Ignite Creation Date:
2024-05-06 @ 7:48 PM
Last Modification Date:
2024-10-26 @ 3:14 PM
Study NCT ID:
NCT06146127
Status:
RECRUITING
Last Update Posted:
2023-11-24
First Post:
2023-11-17
Brief Title:
Precision Medicine for Combined Hepatocellular-Cholangiocarcinoma
Sponsor:
Inserm U955
Organization:
Inserm U955
Study Overview
Official Title:
Precision Medicine for Combined Hepatocellular-Cholangiocarcinoma
Status:
RECRUITING
Status Verified Date:
2023-11
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
PREMED-CHC
Brief 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 geneticimmune 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
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 geneticimmune 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
Study Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
False
Is a FDA Regulated Device?:
False
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?:
None