February 5, 2020

Unraveling the story behind the cancers we can’t explain

Dr. Philip Awadalla
Dr. Philip Awadalla

The Pan-Cancer Analysis of Whole Genomes Project has shown that despite cancer’s complexities, researchers are close to cataloguing all of the biological mechanisms that lead to the disease.

Today, Nature released a special collection of 23 publications related to the analysis, one of which presents the most comprehensive catalogue of RNA alterations in cancer to date.

We sat down with Dr. Philip Awadalla, OICR investigator and National Scientific Director of the Canadian Partnership for Tomorrow Project, and Dr. Fabien Lamaze, Postdoctoral Fellow in the Awadalla Lab, to discuss.

What can RNA show us about cancer?

PA: Cancer is thought to be a disease of the genome, where changes – or mutations – in an individual’s DNA accumulate and eventually lead to the development of the disease. Often, we can identify the mutations that drive this development, figure out the related mechanisms and design new therapies with that information, but sometimes no such ‘driver mutation’ exists.

We believe that RNA can help us unravel the story behind these cancers that we can’t yet explain.

What did the study find?

Dr. Fabien Lamaze
Dr. Fabien Lamaze

FL: In this study, we took a deep dive into the transcriptome – the RNA – of nearly two thousand tumour samples donated by patients from around the world, representing 27 different types of tumours. The group found more than 1.5 million different RNA alterations and related mechanisms in these samples, exposing the true complexity of the disease.

Interestingly, the study found key RNA alterations in patient samples with no DNA driver mutation. This suggests that some of the cellular changes that lead to cancer may manifest in RNA rather than DNA mutations.

What does this mean for the future of cancer research?

PA: We see that cancer is complex and we need even more data to fully understand it, but we’ve also shown that we can make this happen by working together.

FL: The Pan-Cancer Analysis of Whole Genomes Project was the product of an enormous international study that was only made possible by the dedication and true collaboration between thousands of researchers from around the world. For this study, in particular, I’d like to recognize the scientific leadership of Dr. Angela Brooks and collaborators from the University of California, Santa Cruz.

PA: As more patient samples are collected and sequenced, we look forward to using the software tools and infrastructure from the Pan-Cancer Project to gain further insights into cancer biology.

How can this help cancer patients?

FL: Understanding the changes that lead to cancer can help us design better tests and new treatments for future cancer patients. This study, for example, discovered six interesting gene fusions involved with cancer, where two genes come together, join in an abnormal way and wreak havoc. In the future, we could potentially develop new drugs that target the downstream products of these fusions and stop them from causing further damage in the cell.

PA: With the knowledge we’ve gained in this study, we look forward to furthering diagnostic and therapeutic research and development so we can ultimately treat patients more successfully. Work is already underway to make this happen.


Related links

February 5, 2020

Discovering cancer’s vulnerabilities: The whole may be greater than the sum of its parts

OICR and Pan-Cancer Project researchers map key cancer pathways, signposting new directions for its diagnosis and treatment

What works in a lab experiment doesn’t always work in the complex human body. But as technology advances, researchers are gaining the ability to study different features of a cancer cell and the interactions, mechanisms and pathways between them. As more data become available, however, it is becoming increasingly difficult to find the most important molecular pathways that, when blocked, can stop the progression of the disease.

Dr. Jüri Reimand’s lab specializes in this area.

“Researchers often collect molecular data on one aspect of a cancer cell at a time, like its DNA, RNA or proteins,” says Reimand, who is an OICR Investigator. “If we can weave these complex molecular datasets together into a bigger picture, we can gain a more thorough understanding of cancer and potentially find new ways to tackle the driving mechanisms behind the disease.”


Decoding the donors’ data

Thanks to more than 2,500 patient donors from around the world, the Pan-Cancer Project presented one of the largest cancer datasets to date. The Project made hundreds of terabytes of data available to the global cancer research community in a coordinated effort to advance our understanding of the disease.

To help interpret these data, the Reimand Lab developed ActivePathways – a statistical method that can discover significant pathways across multiple molecular omics datasets. These methods, published today in Nature Communications, allow researchers to characterize the cell at a systems-level, decipher how the components interact and tease out the most important pathways.

“We designed a simplified approach to tackle one of the largest cancer genomics datasets to date,” says Reimand. “With these methods we can now chart important interactions that we wouldn’t have recognized by looking at one component or dataset alone.”


The power of the ensemble

The Reimand Lab teamed up with researchers in Belgium, Norway, Spain, Switzerland and across the U.S. who were also interested in analyzing the important pathways within the Pan-Cancer Project dataset. They combined their methods and expertise and identified nearly 200 important driver pathways across 38 different cancer types.

Their findings showed that cancer cells often have related or coordinated mutations in the coding regions and the non-coding regions of the genome.

