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Trial Title:
Precision Medicine for Combined Hepatocellular-Cholangiocarcinoma
NCT ID:
NCT06146127
Condition:
Liver Cancer
Conditions: Official terms:
Cholangiocarcinoma
Conditions: Keywords:
liver
cancer
precision medicine
Study type:
Observational
Overall status:
Recruiting
Study design:
Time perspective:
Retrospective
Intervention:
Intervention type:
Other
Intervention name:
phenotyping
Description:
Large scale molecular phenotyping
Arm group label:
Combined hepatocellular cholangiocarcinoma
Arm group label:
cholangiocarcinoma
Arm group label:
hepatocellular carcinoma
Summary:
Our project is a large-scale characterisation of cHCC-CCA will allow us to determine
which subsets harbor actionable gene alterations. We will also aim to improve diagnosis
of this tumor type by the use of immunohistochemical biomarkers and the development of
deep-learning based models able to help cHCC-CCA diagnosis. This will represent an
important step towards precision medicine for the patients with this highly aggressive
malignancy.
Detailed description:
- Scientific background Combined hepatocellular-cholangiocarcinoma (cHCC-CCA) is a
rare liver cancer characterized by a dual hepatocytic and biliary differentiation.
It is resistant to conventional anti-cancer treatments and there is currently no
effective systemic therapy available. Inter-observer agreement for diagnosis of
cHCC-CCA is low, even among expert pathologists, and the development of clinical
trials remain thus challenging. The molecular mechanisms that drive its progression
also remain under-investigated.
- Project objectives and brief description of the methods which will be used to
achieve them We aim to perform an integrative molecular, immune and phenotypical
study of cHCC-CCA that will allow the distinction of different tumor subgroups
linked to particular actionable genetic/immune alterations. The development of
immunohistochemical markers and artificial intelligence-based approaches is also
likely to improve the diagnosis of cHCC-CCA.
A overall multicentric series of 357 cHCC-CCA samples, already available in our biobanks,
will be investigated by means of gene and RNA sequencing, digital pathology and
immunohistochemistry in order to build a morphomolecular classification of this tumor.
Spatial transcriptomics and in situ proteomics will be performed to decipher the
intra-tumor heterogeneity and identify biomarkers of the different subclasses. Finally,
deep-learning based models will be developed in order to 1) improve the diagnosis of
cHCC-CCA and 2) identify the morphological features linked to prognosis.
• Expected results This large-scale characterisation of cHCC-CCA will allow us to
determine which subsets harbor actionable gene alterations. We will also aim to improve
diagnosis of this tumor type by the use of immunohistochemical biomarkers and the
development of deep-learning based models able to help cHCC-CCA diagnosis. This will
represent an important step towards precision medicine for the patients with this highly
aggressive malignancy.
Criteria for eligibility:
Study pop:
adults
Sampling method:
Non-Probability Sample
Criteria:
Inclusion Criteria:
histological diagnosis of combined tumor biological sample available
Exclusion Criteria:
unequivocal histological features
Gender:
All
Minimum age:
18 Years
Maximum age:
N/A
Locations:
Facility:
Name:
Julien Calderaro
Address:
City:
Créteil
Zip:
94010
Country:
France
Status:
Recruiting
Contact:
Last name:
Julien Calderaro
Email:
julien.calderaro@aphp.fr
Start date:
January 15, 2001
Completion date:
January 30, 2025
Lead sponsor:
Agency:
Inserm U955
Agency class:
Other
Source:
Inserm U955
Record processing date:
ClinicalTrials.gov processed this data on November 12, 2024
Source: ClinicalTrials.gov page:
https://clinicaltrials.gov/ct2/show/NCT06146127
