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Clinical Trial Details — Status: Recruiting

Administrative data

NCT number NCT06342414
Other study ID # 23228/ELUCIDATE
Secondary ID
Status Recruiting
Phase
First received
Last updated
Start date March 15, 2024
Est. completion date March 15, 2025

Study information

Verified date April 2024
Source City of Hope Medical Center
Contact Ajay Goel, PhD
Phone 6262183452
Email AJGOEL@COH.ORG
Is FDA regulated No
Health authority
Study type Observational

Clinical Trial Summary

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.


Description:

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: 1. To perform comprehensive small RNA-Seq from exo-miRNA from patients with ICC and HCC. 2. To develop and train a differential diagnosis panel based on advanced machine-learning models to obtain a final differential diagnosis biomarker. 3. 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.


Recruitment information / eligibility

Status Recruiting
Enrollment 400
Est. completion date March 15, 2025
Est. primary completion date March 15, 2025
Accepts healthy volunteers No
Gender All
Age group 18 Years and older
Eligibility 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

Study Design


Intervention

Diagnostic Test:
ELUCIDATE
ELUCIDATE (Evaluation of Liver Cholangiocarcinoma Intrahepatic)

Locations

Country Name City State
Japan Graduate School of Medical Sciences, Kyushu University Fukuoka
Japan Graduate School of Medical Sciences, Kumamoto University Kumamoto
Japan Hokkaido University Graduate School of Medicine Sapporo
Japan Tokushima University Tokushima
United States City of Hope Medical Center Duarte California

Sponsors (1)

Lead Sponsor Collaborator
City of Hope Medical Center

Countries where clinical trial is conducted

United States,  Japan, 

References & Publications (18)

Arbelaiz A, Azkargorta M, Krawczyk M, Santos-Laso A, Lapitz A, Perugorria MJ, Erice O, Gonzalez E, Jimenez-Aguero R, Lacasta A, Ibarra C, Sanchez-Campos A, Jimeno JP, Lammert F, Milkiewicz P, Marzioni M, Macias RIR, Marin JJG, Patel T, Gores GJ, Martinez I, Elortza F, Falcon-Perez JM, Bujanda L, Banales JM. Serum extracellular vesicles contain protein biomarkers for primary sclerosing cholangitis and cholangiocarcinoma. Hepatology. 2017 Oct;66(4):1125-1143. doi: 10.1002/hep.29291. Epub 2017 Aug 26. — View Citation

Banales JM, Inarrairaegui M, Arbelaiz A, Milkiewicz P, Muntane J, Munoz-Bellvis L, La Casta A, Gonzalez LM, Arretxe E, Alonso C, Martinez-Arranz I, Lapitz A, Santos-Laso A, Avila MA, Martinez-Chantar ML, Bujanda L, Marin JJG, Sangro B, Macias RIR. Serum Metabolites as Diagnostic Biomarkers for Cholangiocarcinoma, Hepatocellular Carcinoma, and Primary Sclerosing Cholangitis. Hepatology. 2019 Aug;70(2):547-562. doi: 10.1002/hep.30319. Epub 2019 Feb 14. — View Citation

Chen VL, Xu D, Wicha MS, Lok AS, Parikh ND. Utility of Liquid Biopsy Analysis in Detection of Hepatocellular Carcinoma, Determination of Prognosis, and Disease Monitoring: A Systematic Review. Clin Gastroenterol Hepatol. 2020 Dec;18(13):2879-2902.e9. doi: 10.1016/j.cgh.2020.04.019. Epub 2020 Apr 11. — View Citation

El-Serag HB, Marrero JA, Rudolph L, Reddy KR. Diagnosis and treatment of hepatocellular carcinoma. Gastroenterology. 2008 May;134(6):1752-63. doi: 10.1053/j.gastro.2008.02.090. — View Citation

Foda ZH, Annapragada AV, Boyapati K, Bruhm DC, Vulpescu NA, Medina JE, Mathios D, Cristiano S, Niknafs N, Luu HT, Goggins MG, Anders RA, Sun J, Meta SH, Thomas DL, Kirk GD, Adleff V, Phallen J, Scharpf RB, Kim AK, Velculescu VE. Detecting Liver Cancer Using Cell-Free DNA Fragmentomes. Cancer Discov. 2023 Mar 1;13(3):616-631. doi: 10.1158/2159-8290.CD-22-0659. — View Citation

Huang C, Xu X, Wang M, Xiao X, Cheng C, Ji J, Fang M, Gao C. Serum N-glycan fingerprint helps to discriminate intrahepatic cholangiocarcinoma from hepatocellular carcinoma. Electrophoresis. 2021 Jun;42(11):1187-1195. doi: 10.1002/elps.202000392. Epub 2021 Mar 1. — View Citation

Kovac JD, Jankovic A, Dikic-Rom A, Grubor N, Antic A, Dugalic V. Imaging Spectrum of Intrahepatic Mass-Forming Cholangiocarcinoma and Its Mimickers: How to Differentiate Them Using MRI. Curr Oncol. 2022 Jan 30;29(2):698-723. doi: 10.3390/curroncol29020061. — View Citation

