Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Urinary proteomics of bladder cancer

ABSTRACT: LC-MS/MS was used to perform proteomic analysis of preoperative and postoperative urine samples of patients with bladder cancer

ORGANISM(S): Homo Sapiens

SUBMITTER: Yunping Zhu

PROVIDER: PXD011871 | iProX | Thu Nov 29 00:00:00 GMT 2018

REPOSITORIES: iProX

ACCESS DATA

Json Xml

Publications

Discovery of bladder cancer biomarkers in paired pre- and postoperative urine samples.

Li Xuechao X Huang Chuanxi C Zhang Xueli X Yang Tao T Zuo Shidong S Fu Chengwei C Zhang Yongjie Y Yang Chunyuan C Chen Lijun L

Translational andrology and urology 20210801 8

<h4>Background</h4>Bladder cancer (BC), a common cancer of the urinary system, has a low mortality but an extremely high recurrence rate. Patients who have undergone initial surgical treatment often undergo frequent prognostic examinations with a substantial burden of discomfort and costs. Urine samples can reflect early disease processes in the urinary system and may be an excellent source of biomarkers.<h4>Methods</h4>In the present study, we used the liquid chromatography with tandem mass spe ...[more]

PMID: 34532265

Similar Datasets

Genome-wide identification of urinary cell-free microRNAs for non-invasive detection of bladder cancer

Project description:Objective was to identify urine cell-free microRNAs enabling early non-invasive detection of bladder cancer. Total RNA enriched for fraction of short RNAs was isolated using Urine microRNA purification kit (Norgen corp.). miRNA profiles were determined using the Affymetrix GeneChip miRNA 3.0 array and analyzed to identify differentially deregulated miRNA in bladder cancer patients compared with helathy controls.

2017-10-29 | E-MTAB-6102 | biostudies-arrayexpress

RNA-associated to Urinary Vesicles as a Suitable Non-invasive Source for Diagnostic Purposes in Bladder Cancer

Project description:Bladder cancer is one of the most common cancers. Since prognosis ameliorates with early detection, it is a challenge to develop techniques that could replace or complement the current diagnosis protocols. The study of extracellular vesicles (EVs) that are present in urine samples has become an attractive alternative. The present study describes the mRNA content of vesicles isolated from voided urine samples within bladder cancer context. To discover a genetic signature of cancer, RNA associated to EVs was analyzed by microarray technique. Total RNA isolated from Extracellular Vesicles obtained from urine of bladder cancer patients was compared with RNA isolated from urinary vesicles of non-cancer patients.

2014-01-29 | E-GEOD-51843 | biostudies-arrayexpress

Urinary extracellular vesicles for high-precision bladder cancer subtyping and prognosis

Project description:Bladder cancer exhibits molecular heterogeneity that complicates early diagnosis and prognosis, and drives confounding clinical outcomes. Non–muscle invasive and muscle-invasive subtypes, especially for intermediate to high grade, carry a 25 – 50% progression-free survival rate, underscoring the need for high precision prognostic strategy. Urinary extracellular vesicles (uEVs) are promising carriers of tumor-derived RNAs and proteins. However, significant challenges in studying uEVs arise from the diverse cellular origin of uEVs associated with the dynamic composition of urine, which presents roadblocks for developing the clinical utility of uEVs. We introduced an AI-driven EV liquid biopsy pipeline that integrates (1) standardized EV isolation via NanoPom magnetic beads, (2) transcriptomic profiling for molecular subtyping, and (3) prognostic scoring algorithm. In a discovery cohort of 16 bladder cancer patients including both MIBC and NMIBC, we compared NanoPom isolated uEVs with ExoEasy and Fujifilm MagCapture isolated uEVs, for identifying bladder cancer subtype-specific gene signatures, and externally validated them using UCSC Xena. The result outperformed currently reported bladder cancer diagnostic biomarkers from assays including Galeas, CxBladder, and Xpert. In a validation cohort of matched 7 patient plasma samples, we confirmed with plasma derived EVs for correlating with urinary EV biomarkers from NGS sequencing. The prognostic score stratified patients into low-, intermediate-, and high-grade risk groups based on Xena's bladder cancer survival outcomes. Our AI-driven uEV liquid biopsy pipeline proves the concept for high precision bladder cancer subtyping and prognosis, which could potentially facilitate treatment decision and lead to advanced profiling of bladder tumor biology using uEV liquid biopsy.

