January 8, 2021
Q&A with new OICR Investigator Dr. Shraddha Pai on uncovering the hidden differences between cancers
OICR is proud to welcome Dr. Shraddha Pai to its Computational Biology Program as a Principal Investigator. Here, Pai discusses current challenges in understanding diseases and what motivates her to tackle some of the biggest challenges in biomedical research.
What are some of the research questions you’re interested in?
I’m very driven to understand why different people with the same cancer type, have different outcomes and respond differently to the same treatment. As genomic assays get cheaper, we learn more about molecular interplay in different cells, and our population datasets become larger and mature, we are able to integrate different layers of the genome and cell types, to try to get at this question. For example, we now believe there are four main types of medulloblastoma with different underlying molecular networks and outcomes. This field of research is called ‘precision medicine’: using patient profiles to match them with the most effective treatment. But really this is just a new phrase to describe what doctors have been doing since the dawn of medicine; it just means that now we’re using powerful computers and algorithms to find patterns in much larger and complex genomic datasets. The principle is the same.
As a trainee in Dr. Gary Bader’s group, I led the development of an algorithm that integrates several types of patient data to classify patients by outcome. Our method – called netDx – adapts the idea of recommender systems, used by Netflix and Amazon, to precision medicine. Just as one would ask Netflix to “find movies like this one”, netDx helps identify patients “with a treatment profile like this”. In a benchmark, netDx out-performed most other methods in predicting binary survival in four different types of cancer. Importantly, netDx is interpretable, and recognizes biological concepts like pathways. This makes it a useful tool to get mechanistic insight into why a predictor is doing well, and provides a way to understand the underlying biology and perhaps drive rational drug design.
I also have a special interest in understanding the link between epigenetics and disease, particularly as this pertains to the brain. Epigenetics refer to molecular changes that change how the genome behaves – for example, turning a gene on or off in a given cell type. My own previous research in mental illness has found epigenetic biomarkers related to psychosis, which explain the distinctive features of this condition. The same may be the case in certain types of cancers, particularly those of developmental origin.
How do you plan to unravel these complex layers of biology?
My research program has two main goals. The first is to build models for precision medicine – predicting disease risk, treatment response – starting with population-scale datasets that have several types of patient data. I’m hoping to use existing and emerging data such as UK BioBank, CanPath, ICGC-ARGO and the Terry Fox Research Institutes’ datasets, and ongoing clinical trials, to identify which clinical outcomes are easily amenable to our approaches. The models my group builds will incorporate prior knowledge about genome organization and regulation, so that these are interpretable. For example, we will use epigenomic maps of specific tissue types, or data from single-cell resolution maps, pathway information, to find and organize relevant needles in the genomic haystack. This feature will give us interpretability, which is key to increasing confidence in a model, as well as to improving the understanding of cellular pathways that affect disease and eventual drug development.
My second goal is to understand the epigenomic contributions – particularly developmental changes – to cancer risk, using a combination of molecular biological, genomic and analytic techniques.
As I work toward these goals, I hope to collaborate on complementary projects, such as identifying DNA methylation changes in circulating tumour DNA and improving how we subtype adult tumours. These projects will hopefully lead to new biomarkers, and ultimately improvements to how we diagnose and treat cancer.
Importantly, the software that my team builds will also be openly available to the research community, so others can apply my methods to different types of diseases. I’m excited to get started.
Your work applies beyond cancer. How do you traverse these different disease areas?
The reclassification of disease based on molecular or other biomarkers, and how disease subtype affects risk and treatment response, isn’t unique to cancer – the same research questions extend to other types of disease such as metabolic diseases, autoimmune diseases and mental illness. At the end of the day, we are looking at the same system organized at the molecular, cellular and organ-level, with similar principles of genomic regulation and perhaps similar considerations for drug discovery. Our algorithms are based on these general principles and can therefore be used to answer similar questions for different disease applications, or very different types of cancer. Of course, it’s important to collaborate with teams that have domain expertise to make sure the algorithms are “fine-tuned” for a particular application, and I look forward to benefitting from those partnerships.
What excites you about this type of work?
I’m excited to join a community where basic research is so strongly connected to clinical purpose. Personally, I am very motivated by the prospect of a positive impact on patients within my lifetime and feel that my group’s work is more likely to have a valuable impact in an environment that combines basic and translational research. That said, we’re only just beginning to see the benefits of precision medicine and many challenges remain to bring genomic knowledge into practice. I hope that I can create more useful methods and models for precision medicine and improved clinical decision-making in the coming decade.
