October 4, 2019
OICR is proud to announce two new partnerships between research trainees in Ontario and collaborators in Israel, supported by Joseph and Wolf Lebovic.
The Joseph and Wolf Lebovic Fellowship Program, a joint initiative between the Hebrew University of Jerusalem’s Institute for Medical Research Israel-Canada (IMRIC) and OICR, is supporting two new partnerships between local cancer researchers and those in Israel.
This is the second round of this fellowship program that aims to strengthen collaboration across the two countries by pairing trainees in complementary areas of expertise. Both projects focus on the interaction between tumours and the immune system to develop new and more effective therapeutic strategies for cancer.
Over the next two years, the new fellows will develop their mutually-beneficial partnerships, allowing them to further their research while building their collaboration skills.
“We are investing in talented trainees with the potential to make a significant impact in cancer research, while fostering international collaboration,” says Dr. Laszlo Radvanyi, President and Scientific Director of OICR. “We cannot wait to see what they will accomplish in the years to come.”
Teaming up to take on a new approach
Principal Investigator in Israel: Dr. Lior Nissim, Assistant Professor at IMRIC
Fellow: Natella Buketov, Master of Science student at IMRIC
Principal Investigator in Ontario: Dr. Samuel Workenhe, Assistant Professor at McMaster University
Fellow: Jeffrey Wei, Master of Science student at McMaster University
Developing viruses that alarm the immune system to fight against cancer is a sought after goal around the world. A common challenge with this approach is that cancer cells can often “shut off” or silence these alarms, and thus, the cancer cells remain undetectable to the immune system.
Workenhe and Nissim hypothesize that synthetic molecules – sequences of DNA that cannot be found in nature – could be used to overcome this challenge and effectively trigger an immune response against cancer cells.
Through the Lebovic Fellowship, these two research groups have teamed up to explore the possibility of using viruses, developed by the Workenhe Lab, to deliver synthetic molecules, developed by the Nissim Lab, to cancer cells. Over the next two years, they will work to optimize their platforms, develop the viruses and test them in infected cell cultures and tumour-bearing mice.
“There’s a lot of drive behind this project,” says Workenhe. “We both want to find a way to make this work and overcome the challenges of viral immunotherapies together.”
Partnering to accelerate research
Principal Investigator in Israel: Dr. Sheera Adar, Senior Lecturer at IMRIC
Fellow: Dr. Pooja Chauhan, Postdoctoral Fellow at IMRIC
Principal Investigator in Ontario: Dr. Carolina Ilkow, Scientist at the Ottawa Hospital Research Institute and Assistant Professor at the University of Ottawa
Fellow: Emily Brown, Master of Science student at Ottawa Hospital Research Institute and the University of Ottawa
The Adar Lab and the Ilkow Lab are both interested in the SWI/SNF complex – a cellular machine that affects how our DNA is packaged and coiled.
The Adar Lab is working to better understand how SWI/SNF affects DNA damage repair in cancer cells. The Ilkow Lab is working to better understand how SWI/SNF can be altered to improve immunotherapies. They recognized that they can study SWI/SNF better together.
With the support of the Lebovic Fellowship, these groups are partnering to investigate SWI/SNF with two different approaches while sharing common methods, resources and expertise. By doing so, the researchers expect to reduce duplicative efforts and accelerate both projects. “I’m excited to be involved in the field of cancer immunotherapy,” says Brown. “Seeing that your work has direct impact is really rewarding, and I’m excited to help contribute to such an innovative approach.”
September 3, 2019
OICR is proud to welcome Dr. Parisa Shooshtari as an OICR Investigator.
Shooshtari specializes in developing computational, statistical and machine learning methods to understand the biological mechanisms underlying complex diseases, like cancer and autoimmune conditions. She is interested in uncovering how genes are dysregulated in complex diseases by integrating multiple data types and applying machine learning methods to analyze single-sell sequencing data.
Of her many achievements, Shooshtari developed a computational pipeline to uniformly process more than 800 epigenomic data samples from different international consortia. She then built and led a team that developed a web-interface and an interactive genome-browser to make the database publicly available to download and explore.
