Literature DB >> 19996289

Gene networks and microRNAs implicated in aggressive prostate cancer.

Liang Wang1, Hui Tang, Venugopal Thayanithy, Subbaya Subramanian, Ann L Oberg, Julie M Cunningham, James R Cerhan, Clifford J Steer, Stephen N Thibodeau.   

Abstract

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 >or= 8) and 63 prostate cancer patients with nonaggressive phenotype (Gleason grade <or= 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.

Entities:  

Mesh:

Substances:

Year:  2009        PMID: 19996289      PMCID: PMC2795036          DOI: 10.1158/0008-5472.CAN-09-2183

Source DB:  PubMed          Journal:  Cancer Res        ISSN: 0008-5472            Impact factor:   12.701


  49 in total

1.  The prognostic value and overexpression of cyclin A is correlated with gene amplification of both cyclin A and cyclin E in breast cancer patient.

Authors:  A Husdal; G Bukholm; I R K Bukholm
Journal:  Cell Oncol       Date:  2006       Impact factor: 6.730

2.  Role of L2DTL, cell cycle-regulated nuclear and centrosome protein, in aggressive hepatocellular carcinoma.

Authors:  Hung-Wei Pan; Han-Yi E Chou; Shu-Hsiang Liu; Shian-Yang Peng; Chao-Lien Liu; Hey-Chi Hsu
Journal:  Cell Cycle       Date:  2006-11-15       Impact factor: 4.534

3.  c-Myc-regulated microRNAs modulate E2F1 expression.

Authors:  Kathryn A O'Donnell; Erik A Wentzel; Karen I Zeller; Chi V Dang; Joshua T Mendell
Journal:  Nature       Date:  2005-06-09       Impact factor: 49.962

4.  A microRNA polycistron as a potential human oncogene.

Authors:  Lin He; J Michael Thomson; Michael T Hemann; Eva Hernando-Monge; David Mu; Summer Goodson; Scott Powers; Carlos Cordon-Cardo; Scott W Lowe; Gregory J Hannon; Scott M Hammond
Journal:  Nature       Date:  2005-06-09       Impact factor: 49.962

5.  Downregulation of both p21/Cip1 and p27/Kip1 produces a more aggressive prostate cancer phenotype.

Authors:  Srirupa Roy; Rana P Singh; Chapla Agarwal; Sunitha Siriwardana; Robert Sclafani; Rajesh Agarwal
Journal:  Cell Cycle       Date:  2008-06-30       Impact factor: 4.534

6.  Gene expression correlates of clinical prostate cancer behavior.

Authors:  Dinesh Singh; Phillip G Febbo; Kenneth Ross; Donald G Jackson; Judith Manola; Christine Ladd; Pablo Tamayo; Andrew A Renshaw; Anthony V D'Amico; Jerome P Richie; Eric S Lander; Massimo Loda; Philip W Kantoff; Todd R Golub; William R Sellers
Journal:  Cancer Cell       Date:  2002-03       Impact factor: 31.743

7.  Polymorphisms in mitochondrial genes and prostate cancer risk.

Authors:  Liang Wang; Shannon K McDonnell; Scott J Hebbring; Julie M Cunningham; Jennifer St Sauver; James R Cerhan; Grazia Isaya; Daniel J Schaid; Stephen N Thibodeau
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2008-12       Impact factor: 4.254

8.  A systems level analysis of transcriptional changes in Alzheimer's disease and normal aging.

Authors:  Jeremy A Miller; Michael C Oldham; Daniel H Geschwind
Journal:  J Neurosci       Date:  2008-02-06       Impact factor: 6.167

9.  Functional links between clustered microRNAs: suppression of cell-cycle inhibitors by microRNA clusters in gastric cancer.

Authors:  Young-Kook Kim; Jieun Yu; Tae Su Han; Seong-Yeon Park; Bumjin Namkoong; Dong Hyuk Kim; Keun Hur; Moon-Won Yoo; Hyuk-Joon Lee; Han-Kwang Yang; V Narry Kim
Journal:  Nucleic Acids Res       Date:  2009-01-19       Impact factor: 16.971

10.  Variations in the transcriptome of Alzheimer's disease reveal molecular networks involved in cardiovascular diseases.

Authors:  Monika Ray; Jianhua Ruan; Weixiong Zhang
Journal:  Genome Biol       Date:  2008-10-08       Impact factor: 13.583

View more
  68 in total

1.  Cross-analysis of gene and miRNA genome-wide expression profiles in human fibroblasts at different stages of transformation.

Authors:  Paola Ostano; Silvia Bione; Cristina Belgiovine; Ilaria Chiodi; Chiara Ghimenti; A Ivana Scovassi; Giovanna Chiorino; Chiara Mondello
Journal:  OMICS       Date:  2012 Jan-Feb

2.  The RNA-binding protein HuR opposes the repression of ERBB-2 gene expression by microRNA miR-331-3p in prostate cancer cells.

Authors:  Michael R Epis; Andrew Barker; Keith M Giles; Dianne J Beveridge; Peter J Leedman
Journal:  J Biol Chem       Date:  2011-10-04       Impact factor: 5.157

3.  Network-based approach to identify prognostic biomarkers for estrogen receptor-positive breast cancer treatment with tamoxifen.

Authors:  Rong Liu; Cheng-Xian Guo; Hong-Hao Zhou
Journal:  Cancer Biol Ther       Date:  2015       Impact factor: 4.742

Review 4.  Orchestrating the Specific Assembly of Centromeric Nucleosomes.

Authors:  Ewelina Zasadzińska; Daniel R Foltz
Journal:  Prog Mol Subcell Biol       Date:  2017

5.  VDR regulation of microRNA differs across prostate cell models suggesting extremely flexible control of transcription.

Authors:  Prashant K Singh; Mark D Long; Sebastiano Battaglia; Qiang Hu; Song Liu; Lara E Sucheston-Campbell; Moray J Campbell
Journal:  Epigenetics       Date:  2015-01-29       Impact factor: 4.528

6.  Regulation of expression of deoxyhypusine hydroxylase (DOHH), the enzyme that catalyzes the activation of eIF5A, by miR-331-3p and miR-642-5p in prostate cancer cells.

Authors:  Michael R Epis; Keith M Giles; Felicity C Kalinowski; Andrew Barker; Ronald J Cohen; Peter J Leedman
Journal:  J Biol Chem       Date:  2012-08-20       Impact factor: 5.157

7.  Prediction of a gene regulatory network linked to prostate cancer from gene expression, microRNA and clinical data.

Authors:  Eric Bonnet; Tom Michoel; Yves Van de Peer
Journal:  Bioinformatics       Date:  2010-09-15       Impact factor: 6.937

Review 8.  Diet, microRNAs and prostate cancer.

Authors:  Sharanjot Saini; Shahana Majid; Rajvir Dahiya
Journal:  Pharm Res       Date:  2010-03-11       Impact factor: 4.200

Review 9.  Aberrant expression of microRNAs in bladder cancer.

Authors:  Hirofumi Yoshino; Naohiko Seki; Toshihiko Itesako; Takeshi Chiyomaru; Masayuki Nakagawa; Hideki Enokida
Journal:  Nat Rev Urol       Date:  2013-05-28       Impact factor: 14.432

10.  MiRNA regulation of TRAIL expression exerts selective cytotoxicity to prostate carcinoma cells.

Authors:  Wei Huo; Ning Jin; Li Fan; Weihua Wang
Journal:  Mol Cell Biochem       Date:  2013-11-30       Impact factor: 3.396

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.