- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT05384184
Next Generation " Pre-clinical Model for Colorectal Cancer Metastases and Hepatocellular Carcinomas (BORG) (BORG)
Next Generation " of Liver Derived-organoïd Biobank: Case of Colorectal Cancer Metastases and Hepatocellular Carcinomas
Recently, oncology has moved to a new clinical practice, more personalized, called Predictive Oncology (PO).
PO comes from our knowledge about tumor heterogeneity that implies that each disease, thus each patient, is unique. PO's goal is to identify and administrate the right treatment to the right patient.
For this, PO requires to go through 3 majors steps:
- A good characterization of the tumor to identify candidates,
- A well-established panel of drugs targeting the identified candidates,
- A relevant model to functionally test these candidates.
The first point could easily be addressed with recent technologies that now allow the Next Generation Sequencing (NGS) and/or the simultaneous analysis of transcriptomic profiles from thousands of patients. The last two points have not been efficiently achieved so far, which prevents PO to be really efficient.
Indeed, even if NGS allows the identification of potential targets, the presence of a molecular candidate does not necessary means obligatory functional response.
The number of drugs approved by the Food and Drug Administration remains limited and most frequent targets in solid tumors (for ex. RAS, P53, MYC, RB1 ...) still do not have specific drugs approved in clinic.
Finally, available pre-clinical models still present many major inconvenient:
- Chimiogrammes on 2D cultures are not sufficiently relevant to be really predictive of the in vivo situation;
- Patient derived xenograft (PDX) are not adapted for clinical use because not all tumors graft and the time to develop a PDX is too long (several months), thus incompatible with the history of the disease (especially for most severe patients). Furthermore the host (NOD-SCID mouse) is immuno-depressed, preventing to objectively test antibodies-mediated drugs.
Recently, the 3D cell culture technology has proven its superiority to predict drug response over classical 2D chimiogrammes. It consists in growing "mini-tissues", or organoid-derived from tumor/healthy tissues, thanks to the amplification of stem cells contained within the sample. The generated organoids are personalized and biologically relevant (organoids are expend form the patient's stem cells which self-organized according to the architecture of the tissue they are originating from), they are genetically stable, their growth is compatible with patient's disease history (organoids grow in few weeks), easy and convenient to achieve, even from small biological material quantities (0.5< x < 1cm3), and they can be amplified, frozen and thawed on demand. Moreover, organoids can be made more complex with the addition of other cell types (fibroblasts, immune cells …). None of the actual available pre-clinical model regroups all these characteristics.
The constitution of a "next generation" biobank of liver samples (Metastases to the liver and Hepato Cellular Adenocarcinoma) will be very useful in the context of predictive oncology.
For this, a biopsy needs to be dissociated and grown in Matrigel™, in presence of a well-defined list of growth factors. Once the culture is established, organoids can be frozen then defrost on demand.
Our main objective is to evaluate the feasibility for building a biobank of liver-derived organoids, from liver metastases of colorectal cancers, hepatocellular adenoma and adenocarcinoma (waste tissues).
Applications related to organoids derived from tumors are quasi indefinite, from drug screening assays, tests for novel therapies or original drug combinations, to patients' stratifications or fundamental research.
In our case, we are interested in building this a biobank in the prospect of using it to build the "next generation of model for predictive oncology" to study liver-related cancers and related drugs testing. Briefly, we want to implement these organoids with cells from the microenvironment in order to makes the global model more pertinent for drug testing.
If successful, the generation of such biobank, including both tumor-derived organoids and healthy counterpart, could be really helpful for the scientific and medical community.
Study Overview
Status
Intervention / Treatment
Detailed Description
Recently, oncology has moved to a new clinical practice, more personalized, called Predictive Oncology (PO).
PO comes from our knowledge about tumor heterogeneity that implies that each disease, thus each patient, is unique. PO's goal is to identify and administrate the right treatment to the right patient.
For this, PO requires to go through 3 majors steps:
- A good characterization of the tumor to identify candidates,
- A well-established panel of drugs targeting the identified candidates,
- A relevant model to functionally test these candidates.
The first point could easily be addressed with recent technologies that now allow the Next Generation Sequencing (NGS) and/or the simultaneous analysis of transcriptomic profiles from thousands of patients. The last two points have not been efficiently achieved so far, which prevents PO to be really efficient.
Indeed, even if NGS allows the identification of potential targets, the presence of a molecular candidate does not necessary means obligatory functional response.
The number of drugs approved by the Food and Drug Administration remains limited and most frequent targets in solid tumors (for ex. RAS, P53, MYC, RB1 ...) still do not have specific drugs approved in clinic.
