Decoding tumor heterogeneity with imaging biomarkers predicts response to TACE plus Immunotherapy and targeted therapy in HCC.
Authors
Affiliations (36)
Affiliations (36)
- Center of Interventional Radiology and Vascular Surgery, Department of Radiology, Zhongda Hospital, Medical School, Southeast University, Nanjing, China.
- Basic Medicine Research and Innovation Center of Ministry of Education, Zhongda Hospital, Southeast University, Nanjing, China.
- Foundation Model Research Center, Institute of Automation, Chinese Academy of Sciences, Beijing, China.
- Departments of Radiology, the Second Xiangya Hospital of Central South University, Changsha, China.
- Department of General Surgery, Jinling Hospital, Medical School of Nanjing University, Nanjing, China.
- Department of Interventional Radiology, Sichuan Cancer Hospital and Institute, Chengdu, China.
- Department of Interventional Radiology, The First Affiliated Hospital of Soochow University, Soochow University, Suzhou, China.
- Jiangsu Key Laboratory of Intelligent Medical Image Computing, School of Artificial Intelligence, Nanjing University of Information Science and Technology, Nanjing, China.
- Department of Radiology, Zhongda Hospital, Medical School, Southeast University, Nanjing, China.
- Department of Minimally Invasive Interventional Medicine, Yunnan Cancer Hospital, The Third Affiliated Hospital of Kunming Medical University, Kunming, China.
- Department of Interventional Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
- Department of Interventional Radiology, The Affiliated Wuxi People's Hospital of Nanjing Medical University, Wuxi People's Hospital, Wuxi Medical Center, Nanjing Medical University, Wuxi, China.
- Department of Interventional Radiology, Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, China.
- Zhejiang Key Laboratory of Multi-omics Precision Diagnosis and Treatment of Liver Diseases, Department of General Surgery, Sir Run-Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China.
- Department of Minimally Invasive Intervention, The Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou, China.
- Department of Interventional Radiology, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research & The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China.
- Department of Radiology, Key Laboratory of Imaging Diagnosis and Minimally Invasive Intervention Research, School of Medicine, Lishui Hospital of Zhejiang University, Lishui, China.
- Department of Oncology, The Second Affiliated Hospital of Nanchang University, Nanchang, China.
- Center of Interventional Oncology and Liver Diseases, Beijing Youan Hospital, Capital Medical University, Beijing, China.
- Department of Interventional Radiology, Union Hospital of Fujian Medical University, Fuzhou, China.
- Department of Interventional Radiology, The Tumor Hospital of Harbin Medical University, Harbin, China.
- Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
- Department of Interventional Therapy, Nantong Tumor Hospital, Nantong, China.
- Department of Interventional Radiology, the Third Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China.
- Department of Interventional Oncology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
- Department of Interventional Therapy, Shanxi Tumor Hospital, Taiyuan, China.
- Interventional Department, Hunan Provincial Tumor Hospital, Changsha, China.
- Department of General Surgery, The Second Hospital of Hebei Medical University, Shijiazhuang, China.
- Hepatobiliary and Pancreatic Interventional Treatment Center, Division of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
- Department of Interventional Radiology, The Affiliated Wuxi People's Hospital of Nanjing Medical University, Wuxi, China.
- Cancer Center, the First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
- Clinical Nutrition Service Center, Department of General Surgery, Jinling Hospital, Medical School of Nanjing University, Nanjing, China.
- Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China.
- Beijing Key Laboratory of Molecular Imaging, Beijing, China.
- Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, School of Engineering Medicine, Beihang University, Beijing, China.
- Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, China.
Abstract
This study aims to quantify intratumor heterogeneity (ITH) and identify prognostic imaging biomarkers in patients with hepatocellular carcinoma (HCC) treated with transarterial chemoembolization combined with immune checkpoint inhibitor plus molecular targeted therapy (TACE-ICI-MTT). This multicenter cohort study included 742 patients with unresectable HCC who received first-line TACE-ICI-MTT from January 2018 to December 2022. Radiomic features representing global tumor regions (GTR) and ITH were extracted from pre-treatment computed tomography scans. A composite GTR-ITH score was generated using principal component analysis to integrate both GTR- and ITH-related features. Ensemble learning with multiple machine learning algorithms was employed to predict treatment response. Model performance was evaluated by the area under the receiver operating characteristic curve (AUC), and survival outcomes were compared between model-defined risk groups using Kaplan-Meier analysis and the log-rank test. To reveal the biological relevance of the radiomic score, immune infiltration patterns were characterized using bulk RNA sequencing data from The Cancer Imaging Archive. Following feature selection, 17 GTR- and 27 ITH-related radiomic features were retained to construct the GTR-ITH score. The model demonstrated high discriminative performance, with AUCs of 0.94 in the training set, 0.82 in the internal validation set, and 0.83 in the independent test set. The GTR-ITH score was strongly associated with treatment response (OR 34.39; p<0.001) and independently predicted overall survival (HR 0.63; p=0.004). Patients classified as GTR-ITH low-risk consistently showed significantly prolonged progression-free survival and overall survival. The GTR-ITH low-risk group also exhibited an immune-inflamed microenvironment characterized by enriched plasma cells and M1 macrophages, and reduced M2 macrophage infiltration. An imaging radiomic biomarker capturing both global and intratumoral heterogeneity robustly predicts response and survival in HCC patients treated with TACE-ICI-MTT, and reflects underlying immune microenvironment phenotypes.