Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Transcriptomic profiling of urine extracellular vesicles reveals alterations of CDH3 in prostate cancer

ABSTRACT: One of the challenges of current research in prostate cancer is to improve the differential non-invasive diagnosis of prostate cancer (PCa) and benign prostate hyperplasia (BPH). Extracellular vesicles (EV) are emerging structures with promising properties for intercellular communication. In addition, the characterization of EV in biofluids is an attractive source of non-invasive diagnostic, prognostic and predictive biomarkers. Here we show that urinary EV (uEV) from prostate cancer patients exhibit genuine and differential physical and biological properties. Importantly, transcriptomics characterization of uEVs led us to define the decreased abundance of Cadherin 3, type 1 (CDH3) transcript in uEV from PCa patients. Tissue and cell line analysis strongly suggested that the status of CDH3 in uEVs is a distal reflection of changes in the expression of this cadherin in the prostate tumor. Our results reveal that uEVs could represent a non-invasive tool to inform about the molecular alterations in prostate cancer.

ORGANISM(S): Homo sapiens

PROVIDER: GSE75441 | GEO | 2016/01/13

SECONDARY ACCESSION(S): PRJNA304301

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Similar Datasets

Transcriptomic profiling of urine extracellular vesicles reveals alterations of CDH3 in prostate cancer

Project description:One of the challenges of current research in prostate cancer is to improve the differential non-invasive diagnosis of prostate cancer (PCa) and benign prostate hyperplasia (BPH). Extracellular vesicles (EV) are emerging structures with promising properties for intercellular communication. In addition, the characterization of EV in biofluids is an attractive source of non-invasive diagnostic, prognostic and predictive biomarkers. Here we show that urinary EV (uEV) from prostate cancer patients exhibit genuine and differential physical and biological properties. Importantly, transcriptomics characterization of uEVs led us to define the decreased abundance of Cadherin 3, type 1 (CDH3) transcript in uEV from PCa patients. Tissue and cell line analysis strongly suggested that the status of CDH3 in uEVs is a distal reflection of changes in the expression of this cadherin in the prostate tumor. Our results reveal that uEVs could represent a non-invasive tool to inform about the molecular alterations in prostate cancer. RNA extraction was performed in 10 ultracentrifuge-isolated-uEVs samples (4 BPH, 6 Pca)

2016-01-13 | E-GEOD-75441 | biostudies-arrayexpress

Deep sequencing identified serum extracellular vesicle delivered miR-181a-5p as an indicator for bone-metastatic prostate cancer (microarray)

Project description:Purpose: The goals of this study are to compare the serum extracellular vesicle (EV) delivered miRNA levels of patients with bone-metastatic prostate cancer (PCa), non-bone -metastatic PCa and benign prostatic hyperplasia (BPH), and to identify EV-delivered microRNAs in patient’s serum as indicators for bone-metastatic PCa. Methods:Serum extracellular vesicle delivered miRNA profiles of patients with bone-metastatic PCa or non-bone -metastatic PCa or BPH were generated by miRNA chip array, using Agilent-070156 Human_miRNA_V21.0_Microarray plateform. Results: Differential analysis showed the expressions of 27 EV delivered miRNAs were significantly different between serum of patients with bone-metastatic PCa and non-bone-metastatic PCa with a p value <0.05. the expressions of 5 EV delivered miRNAs were confirmed with qRT–PCR. Conclusions: Serum EV-delivered miR-181a-5p is a promising diagnostic biomarker for bone-metastatic PCa.

2020-01-31 | GSE134266 | GEO

Deep sequencing identified serum extracellular vesicle delivered miR-181a-5p as an indicator for bone-metastatic prostate cancer

Project description:Purpose: The goals of this study are to compare the serum extracellular vesicle (EV) delivered miRNA levels of patients with bone-metastatic prostate cancer (PCa), non-bone -metastatic PCa and benign prostatic hyperplasia (BPH), and to identify EV-delivered microRNAs in patient’s serum as indicators for bone-metastatic PCa. Methods:Serum extracellular vesicle delivered miRNA profiles of patients with bone-metastatic PCa or non-bone -metastatic PCa or BPH were generated by deep sequencing, using Illumina HiSeqTM 2500 platform Results: Using an optimized data analysis method, we mapped about 17 million sequence reads per sample. Differential analysis showed the expressions of 35 EV delivered miRNAs were significantly different between serum of patients with PCa and BPH, with a p value <0.05. the expressions of 5 EV delivered miRNAs were confirmed with qRT–PCR. Conclusions: Serum EV-delivered miR-181a-5p is a promising diagnostic biomarker for bone-metastatic PCa.

