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Relevant Networks involving the p53 Signalling Pathway in Renal Cell Carcinoma

INTRODUCTION: Renal cell carcinoma is the most common type of kidney cancer. A better understanding of the critical pathways and interactions associated with alterations in renal function and renal tumour properties is required. Our final goal is to combine the knowledge provided by a regulatory net...

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Autores principales: Villaamil, V. Medina, Gallego, G. Aparicio, Caínzos, I. Santamarina, Ruvira, L. Valbuena, Valladares-Ayerbes, M., Aparicio, L. M. Antón
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Master Publishing Group 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3614848/
https://www.ncbi.nlm.nih.gov/pubmed/23675247
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author Villaamil, V. Medina
Gallego, G. Aparicio
Caínzos, I. Santamarina
Ruvira, L. Valbuena
Valladares-Ayerbes, M.
Aparicio, L. M. Antón
author_facet Villaamil, V. Medina
Gallego, G. Aparicio
Caínzos, I. Santamarina
Ruvira, L. Valbuena
Valladares-Ayerbes, M.
Aparicio, L. M. Antón
author_sort Villaamil, V. Medina
collection PubMed
description INTRODUCTION: Renal cell carcinoma is the most common type of kidney cancer. A better understanding of the critical pathways and interactions associated with alterations in renal function and renal tumour properties is required. Our final goal is to combine the knowledge provided by a regulatory network with experimental observations provided by the dataset. METHODS: In this study, a systems biology approach was used, integrating immunohistochemistry protein expression profiles and protein interaction information with the STRING and MeV bioinformatics tools. A group consisting of 80 patients with renal cell carcinoma was studied. The expression of selected markers was assessed using tissue microarray technology on immunohistochemically stained slides. The immunohistochemical data of the molecular factors studied were analysed using a parametric statistical test, Pearson’s correlation coefficient test. RESULTS: Bioinformatics analysis of tumour samples resulted in 2 protein networks. The first network consists of proteins involved in the angiogenesis pathway and the apoptosis suppressor, BCL2, and includes both positive and negative correlations. The second network shows a negative interaction between the p53 tumour suppressor protein and the glucose transporter type 4. CONCLUSION: The comprehensive pathway network will help us to realise the cooperative behaviours among pathways. Regulation of metabolic pathways is an important role of p53. The pathway involving the tumour suppressor gene p53 could regulate tumour angiogenesis. Further investigation of the proteins that interact with this pathway in this type of tumour may provide new strategies for cancer therapies to specifically inhibit the molecules that play crucial roles in tumour progression.
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spelling pubmed-36148482013-05-01 Relevant Networks involving the p53 Signalling Pathway in Renal Cell Carcinoma Villaamil, V. Medina Gallego, G. Aparicio Caínzos, I. Santamarina Ruvira, L. Valbuena Valladares-Ayerbes, M. Aparicio, L. M. Antón Int J Biomed Sci Article INTRODUCTION: Renal cell carcinoma is the most common type of kidney cancer. A better understanding of the critical pathways and interactions associated with alterations in renal function and renal tumour properties is required. Our final goal is to combine the knowledge provided by a regulatory network with experimental observations provided by the dataset. METHODS: In this study, a systems biology approach was used, integrating immunohistochemistry protein expression profiles and protein interaction information with the STRING and MeV bioinformatics tools. A group consisting of 80 patients with renal cell carcinoma was studied. The expression of selected markers was assessed using tissue microarray technology on immunohistochemically stained slides. The immunohistochemical data of the molecular factors studied were analysed using a parametric statistical test, Pearson’s correlation coefficient test. RESULTS: Bioinformatics analysis of tumour samples resulted in 2 protein networks. The first network consists of proteins involved in the angiogenesis pathway and the apoptosis suppressor, BCL2, and includes both positive and negative correlations. The second network shows a negative interaction between the p53 tumour suppressor protein and the glucose transporter type 4. CONCLUSION: The comprehensive pathway network will help us to realise the cooperative behaviours among pathways. Regulation of metabolic pathways is an important role of p53. The pathway involving the tumour suppressor gene p53 could regulate tumour angiogenesis. Further investigation of the proteins that interact with this pathway in this type of tumour may provide new strategies for cancer therapies to specifically inhibit the molecules that play crucial roles in tumour progression. Master Publishing Group 2011-12 /pmc/articles/PMC3614848/ /pubmed/23675247 Text en © V. Medina Villaamil et al. Licensee Master Publishing Group http://creativecommons.org/licenses/by/2.5/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.5/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Article
Villaamil, V. Medina
Gallego, G. Aparicio
Caínzos, I. Santamarina
Ruvira, L. Valbuena
Valladares-Ayerbes, M.
Aparicio, L. M. Antón
Relevant Networks involving the p53 Signalling Pathway in Renal Cell Carcinoma
title Relevant Networks involving the p53 Signalling Pathway in Renal Cell Carcinoma
title_full Relevant Networks involving the p53 Signalling Pathway in Renal Cell Carcinoma
title_fullStr Relevant Networks involving the p53 Signalling Pathway in Renal Cell Carcinoma
title_full_unstemmed Relevant Networks involving the p53 Signalling Pathway in Renal Cell Carcinoma
title_short Relevant Networks involving the p53 Signalling Pathway in Renal Cell Carcinoma
title_sort relevant networks involving the p53 signalling pathway in renal cell carcinoma
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3614848/
https://www.ncbi.nlm.nih.gov/pubmed/23675247
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