AUTHOR=Liu Han , Wang Yiyun , Liu Yingqiao , Lin Dingyi , Zhang Cangui , Zhao Yuyun , Chen Li , Li Yi , Yuan Jianyu , Chen Zhao , Yu Jiang , Kong Wentao , Chen Tao 

TITLE=Contrast-Enhanced Computed Tomography–Based Radiogenomics Analysis for Predicting Prognosis in Gastric Cancer

JOURNAL=Frontiers in Oncology

VOLUME=Volume 12 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2022.882786

DOI=10.3389/fonc.2022.882786

ISSN=2234-943X

ABSTRACT=Abstract
Objective: To identify prognostic imaging biomarkers and create a radiogenomics nomogram to predict overall survival (OS) in gastric cancer (GC). 
Material: 407 GC patients’ RNA sequencing data and 46 patients’ contrast-enhanced computed tomography (CECT) imaging data obtained from The Cancer Genome Atlas (TCGA) and The Cancer Imaging Archive (TCIA) were utilized to identify radiogenomics biomarkers. 392 patients with CECT images from Nanfang hospital database were obtained to create and validate a radiogenomics nomogram based on the biomarkers.
Methods: The prognostic imaging features which correlated with the prognostic gene modules (selected by weighted gene coexpression network analysis) were identified as imaging biomarkers. A nomogram which integrated the radiomics score and clinicopathological factors was created and validated in Nanfang hospital database. Nomogram discrimination, calibration, and clinical usefulness were evaluated. 
Results: Three prognostic imaging biomarkers were identified and had a strong correlation with four prognostic gene modules (P<0.05, FDR<0.05). The radiogenomics nomogram (AUC=0.838) resulted in better performance of the survival prediction than that of the TNM staging system (AUC=0.765, P=0.011, Delong et al.). In addition, the radiogenomics nomogram exhibited good discrimination, calibration, and clinical usefulness in both the training and validation cohorts.
Conclusions: The novel prognostic radiogenomics nomogram that was constructed achieved excellent correlation with prognosis in both the training and validation cohort of Nanfang hospital patients with GC. It is anticipated that this work may assist in clinical preferential treatment decisions and promote the process of precision theranostics in the future.