title: Robust gene network analysis reveals alteration of the STAT5a network as a hallmark of prostate cancer.
abstract: We develop a general method to identify gene networks from pair-wise correlations between genes in a microarray data set and apply it to a public prostate cancer gene expression data from 69 primary prostate tumors. We define the degree of a node as the number of genes significantly associated with the node and identify hub genes as those with the highest degree. The correlation network was pruned using transcription factor binding information in VisANT (http://visant.bu.edu/) as a biological filter. The reliability of hub genes was determined using a strict permutation test. Separate networks for normal prostate samples, and prostate cancer samples from African Americans (AA) and European Americans (EA) were generated and compared. We found that the same hubs control disease progression in AA and EA networks. Combining AA and EA samples, we generated networks for low low (<7) and high (≥7) Gleason grade tumors. A comparison of their major hubs with those of the network for normal samples identified two types of changes associated with disease: (i) Some hub genes increased their degree in the tumor network compared to their degree in the normal network, suggesting that these genes are associated with gain of regulatory control in cancer (e.g. possible turning on of oncogenes). (ii) Some hubs reduced their degree in the tumor network compared to their degree in the normal network, suggesting that these genes are associated with loss of regulatory control in cancer (e.g. possible loss of tumor suppressor genes). A striking result was that for both AA and EA tumor samples, STAT5a, CEBPB and EGR1 are major hubs that gain neighbors compared to the normal prostate network. Conversely, HIF-lα is a major hub that loses connections in the prostate cancer network compared to the normal prostate network. We also find that the degree of these hubs changes progressively from normal to low grade to high grade disease, suggesting that these hubs are master regulators of prostate cancer and marks disease progression. STAT5a was identified as a central hub, with ~120 neighbors in the prostate cancer network and only 81 neighbors in the normal prostate network. Of the 120 neighbors of STAT5a, 57 are known cancer related genes, known to be involved in functional pathways associated with tumorigenesis. Our method is general and can easily be extended to identify and study networks associated with any two phenotypes.
authors.affiliation: BioMaPS Institute, Rutgers University, Piscataway, NJ, USA. anupamar@gmail.com.
authors.forename: Anupama
authors.initials: A
authors.lastname: Reddy
authors.forename: C Chris
authors.initials: CC
authors.lastname: Huang
authors.forename: Huiqing
authors.initials: H
authors.lastname: Liu
authors.forename: Charles
authors.initials: C
authors.lastname: Delisi
authors.forename: Marja T
authors.initials: MT
authors.lastname: Nevalainen
authors.forename: Sandor
authors.initials: S
authors.lastname: Szalma
authors.forename: Gyan
authors.initials: G
authors.lastname: Bhanot
mesh_terms: D001741:Black or African American; D000465:Algorithms; D019295:Computational Biology / Q000379:methods; D020869:Gene Expression Profiling; D015972:Gene Expression Regulation, Neoplastic; D053263:Gene Regulatory Networks; D016147:Genes, Tumor Suppressor; D006801:Humans; D008297:Male; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D011471:Prostatic Neoplasms / Q000208:ethnology / Q000378:metabolism*; D050799:STAT5 Transcription Factor / Q000378:metabolism*; D025521:Tumor Suppressor Proteins / Q000378:metabolism*; D014481:United States; D044465:White People
chemical_list: D050799:STAT5 Transcription Factor; C494092:STAT5A protein, human; D025521:Tumor Suppressor Proteins
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