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Impact of radiogenomics in esophageal cancer on clinical outcomes: A pilot study

BACKGROUND: Esophageal cancer (ESCA) is the sixth most common malignancy in the world, and its incidence is rapidly increasing. Recently, several microRNAs (miRNAs) and messenger RNA (mRNA) targets were evaluated as potential biomarkers and regulators of epigenetic mechanisms involved in early diagn...

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Autores principales: Brancato, Valentina, Garbino, Nunzia, Mannelli, Lorenzo, Aiello, Marco, Salvatore, Marco, Franzese, Monica, Cavaliere, Carlo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Baishideng Publishing Group Inc 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8476334/
https://www.ncbi.nlm.nih.gov/pubmed/34629823
http://dx.doi.org/10.3748/wjg.v27.i36.6110
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author Brancato, Valentina
Garbino, Nunzia
Mannelli, Lorenzo
Aiello, Marco
Salvatore, Marco
Franzese, Monica
Cavaliere, Carlo
author_facet Brancato, Valentina
Garbino, Nunzia
Mannelli, Lorenzo
Aiello, Marco
Salvatore, Marco
Franzese, Monica
Cavaliere, Carlo
author_sort Brancato, Valentina
collection PubMed
description BACKGROUND: Esophageal cancer (ESCA) is the sixth most common malignancy in the world, and its incidence is rapidly increasing. Recently, several microRNAs (miRNAs) and messenger RNA (mRNA) targets were evaluated as potential biomarkers and regulators of epigenetic mechanisms involved in early diagnosis. In addition, computed tomography (CT) radiomic studies on ESCA improved the early stage identification and the prediction of response to treatment. Radiogenomics provides clinically useful prognostic predictions by linking molecular characteristics such as gene mutations and gene expression patterns of malignant tumors with medical images and could provide more opportunities in the management of patients with ESCA. AIM: To explore the combination of CT radiomic features and molecular targets associated with clinical outcomes for characterization of ESCA patients. METHODS: Of 15 patients with diagnosed ESCA were included in this study and their CT imaging and transcriptomic data were extracted from The Cancer Imaging Archive and gene expression data from The Cancer Genome Atlas, respectively. Cancer stage, history of significant alcohol consumption and body mass index (BMI) were considered as clinical outcomes. Radiomic analysis was performed on CT images acquired after injection of contrast medium. In total, 1302 radiomics features were extracted from three-dimensional regions of interest by using PyRadiomics. Feature selection was performed using a correlation filter based on Spearman’s correlation (ρ) and Wilcoxon-rank sum test respect to clinical outcomes. Radiogenomic analysis involved ρ analysis between radiomic features associated with clinical outcomes and transcriptomic signatures consisting of eight N6-methyladenosine RNA methylation regulators and five up-regulated miRNA. The significance level was set at P < 0.05. RESULTS: Of 25, five and 29 radiomic features survived after feature selection, considering stage, alcohol history and BMI as clinical outcomes, respectively. Radiogenomic analysis with stage as clinical outcome revealed that six of the eight mRNA regulators and two of the five up-regulated miRNA were significantly correlated with ten and three of the 25 selected radiomic features, respectively (-0.61 < ρ < -0.60 and 0.53 < ρ < 0.69, P < 0.05). Assuming alcohol history as clinical outcome, no correlation was found between the five selected radiomic features and mRNA regulators, while a significant correlation was found between one radiomic feature and three up-regulated miRNAs (ρ = -0.56, ρ = -0.64 and ρ = 0.61, P < 0.05). Radiogenomic analysis with BMI as clinical outcome revealed that four mRNA regulators and one up-regulated miRNA were significantly correlated with 10 and two radiomic features, respectively (-0.67 < ρ < -0.54 and 0.53 < ρ < 0.71, P < 0.05). CONCLUSION: Our study revealed interesting relationships between the expression of eight N6-methyladenosine RNA regulators, as well as five up-regulated miRNAs, and CT radiomic features associated with clinical outcomes of ESCA patients.