Now, we have better methods and stronger evidence to move forward as we investigate how to block these pathways, and further, block the progression of the disease.
– Dr. Jüri Reimand

“Together, we came to a consensus list of frequently mutated molecular pathways, processes and target genes,” says Reimand. “Now, we have better methods and stronger evidence to move forward as we investigate how to block these pathways, and further, block the progression of the disease.”

All tools, methods and data related to the collaboration are freely available for the research community to use for future research.

“We’re proud of this progress,” says Reimand. “We look forward to the future research that will build on these findings towards better cancer diagnostic tests and treatment options.”


Related links

January 20, 2020

New tumour-driving mutations discovered in the under-explored regions of the cancer genome

Dr. Jüri Reimand, OICR Investigator and lead author of the study.

OICR researchers identify novel causes of cancer progression in the non-coding genome, opening new lines of investigation for several cancer types

Toronto – (January 20, 2020) In an unprecedented pan-cancer analysis of whole genomes, researchers at the Ontario Institute for Cancer Research (OICR) have discovered new regions of non-coding DNA that, when altered, may lead to cancer growth and progression.

The study, recently published in Molecular Cell, reveals novel mechanisms of disease progression that could lead to new avenues of research and ultimately to better diagnostic tests and precision therapies.

Although previous studies have focused on the two per cent of the genome that codes for proteins, known as genes, this study analyzed mutation patterns within the vast non-coding regions of human DNA that control how and when genes are activated.

We found evidence of new molecular mechanisms that may cause cancer and give rise to more-aggressive tumours.

“Cancer-driver mutations are relatively rare in these large non-coding regions that often lie far from genes, presenting major challenges for systematic data analysis,” says Dr. Jüri Reimand, investigator at OICR and lead author of the study. “Powered by novel statistical tools and whole genome sequencing data from more than 1,800 patients, we found evidence of new molecular mechanisms that may cause cancer and give rise to more-aggressive tumours.”

The research group analyzed more than 100,000 sections of each patient’s genome, focusing on the often-overlooked non-coding regions that interact with genes through the three-dimensional genome. One of the 30 key regions discovered was predicted to have a significant role in regulating a known anti-tumour gene in cancer cells, despite being more than 250,000 base pairs away from the gene in the genome. The group performed CRISPR-Cas9 genome editing and functional experiments in human cell lines to explore the cancer-driving properties of this non-coding region.

“We characterized several non-coding regions potentially involved in oncogenesis, but we’ve just scratched the surface,” says Reimand. “With our algorithms and the rapidly growing datasets of patient cancer genomes and epigenetic profiles, we look forward to enabling future discoveries that could lead to new ways to predict how a patient’s cancer will progress and ultimately new ways to target a patient’s disease or diagnose it more precisely.”

Reimand’s research group developed the statistical methods behind this study and made them freely available for the research community to use. These methods have been rigorously tested against other algorithms from around the world.

We’ve shown that our method, called ActiveDriverWGS, can excavate these regions and pinpoint specific areas that are important to cancer growth.

“Looking into the non-coding genome is really important because these vast sections regulate our genes and can switch them on and off. Mutations in these regions can cause these regulatory switches to act abnormally and potentially cause – or advance – cancer,” says Helen Zhu, student at OICR and co-first author of the study. “We’ve shown that our method, called ActiveDriverWGS, can excavate these regions and pinpoint specific areas that are important to cancer growth.”

“Although these candidate driver mutations are rare, we now have the first experimental evidence that one of the mutated regions regulates cancer genes and pathways in human cell lines,” says Dr. Liis Uusküla-Reimand, Research Associate at The Hospital for Sick Children (SickKids) and co-first author of the study. “As the research community collects more data, we plan to look deeper into these regions to understand how the mutations alter gene regulation and chromatin architecture in specific cancer types to enable the development of new precision therapies to patients with these diseases.”

This study was supported by OICR through funding provided by the Government of Ontario, and by the Canadian Institutes of Health Research (CIHR), the Cancer Research Society (CRS), the Estonian Research Council, and the Natural Sciences and Engineering Research Council of Canada (NSERC).

Whole genome sequencing data used in this study was made available by the International Cancer Genome Consortium’s Pan-cancer Analysis of Whole Genomes Project (ICGC PCAWG), also known as the PCAWG Project or the Pan-Cancer Project.

January 10, 2020

New open-source software judges accuracy of algorithms that predict tumour evolution

Adriana Salcedo
Adriana Salcedo

OICR-led international research group develops new open-source software to determine the accuracy of computational methods that can map the genetic history of tumour cells.

A cancer patient’s tumour is often made up of many cells with different genetic traits that can evolve over time. Interest in tumour evolution has grown over the last decade, giving rise to several new computational tools and algorithms that can characterize genetic diversity within a tumour, and infer patterns in how tumours evolve. However, to date there has been no standard way to compare these tools and determine which are most accurate at deciphering these data.

