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NCT Number: NCT06342414

An Exosome-Based Liquid Biopsy for the Differential Diagnosis of Primary Liver Cancer

It is sometimes difficult to precisely understand whether a primary liver cancer is a hepatocellular carcinoma or a cholangiocarcinoma. The researchers will develop and validate a liquid biopsy, based on exosomal content analysis and powered by machine learning, to help clinicians differentiate these two cancers before surgery.

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Key information

Age range

18 year and older

Sex eligibility

All sexes

Study type

Observational

Primary location

Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan

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About this study

Primary liver cancers (PLCs) encompass a diverse group of malignancies originating from the liver, collectively ranking as the third leading cause of cancer-related mortality worldwide in 2020. Among PLCs, intrahepatic cholangiocarcinoma (ICC) and hepatocellular carcinoma (HCC) represent the most predominant subtypes. Despite their collective grouping as PLCs, ICC and HCC patients exhibit distinct etiologies, pathologies, and clinical characteristics, necessitating different treatment approaches. Accurate differentiation between ICC and HCC is paramount to optimize patient outcomes and guide personalized treatment decisions. However, a definitive diagnosis is often obtained only after the pathological review of the resected neoplastic tissue, which requires invasive tumor sampling and poses risks of complications such as hemorrhage and tumor cell seeding. Consequently, there is a pressing clinical need to develop noninvasive diagnostic approaches to achieve an accurate differential diagnosis for patients with these distinct forms of PLCs.

This study involves the development and validation of a liquid biopsy, assessing circulating exosomal microRNAs (exo-miRNA) for indirect sampling of tumor tissue in the bloodstream. The researchers intend to harness machine learning and bioinformatics to create a cost-efficient, non-invasive, clinic-friendly assay with high sensitivity and specificity, aiding the differential diagnosis between ICC and HCC.

The researchers intend to do so in three phases:

  • To perform comprehensive small RNA-Seq from exo-miRNA from patients with ICC and HCC.
  • To develop and train a differential diagnosis panel based on advanced machine-learning models to obtain a final differential diagnosis biomarker.
  • To validate the findings in an independent cohort of ICC and HCC.

In summary, this proposal promises to improve patient care and help clinicians perform a more reliable differential diagnosis between ICC and HCC in patients with primary liver cancer.

Who can participate

Healthy volunteers accepted: No

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

Inclusion criteria

  • A histologically confirmed diagnosis of hepatocellular carcinoma
  • A histologically confirmed diagnosis of intrahepatic cholangiocarcinoma
  • Received standard diagnostic and staging procedures as per local guidelines
  • Availability of at least one blood-derived sample, drawn before receiving any curative-intent treatment

Exclusion criteria

  • Lack of or inability to provide informed consent
  • Synchronous hepatocellular carcinoma and intrahepatic cholangiocarcinoma
  • Primary liver cancer other than hepatocellular carcinoma or intrahepatic cholangiocarcinoma
  • Secondary liver cancer

Treatment and study plan

ELUCIDATE

Diagnostic Test

ELUCIDATE (Evaluation of Liver Cholangiocarcinoma Intrahepatic)

Other names: ELUCIDATE (Evaluation of Liver Cholangiocarcinoma Intrahepatic)

Primary outcomes

  1. Sensitivity

    Time frame: Through study completion, an average of 1 year

    True Positive Rate: the probability of a positive test result, conditioned on the individual truly being positive

Secondary outcomes

  1. Specificity

    Time frame: Through study completion, an average of 1 year

    True Negative Rate: the probability of a negative test result, conditioned on the individual truly being negative

  2. Proportion of correct predictions (true positives and true negatives) among the total number of cases (i.e., accuracy)

    Time frame: Through study completion, an average of 1 year

    A measure of trueness: proportion of correct predictions (both true positives and true negatives) among the total number of cases examined

Study contacts

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

Ajay Goel, PhD

CONTACT

[email protected]

6262183452

Sponsors and collaborators

Lead sponsor

City of Hope Medical Center

Other

Registry information

Acronym: ELUCIDATE

Important dates

Study start
2024
Primary completion
2028
Study completion
2028
First posted
Apr 2, 2024
Registry last updated
Jul 7, 2026

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

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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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