AUTHOR=Qin Haoren , Zhang Heng , Li Haipeng , Xu Qiong , Sun Wanjun , Zhang Shiwu , Zhang Xipeng , Zhu Siwei , Wang Hui 

TITLE=Prognostic risk analysis related to radioresistance genes in colorectal cancer

JOURNAL=Frontiers in Oncology

VOLUME=12

YEAR=2023

URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2022.1100481

DOI=10.3389/fonc.2022.1100481

ISSN=2234-943X

ABSTRACT=<sec><title>Background</title><p>Radiotherapy (RT) is one of the most important treatments for patients with colorectal cancer (CRC). Radioresistance is the crucial cause of poor therapeutic outcomes in colorectal cancer. However, the underlying mechanism of radioresistance in colorectal cancer is still poorly defined. Herein we established a radioresistant colorectal cancer cell line and performed transcriptomics analyses to search for the underlying genes that contribute to radioresistance and investigate its association with the prognosis of CRC patients.</p></sec><sec><title>Methods</title><p>The radioresistant cell line was developed from the parental HCT116 cell by a stepwise increased dose of irradiation. Differential gene analysis was performed using cellular transcriptome data to identify genes associated with radioresistance, from which extracellular matrix (ECM) and cell adhesion-related genes were screened. Survival data from a CRC cohort in the TCGA database were used for further model gene screening and validation. The correlation between the risk score model and tumor microenvironment, clinical phenotype, drug treatment sensitivity, and tumor mutation status were also investigated.</p></sec><sec><title>Results</title><p>A total of 493 different expression genes were identified from the radioresistant and wild-type cell line, of which 94 genes were associated with ECM and cell adhesion-related genes. The five model genes <italic>TNFRSF13C</italic>, <italic>CD36</italic>, <italic>ANGPTL4</italic>, <italic>LAMB3</italic>, and <italic>SERPINA1</italic> were identified for CRC radioresistance <italic>via</italic> screening using the best model. A ROC curve indicated that the AUC of the resulting prognostic model (based on the 5-gene risk score and other clinical parameters, including age, sex, and tumor stages) was 0.79, 0.77, and 0.78 at 1, 2, and 3 years, respectively. The calibration curve showed high agreement between the risk score prediction and actual survival probability. The immune microenvironment, drug treatment sensitivity, and tumor mutation status significantly differed between the high- and low-risk groups.</p></sec><sec><title>Conclusions</title><p>The risk score model built with five radioresistance genes in this study, including <italic>TNFRSF13C</italic>, <italic>CD36</italic>, <italic>ANGPTL4</italic>, <italic>LAMB3</italic>, and <italic>SERPINA1</italic>, showed favorable performance in prognosis prediction after radiotherapy for CRC.</p></sec>