The genetic differences between tumour cells can tell us a lot about a patient’s disease and how it evolves over time – Adriana Salcedo

In a study recently published in Nature Biotechnology, an OICR-led international research group released new open-source software that can be used to judge the accuracy of these novel algorithms.

Continue reading – New open-source software judges accuracy of algorithms that predict tumour evolution

October 9, 2019

Researchers discover a new cancer-driving mutation in the “dark matter” of the cancer genome

Change in just one letter of DNA code in a gene conserved through generations of evolution can cause multiple types of cancer

Toronto – (October 9, 2019) An Ontario-led research group has discovered a novel cancer-driving mutation in the vast non-coding regions of the human cancer genome, also known as the “dark matter” of human cancer DNA.

The mutation, as described in two related studies published in Nature on October 9, 2019, represents a new potential therapeutic target for several types of cancer including brain, liver and blood cancer. This target could be used to develop novel treatments for patients with these difficult-to-treat diseases.

“Non-coding DNA, which makes up 98 per cent of the genome, is notoriously difficult to study and is often overlooked since it does not code for proteins,” says Dr. Lincoln Stein, co-lead of the studies and Head of Adaptive Oncology at the Ontario Institute for Cancer Research (OICR). “By carefully analyzing these regions, we have discovered a change in one letter of the DNA code that can drive multiple types of cancer. In turn, we’ve found a new cancer mechanism that we can target to tackle the disease.”

Continue reading – Researchers discover a new cancer-driving mutation in the “dark matter” of the cancer genome

July 29, 2019

Computational dissection: What can we learn from the cells around cancer cells?

OICR researcher looks into what non-tumour cells can tell us about breast cancer

Natalie Fox
Natalie Fox, OICR

When a biopsy is drawn from a patient, it consists of a mix of cancerous and healthy cells, like fat and blood cells. Researchers are often interested in diseased cells, but without looking into the surrounding tissue, they could be missing part of the story.

Natalie Fox, a PhD candidate at OICR, is investigating what we can learn from the cells surrounding cancer cells.

“When we look into a patient sample computationally, we see distorted signals because of overlapping data from many different types of cells,” says Fox. “We need to dissect the parts we want to study, but instead of using a knife or a laser, we use computers.”

Fox and collaborators have analyzed nearly 1800 tumour samples from patients with breast cancer, examining the transcriptome of tumour cells and the cells around tumours – or the tumour’s microenvironment.

Her study, recently published in Nature Communications, reveals the landscape of transcriptomic interactions between breast cancers and their microenvironments. Her study also sheds light on associations between these transcriptomes and patient survival, gene mutations and breast cancer subtypes.

“We now have a clearer picture that tells us more about the breast microenvironment than we’ve known before,” Fox says. “Bit by bit, we’ve analyzed and scrutinized these data, then assembled these bits into a comprehensive landscape.”

Fox found that mutations in cancer genes such as CDH1 and TP53 are associated with changes in the transcriptome of the tumour’s microenvironment. She says more research is needed to clarify the biologic rationale behind her observations, but her work has set the stage for researchers to do so.

“Above all else, this work demonstrates an important approach for improving our understanding of associations between the tumour and the microenvironment,” Fox says. “We presented a framework that others can use to analyze the tumour microenvironment in their cancer of interest and potentially develop new biomarkers for predicting cancer patient outcomes.”

July 23, 2019

Blood samples, biostatistics and a fresh perspective: The makings of a cancer prediction machine

Jordyn Walton and David Soave
Jordyn Walton and Dr. David Soave

Biostatistics Training Initiative (BTI) alumnus brings on new BTI trainee to study Canada’s largest population health dataset using today’s top technologies

Recently, circulating tumour DNA (ctDNA) – DNA released from cancer cells that freely circulates in the blood – has garnered much attention not only as an alternative to traditional tissue biopsies, but as a potential blood-based biomarker for early cancer diagnosis.

The ability to detect the earliest blood-borne traces of cancer largely rests in our ability to determine which molecular markers indicate that a cancer is developing – or which patterns in ctDNA can predict whether a cancer will grow. Dr. David Soave sees this as a mathematical challenge that, if solved, could have huge impact for better predicting and diagnosing a wide variety of cancers.

“To find cancer earlier or predict who will develop the disease, we need to carefully compare human samples from those who will develop cancer and samples from those who won’t,” Soave, an Assistant Professor at Wilfrid Laurier University and OICR Associate, says. “This type of challenge requires new statistical models, methods and computational techniques that can decipher large, complex and high-dimensional data.”