2025-09-28 | GSE308996 | GEO

Whole genome expression data from human urinary bladder cancer

Project description:At diagnosis approximately 75% of bladder urothelial carcinomas are non muscle invasive bladder cancers (Ta, T1 and Tis), 20% are muscle invasive bladder cancer (T2-T4) and 5% are already metastatic. Non muscle invasive bladder cancers are characterized by tumor recurrence in 60% to 85% of cases and, therefore, long-term followup is needed. The current standard methods to detect and monitor bladder cancer are cystoscopy and cytology. Cystoscopy is an invasive method and cytology is hampered by low sensitivity, especially for low grade tumors. So there is need to develop reliable and noninvasive methods to detect and predict bladder cancer biological behavior. So we have performed high density oligonucleotide microarray for discovery of new molecular markers to diagnose and predict the outcome of bladder cancer. Under an ethical guideline of Chhatrapati Shahuji Maharaj Medical University, India histologically confirmed seven bladder cancer patients were recruited from Department of Urology, Chhatrapati Shahuji Maharaj Medical University, Lucknow, India. Total RNA was extracted from tumor biopsies and hybridized on affymetrix Human Gene ST 1.1 array to determine differentially expressed genes in urinary bladder cancer with muscle invasion in comparison of normal human urinary bladder.

2012-02-22 | E-GEOD-23732 | biostudies-arrayexpress

Urinary microbiota and bladder cancer

Project description:Urinary microbiota and bladder cancer

| PRJEB39977 | ENA

Whole genome expression data from human urinary bladder cancer

2012-02-22 | GSE23732 | GEO

Landscape of genomic alterations in Indian Urinary Bladder cancer patients

Project description:Urinary bladder is an open system and is under constant carcinogenic insults leading to chromosomal aberrations. Chronic retention of urine in the bladder is considered one of the reasons for initiation of bladder cancer. Here, we have explored the genomic alterations in Indian BlCa patients by CGH-SNP microarray. The microarray data (n=10) revealed several alterations throughout the genome. Genomic regions like 2p25.3 [chr2: 3557810-3575411], 4p16.3 [chr4: 656211-657032], 7p22.3 [chr7: 990730-1000575], 10q26.13 [chr10: 123137874-123148372], 16q24.3 [chr16: 88835825-88837868], 17p11.2 [chr17: 17477220-17506264], 19q13.33 [chr19: 49861971-49862491], 20q13.33 [chr20: 63406442-63415195; 63415195-63495407] etc. were found to be frequently (≥40%) amplified among the 10 BlCa samples. Regions like 2q37.2 [chr2: 235384329- 235479250], 8p23.3-11.21 [chr 8: 236477- 39291988], 10q21.1-26.3 [chr 10: 55309072- 133391562], 11p12 [chr 11: 37327799- 38803561], 12q24.31-24.33 [chr 12: 128515048- 133047983], and 13q13.3-34 [chr 13: 35583974- 113996673] etc. are identified as common deletion (30%). Chromosomal regions like 2p25.3, 16q24.3 and 20q13.33 showed the highest frequency of amplification (70%), whereas 2q37.2, 10q21.1, 11p12, 11q22.3, etc. showed the highest frequency of deletion (30%). Chromosome 7, 15 and 21 showed the least alterations in these samples. Almost a complete loss in 8p chromosomal arm (8p23.1-11.22), chromosome 11q (11q14.1-25) and chromosome 13 (13q13.3-34) were found in 30% of samples, signifying their plausible role in development of BlCa.

2020-11-01 | GSE122514 | GEO

microRNA expression profiling of urine and cancer tissues of patients with bladder cancer, and those from the controls with haematuria

Project description:Mid-stream urine was collected from bladder cancer patients prior to surgery. Both tumor tissue and normal bladder mucosa that are located at >3cm away from the tumor edge were obtained by cystoscopy. For the normal controls with haematuria, urine samples were collected from patients who had normal cystoscopic finding and absence of malignancy with >6 months follow-up. All urine samples were centrifuged at 2500 r.c.f. for 20 minutes and the urine supernatant was collected. Total RNA of urine supernatant and frozen tissue was extracted using MirVanaTM PARISTM Kit (Ambion) in accordance with the manufacturerâs recommended protocols. AgilentTM Human miRNA Microarray Chip (Release 13.0, Agilent Technologies, Santa Clara, CA, USA) was used to determine the microRNA expression profiles of the samples.

2014-04-16 | E-MTAB-2573 | biostudies-arrayexpress

Urinary bladder disease in rat experimental diabetes mellitus

Project description:Diabetes mellitus (DM) is a leading cause of chronic kidney disease and the pathobiology of diabetic nephropathy is widely studied. Less, however, is known about urinary bladder disease in DM despite dysfunctional voiding being a common clinical problem. We hypothesised that diabetic cystopathy would have a characteristic molecular signature, due to the adaptive response to increased urine load combined with the metabolic impacts of DM. To distinguish the consequences of DM from polyuria we compared bladders of untreated control, diabetic (streptozotocin-induced) and sucrose-treated male Wistar rats after 16 weeks using gene array

2021-07-17 | E-MTAB-9255 | biostudies-arrayexpress

Single cell RNA sequencing (scRNAseq) of urine-derived cells, peripheral blood mononuclear (PBMC), and tumor cells from bladder cancer patients.

Project description:As no one previously examined urine-derived cells from bladder cancer patients, we performed scRNAseq to profile the diversity of these cells and their transcriptional profiles. We used scRNAseq to compare the profiles of urine-derived cells to matched tumor cells and PBMC from bladder cancer patients.

2024-05-17 | GSE267718 | 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