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NCT Number: NCT07584317

AI-Based Multimodal Integration for Tumor Microenvironment Analysis and Response Prediction in HCC Treated With TACE Plus Immunotherapy and Targeted Therapy (CHANCE2601)

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.

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Key information

Conditions

Hepatocellular Carcinoma Adenocarcinoma Carcinoma Carcinoma, Hepatocellular Digestive System Diseases Digestive System Neoplasms Liver Diseases Liver Neoplasms Neoplasms Neoplasms by Histologic Type Neoplasms by Site Neoplasms, Glandular and Epithelial

Age range

18 year and older

Sex eligibility

All sexes

Study type

Observational

About this study

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.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

  • 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.

Treatment and study plan

Artificial intelligence

Other

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

Primary outcomes

  1. 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.

Secondary outcomes

  1. 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.

  2. 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.

  3. 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.

  4. 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

Study contacts

Contact information is provided by the study sponsor or research team.

Zhicheng Jin, MD

CONTACT

[email protected]

+86-025-83272121

Sponsors and collaborators

Lead sponsor

Gao-jun Teng

Other

Registry information

Official study title

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

Important dates

Study start
2026
Primary completion
2027
Study completion
2028
First posted
May 13, 2026
Registry last updated
May 13, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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