Last year, the Canadian Partnership for Tomorrow Project (CPTP) unified the data from several provincial longitudinal health studies into a national cohort consisting of more than 325,000 participants who are voluntarily donating their health and biologic samples to research. As some CPTP participants will develop disease and others will not, this dataset provides an unprecedented resource for researchers like Soave to discover the earliest traces of cancer that appear several months to years prior to an initial diagnosis.

Continue reading – Blood samples, biostatistics and a fresh perspective: The makings of a cancer prediction machine

May 31, 2019

Q&A with Dr. Trevor Pugh, OICR’s new Director of Genomics

Trevor Pugh
Dr. Trevor Pugh

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

Trevor Pugh

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.

February 25, 2019

Europe and Canada build secure and efficient network to share genomic and health data

Dr. Lincoln Stein, Head, Adaptive Oncology, OICR.
Dr. Lincoln Stein, Head, Adaptive Oncology, OICR.

The Global Alliance for Genomics and Health introduces the European-CANadian Cancer network as one of seven new global Driver Projects

The rapid realization of precision medicine in oncology depends on the cancer research community’s ability to collaborate effectively. For genomics researchers, this means having the necessary computational tools and infrastructure to generate and share data.

Now, a new international initiative called The European-CANadian Cancer network (EUCANCan) has set out to align infrastructure across continents for the efficient analysis, management and sharing of cancer genomic and clinical data. On February 4, The Global Alliance for Genomics and Health (GA4GH) announced that EUCANCan has been named one of seven new GA4GH Driver Projects. 

“Our goal is to enable clinicians and researchers to exchange cancer data in a way that promotes effective analysis of this data while protecting patient privacy,” says Dr. Lincoln Stein, Head of Adaptive Oncology at OICR and leader of EUCANCan’s Toronto node. “With this network, we will be able to accelerate cancer genomics research on a global scale, and in turn, drive cancer discoveries that will lead to improved diagnostics and therapies.”

EUCANCan will realize its mission by uniting groups from Germany, the Netherlands, France, Spain and Canada into a federated network. The network will help define community standards for data formats, harmonize methods to interpret genomic data, and generate strategies to manage, store and distribute data across national borders.

As one of GA4GH’s new Driver Projects, EUCANCan aims to enrich collaborations between Canadian and European genomics groups while serving the greater global research community. The Toronto node, based at OICR, will be leading the development of an open and accessible data portal to allow the research community to search, download, and analyze EUCANCan data locally and in the compute cloud.

“Together, the new Driver Projects significantly expand GA4GH’s global representation, strengthening our collaborations across Africa and Europe, as well as in Japan, and adding connections in 31 countries for a total global reach across more than 100 countries worldwide,” says GA4GH CEO Peter Goodhand.

 “The new Driver Projects join a community that is building the standards and frameworks that will guide the field for years to come,” says Dr. David Altshuler, Founding Chair of GA4GH.

Read more about the 2019 Driver Projects here.

September 25, 2018

Breast cancer radiotherapy in a single visit provides more convenient option to patients, reduces burden of therapy

Seeds used in radiation therapy are shown, along with a penny to provide scale.

Cross-Canada research team moves image-guided ultrasound system into clinical development

Traditional breast cancer radiation treatment requires multiple hospital visits over a period of weeks or months, which may be onerous to patients who live far from hospitals or in remote communities. An alternative radiotherapy technique, Permanent Breast Seed Implantation (PBSI), requires only a single hospital visit, but it involves the implantation of multiple small radioactive metal pellets into the breast of the patient within millimetres of a target. The procedure to administer this treatment is difficult to plan and complex to execute – impeding the adoption of PBSI in the clinic.

Continue reading – Breast cancer radiotherapy in a single visit provides more convenient option to patients, reduces burden of therapy

September 24, 2018

Breaking down barriers to translation: A case of standardization in digital pathology

Jane Bayani In the lab.

OICR takes part in international multicentre study to standardize promising breast cancer digital pathology test

The Ki67 immunohistochemistry assay is a test that can help evaluate the aggressiveness of breast tumours, predict disease outcomes, monitor cancer progression and identify patients who are more likely to respond to a given therapy. Despite its potential to help patients with breast cancer, the analysis of Ki67 has not been widely adopted in the clinic, mostly due to the lack of standardization across laboratories.

Continue reading – Breaking down barriers to translation: A case of standardization in digital pathology

September 13, 2018

Using imaging to better detect, characterize and monitor prostate cancers

Justin Lau

Sunnybrook researchers develop new magnetic resonance imaging methods to help differentiate between aggressive and non-aggressive prostate cancers

Current needle biopsy techniques have limited accuracy in detecting prostate cancer and determining the tumour’s aggressiveness. New methods are needed to better detect and characterize prostate cancer so that each patient can get the treatment that is most appropriate for them.

Continue reading – Using imaging to better detect, characterize and monitor prostate cancers

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