Data Use Projects

The MOHCCN Gold Cohort is Canada’s largest and most comprehensive cancer case resource, comprising paired clinical and genomic data from a diverse cohort of 15,000 Canadian cancer patients.

Network researchers may request access to Gold Cohort data for analysis projects.

Learn more about how to submit a data access request.

Approved Gold Cohort Data Access Projects

Precision Targeting of ecDNA-Driven Tumors through Bioinformatic Identification of Synthetic Lethal Vulnerabilities

Lead Investigator: David Cescon

Lead Institution: Princess Margaret Cancer Centre

Summary:

Cancer cells sometimes have extra loops of DNA called extrachromosomal DNA (ecDNA), which are separate from the normally packaged chromosomes. EcDNA often carries genes that make cancers grow faster, become aggressive, and resist treatment. Patients whose tumors contain ecDNA seem to have poorer outcomes. At the Princess Margaret Cancer Centre, we found that early-stage breast cancer patients with ecDNA-containing tumors responded poorly to curative therapy (chemotherapy and endocrine therapy) and had a higher chance of their cancer coming back. Knowing this, we need new treatments targeting ecDNA-containing cancers to improve outcomes for patients. Our study aims to find these new treatments by identifying weaknesses in ecDNA-driven cancer cells using a concept called synthetic lethality (SL). SL occurs when cancer cells survive losing function in one gene but die when a second function is also disrupted. We think that we can apply this approach for the presence of ecDNA and the genes that are contained in them. Using genomic data from thousands of Canadian cancer patients (the Marathon of Hope Cancer Centres Network Gold Cohort), we will find tumors containing ecDNA and identify gene weaknesses unique to these tumors. First, we will detect ecDNA and the genes it carries in this unique data resource using specialized computer software. Next, we'll find gene pairs where disrupting one gene kills only ecDNA-positive cancer cells, leaving healthy cells unharmed. We will share our findings and methods openly, helping scientists develop new treatments to improve outcomes for patients with ecDNA-positive cancers as quickly as possible.

Date of Approval: August 11, 2025

Duration: 2 years (to August 11, 2027)

Improving assessment of immune cell infiltration in solid tumors (VDJump software)

Lead Investigator: Jennifer Chan
Lead Institution: University of Calgary

Summary:

Tissue samples for bulk tumor genome sequencing often contain non-tumor cells, including tumor infiltrating lymphocytes (TILs) acting as part of the body's immune response to the tumor. TILs are important prognostic and treatment indicators in many cancers. Existing methods for estimating the proportion of TILs and myeloid white blood cells in tumors are based on having an RNA sequence dataset for the tumor. Uniquely, VDJump makes TIL estimates (B cell and T cell fractions) from DNA data, which can be more readily generated or already available for many cancer cases.

Date of Approval: August 11, 2025
Duration: 2 years (to August 11, 2027)

Detection of Clonal Hematopoiesis Driven by Structural Variants

Lead Investigator: Aly Karsan
Lead Institution: BC Cancer

Summary:

"As we get older, our blood cells can develop DNA changes, or mutations, that help some cells grow faster than others. When these mutated cells start to multiply more than usual, it is  called  clonal  hematopoiesis  (CH). CH is fairly common — about 1 in 10 people over age 65 are estimated to have it. While CH doesn’t always lead to illness, CH raises the risk for blood cancers, as well as conditions like heart disease and diabetes.

Evidence indicates that CH may be even more common than currently thought, because  some types of genetic  changes  are  harder  to  detect  with  standard methods. We  want  to explore  those  harder‐to‐find  changes, especially  a  kind called chromosomal translocations. These happen when parts of  two different chromosomes swap places, sometimes creating new, abnormal genes that can lead to cancer. Surprisingly, versions of these cancer‐related changes have been found in the blood of healthy people, which suggests they might also be involved in CH, even in those without cancer. However, this idea has not been studied on a large scale. 

This project will look at genetic data from normal control blood samples collected in  the  MOHCCN  consortium.  The  goal  is  to  see  whether  these  chromosomal translocations  are  present  in  older  adults  without  disease,  and  whether  they become more common with age. If so, that would support the idea that these changes are part of CH. 