Shooshtari joins the OICR community with research experience from Yale University and the Broad Institute of MIT and Harvard. She also served as a Research Associate with the Centre for Computational Medicine at the Hospital for Sick Children (SickKids).
Shooshtari recently became an Assistant Professor in the Schulich School of Medicine and Dentistry at Western University, where she officially began her career as an independent researcher. Here, Shooshtari discusses her commitment to collaboration and her transition to professorship.
Your work spans multiple disease areas from autoimmune diseases to cancer, what do these diseases have in common? Is there a specific disease that you’re more interested in?
My work focuses on complex diseases, where instead of one gene causing the disease, there are sometimes tens or hundreds of genes working together to give rise to an ailment.
When it comes to complex diseases, we also know that there are multiple factors that we need to consider, including genetics, epigenetics and environmental factors. We live in an era where we have rich datasets with many different types of data. Each of these data types sheds light upon a different aspect of the disease mechanism, but we need to integrate these data types to gain a comprehensive understanding of how a complex disease works.
I develop computational methods for integrative analysis, so complex diseases are definitely the most interesting to me. I feel lucky to be a researcher at this time when I can help bring these data types together to understand mechanisms of diseases, which in turn will help inform treatment selection or help find new therapeutic strategies.
I am interested in applying our data integration methods to several complex diseases but I am currently working with a few Canadian groups to help better understand Diffuse Intrinsic Pontine Glioma (DIPG) – a type of fatal childhood brain cancer.
Your current collaborators include researchers from Yale, Harvard, MIT, SickKids and other leading organizations. How did you initiate and sustain these collaborations?
At the beginning of my research career, I would reach out to scientists who were working on interesting, challenging and cutting-edge problems. I enjoy working in collaborative environments because I believe the key to success in biomedical research is through collaborations between researchers from diverse backgrounds.
With the support of my collaborators, I’ve been able to learn and shift my focus from theoretical computational sciences to applications of data science in genetics of complex diseases. Now, sometimes collaborators approach me with their rich data, which I’m eager to help analyze.
With your new appointment, what are you looking forward to over the next few years?
I am eager to continue expanding my research program and working with new scientists on exciting cutting-edge problems in genetics and epigenetics of complex diseases. New technologies have revolutionized how we study diseases, and we are transitioning to a point where these new technologies are revolutionizing how we treat diseases. I am confident that we will have better ways of treating these diseases in the future using personalized medicine, and I want to help make that a reality.
July 30, 2019
Genome Canada, Ontario Institute for Cancer Research and Thermo Fisher Scientific to focus on pancreatic, prostate and breast cancer
CARLSBAD, Calif. – (July 30, 2019) – Genome Canada, the Ontario Institute for Cancer Research (OICR) and Thermo Fisher Scientific are collaborating to develop a complete solution of targeted next generation sequencing (NGS) assays and analysis software designed to more effectively assess – and eventually improve management of – pancreatic, prostate and breast cancer.
The $6 million, three-year initiative aims to standardize advanced molecular profiling in these disease areas and make the assays commercially available globally. Focusing on rapid genomic diagnostics in pancreatic cancer and targeting treatment in breast and prostate cancers, the partnership builds on previous clinical research between OICR and Thermo Fisher and will inform development of three assays that will be utilized to stratify patients in clinical trials in Ontario and other jurisdictions.
“By supporting research and clinical trials, Genome Canada is helping to put more of Ontario’s innovative cancer diagnostics research into clinical use,” said Dr. John Bartlett, program director, diagnostic development at OICR. “This project has the potential to springboard advanced next-generation sequencing to routine clinical use in Ontario and across Canada.”
Breast and prostate cancer are among the most common types of cancer in Canada, and the country’s five-year net survival rate for pancreatic cancer is only 8 percent. However, there is clear evidence that patient outcomes can be improved with NGS-based testing strategies. A recent U.S. health economics study has shown that advanced cancer patients who received treatment based on NGS testing results experienced double the length of progression-free survival without increasing health care costs.1
While some solutions analyze only DNA sequences, the new targeted NGS assays will provide comprehensive genomic profiles by simultaneously assessing DNA and expression signatures from RNA to provide significantly more insight into driver mutations. The OICR/Thermo Fisher team will leverage this advantage by supplementing the new assays with unique DNA/RNA stratification biomarkers – specific to pancreatic, prostate and breast cancer – previously qualified by OICR translational researchers.