2020-01-31 | GSE134205 | GEO

Urinary endogenous peptides as biomarkers for prostate cancer

Project description:Prostate cancer (PCa) is one of the most prevalent cancer types in men worldwide. However, the main diagnostic tests available for PCa have limitations and need biopsy for histopathological confirmation of the disease. The prostate-specific antigen (PSA) is the main biomarker used for PCa early detection, but an elevated serum concentration is not cancer-specific. Therefore, there is a need for discovery of new non-invasive biomarkers that can accurately diagnose PCa. Here, we used trichloroacetic acid-induced protein precipitation and liquid chromatography-mass spectrometry to profile endogenous peptides in urine samples from patients with PCa (n = 33), benign prostatic hyperplasia (n = 25), and healthy individuals (n = 28). Receiver operating characteristic (ROC) curves were performed to evaluate the diagnostic performance of urinary peptides. In addition, proteasix tool was used for in silico prediction of protease cleavage sites. We found five urinary peptides derived from uromodulin significantly altered between the study groups, all of which were less abundant in the PCa group. In addition, urinary peptides outperformed PSA in discriminating between malignant and benign prostate conditions (AUC = 0.847), showing high sensitivity (81.82%) and specificity (88%). Overall, our study allowed the identification of urinary peptides with potential for use as non-invasive biomarkers in PCa diagnosis.

2022-10-25 | PXD037031 | Pride

Characterization of the human urine proteome in Prostate Cancer

Project description:Prostate cancer (PCa) is one of the most prevalent cancers among men and the fifth leading cause of cancer-related death in men. Currently, PCa suspicion is based on abnormal digital rectal examination and/or raised PSA serum levels, with prostate needle biopsy being required for a definitive diagnosis. Histopathological classification of tumours based on GS grading, cancer staging and PSA levels are used to predict the indolent or aggressive progression of the tumour as well as the likelihood of disease recurrence. These diagnosis and prognosis tools for PCa have revealed limited usefulness, especially PSA testing, which despite organ-specificity is not cancer-specific, being associated with low specificity. In this vein, new markers have been proposed in order to increase the accuracy of PCa detection, most of them proteins. Despite the significant efforts that have been undertaken for discovering other biomarkers for PCa management, few were translated into clinical practice. The simple and non-invasive nature of urine collection along with its proteome stability and storing many secreted proteins of prostate origin, makes the identification of PCa urinary biomarkers an attractive approach. With this in mind, we aimed to compare the urinary proteome profile of PCa patients with non-cancer patients in order to identify non-invasive candidate biomarkers for PCa prediction. To fulfil this task, we followed a shotgun LC-MS/MS approach using an Orbitrap instrument. A combination of two different software packages, MaxQuant and Proteome Discover was used to increase the robustness of analysis and enhance the search for new biomarkers. Proteins quantification was based on a label-free quantification approach (false discovery rate (FDR) 1%). The present dataset was used to disclosure potential markers in PCa management.

2022-05-19 | PXD017902 | Pride

miRNA expression differences between FFPE prostate cancer and adjacent normal tissues using real-time quantitative PCR array analysis

2013-11-15 | GSE48430 | GEO

miRNA expression differences between FFPE prostate cancer and adjacent normal tissues using real-time quantitative PCR array analysis

Project description:Laser Capture Microdissected cells from archival FFPE Prostate cancer and normal adjacent tissues from 10 patients (5 CA and 5 AA) were converted to cDNA and analysed by PCR array to identify differentially expressed miRNAs between the groups. Selected differentially expressed miRNAs were further validated in tissues from 40 prostate cancer patients. The miRNAs which were differentially modulated in PCa patients in the validation set were further analysed in 32 urine samples from PCa patients and compared with 12 healthy individuals. Differentially expressed miRNAs were explored to e used as non-invasive biomarker for PCa. qPCR miRNA expression profiling. mRNA from 10 Prostate Cancer patients (5 Caucasian American and 5 African American) and their paired adjacent normal tissue were analysed to identify the differentially expressed miRNA between the groups. Equal amount small RNA from each group was pooled prior to gene expression analysis.

