Gene expression profiling of prostate cancer
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE9347 | GEO | 2009/01/21
SECONDARY ACCESSION(S): PRJNA103037
REPOSITORIES: GEO
Similar Datasets
Project description:Heparan sulfate (HS) is a linear, sulfated polysaccharide, and expresses abundantly in prostate and PCa tissues. Intriguingly, the HS content and sulfation modifications appear to increase when the prostate becomes malignance, suggesting that HS may critically modulate PCa pathogenesis. We specifically ablated Ext1, the enzyme that initiates HS biosynthesis, in mouse prostate at late development stage. And used microarray to detail the gene expressions affected by Ext1 ablation and identified distinct classes of up-regulated genes during this process. Prostate tissues were removed from euthanized mice at 5 weeks old for RNA extraction and hybridization on Affymetrix microarrays. We sought to compare gene expression during tumorigenesis among the wildtype, prostate specific knockout of Pten and double knockout of Pten and Ext1 in prostate.
2013-05-15 | E-GEOD-46898 | biostudies-arrayexpress
Project description:Predicting Outcomes of Prostate Cancer Immunotherapyby Personalized Mathematical Models
Natalie Kronik1¤, Yuri Kogan1, Moran Elishmereni1, Karin Halevi-Tobias1, Stanimir Vuk-Pavlovic ́2.,Zvia Agur1*.1Institute for Medical BioMathematics, Bene Ataroth, Israel,2College of Medicine, Mayo Clinic, Rochester, Minnesota, United States of America
Abstract
Background:Therapeutic vaccination against disseminated prostate cancer (PCa) is partially effective in some PCa patients.We hypothesized that the efficacy of treatment will be enhanced by individualized vaccination regimens tailored by simplemathematical models.Methodology/Principal Findings:We developed a general mathematical model encompassing the basic interactions of avaccine, immune system and PCa cells, and validated it by the results of a clinical trial testing an allogeneic PCa whole-cellvaccine. For model validation in the absence of any other pertinent marker, we used the clinically measured changes inprostate-specific antigen (PSA) levels as a correlate of tumor burden. Up to 26 PSA levels measured per patient were dividedinto each patient’s training set and his validation set. The training set, used for model personalization, contained thepatient’s initial sequence of PSA levels; the validation set contained his subsequent PSA data points. Personalized modelswere simulated to predict changes in tumor burden and PSA levels and predictions were compared to the validation set.The model accurately predicted PSA levels over the entire measured period in 12 of the 15 vaccination-responsive patients(the coefficient of determination between the predicted and observed PSA values wasR2= 0.972). The model could notaccount for the inconsistent changes in PSA levels in 3 of the 15 responsive patients at the end of treatment. Each validatedpersonalized model was simulated under many hypothetical immunotherapy protocols to suggest alternative vaccinationregimens. Personalized regimens predicted to enhance the effects of therapy differed among the patients.Conclusions/Significance:Using a few initial measurements, we constructed robust patient-specific models of PCaimmunotherapy, which were retrospectively validated by clinical trial results. Our results emphasize the potential value andfeasibility of individualized model-suggested immunotherapy protocols.
2020-01-13 | MODEL2001130003 | BioModels
Project description:Due to heterogeneous multifocal nature of prostate cancer (PCa), there is currently a lack of biomarkers that stably distinguish it from benign prostatic hyperplasia (BPH), predict clinical outcome and guide the choice of optimal treatment. In this study, RNA-seq analysis was applied to formalin-fixed paraffin-embedded (FFPE) tumor and matched normal tissue samples collected from Russian patients with PCa and BPH. We identified 3384 genes differentially expressed (DE) (FDR < 0.05) between tumor tissue of PCa patients and adjacent normal tissue as well as both tissue types from BPH patients. Overexpression of four of the genes previously not associated with PCa (ANKRD34B, NEK5, KCNG3, and PTPRT) was validated by RT-qPCR. Furthermore, the enrichment analysis of overrepresented microRNA and transcription factor (TF) recognition sites within DE genes revealed common regulatory elements of which 13 microRNAs and 53 TFs were thus linked to PCa for the first time. Moreover, 8 of these TFs (FOXJ2, GATA6, NFE2L1, NFIL3, PRRX2, TEF, EBF2 and ZBTB18) were found to be differentially expressed in this study, making them not only candidate biomarkers of prostate cancer but also potential therapeutic targets.
2017-03-27 | GSE89223 | GEO
Project description:Higher expression levels of DLX1 has been associated with primary and metastatic prostate tumor. DLX1 along with HOXC6 is well-established diagnostic biomarker for the early detection of prostate cancer (PCa). However, the mechanism involved in DLX1 up-regulation and functional significance in metastatic castration-resistant prostate cancer (mCRPC) progression remains unexplored. Here, we identified that DLX1 serves as an oncogene thereby regulating several oncogenic properties associated with PCa progression.
2021-07-30 | GSE138738 | GEO
Project description:In spite of its prevalence as one of the world’s leading malignancies, prostate cancer (PCa) continues to evade molecular taxonomic sub-classification. However, gross clinical differences are observed within the umbrella term ‘prostate adenocarcinoma’; the majority of tumors appear indolent in nature, whilst a subset manifest aggressively. Contributing factors towards this resistance to molecular classification are an atypically low mutation frequency and a poorly delineated pathobiology. Conversely, epigenetic changes are evidenced to be amongst the earliest and most-widespread aberrations in PCa . We thus hypothesized that delineating epigenomic alterations during the stepwise progression of PCa would improve our understanding of the disease pathobiology and the molecular underpinning of indolent and aggressive tumors. Herein, we report the first epigenomic roadmap of prostate tumorigenesis, in which we dissected DNA methylation and microRNA expression in enriched epithelial cells across the entire trajectory of PCa, through tumor initiation, primary disease and metastatic dissemination. Infinium Human Methylation450K Beachip (Illumina) technology was employed to assess the methylation status of >485,000 CpG sites throughout the genome across six histological stages of prostate cancer (PCa) tumorigenesis: benign (n=10), proliferative inflammatory atrophy (PIA; n=7), high grade prostatic intra-epithelial neoplasia (HGPIN; n=6), indolent PCa (PCI, n=7), agressive PCa (PCA; n=8) and lethal metastatic PCa (PCM; n=6). Three peripheral blood lymphocytes (PBL) samples were also included for control purposes.