The collaboration is partly funded with a grant from Genome Canada through the Genomic Applications Partnership Program (GAPP). Genome Canada will contribute $2 million, the highest possible level of funding support, with the balance split between OICR and Thermo Fisher, which will cover development costs and validation activities.
Previous research collaborations led by OICR and Thermo Fisher are already well on their way to impacting cancer treatment in the future. Of particular note is a 2016 study designed to identify mutations and copy number variation changes in breast cancer, and clinical research utilizing the Oncomine Comprehensive Assay, which also supports both the National Cancer Institute’s Adult and Pediatric MATCH trials in the United States.
“OICR is a leader in clinical research, with extensive clinical trials in progress to improve care for patients with pancreatic, prostate and breast cancer,” said Jeff Smith, global lead of NGS precision medicine initiatives, clinical NGS and oncology for Thermo Fisher Scientific. “When OICR approached our team with the idea for this project, we saw it as another exciting for opportunity to bring Thermo Fisher’s proven Ion Torrent technology to clinical laboratories across Canada and to contribute to future improvement of patient care.”
1 “A Retrospective Analysis of Precision Medicine Outcomes in Patients With Advanced Cancer Reveals Improved Progression- Free Survival Without Increased Health Care Costs,” Journal of Oncology Practice, Vol 13, Issue 2, February 2017
May 31, 2019
In May, OICR welcomed Dr. Trevor Pugh as Director of Genomics and Senior Principal Investigator. Trevor is a cancer genomics researcher and board-certified molecular geneticist who has led the Princess Margaret Cancer Centre-OICR Translational Genomics Laboratory (PM-OICR TGL) since 2016.
In his new role, he will lead the OICR Genomics program, which brings together the Princess Margaret Genomics Centre, OICR’s Genome Technologies, Translational Genomics Laboratory and Genome Sequence Informatics teams under an integrated initiative to support basic, translational and clinical research. Here, Pugh describes some of his strategies and how he plans to take on this ambitious mandate.
You’re involved with a number of projects across many disease sites and you collaborate with researchers from vastly different areas of cancer research. Can you summarize what you focus on?
Simply put – I want to use genome technologies to guide the best patient care. The overall philosophy is to extract as much genomic information as we can from small amounts of tumour tissue, and turn that information into knowledge so that clinicians and patients can make targeted treatment decisions. I also want to open up these comprehensive data for researchers to mine and find new cures for these cancers.
Whether they are a graduate student working on myeloma or a postdoc working on liver cancer, we all learn from one another’s disease specialties.
And yes – I am involved with many areas of cancer research. Every member in my lab speaks the same genomics language. Whether they are a graduate student working on myeloma or a postdoc working on liver cancer, we all learn from one another’s disease specialties. We do genomics in a similar way as there are many genomic commonalities across cancer types and computational algorithms or infrastructure we build for one project invariably get reused for another project.
You are a board-certified molecular geneticist and a genomics researcher, but you also have a background in bioinformatics and software development. How do you balance making tools and making discoveries?
The tools we create and the research we perform go hand in hand. You can’t make discoveries without the infrastructure, and it is hard to develop technologies successfully without a guiding scientific question. With that said, the software that we make is designed to help not only our own research and clinical projects, but those of others. If we can make software work for us really well, we want to share it and make it easier for groups and labs across Ontario and around the world. This also holds for the data we generate, as there is great value to integrating our data with similar data sets from other hospitals.
How will this new role help you do that?
I have a few main goals in this role that I’m excited about. The first and the largest is to integrate the Princess Margaret Genomics Centre, PM-OICR TGL, Genome Technologies and Genome Sequence Informatics into one fully-coordinated machine. The people, tools and methods that we have at OICR and Princess Margaret are incredible and the infrastructure already in place can serve as a powerful vehicle for both research and clinical applications. In the first two weeks, I’ve been really impressed with how the leads of these programs have come together to form concrete plans for making this a reality.
