Proteomics

Dataset Information

0

Integrated tissue and urinary proteomic analysis of prostate cancer and MRI visibility

ABSTRACT: This study aimed to explore proteomic alterations associated with prostate cancer presence, aggressiveness, and MRI visibility. Tissue and preoperative urine samples were collected from patients diagnosed with benign prostatic hyperplasia, indolent prostate cancer, and clinically significant prostate cancer, including MRI-visible and MRI-non-visible cases. Proteins were extracted, digested using standard trypsin-based protocols, and analyzed by nanoLC–MS/MS using a high-resolution mass spectrometry platform operating in data-independent acquisition (DIA) mode. Protein identification and quantification were performed using established computational workflows. Statistical analyses were conducted to identify differentially expressed proteins across the clinical groups. This dataset includes raw mass spectrometry files, processed identification and quantification results, and supporting files necessary for data interpretation.

INSTRUMENT(S):

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Urine, Prostate Gland

SUBMITTER: Ana Blanca  

LAB HEAD: Enrique Gomez Gomez

PROVIDER: PXD074635 | Pride | 2026-04-06

REPOSITORIES: Pride

Json Xml

Dataset's files

Source:
Action DRS
Spectronaut_tissue.7z Other
Spectronaut_urine.7z Other
checksum.txt Txt
tissue.7z Other
urine.7z Other
Items per page:
1 - 5 of 5
altmetric image

Publications

Integrated Urinary and Tissue Proteomic Signatures Reveal Core and Progression Biomarkers in MRI-Visible and MRI-Non-Visible Prostate Cancer.

Blanca Ana A   Morillo Ana C AC   Lopez-Beltran Antonio A   Lendinez Cano Guillermo G   Medina Rafael A RA   Chamorro Castillo Laura L   López Ruiz Daniel D   Chicano-Galvez Eduardo E   Campos Hernández Juan Pablo JP   Gómez Gómez Enrique E  

Life (Basel, Switzerland) 20260227 3

<b>Background:</b> Prostate cancer (PCa) shows a marked biological heterogeneity that is closely associated with tumor aggressiveness. A substantial proportion of clinically significant tumors remain undetected by multiparametric magnetic resonance imaging (mpMRI). Elucidating the molecular basis of MRI visibility and identifying non-invasive biomarkers could improve the risk stratification and clinical management of patients. Accordingly, this study aimed to assess tissue and urine proteomic si  ...[more]

Similar Datasets

Proteomics Combination of autoantibody signature with PSA level enables a highly accurate blood-based differentiation of prostate cancer patients from patients with benign prostatic hyperplasia
2017-02-10 | GSE67068 | GEO
Transcriptomics Single-cell RNA-seq analysis of benign prostatic hyperplasia prostate specimens stratified by prostate weight
2026-07-20 | GSE330752 | GEO
Genomics CDK13 upregulation-induced formation of the positive feedback loop among circCDK13, miR-212-5p/miR-449a and E2F5 contributes to prostate carcinogenesis
2022-09-01 | GSE154075 | GEO
Transcriptomics Prostate cancer specific gene expression
2014-07-30 | E-GEOD-30994 | biostudies-arrayexpress
Proteomics General proteomics and lactylation-modified proteomics were used to detect 5 cases of prostate cancer tissues and 5 cases of benign prostatic hyperplasia tissues
2026-01-23 | PXD066054 | Pride
Proteomics Multi-omic diagnostics of prostate cancer in the presence of benign prostatic hyperplasia
2024-01-26 | PXD046530 | Pride
Transcriptomics Prostate cancer specific gene expression
2014-07-30 | GSE30994 | GEO
Transcriptomics Gene expression profiling of hormone resistant prostate cancer
2007-07-01 | GSE5377 | GEO
Transcriptomics Identification of urinary exosomal non-coding RNAs biomarkers for high-grade prostate cancer using RNA-seq analysis
2021-07-28 | GSE147761 | GEO
Transcriptomics RNA sequencing of prostate cancers reveal insights on the prognostic significance of visibility on multi-parametric MRI
2018-02-22 | GSE95369 | GEO