2021-09-01 | GSE157272 | GEO
Project description:ETS transcription factors have recently emerged as important elements in the pathogenesis of prostate cancer (PCa). ETS gene rearrangements leading to over-expression of ETS factors, like ERG, ETV1 and ETV4, are found in about 50% of prostate tumors. While the oncogenic potential of translocated ETS has been demonstrated in several contexts, the impact of endogenously expressed ETS factors on prostate tumorigenesis has been largely overlooked. Here we show that the epithelial-specific ETS factor ESE3, which is normally expressed in basal prostate epithelial (PrE) cells and frequently down-regulated in prostate tumors, serves as gatekeeper to maintain cell differentiation and its down-regulation leads to the acquisition of mesenchymal, stem cell (SC) and tumorigenic properties. ESE3 exerts this function by regulating critical genes involved in the epithelial to mesenchymal transition (EMT) and cell “stemness” and maintaining the equilibrium between cell differentiation and proliferation. Loss of ESE3 may be an important step in prostate tumorigenesis. Keywords: prostate epithelial cells, prostate cancer, gene expression profiling, ETS genes, EMT, cancer stem cells
2012-06-05 | GSE23197 | GEO
Project description:PRMT5 is the major type II protein arginine methyltransferase catalyzing the symmetric dimethylation of arginine. Recent reports have indicated that PRMT5 is overexpressed in multiple cancer types, including prostate. However, the exact contribution of PRMT5 to prostate tumorigenesis is unknown. To explore the functional role of PRMT5 in prostate cancer (PCa), we knocked down PRMT5 by lentiviral shRNAs in both AR-dependent LNCaP cells and AR-independent PC3 cells. Our data suggests that PRMT5 regulates PCa cell biology. To further identify PRMT5-regulated genes in PCa, we performed paired-end RNA-seq analysis in PC3 and LNCaP cells with or without PRMT5-knockdown.
2023-12-25 | GSE117596 | GEO
Project description:African American (AA) men have a significantly higher mortality rate from prostate cancer (PCa) compared to European American (EA) men. AA men are twice as likely to die from PCa compared to EA men and 8 times as likely as Asian American men to die from PCa. The biological basis for these differences in PCa mortality are unclear. We carried out Copy Number Alteration (CNA) studies on a new set of 40 highly tumor-enriched primary PCas and matched benign prostate tissues from AA men using high resolution Affymetrix 6.0 SNP arrays and expression array analysis using RNAs (GSE71016) from the same tissues using high purity tumors from AA men and matched benign tissue. We have confirmed the specific loss of 4p16.3 described previously and identified a novel tumor suppressor gene, RGS12 at this locus that shows significantly decreased expression in AA PCa but not EA EA PCa.
2018-06-06 | GSE95726 | GEO
Project description:It is well known that prostate cancer (PCa) is a progressive disease involving multiple gene alterations. The Gleason score (GS) is a morphologic feature of PCa used in the clinic to evaluate the risk of disease progression. However, GS often fail to clearly distinguish between indolent and aggressive disease. The aim of this study was to identify potential biomarkers for PCa risk stratification. An in-depth proteomics analysis (LC ESI-MS/MS) was performed on human PCa and BPH tissues. First, we identified differentially expressed proteins between PCa and BPH samples. We then filtered the proteins based on peptide spectrum matches and selected a panel of candidates. To assess and validate the clinical significance of these peptides we performed an integrative bioinformatics analysis using public database repositories. We identified YWHAZ, an androgen receptor downstream target, as one of the proteins enriched in PCa compared with BPH. We also found a strong association of YWHAZ expression with poor prognosis across different PCa datasets. Briefly, overall and relapse-free survival were significantly shorter in PCa cases expressing high vs. low YWHAZ expression. Further, multivariate analyses displayed high significant correlation with poor prognosis, independent from GS, age, PSA at diagnosis and TMPRSS2-ERG fusion. A multi-cancer screening for YWHAZ unveils amplification as the main alteration for this gene correlating with increased mRNA expression levels across all types of cancer through the cBioPortal platform. YWHAZ rises as a promising prognostic factor in PCa, independent from GS, aiding in disease risk stratification.
2021-09-08 | PXD014291 | Pride
Project description:GENPROS aims to analyse the outcomes of patients with rare gene mutations in the cancer predisposition genes, BRCA1, BRCA2, HOXB13, and Lynch Syndrome, after a diagnosis of and treatment for prostate cancer (PCa). The study includes a cohort of gene mutation carriers with PCa matched with a control group of men with PCa who are known not to carry a mutation in the same gene. Clinical data regarding treatment and patient outcome will be collected retrospectively and prospectively. Archived tumour samples will also be collected for tumour profiling. A blood or saliva sample will be taken, if the participant consents to this part of the study, for genetic profiling to investigate any association of other inherited factors with PCa outcomes. Information obtained from this study will be of critical importance to support clinical trials investigating the most appropriate management of PCa in this group of patients at increased risk of prostate cancer.
| 2210056 | ecrin-mdr-crc