The part that excites me about my new role is the O in OICR. Within this position, I can have a provincial outlook on translational research which is important as genomics research becomes increasingly dependent on multi-centre studies and inter-institutional collaborations. I think OICR can help facilitate a future where sharing ideas, data, and knowledge between institutions is much easier than it is today. I’m excited to help take things that work locally and make them available and easy-to-use across the entire province, so that we can benefit from the advances made by our neighbours. We are stronger when we work together in a collaborative way.
OICR is well-known as a developer of similar high-quality data sharing systems and I am looking forward to integrating these efforts to support our internal genomics enterprise
It sounds like a lot of your work addresses local needs, but how do you have so many international collaborations?
In computational biology, a lot of our concerns and challenges are shared with other groups as well. For example, the cBioPortal data sharing platform was originally built at Memorial-Sloan Kettering to allow researchers to easily query data from The Cancer Genome Atlas project. This initiative soon grew to include a team at Dana-Faber and now the software is fully open-source with five core, NIH-funded teams contributing to its development, including my own lab. In addition, there are groups working on improving and enhancing cBioPortal instances around the world as it expands to new applications beyond genomics. cBioPortal has emerged as a very powerful resource rooted in an international crowdsourcing model. Naturally, OICR is well-known as a developer of similar high-quality data sharing systems and I am looking forward to integrating these efforts to support our internal genomics enterprise, as well as national and international data sharing networks.
You’ve been involved with the evolution of genomics over the last two decades. What technologies excite you these days?
Hands down, it’s single cell sequencing. This is an amazing technology that allows us to see parts of the tumours that we could never see before. In one of my projects, we’re looking at each cancer population within a tumour sample and mapping each population to a drug treatment. With Drs. Benjamin Haibe-Kains, we’re applying this concept across hundreds of thousands of cells from brain tumours we have sequenced in collaboration with Peter Dirks and from myeloma cells with Suzanne Trudel. If we can find distinct clones – or types of cells – with tailored treatment options, we could potentially eradicate the cancer entirely using combination therapies. I think the future of precision medicine is dependent on single cell technology and I look forward to integrating this technology into clinical studies with collaborators at cancer centres across the province.
May 30, 2019
Meta-analysis of 1,200 patients with pancreatic cancer reveals a new way to identify those with very aggressive tumours who may benefit from alternate treatment approaches
Only half of pancreatic cancer patients who undergo standard chemotherapy and surgery live a year after their initial diagnosis. In the face of these dismal statistics, patients are faced with the challenge of deciding whether they want to proceed with treatment that may have unpleasant side effects. If clinicians could identify patients who would not benefit from standard therapies, they could help these patients make more informed treatment decisions or recommend alternative palliative treatment approaches.
As part of OICR’s Pancreatic Cancer Translational Research Initiative (PanCuRx) team led by Dr. Steven Gallinger, Dr. Benjamin Haibe-Kains recognized that computational modeling can be used to help inform these decisions, but to design a robust predictive model he would need much more data than any individual study had ever collected.
Building the data foundations
Haibe-Kains, who is a Senior Scientist at the Princess Margaret Cancer Centre and OICR Associate, began his investigation with a dataset from PanCuRx – the largest collection of genomic and transcriptomic data on primary and metastatic pancreatic tumours to date. He and his lab then incorporated an additional 1,000 cases of pancreatic tumours from studies around the world that had collected both patient samples and information about how each patient responded to treatment.
“The datasets that we aggregated were a mixed bag of different types of data collected through different profiling platforms by different institutions,” says Haibe-Kains. “We took on the challenge of harmonizing the heterogeneity of these resources which nobody else had done.”
Previously, the Haibe-Kains Lab developed a computational method that could make incompatible transcriptomic data compatible. They had used this method to find four new breast cancer biomarkers to predict treatment response and they recognized that they could apply similar methods to harmonize pancreatic cancer data as well.