I’m especially excited to be at OICR because of the Institute’s access to clinical trials, strong genomics and computational biology program, and pharmacology team. If my group can find promising biomarkers and leads, we can work with OICR collaborators in the Genomics and Drug Discovery groups to move from basic research to application.
December 9, 2020
The tool can accurately distinguish real mutations from sequencing mistakes to improve the early detection of cancer
DNA mutations in cancer cells are caused by different processes, each of which leaves a genetic fingerprint that can provide clues to how the cancer develops. Researchers have now applied this understanding to reduce errors when reading DNA, allowing them to accurately and efficiently detect the smallest traces of mutated cells in the blood.
In a recent publication in Science Advances, an OICR-supported research group outlines a new and improved statistical model to reduce error rates in DNA sequencing data. They demonstrate that their model, called Espresso, outperforms current error suppression methods.
“When we isolate, amplify and try to read the individual building blocks of DNA, we encounter a lot of errors,” says Dr. Sagi Abelson, OICR Investigator, Assistant Professor at the University of Toronto and first author of the publication. “This is a major obstacle. The high error background makes it difficult to pinpoint authentic rare mutations. This is what Espresso aims to solve.”
To build an effective error-suppressing statistical model, the group assessed the different types of errors in their relative genomic contexts across more than 1,000 sequencing samples. Their approach was based on assessing the genetic fingerprints within these samples and mapping them to the regions around the errors to understand if the error was a true mistake, or if it was an important mutation.
“The key advantage of our method is that it allows scientists to read DNA more accurately without the need to duplicate efforts using a set of independent control measurements to estimate error rates,” says Abelson. “This means that researchers can be more efficient with their time and resources. They can do more with less. We’re proud to have developed methods that can make research more practical and simple, but also more effective, efficient and accurate.”
This model is built on Abelson’s prior research published in Nature, which discovered early indicators of acute myeloid leukemia (AML) in the blood up to 10 years before symptoms surfaced. With Espresso, the research group was able to develop and test a new strategy to predict leukemia development, which could predict up to 30 per cent of AML cases years before clinical diagnosis with extremely high specificity. Importantly, this study demonstrated that the risk of developing AML can be measured by looking into only a small number of genomic bases, which suggests a more practical route to clinical testing and implementation.
“This work builds on our prior research, which has shown that we can detect AML earlier than thought possible,” says Dr. John Dick, Senior Scientist at the Princess Margaret Cancer Centre, Co-lead of OICR’s Acute Leukemia Translational Research Initiative and co-senior author of the study. “With these methods, we’ve now shown that we can focus in on specific areas of DNA to detect those early traces of AML with higher accuracy than ever before.”
“These methods are essential to advancing personalized cancer care in practice,” says Dr. Scott Bratman, Senior Scientist at the University Health Network’s Princess Margaret Cancer Centre and co-senior author of the study. “With these tools, we can enable clinicians to treat cancer more effectively, tailor treatment decisions and monitor minimal residual disease. We look forward to furthering our research for patients today and those who will develop cancer in the future.”
December 1, 2020
A national consortium including the Ontario Institute for Cancer Research will expand development of a software platform for genomics and health data and apply it to COVID-19. The $5.1 million project, called COVID Cloud, is co-funded by Canada’s Digital Technology Supercluster and aims to increase Canada’s capacity to harness exponentially growing volumes of genomics and biomedical data to advance precision health. The platform will be used by data scientists and domain experts to help understand, predict, and treat COVID-19 with molecular precision. With a global death count of over 1.4 million people and record numbers of cases nationally, solutions that can help Canada respond to ongoing challenges of the pandemic are urgently needed.
“We are proud to continue to support this consortium’s groundbreaking work through our COVID-19 program,” said Sue Paish, CEO of the Digital Technology Supercluster. “This project shows how Canadian partnerships across multiple organizations and sectors can drive innovation, help us address global health issues, showcase Canadian expertise, and position us well to rebuild and grow our economy.”
The project — a collaboration between BioSymetrics, Centre of Genomics and Policy at McGill University, DNAstack, FACIT, Genome BC, Mannin Research, McMaster University, Microsoft Canada, Ontario Genomics, Ontario Institute for Cancer Research, Roche Canada, Sunnybrook Research Institute, and Vector Institute — brings together Canadian leaders in software engineering, artificial intelligence, cloud computing, genomics, infectious disease, pharmaceuticals, commercialization, and policy. It leverages past work of partners to address needs of infectious disease research with guidance from domain experts.
