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Proteomics Characterization of Clear Cell Renal Cell Carcinoma
Purpose: To explore the tumor proteome of patients diagnosed with localized clear cell renal cancer (ccRCC) and treated with surgery. Material and methods: A total of 165 FFPE tumor samples from patients diagnosed with ccRCC were analyzed using DIA-proteomics. Proteomics ccRCC subtypes were defined...
Autores principales: | , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9821535/ https://www.ncbi.nlm.nih.gov/pubmed/36615183 http://dx.doi.org/10.3390/jcm12010384 |
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author | Miranda-Poma, Jesús Trilla-Fuertes, Lucía López-Vacas, Rocío López-Camacho, Elena García-Fernández, Eugenia Pertejo, Ana Lumbreras-Herrera, María I. Zapater-Moros, Andrea Díaz-Almirón, Mariana Dittmann, Antje Fresno Vara, Juan Ángel Espinosa, Enrique González-Peramato, Pilar Pinto-Marín, Álvaro Gámez-Pozo, Angelo |
author_facet | Miranda-Poma, Jesús Trilla-Fuertes, Lucía López-Vacas, Rocío López-Camacho, Elena García-Fernández, Eugenia Pertejo, Ana Lumbreras-Herrera, María I. Zapater-Moros, Andrea Díaz-Almirón, Mariana Dittmann, Antje Fresno Vara, Juan Ángel Espinosa, Enrique González-Peramato, Pilar Pinto-Marín, Álvaro Gámez-Pozo, Angelo |
author_sort | Miranda-Poma, Jesús |
collection | PubMed |
description | Purpose: To explore the tumor proteome of patients diagnosed with localized clear cell renal cancer (ccRCC) and treated with surgery. Material and methods: 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. Results: We identified and quantified 3091 proteins, including 2026 high-confidence proteins. Two proteomics subtypes of ccRCC (CC1 and CC2) were identified by CC using the high-confidence proteins only. Characterization of molecular differences between CC1 and CC2 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 CC1 were mainly related to translation and ribosome, while proteins overexpressed in CC2 were mainly related to focal adhesion and membrane. Second, a functional analysis using probabilistic graphical models was performed. CC1 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 CC2 subtype showed higher expression of proteins involved in focal adhesion, extracellular matrix, and collagen organization. Conclusions: ccRCC tumors can be classified in two different proteomics subtypes. CC1 and CC2 present specific proteomics profiles, reflecting alterations of different molecular pathways in each subtype. The knowledge generated in this type of studies could help in the development of new drugs targeting subtype-specific deregulated pathways. |
format | Online Article Text |
id | pubmed-9821535 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-98215352023-01-07 Proteomics Characterization of Clear Cell Renal Cell Carcinoma Miranda-Poma, Jesús Trilla-Fuertes, Lucía López-Vacas, Rocío López-Camacho, Elena García-Fernández, Eugenia Pertejo, Ana Lumbreras-Herrera, María I. Zapater-Moros, Andrea Díaz-Almirón, Mariana Dittmann, Antje Fresno Vara, Juan Ángel Espinosa, Enrique González-Peramato, Pilar Pinto-Marín, Álvaro Gámez-Pozo, Angelo J Clin Med Article Purpose: To explore the tumor proteome of patients diagnosed with localized clear cell renal cancer (ccRCC) and treated with surgery. Material and methods: 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. Results: We identified and quantified 3091 proteins, including 2026 high-confidence proteins. Two proteomics subtypes of ccRCC (CC1 and CC2) were identified by CC using the high-confidence proteins only. Characterization of molecular differences between CC1 and CC2 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 CC1 were mainly related to translation and ribosome, while proteins overexpressed in CC2 were mainly related to focal adhesion and membrane. Second, a functional analysis using probabilistic graphical models was performed. CC1 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 CC2 subtype showed higher expression of proteins involved in focal adhesion, extracellular matrix, and collagen organization. Conclusions: ccRCC tumors can be classified in two different proteomics subtypes. CC1 and CC2 present specific proteomics profiles, reflecting alterations of different molecular pathways in each subtype. The knowledge generated in this type of studies could help in the development of new drugs targeting subtype-specific deregulated pathways. MDPI 2023-01-03 /pmc/articles/PMC9821535/ /pubmed/36615183 http://dx.doi.org/10.3390/jcm12010384 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Miranda-Poma, Jesús Trilla-Fuertes, Lucía López-Vacas, Rocío López-Camacho, Elena García-Fernández, Eugenia Pertejo, Ana Lumbreras-Herrera, María I. Zapater-Moros, Andrea Díaz-Almirón, Mariana Dittmann, Antje Fresno Vara, Juan Ángel Espinosa, Enrique González-Peramato, Pilar Pinto-Marín, Álvaro Gámez-Pozo, Angelo Proteomics Characterization of Clear Cell Renal Cell Carcinoma |
title | Proteomics Characterization of Clear Cell Renal Cell Carcinoma |
title_full | Proteomics Characterization of Clear Cell Renal Cell Carcinoma |
title_fullStr | Proteomics Characterization of Clear Cell Renal Cell Carcinoma |
title_full_unstemmed | Proteomics Characterization of Clear Cell Renal Cell Carcinoma |
title_short | Proteomics Characterization of Clear Cell Renal Cell Carcinoma |
title_sort | proteomics characterization of clear cell renal cell carcinoma |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9821535/ https://www.ncbi.nlm.nih.gov/pubmed/36615183 http://dx.doi.org/10.3390/jcm12010384 |
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