Dataset Information

Proteomics characterization of clear cell renal cell carcinoma

ABSTRACT: The aims of the study was to explore the tumor proteome of patients diagnosed with localized ccRCC and treated with surgery and the identification of altered pathways that could be the target of new treatments. A total of 165 FFPE tumor samples from patients diagnosed with ccRCC were analyzed using DIA-proteomics. Proteomics ccRCC subtypes were defined using a Consensus Cluster Algorithm (CCA) and characterized by a functional approach using probabilistic graphical models and survival analyses. Two proteomics subtypes of ccRCC (CCA1 and CCA2) were identified by CCA using the high confidence proteins only. Characterization of molecular differences between CCA1 and CCA2 was performed in two steps. First, we defined 514 proteins showing differential expression between the two subtypes using a significance analysis of microarrays analysis. Proteins overexpressed in CCA1 were mainly related to translation and ribosome, while proteins overexpressed in CCA2 were mainly related to focal adhesion and membrane. Second, a functional analysis using probabilistic graphical models was performed. The CCA1 subtype is characterized by an increased expression of proteins related to glycolysis, mitochondria, translation, adhesion proteins related to cytoskeleton and actin, nucleosome, and spliceosome, while CCA2 subtype showed higher expression o proteins involved in focal adhesion, extracellular matrix and collagen organization.

INSTRUMENT(S): Orbitrap Fusion

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Kidney

DISEASE(S): Renal Clear Cell Carcinoma

SUBMITTER: Lucia Trilla-Fuertes

LAB HEAD: Angelo Gámez-Pozo

PROVIDER: PXD039258 | Pride | 2025-05-09

REPOSITORIES: Pride

ACCESS DATA

Dataset's files

Source:

			Action	DRS
	20200811_002_S220059_54.raw	Raw
	20200811_003_S220030_25.raw	Raw
	20200811_004_S220061_56.raw	Raw
	20200811_005_S220035_30.raw	Raw
	20200811_007_S220055_50.raw	Raw

Items per page:

1 - 5 of 181

Publications

A prognostic microRNA-based signature for localized clear cell renal cell carcinoma: the Bio-miR study.

Pinto-Marín Álvaro Á Trilla-Fuertes Lucía L Miranda Poma Jesús J Vasudev Naveen S NS García-Fernández Eugenia E López-Vacas Rocío R Miranda Natalia N Wilson Michelle M López-Camacho Elena E Pertejo Ana A Dittmann Antje A Kunz Laura L Brown Joanne J Pedroche-Just Yaiza Y Zapater-Moros Andrea A de Velasco Guillermo G Castellano Daniel D González-Peramato Pilar P Espinosa Enrique E Banks Rosamonde E RE Fresno Vara Juan Ángel JÁ Gámez-Pozo Angelo A

British journal of cancer 20250507

<h4>Background</h4>Two thirds of renal cell carcinoma (RCC) patients have localized disease at diagnosis. A significant proportion of these patients will relapse. There is a need for prognostic biomarkers to improve risk-stratification and specific treatments for patients that relapse. The objective of this study is to determine the clinical utility of microRNA signatures as prognostic biomarkers in localized clear cell RCC (ccRCC) and propose new therapeutic targets in patients with a high-risk ...[more]

PMID: 40335662

Similar Datasets

Project description:The Colorectal Cancer Subtyping Consortium established four Consensus Molecular Subtypes (CMS) in colorectal cancer: CMS1 (microsatellite-instability [MSI], Immune), CMS2 (Canonical, epithelial), CMS3 (Metabolic), and CMS4 (Mesenchymal). However, in the clinical practice only patients with MSI tumors have experienced a change in the management of their disease. Proteomics has experimented significant technical advances with the implementation of data-independent acquisition (DIA) as the gold-standard for the analysis of large cohort of patients, providing a dynamic framework of the disease and direct information about the effectors of the biological processes. The aim of this study is the characterization of the proteome of colon cancer CMS by DIA–based proteomics and expand the utility of CMS in the clinical practice. CMS were assigned and differences in the protein profiles between CMS were defined and evaluated using a Systems Biology approach. One hundred fifty-eight paraffin samples from colon cancer patients with stage II-III disease treated with adjuvant chemotherapy were analyzed. After applying quality criteria, 1,940 identified and quantified proteins were used for the analyses. CMS1 had an overexpression of proteins related to immune system, specifically neutrophils, phagocytosis and antimicrobial response, and a glycolytic profile. CMS3 had an overexpression of proteins related to metabolic pathways, while CMS2 showed an intermediate protein profile between CMS1-3, but with a characteristic profile regarding translation, adhesion, and mitochondria and metabolism biological processes. Two proteomics subtypes within CMS2 with different protein characteristics and prognosis were identified. CMS4 was the most different group with an overexpression of proteins related to angiogenesis, extracellular matrix, focal adhesion, and complement activation. In conclusion, DIA LC-MS/MS proteomics characterization of CRC CMS established new features for each CMS, such as a higher mitochondrial activity in CMS2 or an overexpression of proteins related to phagocytosis in CMS1, but also confirmed previous findings established using transcriptomics such as an overexpression of proteins related to angiogenesis in CMS4. In this CMS4 subtype, several adhesion-related proteins suggested a high metastatic profile and a possible chemoresistance that may explain the worse prognosis of this subtype. CMS1 was characterized as immune and glycolitic-active subtype, being the combination of immunotherapy and glycolytic inhibitors a possible therapeutic strategy. Additionally, two different CMS2 proteomics-based subtypes with different prognosis and possible therapeutic targets were identified. These proccesses could be used as therapeutic targets in the future.