“Tools that allow us to interrogate SARS-CoV-2 at a molecular level are essential to addressing this global health crisis, both now and in the future,” said Dr. Samira Mubareka, a microbiologist and infectious diseases physician at Sunnybrook, whose team was one of the first in Canada to isolate the novel coronavirus. “The insights we will learn by analysing integrated datasets using technology platforms like COVID Cloud can increase our preparedness for future waves and outbreaks.” Dr. Mubareka will co-chair the project’s translational science efforts along with Dr. Gabriel Musso, Chief Scientific Officer for BioSymetrics. “The infrastructure developed by this initiative will propel collaborative Canadian drug discovery efforts for COVID-19,” said Musso, whose team will lead bioinformatics and computational drug discovery for the project.
A major goal of the project is to make it easy for producers of genomic and health data to share data responsibly over industry standards, and for researchers to harness the collective power of information shared through them. The project deliverables include a suite of software products powered by enterprise-grade implementations of standards developed by Global Alliance for Genomics & Health (GA4GH), protocols that are being designed to facilitate the responsible sharing of genomic and health data, which will help advance precision medicine initiatives around the world.
“The platform is being built on a foundation of open standards that will allow for distributed networks of genomics and biomedical data to be built,” said Dr. Marc Fiume, CEO at DNAstack, whose team will lead software engineering for the project. “We are excited to see these technologies breaking down barriers to data sharing, access, and analysis and create new opportunities for genomics-based discoveries for our partners.”
This project is responding to global demand for highly specialized, scalable, distributed software infrastructure to support collaborative genomics research — a need that has surged since the onset of the COVID-19 pandemic. “COVID-19 has accelerated digital transformation of many industries, especially in healthcare,” said Kevin Peesker, President of Microsoft Canada. “The incredible power of Cloud applied to COVID at scale is expanding development of an information superhighway to securely connect scientists in Canada and around the world to the data and compute power they urgently need to help us overcome one of the greatest global health crises of our time.”
The platform will be used to support a series of projects in partnership with Canadian academic, clinical, and pharmaceutical collaborators, which are being coordinated by Canadian genome centres, Genome British Columbia and Ontario Genomics. These initial projects are being prioritized based on urgency and potential impact on Canada’s response to the COVID-19 pandemic.
“The COVID Cloud is an incredible platform that brings together resources and capacity to enable timely and comprehensive genomic analysis of SARS-CoV-2 for our province and our country,” said Bettina Hamelin, President and CEO of Ontario Genomics, whose team leads the ONCoV Genomics Coalition. “This made-in-Canada solution will immediately accelerate Canada’s response to COVID-19, while being a technological springboard for translating genomic data analysis into actionable medical insights across other disease areas in years to come.”
For more information, visit dnastack.com/solutions/covid-cloud.
November 24, 2020
As records are becoming more accessible and patients are becoming more engaged with their health data, who will make it all make sense?
Cancer patients are becoming increasingly involved with their care decisions and care systems are increasingly providing patients access to their test results, health data and relevant reports. These reports, however, can be dense, technical and confusing, leading to more questions than answers for patients and their caregivers. Dr. Nathan Perlis at the Princess Margaret Cancer Centre is dedicated to bridging this gap between patients and their health information.
“Traditional radiology and pathology reports were designed for a specific reason, to communicate results between experts in the field, from physician to physician,” says Perlis, Staff Urologist in the Department of Surgical Oncology at the Princess Margaret Cancer Centre and Assistant Professor at the University of Toronto. “We can’t expect that traditional forms will communicate information effectively with patients and caregivers. Our team recognized the need to design new documents to convey the most relevant information for patients in an easy-to-understand way.”
Perlis and collaborators – including OICR and Sinai Health’s Dr. Masoom Haider, UHN’s Healthcare Human Factors team and a group of patient partners – decided to address a key report used in making prostate cancer treatment decisions – the prostate magnetic resonance imaging (MRI) radiology report.
“Unlike a blood pressure measurement or a fever, prostate MRI results are difficult to interpret,” says Perlis. “This can cause unnecessary anxiety and confusion and barriers between patients and their care team. Our new patient-centred design addresses these concerns, providing a steppingstone for further discussion between patients and their clinicians.”
The team recently published their patient-centred radiology report design, coined PACERR, in the Canadian Urological Association Journal. Their design includes key elements including diagrams, a legend and a glossary to help make the MRI results more understandable. All elements of the form – including the format, layout and the language – were developed and evaluated in partnership with patients and caregivers. The group is now evaluating the form in a clinical trial.
