AI-Based Multimodal Integration for Tumor Microenvironment Analysis and Response Prediction in HCC Treated With TACE Plus Immunotherapy and Targeted Therapy (CHANCE2601)
May 7, 2026 updated by: Gao-jun Teng
Artificial Intelligence-Based Multimodal Data Integration for Tumor Microenvironment Analysis and Response Prediction in Hepatocellular Carcinoma Patients Undergoing TACE Combined With Immunotherapy and Targeted Therapy
This study aims to prospectively validate a retrospective cohort-derived AI-based multimodal model and explore tumor heterogeneity and the immune microenvironment to guide TACE combined with immunotherapy and targeted therapy in HCC.
Study Overview
Status
Not yet recruiting
Conditions
Intervention / Treatment
Detailed Description
This study will integrate a retrospective cohort with a prospective observational cohort.
Multimodal data will be collected in the prospective cohort to validate the AI-based imaging model developed from the retrospective cohort.
In addition, advanced multi-omics technologies will be incorporated to characterize tumor heterogeneity and the immune microenvironment, thereby supporting early and precise guidance for TACE combined with immunotherapy and targeted therapy in HCC.
Study Type
Observational
Enrollment (Estimated)
1170
Contacts and Locations
This section provides the contact details for those conducting the study, and information on where this study is being conducted.
Study Contact
- Name: Zhicheng Jin, MD
- Phone Number: +86-025-83272121
- Email: jinzhic@foxmail.com
Participation Criteria
Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.
Eligibility Criteria
Ages Eligible for Study
- Adult
- Older Adult
Accepts Healthy Volunteers
No
Sampling Method
Non-Probability Sample
Study Population
In the retrospective cohort, patients with HCC who received TACE combined with immunotherapy and targeted therapy, as well as other treatment modalities, will be retrospectively included.
Multimodal data from this cohort will be used to develop and train the AI-based model.
In the prospective cohort, patients with HCC who receive TACE combined with immunotherapy and targeted therapy will be prospectively enrolled.
Multimodal data, including clinical, imaging, and biospecimen-related data when available, will be collected to validate the AI-based multimodal model.
Description
Retrospective Study Cohort 1.1 Inclusion Criteria Age ≥18 years; Patients with hepatocellular carcinoma confirmed by histopathology or clinical diagnosis; At least one intrahepatic lesion that is repeatedly measurable according to RECIST v1.1.
1.2 Exclusion Criteria Known sarcomatoid hepatocellular carcinoma or fibrolamellar hepatocellular carcinoma; Presence of other active malignancies within the past 5 years or concurrent active malignancies other than hepatocellular carcinoma; Missing preoperative imaging examinations, including CT or MRI, or poor image quality; Missing key baseline clinical data; Loss to follow-up after treatment.
- Prospective Study Cohort 2.1 Inclusion Criteria Age ≥18 years; Patients with hepatocellular carcinoma confirmed by histopathology or clinical diagnosis; Scheduled to receive first-line TACE combined with immunotherapy and targeted therapy; At least one intrahepatic lesion that is repeatedly measurable according to RECIST v1.1; Expected survival of more than 3 months. 2.2 Exclusion Criteria Known sarcomatoid hepatocellular carcinoma or fibrolamellar hepatocellular carcinoma; Presence of other active malignancies within the past 5 years or concurrent active malignancies other than hepatocellular carcinoma; Other factors that, in the investigator's judgment, make the patient unsuitable for participation in this study; Severe allergy to iodinated contrast agents that preclude imaging examinations or TACE treatment.
Study Plan
This section provides details of the study plan, including how the study is designed and what the study is measuring.
How is the study designed?
Design Details
Cohorts and Interventions
Group / Cohort |
Intervention / Treatment |
|---|---|
|
Retrospective cohort
Patients with hepatocellular carcinoma who received TACE combined with immunotherapy and targeted therapy, as well as other treatment modalities, will be retrospectively included.
Multimodal data from this cohort will be used to develop and train the AI-based model.
|
Investigators utilize a AI-based supportive system to predict clinical outcomes for patients with hepatocellular carcinoma who received TACE combined with immunotherapy and targeted therapy
|
|
Prospective cohort
Patients with hepatocellular carcinoma who receive TACE combined with immunotherapy and targeted therapy will be prospectively enrolled.
