Published online Sep 28, 2021. doi: 10.3748/wjg.v27.i36.6110
Peer-review started: March 2, 2021
First decision: June 3, 2021
Revised: June 16, 2021
Accepted: July 30, 2021
Article in press: July 30, 2021
Published online: September 28, 2021
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.
To explore the combination of CT radiomic features and molecular targets associated with clinical outcomes for characterization of ESCA patients.
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.
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).
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.
Core Tip: This is a retrospective study aiming at investigating the relationship between the expression levels of transcriptomic features (eight N6-methyladenosine RNA methylation regulators and five up-regulated microRNAs) and radiomic features extracted from computed tomography images that were significantly associated to clinical outcomes (stage, alcohol history, body mass index) in patients with esophageal cancer . Radiogenomic analysis revealed significant correlations between the expression of the N6-methyladenosine RNA regulators, as well as five up-regulated microRNAs, and several computed tomography radiomic features associated with three investigated clinical outcomes of esophageal cancer patients.