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Gene expression profiles of prostate cancer reveal involvement of multiple molecular pathways in the metastatic process.

ABSTRACT: Prostate cancer is characterized by heterogeneity in the clinical course that often does not correlate with morphologic features of the tumor. Metastasis reflects the most adverse outcome of prostate cancer, and to date there are no reliable morphologic features or serum biomarkers that can reliably predict which patients are at higher risk of developing metastatic disease. Understanding the differences in the biology of metastatic and organ confined primary tumors is essential for developing new prognostic markers and therapeutic targets.Using Affymetrix oligonucleotide arrays, we analyzed gene expression profiles of 24 androgen-ablation resistant metastatic samples obtained from 4 patients and a previously published dataset of 64 primary prostate tumor samples. Differential gene expression was analyzed after removing potentially uninformative stromal genes, addressing the differences in cellular content between primary and metastatic tumors.The metastatic samples are highly heterogenous in expression; however, differential expression analysis shows that 415 genes are upregulated and 364 genes are downregulated at least 2 fold in every patient with metastasis. The expression profile of metastatic samples reveals changes in expression of a unique set of genes representing both the androgen ablation related pathways and other metastasis related gene networks such as cell adhesion, bone remodelling and cell cycle. The differentially expressed genes include metabolic enzymes, transcription factors such as Forkhead Box M1 (FoxM1) and cell adhesion molecules such as Osteopontin (SPP1).We hypothesize that these genes have a role in the biology of metastatic disease and that they represent potential therapeutic targets for prostate cancer.

SUBMITTER: Chandran UR

PROVIDER: S-EPMC1865555 | biostudies-literature | 2007 Apr

REPOSITORIES: biostudies-literature

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Gene expression profiles of prostate cancer reveal involvement of multiple molecular pathways in the metastatic process.

Chandran Uma R UR Ma Changqing C Dhir Rajiv R Bisceglia Michelle M Lyons-Weiler Maureen M Liang Wenjing W Michalopoulos George G Becich Michael M Monzon Federico A FA

BMC cancer 20070412

<h4>Background</h4>Prostate cancer is characterized by heterogeneity in the clinical course that often does not correlate with morphologic features of the tumor. Metastasis reflects the most adverse outcome of prostate cancer, and to date there are no reliable morphologic features or serum biomarkers that can reliably predict which patients are at higher risk of developing metastatic disease. Understanding the differences in the biology of metastatic and organ confined primary tumors is essentia ...[more]

PMID: 17430594

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Project description:BackgroundCancer metastasis is well known as the most adverse outcome and the major cause of mortality in cancer patients, including prostate cancer (PCa). There are no credible predictors, to this day, that can reflect the metastatic ability of localized PCa. In the present study, we firstly identified the differentially expressed genes (DEGs) and molecular pathways involved in the metastaic process of PCa by comparing gene expressions of metastaic PCa with localized PCa directly, with the purpose of identifying potential markers or therapeutic targets.MethodsThe gene expression profiles (GSE6919 and GSE32269) were downloaded from the Gene Expression Omnibus database, which contained 141 tissue samples, including 87 primary localized PCa samples and 54 metastaic PCa samples. After data processing, DEGs were identified by R language using the Student's t-test adjusted via the Beniamini-Hochberg method. Subsequently, the gene ontology functional and pathway enrichment analyses of DEGs were performed and the protein-protein interaction network was constructed. Hub genes were identified using the plug-in cytoHubba in Cytoscape software by MCC and degree. Furthermore, validation and prognostic significance analysis of the hub genes were performed by UALCAN and gene expression profiling interactive analysis (GEPIA).ResultsA total of 90 DEGs were identified between localized and metastaic PCa, which consisted of 47 upregulated and 43 downregulated genes. The enriched functions and pathways of the DEGs include catabolic process, cell cycle, response to steroid hormone, extracellular matrix (ECM)-receptor interaction and vascular smooth muscle contraction. A total of 10 genes were identified as hub genes and biological process analysis of hub genes showed that cell cycle phase, cell division, and mitotic cell cycle process were mainly enriched. The expression of hub genes were confirmed in metastaic PCa when compared with localized PCa tissues by The Cancer Genome Atlas database. Moreover, the disease-free survival analysis of hub genes revealed that these genes may play an important role in invasion, progression or recurrence. Therefore, these hub genes might be the key genes contributed to tumor progression or metastasis in PCa and provide candidate therapeutic targets for PCa.ConclusionsThe present study identified some DEGs between localized and metastaic PCa tissue samples. These key genes might be potential therapeutic targets and biomarkers for the metastaic process of PCa.

Project description:The objective of this study is to determine if multiple systemic autoimmune diseases (SAID) share gene expression pathways that could provide insights into pathogenic mechanisms common to these disorders.RNA microarray analyses (Agilent Human 1A(V2) 20K oligo arrays) were used to quantify gene expression in peripheral blood cells from 20 monozygotic (MZ) twin pairs discordant for SAID. Six affected probands with systemic lupus erythematosus (SLE), six with rheumatoid arthritis (RA), eight with idiopathic inflammatory myopathies (IIM), and their same-gendered unaffected twins, were enrolled. Comparisons were made between discordant twin pairs and these were also each compared to 40 unrelated control subjects (matched 2:1 to each twin by age, gender and ethnicity) using statistical and molecular pathway analyses. Relative quantitative PCR was used to verify independently measures of differential gene expression assessed by microarray analysis.Probands and unrelated, matched controls differed significantly in gene expression for 104 probes corresponding to 92 identifiable genes (multiple-comparison adjusted P values < 0.1). Differentially expressed genes involved several overlapping pathways including immune responses (16%), signaling pathways (24%), transcription/translation regulators (26%), and metabolic functions (15%). Interferon (IFN)-response genes (IFI27, OASF, PLSCR1, EIF2AK2, TNFAIP6, and TNFSF10) were up-regulated in probands compared to unrelated controls. Many of the abnormally expressed genes played regulatory roles in multiple cellular pathways. We did not detect any probes expressed differentially in comparisons among the three SAID phenotypes. Similarly, we found no significant differences in gene expression when comparing probands to unaffected twins or unaffected twins to unrelated controls. Gene expression levels for unaffected twins appeared intermediate between that of probands and unrelated controls for 6535 probes (32% of the total probes) as would be expected by chance. By contrast, in unaffected twins intermediate ordering was observed for 84 of the 104 probes (81%) whose expression differed significantly between probands and unrelated controls.Alterations in expression of a limited number of genes may influence the dysregulation of numerous, integrated immune response, cell signaling and regulatory pathways that are common to a number of SAID. Gene expression profiles in peripheral blood suggest that for genes in these critical pathways, unaffected twins may be in a transitional or intermediate state of immune dysregulation between twins with SAID and unrelated controls, perhaps predisposing them to the development of SAID given the necessary and sufficient environmental exposures.

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Gene expression profiles of prostate cancer reveal involvement of multiple molecular pathways in the metastatic process.

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Gene expression profiles of prostate cancer reveal involvement of multiple molecular pathways in the metastatic process.

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