ABSTRACT: Whole-transcript and exon-level expression data for human primary and metastatic prostate cancer samples and control normal adjacent benign prostate
Project description:An integrative analysis of this compendium of proteomic alterations and transcriptomic data was performed revealing only 48-64% concordance between protein and transcript levels. Importantly, differential proteomic alterations between metastatic and clinically localized prostate cancer that mapped concordantly to gene transcripts served as predictors of clinical outcome in prostate cancer as well as other solid tumors. Keywords: prostate cancer progression 13 individual benign prostate, primary and metastatic prostate cancer samples and 6 pooled samples from benign,primary or metastatic prostate cancer tissues.
Project description:Through digital rectal examinations and routine prostate-specific antigen (PSA) screening, early treatment of prostate cancer has become possible. However, prostate cancer is a complex and heterogeneous disease. In many patients, cancer cells can invade adjacent tissues and metastasize to other tissues, resulting in difficultly to cure. For the treatment of primary and metastatic prostate cancer, a significant problem is how to improve its survival time. Here, we collect 7 untreated primary and metastatic prostate cancer and 6 benign prostate hyperplasia samples under ultrasound guidance by experienced radiologists using the 18-G needle. Through mass spectrometry, we have completely depicted the protein atlas of primary and metastatic prostate cancer and benign prostate hyperplasia. Through bioinformatics analysis, experimental verification, and combined clinical data, we discover that the ribosome signaling pathway promotes the progression of prostate cancer and is associated with a poor prognosis. Among them, Mrpl1, Mrpl4, and Mrpl16 may be biomolecular markers for diagnosis and prognosis.
Project description:Molecular and genomic analysis of microscopic quantities of tumor from formalin-fixed and paraffin-embedded (FFPE) biopsies has many unique challenges. Here we evaluated the feasibility of obtaining transcriptome-wide RNA expression to measure prognostic classifiers from diagnostic prostate needle core biopsies. 158 samples from diagnostic needle core biopsies (Bx) and radical prostatectomies (RP) were collected from 33 patients at three hospitals, each patient provided up to 6 tumor and benign samples. Genome-wide transcriptomic profiles were generated using Affymetrix Human Exon arrays for comparison of gene expression alterations and prognostic signatures between the Bx and RP samples. For 23 patients from UCSF and CSMC, six prostate tissue samples were obtained from each patient: tumor biopsy, tumor RP, benign adjacent biopsy, benign adjacent RP, and benign contralateral biopsy, and benign contralateral RP. For the 10 UHN patients only tumor biopsy and tumor RP samples were obtained. A total of 147 samples passed RNA, cDNA, and microarray quality control.
Project description:Large-scale gene expression profiles were investigated in 48 normal and 47 prostate tumor tissue samples using Affymetrix GeneChip Exon 1.0 ST microarrays. Gene expression profiling of human prostate samples using Affymetrix Human Exon 1.0 ST arrays Two disease subtype analyses were performed: - Prostate Tumor vs Benign - TMPRSS2-ERG fusion-positive vs fusion-negative prostate tumors
Project description:This SuperSeries is composed of the following subset Series:; GSE6604: Expression data from Normal Prostate Tissue free of any pathological alteration; GSE6605: Expression data from Metastatic Prostate Tumor; GSE6606: Expression data from Primary Prostate Tumor; GSE6608: Expression data from Normal Prostate Tissue Adjacent to Tumor Experiment Overall Design: Refer to individual Series
Project description:Twenty-nine radical prostatectomy samples were laser capture microdissected (LCM) to obtain the most common Gleason patterns (patterns 3, 4, and 5) and matched benign adjacent luminal prostate epithelial cells. We performed cDNA microarrays on matched cancer and adjacent normal samples and identified an 86-gene model capable of distinguishing low Gleason grade (pattern 3) from high Gleason grade (pattern 4 and 5) cancers, which contributes a set of potential targets for modulating the development and progression of the lethal prostate cancer phenotype. Keywords: disease state analysis
Project description:Here we used Illumina NGS for high-throughput profiling of the DNA methylome in seven human benign prostate tissues, seven human primary prostate cancer and six human castration resistant prostate cancer patient samples. These data were used to profile the CpG cytosine methylation pattern at single base resolution in each sample and to determine differentially methylated cytosines and regions among samples. Enhanced Reduced Representation Bisulfite Sequencing (ERRBS, MspI,150M-bM-^@M-^S400 bp size fractions) of 20 human prostate tissues (benign prostate tissues, localized and metastatic prostate cancer)