Retrospective Study
Copyright ©The Author(s) 2022. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastroenterol. Apr 14, 2022; 28(14): 1479-1493
Published online Apr 14, 2022. doi: 10.3748/wjg.v28.i14.1479
Radiomics signature: A potential biomarker for β-arrestin1 phosphorylation prediction in hepatocellular carcinoma
Feng Che, Qing Xu, Qian Li, Zi-Xing Huang, Cai-Wei Yang, Li Ye Wang, Yi Wei, Yu-Jun Shi, Bin Song
Feng Che, Qian Li, Zi-Xing Huang, Cai-Wei Yang, Yi Wei, Bin Song, Department of Radiology, West China Hospital, Sichuan University, Chengdu 610041, Sichuan Province, China
Qing Xu, Yu-Jun Shi, Institute of Clinical Pathology, West China Hospital, Sichuan University, Chengdu 610041, Sichuan Province, China
Li Ye Wang, Department of Research and Development, Shanghai United Imaging Intelligence Co., Ltd, Shanghai 200232, China
Author contributions: Che F, Xu Q, Shi YJ and Song B designed the research; Che F, Li Q and Xu Q conducted literature search and analysis; Yang CW, Huang ZX, Wang LY and Wei Y provided material support; Song B provided funding for the article; Che F and Xu Q wrote the paper; Che F and Xu Q contributed equally to this work.
Supported by the Science and Technology Support Program of Sichuan Province, No. 2021YFS0144 and No. 2021YFS0021; China Postdoctoral Science Foundation, No. 2021M692289; and National Natural Science Foundation of China, No. 81971571.
Institutional review board statement: This study was approved by the Ethics Committee of West China Hospital.
Informed consent statement: Patients were not required to give informed consent to the study because this retrospective study used anonymous clinical data that were obtained after each patient agreed to treatment by written consent.
Conflict-of-interest statement: We have no financial relationships to disclose.
Data sharing statement: No additional data are available.
Open-Access: 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: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Bin Song, MD, Chief Doctor, Doctor, Professor, Department of Radiology, West China Hospital, Sichuan University, No 37, Guoxue Alley, Wuhou District, Chengdu 610041, Sichuan Province, China. songlab_radiology@163.com
Received: November 9, 2021
Peer-review started: November 9, 2021
First decision: January 9, 2022
Revised: January 22, 2022
Accepted: March 6, 2022
Article in press: March 6, 2022
Published online: April 14, 2022
ARTICLE HIGHLIGHTS
Research background

Sorafenib is regarded as a first-line systematic treatment option for patients with advanced hepatocellular carcinoma (HCC), but its efficacy is largely influenced by raising resistance. The phosphorylation status of β-arrestin1 influences its function as a signal strongly related to sorafenib resistance.

Research motivation

Identifying patients who are more likely to benefit from sorafenib treatment and discovering related biomarkers associated with sorafenib treatment response can guide personal management.

Research objectives

The purpose of this study was to develop and validate radiomics-based models for predicting β-arrestin1 phosphorylation in HCC with contrast-enhanced computed tomography (CT).

Research methods

We included ninety-nine HCC patients (training cohort: n = 69; validation cohort: n = 30) who received systemic sorafenib treatment after surgery. Radiomics features were generated and selected to build a radiomics score and then combined with clinical and imaging features to establish clinico-radiological (CR) and clinico-radiological-radiomics (CRR) models. The performance and clinical usefulness of the models were measured by receiver operating characteristic and decision curves. Their association with prognosis was also evaluated using the Kaplan-Meier method.

Research results

Our study found that the ALT level, tumor size and tumor margin were significant independent factors for predicting β-arrestin1 phosphorylation. The CRR model showed better discriminative performance than the radiomic score or the CR model. The β-arrestin1 phosphorylation status predicted by the CRR model was shown to be significantly associated with overall survival.

Research conclusions

The radiomics signature is a reliable tool for evaluating β-arrestin1 phosphorylation, and may help to better identify patients who would benefit from sorafenib treatment.

Research perspectives

The results of this study suggests that CT-based radiomics may provide promising and noninvasive biomarkers for the evaluation of β-arrestin1 phosphorylation and may help to identify the subset of HCC patients who are more sensitive to sorafenib treatment, thus potentially guiding personalized treatment strategies.