Identifying molecular features for prostate cancer with Gleason 7 based on microarray gene expression profiles

• Published in: Romanian journal of morphology and embryology Vol. 52; no. 4; pp. 1195 - 1202
• Main Authors: Bălăcescu, Loredana, Bălăcescu, O, Crişan, N, Fetica, B, Petruţ, B, Bungărdean, Cătălina, Rus, Meda, Tudoran, Oana, Meurice, G, Irimie, Al, Dragoş, N, Berindan-Neagoe, Ioana
• Format: Journal Article
• Language: English
• Published: Romania 2011
• Subjects: Aged; Cluster Analysis; Gene Expression Profiling; Gene Expression Regulation, Neoplastic; Gene Regulatory Networks - genetics; Humans; Male; Middle Aged; Neoplasm Grading; Oligonucleotide Array Sequence Analysis; Prostate - metabolism; Prostate - pathology; Prostatic Neoplasms - genetics; Prostatic Neoplasms - pathology; Real-Time Polymerase Chain Reaction; Reproducibility of Results
• ISSN: 1220-0522

Prostate cancer represents the first leading cause of cancer among western male population, with different clinical behavior ranging from indolent to metastatic disease. Although many molecules and deregulated pathways are known, the molecular mechanisms involved in the development of prostate cancer are not fully understood. The aim of this study was to explore the molecular variation underlying the prostate cancer, based on microarray analysis and bioinformatics approaches. Normal and prostate cancer tissues were collected by macrodissection from prostatectomy pieces. All prostate cancer specimens used in our study were Gleason score 7. Gene expression microarray (Agilent Technologies) was used for Whole Human Genome evaluation. The bioinformatics and functional analysis were based on Limma and Ingenuity software. The microarray analysis identified 1119 differentially expressed genes between prostate cancer and normal prostate, which were up- or down-regulated at least 2-fold. P-values were adjusted for multiple testing using Benjamini-Hochberg method with a false discovery rate of 0.01. These genes were analyzed with Ingenuity Pathway Analysis software and were established 23 genetic networks. Our microarray results provide new information regarding the molecular networks in prostate cancer stratified as Gleason 7. These data highlighted gene expression profiles for better understanding of prostate cancer progression.