The dataset resulting from the harmonization is now the largest pancreatic cancer dataset, and Haibe-Kains has made it freely available for other researchers to use and study through the MetaGxPancreas package.
Making a predictive model
Haibe-Kains and his team set out to develop a computational model that could predict if a patient would survive for a year after their biopsy. They used machine learning techniques to exploit their rich dataset, find common patterns in the genomic data of aggressive tumours, and developed PCOSP – the Pancreatic Cancer Overall Survival Predictor.
“Our approach was to look at how one gene was expressed relative to another and relate that to how long a patient lived after biopsy,” says Haibe-Kains. “That may sound simple, but that means dealing with nearly 200 million pairs of genes, which is a significant amount of data to compute.”
As recently described in JCO Clinical Cancer Informatics, the group refined PCOSP using ensemble learning – the combination of several machine learning techniques to improve a model’s accuracy of predictions.
“PCOSP is actually a combination of hundreds of models and not just one,” says Haibe-Kains. “We tested about a thousand models, selected the models that could predict early death very well and combined them to make a stronger classifier.”
Using prediction to power patient decisions
Haibe-Kains says that as the infrastructure for routine sequencing progresses, PCOSP can be translated into clinical practice to help clinicians determine which patients would not benefit from standard treatment and which may benefit from alternative treatment approaches.
“Pancreatic cancer is a challenging disease but if we can predict the course of the disease, we can give clinicians and patients more information. With that information, they can make more personalized decisions to improve their treatment and ideally, their lives.”
January 10, 2019
Capital leverages Ontario’s strengths in genomics and informatics, deepens FACIT’s tech portfolioContinue reading – FACIT makes follow-on investment in AI-based genomics company, DNAstack
December 17, 2018
Large-scale genomic study discovers 40 new genetic variants associated with colorectal cancer risk
The most comprehensive genome-wide association study of colorectal cancer risk to date has discovered 40 new genetic variants and validated 55 previously identified variants that signal an increased risk of colon cancer. The study, recently published in Nature Genetics, is a product of the world’s largest molecular genetic consortium for colorectal cancer – the Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO) – which was established nearly 10 years ago.Continue reading – When it comes to finding cancer risk, there’s power in numbers
December 13, 2018
What can we gain from looking at the outliers?: An investigation into long and short-term ovarian cancer survivors
Researchers investigate the clinical, molecular and microenvironment factors that contribute to extreme therapy response and resistance in ovarian cancer patients
Some patients with high-grade serous ovarian cancer (HGSOC) respond exceptionally well to therapy, while others experience rapid disease relapse. The mechanisms behind these disparate outcomes are poorly understood, but a group of researchers based at the Princess Margaret Cancer Centre (PM) supported by OICR’s Ovarian Cancer Translational Research Initiative (TRI) are working to change that.Continue reading – What can we gain from looking at the outliers?: An investigation into long and short-term ovarian cancer survivors
November 14, 2018
Researchers find a new way to detect small traces of tumour DNA in blood and determine the tumour’s tissue of origin
A blood sample can be used to detect and monitor certain cancers in select patients, but there are significant technical barriers that prevent the widespread adoption of this “liquid biopsy”. This type of blood test analyzes the rare traces of tumour DNA that are circulating in the blood, but distinguishing tumour DNA from healthy DNA is both difficult and expensive. New methods are needed to improve the accuracy, sensitivity and cost-effectiveness of liquid biopsies so that more patients can benefit from this less-invasive test.
October 2, 2018
OICR researchers uncover sex-linked genetic differences that may be able to predict cancer severity and response to therapy
Cancer differs in males and females but the origins and mechanisms of these sex differences remain unresolved. A better understanding of sex-linked differences in cancer could lead to more accurate tests and treatments that are personalized for patients based on their sex.
September 4, 2018
Meet Dike Aduluso-Nwaobasi, Sarah Donald and Benson Wan. Find out how summer co-op positions affected their career and educational journeys.
August 22, 2018
OICR-developed software tool, Heliotrope, gains attention from the private sector for its potential to analyze large amounts of genomic information and inform clinical decision making