Lapitz A, Azkargorta M, Milkiewicz P, Olaizola P, Zhuravleva E, Grimsrud MM, Schramm C, Arbelaiz A, O'Rourke CJ, La Casta A, Milkiewicz M, Pastor T, Vesterhus M, Jimenez-Aguero R, Dill MT, Lamarca A, Valle JW, Macias RIR, Izquierdo-Sanchez L, Perez Castano Y, Caballero-Camino FJ, Riano I, Krawczyk M, Ibarra C, Bustamante J, Nova-Camacho LM, Falcon-Perez JM, Elortza F, Perugorria MJ, Andersen JB, Bujanda L, Karlsen TH, Folseraas T, Rodrigues PM, Banales JM. Liquid biopsy-based protein biomarkers for risk prediction, early diagnosis, and prognostication of cholangiocarcinoma. J Hepatol. 2023 Jul;79(1):93-108. doi: 10.1016/j.jhep.2023.02.027. Epub 2023 Mar 1. — View Citation

Li S, Yao J, Xie M, Liu Y, Zheng M. Exosomal miRNAs in hepatocellular carcinoma development and clinical responses. J Hematol Oncol. 2018 Apr 11;11(1):54. doi: 10.1186/s13045-018-0579-3. — View Citation

Marrero JA, Kulik LM, Sirlin CB, Zhu AX, Finn RS, Abecassis MM, Roberts LR, Heimbach JK. Diagnosis, Staging, and Management of Hepatocellular Carcinoma: 2018 Practice Guidance by the American Association for the Study of Liver Diseases. Hepatology. 2018 Aug;68(2):723-750. doi: 10.1002/hep.29913. No abstract available. — View Citation

Sasaki R, Kanda T, Yokosuka O, Kato N, Matsuoka S, Moriyama M. Exosomes and Hepatocellular Carcinoma: From Bench to Bedside. Int J Mol Sci. 2019 Mar 20;20(6):1406. doi: 10.3390/ijms20061406. — View Citation

Si YQ, Wang XQ, Pan CC, Wang Y, Lu ZM. An Efficient Nomogram for Discriminating Intrahepatic Cholangiocarcinoma From Hepatocellular Carcinoma: A Retrospective Study. Front Oncol. 2022 Apr 11;12:833999. doi: 10.3389/fonc.2022.833999. eCollection 2022. — View Citation

Vigano L, Lleo A, Muglia R, Gennaro N, Sama L, Colapietro F, Roncalli M, Aghemo A, Chiti A, Di Tommaso L, Solbiati L, Colombo M, Torzilli G. Intrahepatic cholangiocellular carcinoma with radiological enhancement patterns mimicking hepatocellular carcinoma. Updates Surg. 2020 Jun;72(2):413-421. doi: 10.1007/s13304-020-00750-5. Epub 2020 Apr 22. — View Citation

Wang M, Gao Y, Feng H, Warner E, An M, Jia J, Chen S, Fang M, Ji J, Gu X, Gao C. A nomogram incorporating six easily obtained parameters to discriminate intrahepatic cholangiocarcinoma and hepatocellular carcinoma. Cancer Med. 2018 Mar;7(3):646-654. doi: 10.1002/cam4.1341. Epub 2018 Feb 23. — View Citation

Wang P, Song Q, Ren J, Zhang W, Wang Y, Zhou L, Wang D, Chen K, Jiang L, Zhang B, Chen W, Qu C, Zhao H, Jiao Y. Simultaneous analysis of mutations and methylations in circulating cell-free DNA for hepatocellular carcinoma detection. Sci Transl Med. 2022 Nov 23;14(672):eabp8704. doi: 10.1126/scitranslmed.abp8704. Epub 2022 Nov 23. — View Citation

Wang Y, Zhang C, Zhang P, Guo G, Jiang T, Zhao X, Jiang J, Huang X, Tong H, Tian Y. Serum exosomal microRNAs combined with alpha-fetoprotein as diagnostic markers of hepatocellular carcinoma. Cancer Med. 2018 May;7(5):1670-1679. doi: 10.1002/cam4.1390. Epub 2018 Mar 23. — View Citation

Wu Y, Xia C, Chen J, Qin Q, Ye Z, Song B. Diagnostic performance of magnetic resonance imaging and contrast-enhanced ultrasound in differentiating intrahepatic cholangiocarcinoma from hepatocellular carcinoma: a meta-analysis. Abdom Radiol (NY). 2024 Jan;49(1):34-48. doi: 10.1007/s00261-023-04064-z. Epub 2023 Oct 12. — View Citation

Ye Q, Ling S, Zheng S, Xu X. Liquid biopsy in hepatocellular carcinoma: circulating tumor cells and circulating tumor DNA. Mol Cancer. 2019 Jul 3;18(1):114. doi: 10.1186/s12943-019-1043-x. — View Citation

* Note: There are 18 references in allClick here to view all references

Outcome

Type Measure Description Time frame Safety issue
Primary Sensitivity True Positive Rate: the probability of a positive test result, conditioned on the individual truly being positive Through study completion, an average of 1 year
Secondary Specificity True Negative Rate: the probability of a negative test result, conditioned on the individual truly being negative Through study completion, an average of 1 year
Secondary Proportion of correct predictions (true positives and true negatives) among the total number of cases (i.e., accuracy) A measure of trueness: proportion of correct predictions (both true positives and true negatives) among the total number of cases examined Through study completion, an average of 1 year
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