Finally, available pre-clinical models still present many major inconvenient:
- Chimiogrammes on 2D cultures are not sufficiently relevant to be really predictive of the in vivo situation;
- Patient derived xenograft (PDX) are not adapted for clinical use because not all tumors graft and the time to develop a PDX is too long (several months), thus incompatible with the history of the disease (especially for most severe patients). Furthermore the host (NOD-SCID mouse) is immuno-depressed, preventing to objectively test antibodies-mediated drugs.
Recently, the 3D cell culture technology has proven its superiority to predict drug response over classical 2D chimiogrammes. It consists in growing "mini-tissues", or organoid-derived from tumor/healthy tissues, thanks to the amplification of stem cells contained within the sample. The generated organoids are personalized and biologically relevant (organoids are expend form the patient's stem cells which self-organized according to the architecture of the tissue they are originating from), they are genetically stable, their growth is compatible with patient's disease history (organoids grow in few weeks), easy and convenient to achieve, even from small biological material quantities (0.5< x < 1cm3), and they can be amplified, frozen and thawed on demand. Moreover, organoids can be made more complex with the addition of other cell types (fibroblasts, immune cells …). None of the actual available pre-clinical model regroups all these characteristics.
The constitution of a "next generation" biobank of liver samples (Metastases to the liver and Hepato Cellular Adenocarcinoma) will be very useful in the context of predictive oncology.
For this, a biopsy needs to be dissociated and grown in Matrigel™, in presence of a well-defined list of growth factors. Once the culture is established, organoids can be frozen then defrost on demand.
Our main objective is to evaluate the feasibility for building a biobank of liver-derived organoids, from liver metastases of colorectal cancers, hepatocellular adenoma and adenocarcinoma (waste tissues).
Applications related to organoids derived from tumors are quasi indefinite, from drug screening assays, tests for novel therapies or original drug combinations, to patients' stratifications or fundamental research.
In our case, we are interested in building this a biobank in the prospect of using it to build the "next generation of model for predictive oncology" to study liver-related cancers and related drugs testing. Briefly, we want to implement these organoids with cells from the microenvironment in order to makes the global model more pertinent for drug testing.
If successful, the generation of such biobank, including both tumor-derived organoids and healthy counterpart, could be really helpful for the scientific and medical community.
Study Type
Enrollment (Anticipated)
Contacts and Locations
Study Contact
- Name: david birnbaum
- Phone Number: + 33 4 91 96 81 45
- Email: david.birnbaum@ap-hm.fr
Study Locations
-
-
-
Marseille, France, 13915
- Recruiting
- AP-HM Hopital nord
-
Contact:
- david birnbaum
- Phone Number: + 33 4 91 96 81 45
- Email: david.birnbaum@ap-hm.fr
-
Principal Investigator:
- david birnbaum
-
-
Participation Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Genders Eligible for Study
Sampling Method
Study Population
Description
Inclusion Criteria:
- > 18 yo
- Patient with a diagnosis of hepatocellular carcinomas or colorectal cancer metastases
- Patient affiliated to the national healthcare program " sécurité sociale "
- Patient who has been informed and agreed to the proposed research program
Exclusion Criteria:
- Patients with more than one malignancy
- Patients receiving sustained immunosupressive treatments
- Patient with severe infection
- Patient under legal supervision, in situation of emergency or not able to express its consent
Study Plan
How is the study designed?
Design Details
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
---|---|---|
Build the next generation biobank of liver-derived organoids
Time Frame: 2 years
|
Grow and store organoids derived from liver biopsies (HC and CRC mets)
|
2 years
|
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
---|---|---|
Biobank of liver-derived organoids efficiency
Time Frame: 2 years
|
Evaluate the efficicency for building a biobank of liver-derived organoids either from HCC or from CRC mets
|
2 years
|
Evaluate the clinical relevance of the generated organoids
Time Frame: 2 years
|
Compared histologic & phenotypic traits between the tumor of origin and the corresponding organoids
|
2 years
|
Collaborators and Investigators
Study record dates
Study Major Dates
Study Start (Actual)
Primary Completion (Anticipated)
Study Completion (Anticipated)
Study Registration Dates
First Submitted
First Submitted That Met QC Criteria
First Posted (Actual)
Study Record Updates
Last Update Posted (Actual)
Last Update Submitted That Met QC Criteria
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
- Digestive System Diseases
- Pathologic Processes
- Neoplasms by Histologic Type
- Neoplasms
- Neoplasms by Site
- Adenocarcinoma
- Neoplasms, Glandular and Epithelial
- Gastrointestinal Neoplasms
- Digestive System Neoplasms
- Gastrointestinal Diseases
- Liver Diseases
- Colonic Diseases
- Intestinal Diseases
- Liver Neoplasms
- Intestinal Neoplasms
- Rectal Diseases
- Neoplastic Processes
- Carcinoma
- Carcinoma, Hepatocellular
- Colorectal Neoplasms
- Neoplasm Metastasis
Other Study ID Numbers
- RCAPHM19_0407
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.
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