2013-11-15 | E-GEOD-48430 | biostudies-arrayexpress

Proteomic signatures of extracellular vesicles secreted by non-mineralizing and mineralizing human osteoblasts and stimulation of tumor cell growth

Project description:Beyond forming bone, osteoblasts play pivotal roles in various biological processes, including hematopoiesis and bone metastasis. Extracellular vesicles (EVs) have recently been implicated in intercellular communication via transfer of proteins and nucleic acids between cells. Here, we focused on the proteomic characterization of non-mineralizing (NMOBs) and mineralizing (MOBs) human osteoblast (SV-HFOs) EVs and investigated their effect on human prostate cancer (PC3) cells by microscopic, proteomic and gene expression analyses. Proteomic analysis showed that 97% of the proteins were shared among NMOB and MOB EVs, and 30% were novel osteoblast-specific EV proteins. Label-free quantification demonstrated mineralization stage-dependent five-fold enrichment of 59 and 451 EV proteins in NMOBs and MOBs, respectively. Interestingly, bioinformatic analyses of the osteoblast EV proteomes and EV-regulated prostate cancer gene expression profiles showed that they converged on pathways involved in cell survival and growth. This was verified by in vitro proliferation assays where osteoblast EV uptake led to two-fold increase in PC3 cell growth compared to cell-free culture medium-derived vesicle controls. Our findings elucidate the mineralization stage-specific protein content of osteoblast-secreted EVs, show a novel way by which osteoblasts communicate with prostate cancer, and open up innovative avenues for therapeutic intervention. PC3 cells were treated with extracellular vesicles from non-mineralizing and mineralizing SV-HFOs for three different incubation times (4hrs, 24hrs, 48hr)

2014-10-28 | E-GEOD-56172 | biostudies-arrayexpress

miR-26a regulate the extracellular vesicle secretion from prostate cancer cells via targeting PFDN4, CHORDC1 and SHC4

Project description:Extracellular vesicles (EVs) are known to be involved in inter-cellular communication during cancer progression, however, the biogenesis of EVs in cancer cells is not completely unveiled. It has been shown that microRNAs (miRNAs) regulated variety of physiological and pathological phenomena, thus, miRNAs could regulate the EV secretion. Here, we have performed high throughput miRNA-based screening to identify the regulators of EV secretion using ExoScreen assay. By this miRNA-based screening, we identified miR-26a, which was reported as tumor suppressive miRNA, was found to be an miRNA involved in EV secretion from prostate cancer (PCa) cells. To study the effect of miR-26a on gene expression in EV secretion, transcriptome analysis for miR-26a overexpressing PCa cell lines was performed.

2020-05-12 | GSE132161 | GEO

Esophageal keratinocyte invasion after loss of E-cadherin and TGF receptor type II

Project description:Esophageal cancer is one of the deadliest cancers as patients present at late stages of disease. Frequent gene alterations include the loss of E-cadherin and TGFb receptor type II. The goal of this study was to establish a model of esophageal cancer by introducing dominant-negative mutants of E-cadherin and TGFb receptor II. To analyze the functional consequences and gene expression chages induced by E-cadherin and TGFb receptor type II loss in esophageal cancer. Human esophageal keratinocytes were retrovirally transfected with wild-type full length E-cadherin, dominant-negative E-cadherin and dominant-negative TGFb receptor type II. Grown in organotypic cultures on a collagen/matrigel matrix with embedded fibroblast, the generated cell lines were analyzed for their potential to invade into the underlying matrix. Each cell lines was grown in duplicate in organotypic culture and therefore 2 replicates analyzed. Gene expression changes in invasive versus non-invasive areas were analyzed after RNA isolation using laser-capture microdissection resulting in 2 samples representing a normal esophageal epithelium (Ecad), 2 each of dominant-negative Ecad (Ecyto) non-invasive and invasive. To model the genetic alterations in esophageal cancer dominant-negative E-cadherin and dominant-negative TGFb receptor type II (Ecyto-dnTGFR) were expressed and 2 samples each, non-invasive and invasive, analyzed.

2013-11-12 | E-GEOD-19472 | biostudies-arrayexpress

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data