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Radiogenomics in Clear Cell Renal Cell Carcinoma: Correlations Between Advanced CT Imaging (Texture Analysis) and MicroRNAs Expression

PURPOSE: A relevant challenge for the improvement of clear cell renal cell carcinoma management could derive from the identification of novel molecular biomarkers that could greatly improve the diagnosis, prognosis, and treatment choice of these neoplasms. In this study, we investigate whether quant...

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Autores principales: Marigliano, Chiara, Badia, Stefano, Bellini, Davide, Rengo, Marco, Caruso, Damiano, Tito, Claudia, Miglietta, Selenia, Palleschi, Giovanni, Pastore, Antonio Luigi, Carbone, Antonio, Fazi, Francesco, Petrozza, Vincenzo, Laghi, Andrea
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6767738/
https://www.ncbi.nlm.nih.gov/pubmed/31564221
http://dx.doi.org/10.1177/1533033819878458
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author Marigliano, Chiara
Badia, Stefano
Bellini, Davide
Rengo, Marco
Caruso, Damiano
Tito, Claudia
Miglietta, Selenia
Palleschi, Giovanni
Pastore, Antonio Luigi
Carbone, Antonio
Fazi, Francesco
Petrozza, Vincenzo
Laghi, Andrea
author_facet Marigliano, Chiara
Badia, Stefano
Bellini, Davide
Rengo, Marco
Caruso, Damiano
Tito, Claudia
Miglietta, Selenia
Palleschi, Giovanni
Pastore, Antonio Luigi
Carbone, Antonio
Fazi, Francesco
Petrozza, Vincenzo
Laghi, Andrea
author_sort Marigliano, Chiara
collection PubMed
description PURPOSE: A relevant challenge for the improvement of clear cell renal cell carcinoma management could derive from the identification of novel molecular biomarkers that could greatly improve the diagnosis, prognosis, and treatment choice of these neoplasms. In this study, we investigate whether quantitative parameters obtained from computed tomography texture analysis may correlate with the expression of selected oncogenic microRNAs. METHODS: In a retrospective single-center study, multiphasic computed tomography examination (with arterial, portal, and urographic phases) was performed on 20 patients with clear cell renal cell carcinoma and computed tomography texture analysis parameters such as entropy, kurtosis, skewness, mean, and standard deviation of pixel distribution were measured using multiple filter settings. These quantitative data were correlated with the expression of selected microRNAs (miR-21-5p, miR-210-3p, miR-185-5p, miR-221-3p, miR-145-5p). Both the evaluations (microRNAs and computed tomography texture analysis) were performed on matched tumor and normal corticomedullar tissues of the same patients cohort. RESULTS: In this pilot study, we evidenced that computed tomography texture analysis has robust parameters (eg, entropy, mean, standard deviation) to distinguish normal from pathological tissues. Moreover, a higher coefficient of determination between entropy and miR-21-5p expression was evidenced in tumor versus normal tissue. Interestingly, entropy and miR-21-5p show promising correlation in clear cell renal cell carcinoma opening to a radiogenomic strategy to improve clear cell renal cell carcinoma management. CONCLUSION: In this pilot study, a promising correlation between microRNAs and computed tomography texture analysis has been found in clear cell renal cell carcinoma. A clear cell renal cell carcinoma can benefit from noninvasive evaluation of texture parameters in adjunction to biopsy results. In particular, a promising correlation between entropy and miR-21-5p was found.
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spelling pubmed-67677382019-10-18 Radiogenomics in Clear Cell Renal Cell Carcinoma: Correlations Between Advanced CT Imaging (Texture Analysis) and MicroRNAs Expression Marigliano, Chiara Badia, Stefano Bellini, Davide Rengo, Marco Caruso, Damiano Tito, Claudia Miglietta, Selenia Palleschi, Giovanni Pastore, Antonio Luigi Carbone, Antonio Fazi, Francesco Petrozza, Vincenzo Laghi, Andrea Technol Cancer Res Treat Original Article PURPOSE: A relevant challenge for the improvement of clear cell renal cell carcinoma management could derive from the identification of novel molecular biomarkers that could greatly improve the diagnosis, prognosis, and treatment choice of these neoplasms. In this study, we investigate whether quantitative parameters obtained from computed tomography texture analysis may correlate with the expression of selected oncogenic microRNAs. METHODS: In a retrospective single-center study, multiphasic computed tomography examination (with arterial, portal, and urographic phases) was performed on 20 patients with clear cell renal cell carcinoma and computed tomography texture analysis parameters such as entropy, kurtosis, skewness, mean, and standard deviation of pixel distribution were measured using multiple filter settings. These quantitative data were correlated with the expression of selected microRNAs (miR-21-5p, miR-210-3p, miR-185-5p, miR-221-3p, miR-145-5p). Both the evaluations (microRNAs and computed tomography texture analysis) were performed on matched tumor and normal corticomedullar tissues of the same patients cohort. RESULTS: In this pilot study, we evidenced that computed tomography texture analysis has robust parameters (eg, entropy, mean, standard deviation) to distinguish normal from pathological tissues. Moreover, a higher coefficient of determination between entropy and miR-21-5p expression was evidenced in tumor versus normal tissue. Interestingly, entropy and miR-21-5p show promising correlation in clear cell renal cell carcinoma opening to a radiogenomic strategy to improve clear cell renal cell carcinoma management. CONCLUSION: In this pilot study, a promising correlation between microRNAs and computed tomography texture analysis has been found in clear cell renal cell carcinoma. A clear cell renal cell carcinoma can benefit from noninvasive evaluation of texture parameters in adjunction to biopsy results. In particular, a promising correlation between entropy and miR-21-5p was found. SAGE Publications 2019-09-29 /pmc/articles/PMC6767738/ /pubmed/31564221 http://dx.doi.org/10.1177/1533033819878458 Text en © The Author(s) 2019 http://creativecommons.org/licenses/by-nc/4.0/ This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (http://www.creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Original Article
Marigliano, Chiara
Badia, Stefano
Bellini, Davide
Rengo, Marco
Caruso, Damiano
Tito, Claudia
Miglietta, Selenia
Palleschi, Giovanni
Pastore, Antonio Luigi
Carbone, Antonio
Fazi, Francesco
Petrozza, Vincenzo
Laghi, Andrea
Radiogenomics in Clear Cell Renal Cell Carcinoma: Correlations Between Advanced CT Imaging (Texture Analysis) and MicroRNAs Expression
title Radiogenomics in Clear Cell Renal Cell Carcinoma: Correlations Between Advanced CT Imaging (Texture Analysis) and MicroRNAs Expression
title_full Radiogenomics in Clear Cell Renal Cell Carcinoma: Correlations Between Advanced CT Imaging (Texture Analysis) and MicroRNAs Expression
title_fullStr Radiogenomics in Clear Cell Renal Cell Carcinoma: Correlations Between Advanced CT Imaging (Texture Analysis) and MicroRNAs Expression
title_full_unstemmed Radiogenomics in Clear Cell Renal Cell Carcinoma: Correlations Between Advanced CT Imaging (Texture Analysis) and MicroRNAs Expression
title_short Radiogenomics in Clear Cell Renal Cell Carcinoma: Correlations Between Advanced CT Imaging (Texture Analysis) and MicroRNAs Expression
title_sort radiogenomics in clear cell renal cell carcinoma: correlations between advanced ct imaging (texture analysis) and micrornas expression
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6767738/
https://www.ncbi.nlm.nih.gov/pubmed/31564221
http://dx.doi.org/10.1177/1533033819878458
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