In parallel, the group has recognized a key barrier to implementing these forms in practice. Creating these forms would significantly add to the reporting burden on radiologists. Perlis and collaborators have now set out to create a software package that can read a traditional standard report and automatically complete a tailored patient-centred report. As they develop this software, they hope to apply their learnings to other types of reports across different cancer types.
“Patient-centred communication tools are necessary for shared decision-making,” say Perlis. “We can imagine a future where patients are truly enabled and engaged in their health decisions and this work is a purposeful step toward that goal.”
This research was funded in part by OICR’s Investigator Awards Program.
November 13, 2020
Research team develops a Google maps-like algorithm to pinpoint when cancer patients may diverge from the standard course of treatment
Every cancer patient’s experience is unique but there are standard sequences of steps that help patients and their care teams navigate through screening, diagnosis, treatment and monitoring. These steps are published in pathway maps but are these maps followed in practice? Researchers supported by OICR’s Health Services Research Network, led by Drs. Timothy Chan and Claire Holloway, are working to answer that question.
Chan and collaborators at Ontario Health have developed new methods to measure the difference between a standard clinical pathway map and the actual care that a patient receives in practice. They leveraged real-world health data from Ontario patients to develop these methods, which could potentially be used to identify targets for quality-improvement initiatives.
“Pathway maps help optimize patient survival, healthcare costs and wait times at a population level,” says Holloway, co-principal investigator of the project and Provincial Clinical Lead of Disease Pathway Management (DPM) at Ontario Health.
“We have now derived a way to measure the alignment between actual care and the care described in a pathway map, analogous to measuring how a driver’s route differs from the Google Maps-suggested route,” says Chan, co-principal investigator of the project, Professor at the University of Toronto and Canada Research Chair in Novel Optimization and Analytics in Health.
To address this challenge, the team based their algorithm on an inverse optimization framework, a type of framework used to solve problems across a variety of disciplines, including telecommunications routing, medical radiation therapy planning, and investment portfolio management.
The research team first applied their methods to stage III colon cancer patient data and is now applying their methods to breast cancer care. The ultimate goal would be to use these methods across different cancer sites and potentially different diseases to help promote and implement best practices along the care continuum in Ontario’s healthcare system.
“We’re proud to apply our framework at a large scale to help provide meaningful quantitative measures of system efficiency and variation,” says Chan. “It’s exciting to see that these methods could allow Ontario Health to monitor and evaluate complex practice patterns at a population level.”
“Variations between a patient’s experience and the standard clinical pathway map isn’t necessarily a bad thing but it may prompt us to investigate further,” says Dr. Katharina Forster, Team Lead of DPM at Ontario Health. “We can look into why, when and where the variation is occurring. In this way these new methods and tools are allowing us to generate hypotheses about the causes of variation so we can better understand our care practices, make data-driven decisions and ultimately improve our cancer care system.”
“Ultimately, we’re looking to measure, monitor and improve our system across the province,” says Holloway. “Our rich data in Ontario and our capabilities in machine learning are outstanding. Thanks to OICR, we can bring these disciplines together to make a positive impact on our health system.”
The Health Services Research Network is co-funded by OICR and Cancer Care Ontario, now part of Ontario Health.
October 23, 2020
This year, more than 5,700 people with cancer received innovative treatments or interventions through participating in clinical trials supported by the Canadian Cancer Clinical Trials Network (3CTN). Today, 3CTN has published their 2019-2020 Annual Report, highlighting their progress made towards enhancing the impact of academic cancer clinical trials across Canada. The report marks the midpoint of their strategic plan for 2018-2022.
Highlights of the report include feature articles on:
- How 3CTN has boosted recruitment for their supported trials by nearly 130 per cent, surpassing all expectations and targets;
- New Network initiatives such as improving trial options for children and people outside of urban areas;
- The tools and technologies that are streamlining and standardizing clinical trial management;
- The patient representatives who play a key role in the success of the Network.
October 7, 2020
Vivian talks about the research that OICR is doing during COVID-19 and the kinds of safety precautions that OICR is taking.
September 21, 2020
Q&A with new OICR Investigator Dr. Anastasia Tikhonova on tackling cancer cell cross-talk and adapting in a rapidly evolving field
OICR welcomes Dr. Anastasia Tikhonova to Toronto as an OICR Investigator and Scientist at the Princess Margaret Cancer Centre
The pandemic has compelled many people to adapt, and researchers are no exception. For Dr. Anastasia Tikhonova, adapting has always been an essential part of her career.
