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Hepatocellular CarcinomaNCT07584317

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

An observational study of Hepatocellular Carcinoma, run by Gao-jun Teng.

Not yet recruiting

Opening soon. The study is approved but enrolment has not started yet. Sites may already take enquiries.

Sites and contacts
Official record
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Trial summary

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. Read more about this study

Who is it for?
Ages 18 years and older
Conditions the study is for
Hepatocellular Carcinoma
What is being tested?
Artificial Intelligence
How many people
1,170 participants
Where
No sites listed yet
Study dates
18 May 2026to 31 Dec 2028
How long will I take part?
24 Months
Phase
Observational
Are there results?
Not yet: the study is under way

Key requirements

Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.

  • Ages 18 years and older
  • All sexes
  • No healthy volunteers
  • Adult, Older adult

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.

  1. 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.
  2. 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.

Trial locations and contacts

No sites are listed yet. Contact the study team or a site near you to ask about taking part.

Zhicheng Jin, MD contact

+86-025-83272121

jinzhic@foxmail.com

About this study

Official 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

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.

Read the 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.

Being tested
Artificial Intelligence
Medical subject headings
Carcinoma, Hepatocellular

What participants receive

What participants receive. In a randomised study each person is assigned to one group by chance.

  • Artificial IntelligenceOther

    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

Study groups in NCT07584317
Study groupRoleWhat they receive
Retrospective cohortPatients 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.
Receives: Other: Artificial Intelligence
Prospective cohortPatients 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.
Receives: Other: Artificial Intelligence

What is being measured

The primary outcome is the main question the study is designed to answer.

  1. Prediction Performance of the AI Model

    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.

    Measured: From enrollment to approximately 2 years

Secondary outcomes (4)

  1. Objective response rate(ORR)

    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.

    Measured: up to approximately 2 years

  2. Overall Survival(OS)

    The OS is defined as the time from the initiation of any combination treatment to death due to any cause.

    Measured: up to approximately 2 years

  3. Progression free survival(PFS)

    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.

    Measured: up to approximately 2 years

  4. Other prediction performance of the model

    Evaluation of the accuracy, sensitivity, and specificity of the prediction model in clinical application

    Measured: From enrollment to approximately 2 years

Timeline

From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.

  1. First posted13 May 2026
  2. Study start18 May 2026 (estimated)
  3. Primary completion31 May 2027 (estimated)
  4. Study completion31 Dec 2028 (estimated)

Resources

More details

For doctors and researchers: how the study is designed, who runs it, and its registry IDs.

Study design
Study type
Observational
Observational model
Cohort
Time perspective
Other
Enrolment
1,170 participants (estimated)
Target duration
24 Months
IDs, dates and publications
ClinicalTrials.gov ID
NCT07584317
Sponsor's protocol ID
CHANCE2601
Status last verified
May 2026
First submitted
7 May 2026
Last updated
13 May 2026
Results posted
No
Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
No
Individual data sharing
No

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.

    PubMed 39993404

  • 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.

    PubMed 41213031

  • 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.

    PubMed 40246150

Questions about this trial

What is this clinical trial studying?

An observational study of Hepatocellular Carcinoma, run by Gao-jun Teng.

The full registered description is in the About this study section and the official record.

Who may be eligible to take part?

Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.

Is this clinical trial currently recruiting?

The record says: opening soon, as of the sponsor's last update on 13 May 2026. Status can change between updates, so confirm with the study contact before making plans.

What are the possible benefits and risks?

They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.

Are results available for this study?

This study is still under way. Results are not available in the source record yet.

How can a doctor refer a patient or contact the research team?

Contact Zhicheng Jin, MD (+86-025-83272121, jinzhic@foxmail.com), or a site near the patient. AzTrials does not enrol participants or take referrals.

What does the primary outcome measure?

Prediction Performance of the AI Model (time frame: From enrollment to approximately 2 years). It is what the study was designed to measure, not a finding.

Where can I read the original study information?

On the ClinicalTrials.gov record for NCT07584317, which also lists 3 linked publications.

Does a listing mean the treatment is approved or proven to work?

No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.

How often is this information updated?

AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 13 May 2026.

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