We will use advanced computer tools and powerful data‐sharing systems to scan for these large‐scale DNA changes, which are usually missed in routine genetic analyses. This pilot study will also test whether researchers across different sites can collaborate effectively using shared resources. 

If successful, the study could change how physicians and scientists detect and understand CH. Instead of focusing only on small mutations, they may also need to look for bigger structural changes in DNA. In the long run, this could improve early detection of blood cancers and help prevent other health problems linked to CH. "

Date of Approval: August 11, 2025
Duration: 2 years (to August 11, 2027)

Computational synthetic lethal analysis of MOHCCN genomic data to expand precision cancer genomic medicine options for glioblastoma multiforme patients

Lead Investigator: Marco Marra
Lead Institutions: Canada’s Michael Smith Genome Sciences Centre, University of British Columbia

Summary:

Today, only a small number of genetic changes found in cancer patients can be matched to drugs. This is especially true for aggressive cancers like glioblastoma, where most patients have no treatment options based on their tumour’s unique genetics.

Our project aims to improve this by finding new ways to match existing drugs to more patients. We use a strategy called synthetic lethality—a situation where two genes, when altered together, can cause cancer cells to die, while healthy cells remain unharmed. To do this, we use a computational tool called GRETTA, developed by our team, to search for these gene pairs using large datasets. GRETTA has already been used to match existing drugs to several cancers based on their unique genetic features. Now, we plan to apply this method to ~120 glioblastoma cases from across Canada, using genetic data from the MOHCCN gold cohort. We’ll computationally search for genetic patterns that may enable an existing drug to kill glioblastoma cells, even if those drugs weren’t originally designed for brain cancer.

In addition to potentially helping patients who currently have few or no treatment options, this project will also test how well different MOHCCN members across Canada can share and use genetic data together to accelerate research. This will strengthen national collaboration in precision medicine and help bring the benefits of this research and others to more Canadians.

Date of Approval: August 11, 2025
Duration: 2 years (to August 11, 2027)

Combined analysis of MOHCCN Gold Cohort and TCGA/ICGC data to Improve Detection of Low-Frequency Cancer Driver Genes

Lead Investigator: Ian Watson
Lead Institution: McGill University Goodman Cancer Institute

Summary:

Cancer is caused by changes in our DNA that allow cells to grow out of control. Some of these changes, called driver mutations, directly contribute to cancer development. Finding these driver mutations helps researchers understand how cancers form and grow and can also guide treatment decisions or lead to new therapies.

Over the past decade, large international research efforts, like The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC), have studied thousands of tumors and successfully identified many common driver mutations in cancer. However, many less common, but still important, driver mutations remain undiscovered. This is especially true in cancers that have many DNA changes, where it becomes harder to tell which mutations are important and which are just “background noise.” A previous study showed that thousands of patient samples are needed to reliably detect these rare drivers.

This project will utilize the MOHCCN Gold Cohort, a growing national resource that includes detailed genetic and clinical data from cancer patients across Canada, to look for these rare driver mutations. We will analyze the complete DNA sequence (whole-genome sequencing) of many tumors to identify genes that are mutated more often than expected by chance. We will also look beyond the parts of DNA that code for proteins, and search for driver mutations in non-coding regions—areas that help regulate genes, but where mutations are harder to study and researchers still don’t have a clear understanding of their function from smaller studies.

Importantly, we will combine different types of data to improve the accuracy of our results. For example, we will use RNA data (which shows which genes are turned on or off in the tumor) to check whether a mutation actually affects gene activity. We will also examine whether certain mutations are paired with losses of other parts of the genome, which is a pattern often seen in important genes that play a role in suppressing tumor formation. Finally, we will compare our findings to large experimental datasets that show which genes are essential for cancer cell survival, helping us focus on mutations that are most likely to matter.

The goal of this work is twofold: first, to discover new cancer driver genes and mutations that could lead to better diagnostics or therapies in the future, and second, to demonstrate that sharing and analyzing data across cancer centers in Canada through the MOHCCN platform is both feasible and scientifically valuable.

In the long run, this project could help identify new targets for therapy, improve how we diagnose and classify cancers, and contribute to more personalized care for cancer patients. It will also help build Canada’s capacity to do large-scale, collaborative cancer research that benefits patients nationwide.

Date of Approval: August 11, 2025
Duration: 2 years (to August 11, 2027)