Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

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Gene expression profiling of the prostate biopsy samples from African American and European American prostate cancer patients

ABSTRACT: Prostate cancer (PCa) tends to be more aggressive and lethal in African Americans (AA) compared to European Americans (EA). To further understand the biological factors accounting for the PCa disparities observed in AA and EA patients, we performed gene profiling analysis using Affymetrix human exon 1.0 ST arrays to identify the differentially expressed genes in AA and EA patients. 35 prostate biopsy specimens (tumor and adjacent normal tissues) were collected from 20 African American and 15 European American prostate cancer patients. RNA samples, purified from the collected biopy specimens, were process and applied to Affymetrix human exon ST 1.0 arrays. Array data was normalized, batch corrected and analyzed (1-way ANOVA) using Partek Genomics Suite program.

ORGANISM(S): Homo sapiens

SUBMITTER: Bi-Dar Wang 

PROVIDER: E-GEOD-64331 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Identification and Functional Validation of Reciprocal microRNA-mRNA Pairings in African American Prostate Cancer Disparities.

Wang Bi-Dar BD   Ceniccola Kristin K   Yang Qi Q   Andrawis Ramez R   Patel Vyomesh V   Ji Youngmi Y   Rhim Johng J   Olender Jacqueline J   Popratiloff Anastas A   Latham Patricia P   Lai Yinglei Y   Patierno Steven R SR   Lee Norman H NH  

Clinical cancer research : an official journal of the American Association for Cancer Research 20150618 21

<h4>Purpose</h4>African Americans (AA) exhibit higher rates of prostate cancer incidence and mortality compared with European American (EA) men. In addition to socioeconomic influences, biologic factors are believed to play a critical role in prostate cancer disparities. We investigated whether population-specific and -enriched miRNA-mRNA interactions might contribute to prostate cancer disparities.<h4>Experimental design</h4>Integrative genomics was used, combining miRNA and mRNA profiling, miR  ...[more]

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