Tikhonova recently joined the OICR community as an OICR Investigator working at the Princess Margaret Cancer Centre. Her research focuses on hematological malignancies – or blood cancers – and how the environment around these cells can regulate their growth or help them resist standard treatments. Her research in this area will support the development of new cancer therapies that can ultimately help patients live longer and healthier lives.
Here, she describes her research program and why this community is a great place for her.
What is your research all about?
AT: Cancer cells do not exist in isolation. They are surrounded – and influenced – by their healthy neighbouring cells. For a long time, we didn’t fully understand the interactions between a cancer cell and its surrounding environment and how this dialogue impacts tumour growth. The last five years have significantly advanced imaging and genomic technologies that allow us to precisely decode the cross-talk between diseased cells and their environment – or their niche.
This is what my research is all about. My team uses single-cell transcriptomics, high-resolution imaging, and functional genomics to understand the connection between the complex elements in the bone marrow and cancer. Our goal is to untangle these connections and devise new strategies to target the interaction between leukemic cells and their environment, with the goal of eliminating blood cancers.
What got you interested in this space?
AT: I was fascinated by biology as a child. I remember learning about evolution in my first biology class in the fifth grade – I have been hooked ever since! I love being in the lab. I am exhilarated by seeing results for the first time and being able to connect the dots between different experiments. When I recognize a gap in my understanding, I feel compelled to learn more. This is how I became interested in the stem cell niche and leukemic microenvironment. As a Postdoctoral Fellow, I was fortunate to have had the opportunity to work in a top hematopoietic lab where I started to scratch the surface of understanding the niche’s molecular architecture, but many questions remain. Continuing this line of inquiry, I look forward to translating my findings into innovative therapies here in Ontario.
Why did you choose to come to Ontario?
AT: Princess Margaret is one of the top cancer research centres in the world. During my recruitment I had an amazing experience interacting with the faculty and trainees here. They were highly engaged and asked great questions, indicating a rich intellectual environment. Since most of my ideas come to me when I am working with others, this is the ideal place for my young lab to grow intellectually. Plus, the people here are genuinely supportive. My move was delayed due to COVID, but everyone here has been exceptionally helpful.
How has COVID impacted your work?
AT: An important trait to have as a scientific researcher is agility or the ability to quickly adapt to changing environments. Furthermore, COVID made me realize that nothing can shake my enthusiasm for starting a research group.
As a result of pandemic, I think people have become more open to collaboration. In some ways, online communication has leveled the playing field, bringing geographically distant researchers into the same space as colleagues accustomed to side-by-side interactions.
I also think COVID has brought science into public view. For the first time in my life, I hear immunology terms on the morning news. I’m excited by the prospect of biomedical research being a common discussion topic.
Does your work apply to other diseases?
AT: Yes, it does. I have a specific focus in a rare form of leukemia, called T-ALL. My research applies to other cancers as well. Insights from one disease can often guide our understanding of other malignancies.
Notably, my research in the regenerative medicine space of the bone marrow niche has the potential to impact thousands of patients treated every year with bone marrow transplantation. Additionally, if we can better understand how to regenerate the bone marrow microenvironment, we could bring a whole new treatment paradigm to patients with a wide spectrum of benign and malignant diseases. At the end of the day, this is what it’s all about.
September 10, 2020
OICR-supported researcher Dr. Harriet Feilotter leads liquid biopsy research program
As the COVID-19 pandemic has impacted many areas of life, including the diagnosis and treatment of other health conditions, people have chosen to forgo cancer screening and care in attempt to minimize their potential exposure to the virus. Relative to the general population, people living with cancer are more susceptible to the virus, but delaying cancer treatment may allow the disease to grow or spread.
Dr. Harriet Feilotter has teamed up with members of the pan-Canadian Digital Technology Supercluster to bring greater access to cancer testing and treatment during the pandemic and beyond. Through the $2.59 million Project ACTT (Access to Cancer Testing & Treatment in Response to COVID-19), they aim to provide liquid biopsy solutions, which require only a simple blood draw, as alternatives to surgical tissue biopsies for cancer diagnosis and care.
“The goal is to allow patients alternatives to invasive procedures that may be difficult to access during a pandemic,” says Feilotter, Molecular Geneticist and Scientist at Kingston Health Sciences Centre, faculty member of Queen’s Cancer Research Institute and OICR Associate. “Not only would this benefit those patients who live far from large cancer centres, but it could limit patient exposure to COVID-19 and increase health system capacity.”
