Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

UPLC-MS based urine metabolomics for bladder cancer diagnosis and grading

ABSTRACT: In our study, we collected urine samples from 246 cases, including 131 BC patients, 27 benign bladder disease patients, and 88 healthy adults as the control group. Ultra-performance liquid chromatography coupled to mass spectrometry (UPLC-MS) was applied for urine metabolomics analysis to distinguish the BC group from the healthy controls and the benign group, and the low-grade BC group from the high-grade BC group.

ORGANISM(S): Homo Sapiens

SUBMITTER: Wei Sun

PROVIDER: PXD058310 | iProX | Wed Nov 27 00:00:00 GMT 2024

REPOSITORIES: iProX

ACCESS DATA

Json Xml

Similar Datasets

Identification of gene expression biomarkers in urine for the non-invasive detection of bladder cancer

Project description:Fifty patient urine samples diagnosed as high-grade urothelial carcinoma (HGUC) or benign were evaluated for bladder cancer via urine cytology. RNA was isolated and analyzed by microarray to identify a panel of biomarkers differentially expressed in HGUC and benign.

2018-04-17 | GSE68020 | 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

Proteomics and lipidomics analysis of plasma biomarkers for cervical cancer

Project description:This study leverages integrated proteomic and lipidomic analyses on plasma samples from 115 high-grade squamous intraepithelial lesion (HSIL) patients, 133 CC patients, and 88 healthy controls (CT) and develops robust models for effectively predicting HSIL and CC.

| PXD063876 |

Detection of urinary microRNAs from epithelial ovarian cancer patients as biomarker

Project description:The Urine RNA from 5 ovarian cancer and 5 healthy control were analyzed with the Human miRNA Microarray and then validated with a quantitative reverse-transcription PCR assay with 29 individual samples, 20 benign gynecological disease and 26 age/sex-matched healthy control. This study determines the clinical value of urine miRNAs as biomarker for epithelial ovarian cancer. Results: The miRNA microarray results demonstrate that the original 38 were identified that were significantly differentially expression in epithelial ovarian cancer compared with healthy control (P<0.01). A total of 1 miRNA was up-regulated in ovarian cancer, while 37 miRNA were down-regulated. the urine RNA from 5 ovarian cancer and 5 healthy women were analysised with Human mirRNA microarry

2015-06-17 | E-GEOD-58517 | biostudies-arrayexpress

Cell-free lncRNA expression signatures in urine serve as novel noninvasive biomarkers for diagnosis and recurrence prediction of bladder cancer

Project description:To identify lncRNAs dysregulated in BC, we assessed the lncRNA expression profile in pooled urine samples of 10 BC patients and 10 controls by microarray. A total of 3093 lncRNAs determined differential expression (fold change>=2.0) between BC patients and controls. Among them, 1680 lncRNAs were up-regulated and 1413 lncRNAs were down-regulated in BC. Of all the differentially expressed lncRNAs indicated by lncRNA expression profiling, 26 lncRNAs (fold change>25) were firstly selected for further evaluation, in which 16 lncRNAs were up-regulated and 10 lncRNAs were down-regulated in BC.

2018-04-25 | GSE106074 | GEO

A validated single-cell-based strategy to identify diagnostic and therapeutic targets in complex diseases [breast cancer validation cohort]

Project description:Breast cancer validation study of CD4+ T cells in an independent group of 24 patients (median age [range], 61.5 [35–88] years) was recruited, based on the same inclusion criteria. All recruited patients were women. Additionally, 14 independent healthy controls were profiled.

2021-11-23 | GSE123087 | GEO

Human primary meningioma vs. non-neoplastic adult meningeal tissue

Project description:Meningiomas are common brain tumors that are classified into three World Health Organization grades (Grade I: benign, Grade II: atypical and Grade III: malignant) and are molecularly ill-defined tumors. The purpose of this study was identify microRNA (miRNA) molecular signatures unique to the different grades of meningiomas correlating them to prognosis. We have used a miRNA expression microarray to show that meningiomas of all three grades fall into two main molecular groups designated “benign” and “malignant” meningiomas. While all typical meningiomas fall into the benign group and all anaplastic meningiomas fall into the malignant group, atypical meningiomas distribute into either one of these groups. We have identified a miRNA signature that distinguishes benign meningiomas from malignant meningiomas.

2011-01-02 | GSE19720 | GEO

Liquid chromatography-mass spectrometry based tissue metabolic profiling reveals major metabolic pathway alterations and potential biomarkers of lung cancer

Project description:MS spectrum of lung tissue metabolic analysis in 131 patients with lung cancer or benign lung tumor. These include lung cancer tissues/benign tumor tissues, adjacent normal tissues and distal normal tissues.

| PXD019969 |

Detection of urinary microRNAs from epithelial ovarian cancer patients as biomarker

2015-06-17 | GSE58517 | GEO

DNA methylation profiling of genomic DNA isolated from urine in Diabetic Chronic-Kidney Disease: a pilot study

Project description:Genome wide DNA methylation profiling of urine and blood samples from patients with diabetic chronic kidney disease. The Illumina Infinium MethylationEPIC BeadChip kit was used to obtain DNA methylation profiles across approximately 850,000 CpGs. Samples included two urine and four buffy coat samples from adults with diabetic chronic kidney disease.

2017-11-16 | GSE106902 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

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