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spelling pubmed-84763342021-10-08 Impact of radiogenomics in esophageal cancer on clinical outcomes: A pilot study Brancato, Valentina Garbino, Nunzia Mannelli, Lorenzo Aiello, Marco Salvatore, Marco Franzese, Monica Cavaliere, Carlo World J Gastroenterol Retrospective Study BACKGROUND: Esophageal cancer (ESCA) is the sixth most common malignancy in the world, and its incidence is rapidly increasing. Recently, several microRNAs (miRNAs) and messenger RNA (mRNA) targets were evaluated as potential biomarkers and regulators of epigenetic mechanisms involved in early diagnosis. In addition, computed tomography (CT) radiomic studies on ESCA improved the early stage identification and the prediction of response to treatment. Radiogenomics provides clinically useful prognostic predictions by linking molecular characteristics such as gene mutations and gene expression patterns of malignant tumors with medical images and could provide more opportunities in the management of patients with ESCA. AIM: To explore the combination of CT radiomic features and molecular targets associated with clinical outcomes for characterization of ESCA patients. METHODS: Of 15 patients with diagnosed ESCA were included in this study and their CT imaging and transcriptomic data were extracted from The Cancer Imaging Archive and gene expression data from The Cancer Genome Atlas, respectively. Cancer stage, history of significant alcohol consumption and body mass index (BMI) were considered as clinical outcomes. Radiomic analysis was performed on CT images acquired after injection of contrast medium. In total, 1302 radiomics features were extracted from three-dimensional regions of interest by using PyRadiomics. Feature selection was performed using a correlation filter based on Spearman’s correlation (ρ) and Wilcoxon-rank sum test respect to clinical outcomes. Radiogenomic analysis involved ρ analysis between radiomic features associated with clinical outcomes and transcriptomic signatures consisting of eight N6-methyladenosine RNA methylation regulators and five up-regulated miRNA. The significance level was set at P < 0.05. RESULTS: Of 25, five and 29 radiomic features survived after feature selection, considering stage, alcohol history and BMI as clinical outcomes, respectively. Radiogenomic analysis with stage as clinical outcome revealed that six of the eight mRNA regulators and two of the five up-regulated miRNA were significantly correlated with ten and three of the 25 selected radiomic features, respectively (-0.61 < ρ < -0.60 and 0.53 < ρ < 0.69, P < 0.05). Assuming alcohol history as clinical outcome, no correlation was found between the five selected radiomic features and mRNA regulators, while a significant correlation was found between one radiomic feature and three up-regulated miRNAs (ρ = -0.56, ρ = -0.64 and ρ = 0.61, P < 0.05). Radiogenomic analysis with BMI as clinical outcome revealed that four mRNA regulators and one up-regulated miRNA were significantly correlated with 10 and two radiomic features, respectively (-0.67 < ρ < -0.54 and 0.53 < ρ < 0.71, P < 0.05). CONCLUSION: Our study revealed interesting relationships between the expression of eight N6-methyladenosine RNA regulators, as well as five up-regulated miRNAs, and CT radiomic features associated with clinical outcomes of ESCA patients. Baishideng Publishing Group Inc 2021-09-28 2021-09-28 /pmc/articles/PMC8476334/ /pubmed/34629823 http://dx.doi.org/10.3748/wjg.v27.i36.6110 Text en ©The Author(s) 2021. Published by Baishideng Publishing Group Inc. All rights reserved. https://creativecommons.org/licenses/by-nc/4.0/This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/Licenses/by-nc/4.0/
spellingShingle Retrospective Study
Brancato, Valentina
Garbino, Nunzia
Mannelli, Lorenzo
Aiello, Marco
Salvatore, Marco
Franzese, Monica
Cavaliere, Carlo
Impact of radiogenomics in esophageal cancer on clinical outcomes: A pilot study
title Impact of radiogenomics in esophageal cancer on clinical outcomes: A pilot study
title_full Impact of radiogenomics in esophageal cancer on clinical outcomes: A pilot study
title_fullStr Impact of radiogenomics in esophageal cancer on clinical outcomes: A pilot study
title_full_unstemmed Impact of radiogenomics in esophageal cancer on clinical outcomes: A pilot study
title_short Impact of radiogenomics in esophageal cancer on clinical outcomes: A pilot study
title_sort impact of radiogenomics in esophageal cancer on clinical outcomes: a pilot study
topic Retrospective Study
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8476334/
https://www.ncbi.nlm.nih.gov/pubmed/34629823
http://dx.doi.org/10.3748/wjg.v27.i36.6110
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