.
AU - Cerhan, James R.
AU - Steer, Clifford J.
AU - Thibodeau, Stephen N.
PY - 2009/12/15
Y1 - 2009/12/15
N2 - Prostate cancer, a complex disease, can be relatively harmless or extremely aggressive. To identify candidate genes involved in causal pathways of aggressive prostate cancer, we implemented a systems biology approach by combining differential expression analysis and coexpression network analysis to evaluate transcriptional profiles using lymphoblastoid cell lines from 62 prostate cancer patients with aggressive phenotype (Gleason grade ≥ 8) and 63 prostate cancer patients with nonaggressive phenotype (Gleason grade ≤ 5). From 13,935 mRNA genes and 273 microRNAs (miRNA) tested, we identified significant differences in 1,100 mRNAs and 7 miRNAs with a false discovery rate (FDR) of <0.01. We also identified a coexpression module demonstrating significant association with the aggressive phenotype of prostate cancer (P = 3.67 x 10-11). The module of interest was characterized by overrepresentation of cell cycle-related genes (FDR = 3.50 x 10-50). From this module, we further defined 20 hub genes that were highly connected to other genes. Interestingly, 5 of the 7 differentially expressed miRNAs have been implicated in cell cycle regulation and 2 (miR-145 and miR-331-3p) are predicted to target 3 of the 20 hub genes. Ectopic expression of these two miRNAs reduced expression of target hub genes and subsequently resulted in cell growth inhibition and apoptosis. These results suggest that cell cycle is likely to be a molecular pathway causing aggressive phenotype of prostate cancer. Further characterization of cell cycle-related genes (particularly, the hub genes) and miRNAs that regulate these hub genes could facilitate identification of candidate genes responsible for the aggressive phenotype and lead to a better understanding of prostate cancer etiology and progression.
AB - Prostate cancer, a complex disease, can be relatively harmless or extremely aggressive. To identify candidate genes involved in causal pathways of aggressive prostate cancer, we implemented a systems biology approach by combining differential expression analysis and coexpression network analysis to evaluate transcriptional profiles using lymphoblastoid cell lines from 62 prostate cancer patients with aggressive phenotype (Gleason grade ≥ 8) and 63 prostate cancer patients with nonaggressive phenotype (Gleason grade ≤ 5). From 13,935 mRNA genes and 273 microRNAs (miRNA) tested, we identified significant differences in 1,100 mRNAs and 7 miRNAs with a false discovery rate (FDR) of <0.01. We also identified a coexpression module demonstrating significant association with the aggressive phenotype of prostate cancer (P = 3.67 x 10-11). The module of interest was characterized by overrepresentation of cell cycle-related genes (FDR = 3.50 x 10-50). From this module, we further defined 20 hub genes that were highly connected to other genes. Interestingly, 5 of the 7 differentially expressed miRNAs have been implicated in cell cycle regulation and 2 (miR-145 and miR-331-3p) are predicted to target 3 of the 20 hub genes. Ectopic expression of these two miRNAs reduced expression of target hub genes and subsequently resulted in cell growth inhibition and apoptosis. These results suggest that cell cycle is likely to be a molecular pathway causing aggressive phenotype of prostate cancer. Further characterization of cell cycle-related genes (particularly, the hub genes) and miRNAs that regulate these hub genes could facilitate identification of candidate genes responsible for the aggressive phenotype and lead to a better understanding of prostate cancer etiology and progression.
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U2 - 10.1158/0008-5472.CAN-09-2183
DO - 10.1158/0008-5472.CAN-09-2183
M3 - Article
C2 - 19996289
AN - SCOPUS:73649135801
SN - 0008-5472
VL - 69
SP - 9490
EP - 9497
JO - Cancer Research
JF - Cancer Research
IS - 24
ER -