Multimodal data, including clinical, imaging, and biospecimen-related data when available, will be collected to validate the AI-based multimodal model.
|
Investigators utilize a AI-based supportive system to predict clinical outcomes for patients with hepatocellular carcinoma who received TACE combined with immunotherapy and targeted therapy
|
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Prediction Performance of the AI Model
Time Frame: From enrollment to approximately 2 years
|
The area under curve (AUC) of Receiver Operating Characteristic (ROC) curves o f the AI model in predicting the clinical outcomes in patients receiving TACE combined with immunotherapy and targeted therapy.
|
From enrollment to approximately 2 years
|
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Overall Survival(OS)
Time Frame: up to approximately 2 years
|
The OS is defined as the time from the initiation of any combination treatment to death due to any cause.
|
up to approximately 2 years
|
|
Objective response rate(ORR)
Time Frame: up to approximately 2 years
|
The ORR is defined as the proportion of patients with a documented complete response(CR) or partial response(PR) per RECIST 1.1 or per mRECIST.
|
up to approximately 2 years
|
|
Progression free survival(PFS)
Time Frame: up to approximately 2 years
|
The PFS is defined as the time from the initiation of any combination treatment to the first documented progressive disease (according to RECIST 1.1 or mRECIST) or death due to any cause, whichever occurs first.
|
up to approximately 2 years
|
|
Other prediction performance of the model
Time Frame: From enrollment to approximately 2 years
|
Evaluation of the accuracy, sensitivity, and specificity of the prediction model in clinical application
|
From enrollment to approximately 2 years
|
Collaborators and Investigators
This is where you will find people and organizations involved with this study.
Sponsor
Publications and helpful links
The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.
General Publications
- Zhong BY, Fan W, Guan JJ, Peng Z, Jia Z, Jin H, Jin ZC, Chen JJ, Zhu HD, Teng GJ. Combination locoregional and systemic therapies in hepatocellular carcinoma. Lancet Gastroenterol Hepatol. 2025 Apr;10(4):369-386. doi: 10.1016/S2468-1253(24)00247-4. Epub 2025 Feb 21.
- Jin ZC, Wei J, Xiao YD, Si A, Chen JJ, Zhu XL, Li JZ, Nie F, Ding R, Zhou HF, Ding W, Zhong BY, Xie Y, Hu HT, Yin GW, Ji JS, Zhang WH, Shi HB, Wu JB, Xu GH, Yuan CW, Yang WZ, Liu RB, Wu YM, Zheng CS, Xu AB, Huang MS, Li JP, Chen L, Wen SW, Wang YQ, Gu SZ, Li D, Wang D, Zhou GH, Wang WD, Peng Z, Wang X, Zhu HD, Tian J, Teng GJ. Decoding tumor heterogeneity with imaging biomarkers predicts response to TACE plus immunotherapy and targeted therapy in HCC (CHANCE2204). Hepatology. 2025 Nov 10. doi: 10.1097/HEP.0000000000001593. Online ahead of print.
- Vithayathil M, Koku D, Campani C, Nault JC, Sutter O, Ganne-Carrie N, Aboagye EO, Sharma R. Machine learning based radiomic models outperform clinical biomarkers in predicting outcomes after immunotherapy for hepatocellular carcinoma. J Hepatol. 2025 Oct;83(4):959-970. doi: 10.1016/j.jhep.2025.04.017. Epub 2025 Apr 17.
Study record dates
These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.
Study Major Dates
Study Start (Estimated)
May 18, 2026
Primary Completion (Estimated)
May 31, 2027
Study Completion (Estimated)
December 31, 2028
Study Registration Dates
First Submitted
May 7, 2026
First Submitted That Met QC Criteria
May 7, 2026
First Posted (Actual)
May 13, 2026
Study Record Updates
Last Update Posted (Actual)
May 13, 2026
Last Update Submitted That Met QC Criteria
May 7, 2026
Last Verified
May 1, 2026
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
- CHANCE2601
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
NO
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
No
Studies a U.S. FDA-regulated device product
No
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