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Diagnostic and Prognostic Biomarkers in Renal Clear Cell Carcinoma
Renal clear cell carcinoma (ccRCC) comprises over 75% of all renal tumors and arises in the epithelial cells of the proximal convoluted tubule. Molecularly ccRCC is characterized by copy number alterations (CNAs) such as the loss of chromosome 3p and VHL inactivation. Additional driver mutations (SE...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9687861/ https://www.ncbi.nlm.nih.gov/pubmed/36428521 http://dx.doi.org/10.3390/biomedicines10112953 |
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author | Weaver, Chaston Bin Satter, Khaled Richardson, Katherine P. Tran, Lynn K. H. Tran, Paul M. H. Purohit, Sharad |
author_facet | Weaver, Chaston Bin Satter, Khaled Richardson, Katherine P. Tran, Lynn K. H. Tran, Paul M. H. Purohit, Sharad |
author_sort | Weaver, Chaston |
collection | PubMed |
description | Renal clear cell carcinoma (ccRCC) comprises over 75% of all renal tumors and arises in the epithelial cells of the proximal convoluted tubule. Molecularly ccRCC is characterized by copy number alterations (CNAs) such as the loss of chromosome 3p and VHL inactivation. Additional driver mutations (SETD2, PBRM1, BAP1, and others) promote genomic instability and tumor cell metastasis through the dysregulation of various metabolic and immune-response pathways. Many researchers identified mutation, gene expression, and proteomic signatures for early diagnosis and prognostics for ccRCC. Despite a tremendous influx of data regarding DNA alterations, gene expression, and protein expression, the incorporation of these analyses for diagnosis and prognosis of RCC into the clinical application has not been implemented yet. In this review, we focused on the molecular changes associated with ccRCC development, along with gene expression and protein signatures, to emphasize the utilization of these molecular profiles in clinical practice. These findings, in the context of machine learning and precision medicine, may help to overcome some of the barriers encountered for implementing molecular profiles of tumors into the diagnosis and treatment of ccRCC. |
format | Online Article Text |
id | pubmed-9687861 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-96878612022-11-25 Diagnostic and Prognostic Biomarkers in Renal Clear Cell Carcinoma Weaver, Chaston Bin Satter, Khaled Richardson, Katherine P. Tran, Lynn K. H. Tran, Paul M. H. Purohit, Sharad Biomedicines Review Renal clear cell carcinoma (ccRCC) comprises over 75% of all renal tumors and arises in the epithelial cells of the proximal convoluted tubule. Molecularly ccRCC is characterized by copy number alterations (CNAs) such as the loss of chromosome 3p and VHL inactivation. Additional driver mutations (SETD2, PBRM1, BAP1, and others) promote genomic instability and tumor cell metastasis through the dysregulation of various metabolic and immune-response pathways. Many researchers identified mutation, gene expression, and proteomic signatures for early diagnosis and prognostics for ccRCC. Despite a tremendous influx of data regarding DNA alterations, gene expression, and protein expression, the incorporation of these analyses for diagnosis and prognosis of RCC into the clinical application has not been implemented yet. In this review, we focused on the molecular changes associated with ccRCC development, along with gene expression and protein signatures, to emphasize the utilization of these molecular profiles in clinical practice. These findings, in the context of machine learning and precision medicine, may help to overcome some of the barriers encountered for implementing molecular profiles of tumors into the diagnosis and treatment of ccRCC. MDPI 2022-11-17 /pmc/articles/PMC9687861/ /pubmed/36428521 http://dx.doi.org/10.3390/biomedicines10112953 Text en © 2022 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 | Review Weaver, Chaston Bin Satter, Khaled Richardson, Katherine P. Tran, Lynn K. H. Tran, Paul M. H. Purohit, Sharad Diagnostic and Prognostic Biomarkers in Renal Clear Cell Carcinoma |
title | Diagnostic and Prognostic Biomarkers in Renal Clear Cell Carcinoma |
title_full | Diagnostic and Prognostic Biomarkers in Renal Clear Cell Carcinoma |
title_fullStr | Diagnostic and Prognostic Biomarkers in Renal Clear Cell Carcinoma |
title_full_unstemmed | Diagnostic and Prognostic Biomarkers in Renal Clear Cell Carcinoma |
title_short | Diagnostic and Prognostic Biomarkers in Renal Clear Cell Carcinoma |
title_sort | diagnostic and prognostic biomarkers in renal clear cell carcinoma |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9687861/ https://www.ncbi.nlm.nih.gov/pubmed/36428521 http://dx.doi.org/10.3390/biomedicines10112953 |
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