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| Name | Class |
|---|---|
| Ontario Institute for Cancer Research | OTHER |
| Ottawa Hospital Research Institute | OTHER |
| London Health Sciences Centre Research Institute OR Lawson Research Institute of St. Joseph's | OTHER |
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This is a prospective, multi-centre, translational and observational study. Two cohorts of patients with pancreatic ductal adenocarcinoma (PDAC) are eligible to enroll 1) Upfront resectable PDAC 2) Advanced (unresectable PDAC or metastatic). Patients will have tissue either at resection or from a biopsy at enrolment processed for whole genome sequencing, RNA sequencing and for establishment of patient derived organoids (PDOs). Background epidemiological history and outcome data will be prospectively annotated. Serial blood and stool samples will be collected for exploratory analyses. All electronic medical record information will also be collected. Data will be used to determine if an integrated correlative analysis of whole genome sequencing/RNAsequencing (WGS/RNAseq) and PDOs in the enrolled population will increase the number of patients receiving a precision-matched treatment in Ontario
This study is being done to answer the following question: Can creating 3D models using tumour samples and looking at genetic information from pancreatic ductal adenocarcinoma (PDAC) tumours, help us to provide more patients with a specific, personalized treatment? Two groups of patients with PDAC are eligible to enroll 1) PDAC patients that will go straight to surgery 2) PDAC patients where the disease is either too advanced for a surgical option, or the disease has spread to other areas in the body. Patients will have tumour tissue taken either during their surgery or from a biopsy at enrolment. Background history, outcome data, questionnaires, series of blood draws and stool samples will be collected for analyses. All electronic medical record information will also be collected.
Researchers are looking for better ways of understanding and treating pancreatic cancer by looking to see how useful it is to know about changes and characteristics in the genes in the tumour (molecules that contain instructions for the development and functioning of the cells). Results from analyzed data may be useful in choosing treatments for enrolled patients and for patients in the future. Patients current treatment plan will not change if they choose to take part in this study.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Cohort 1 | Upfront resectable PDAC |
| |
| Cohort 2 | Advanced (unresectable PDAC or metastatic) |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Non-interventional | Other | Standard of care intervention |
|
| Measure | Description | Time Frame |
|---|---|---|
| Precision-Matched Treatment Utilization Rate | Number of patients receiving precision-matched treatment in Ontario based on integrated correlative analysis of whole-genome sequencing (WGS), RNA sequencing (RNAseq), and patient-derived organoids (PDOs). | 4 years |
| Measure | Description | Time Frame |
|---|---|---|
| Build a comprehensive dataset of pancreatic cancer specimens (tissue and blood) and matched patient-derived organoids (PDOs) | 4 years | |
| Correlate drug sensitivities in patient-derived organoids (PDOs) and molecular information | 4 Years |
| Measure | Description | Time Frame |
|---|---|---|
| Develop an electronic medical record (EMR) platform utilizing artificial intelligence (AI) modeling | 4 Years | |
| Correlate serial plasma whole-genome sequencing (WGS) and tissue WGS | 4 Years | |
Inclusion Criteria:
Exclusion Criteria:
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| Name | Affiliation | Role |
|---|---|---|
| Erica Tsang, MD | University Health Network, Toronto | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Princess Margaret Cancer Centre | Toronto | Ontario | M5G 2M9 | Canada |
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| ID | Term |
|---|---|
| D010190 | Pancreatic Neoplasms |
| ID | Term |
|---|---|
| D004067 | Digestive System Neoplasms |
| D009371 | Neoplasms by Site |
| D009369 | Neoplasms |
| D004701 | Endocrine Gland Neoplasms |
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Tumour tissue will undergo WGS/RNAseq. Germline blood samples will be used as reference
| Correlate immune phenotypes and molecular profiles | 4 Years |
| Characterize the epigenome in established patient-derived organoids (PDOs) |
| 4 Years |
| Assess oncolytic virus efficacy in combination with immune checkpoint inhibitors in a subset of 50 patient-derived organoids (PDOs) co-cultured with autologous peripheral blood mononuclear cells (PBMCs) | 4 Years |
| Identify microbiome differences in patients at various stages of pancreatic ductal adenocarcinoma (PDAC) and their correlation with whole-genome sequencing (WGS)/RNA subtypes | 4 Years |
| Document stroma subtypes in pancreatic cancer and their correlation with clinical outcomes | 4 Years |
| Evaluate treatment responses in patients receiving precision-matched treatment using the Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1 | 4 Years |
| Investigate the involvement of genetic and environmental factors in the development and progression of pancreatic cancer | 4 Years |
| Assess comparability between WGS and commercial panel | 4 Years |
| Explore the feasibility and efficacy of utilizing digitized whole-slide images of biopsy or resection specimens for an AI-based digital pathology prediction system | 4 Years |
| D004066 |
| Digestive System Diseases |
| D010182 | Pancreatic Diseases |
| D004700 | Endocrine System Diseases |