The collaborative team is led in part by Canexia Health, which develops specialized cancer genomic assays, and Patriot One Technologies Inc.’s subsidiary Xtract AI, which specializes in machine learning solutions across a variety of applications, among other private and public partners. Together, they will work to enhance their current tests that detect mutations in circulating tumour DNA (ctDNA) from blood and deploy these tests for multiple cancer types across Canada.
Now through ACTT, some patients have access to these tests in British Columbia, Ontario, Quebec and Saskatchewan. The long-term objective is to increase access across the country.
“The development of liquid biopsies and ctDNA testing has been accelerated by this pandemic,” says Feilotter. “We’re proud to team up in this cross-disciplinary, cross-sector collaboration to bring these promising solutions to more patients.”
August 28, 2020
In the most comprehensive analysis of whole cancer genomes to date, OICR researchers identify novel sex-linked genomic 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 differences remain unresolved. A better understanding of sex-linked differences in cancer could lead to more accurate tests and allow sex to be included as a consideration when personalizing treatments for patients.
In a study, published in Nature Communications, OICR’s Constance Li and collaborators identify key genetic characteristics that differ between sexes. Here, Li describes what they found and what this means for patients.
Some studies have already hinted that cancer genomes differ between males and females. What is new about this study?
Previous studies focused on the exomes of patient tumours. That means that they were only looking at a small fraction of the genome that codes for proteins. This study allowed us to look at the entire genome – all of our DNA code – and take a dive deep into many aspects of the disease, like how tumours evolve over time.
By looking at the entire genome and in this ‘dark space’ that we hadn’t explored, we were able to confirm some previous findings but also find new differences between male and female tumour samples.
What sort of differences did you find?
We catalogued the differences we found across nearly 2,000 patient tumours representing more than two dozen different cancer types. Interestingly, we found that biliary cancers – like some liver, gall bladder and bile duct cancers – evolve differently in males than they do in females.
We also found that mutations in the TERT promoter – which is a hot topic in cancer research – occur much more often in men than in women, especially in thyroid cancers.
What does this mean for researchers who are looking into this subject?
Our findings suggest that there are underlying biological differences in the way that male and female tumours begin and progress. Overall, we need to be aware of these differences and consider the sex differences as we develop new tools that can match patients to appropriate treatments.
How else could this be helpful for cancer patients?
These findings are preliminary but powerful. It is important to note that more clinical data and research are needed to validate the differences we found. Ultimately, if we look deeper and find that a cancer progresses along one course in females and a different course in males, we can design roadblocks – or therapies – to stop the cancer along that specific course for that sex.
This paper is part of the Pan-Cancer Analysis of Whole Genomes Project. Read more about the Pan-Cancer project here.
August 25, 2020
OICR-supported researchers demonstrate new drug may eliminate triple negative breast cancer cells in certain patients, discover a new method to identify which patients will benefit
Adapted from UHN’s Media Release.
Triple negative breast cancer (TNBC) is a highly aggressive subtype of breast cancer that often spreads to other organs and accounts for one in four breast cancer deaths. OICR-supported researchers at the University Health Network’s Princess Margaret Cancer Centre are zeroing in on the molecular mechanisms that fuel this deadly cancer’s runaway growth to develop more effective treatments for this disease.
In their study, recently published in Nature Communications, they found a promising approach that could potentially identify the patients who could benefit from a more precise, targeted therapy for TNBC.
“This disease has no precision medicine, so patients are treated with chemotherapy because we don’t have a defined therapeutic target,” says co-lead of the study Dr. Mathieu Lupien, Senior Scientist at the Princess Margaret Cancer Centre and OICR Investigator. “Initially, it works for some patients, but close to a quarter of patients recur within five years from diagnosis, and many develop chemotherapy-resistant tumours.”
“These savage statistics mean that we must improve our understanding of the molecular basis for this cancer’s development to discover effective, precise targets for drugs, and a companion test to identify which patients are most likely to benefit the most from such a therapy.”
The study investigated how TNBC cells are dependent on a specific protein called GLUT1 and its associated molecular pathways. Prior studies suggested that TNBC cells were dependent on GLUT1, but this study is the first to demonstrate that blocking GLUT1 function may be an effective therapeutic strategy for certain patients with TNBC.
Using a collection of cell lines, the researchers found that blocking this pathway with a drug-like chemical compound “starved” the cancer cells, but only in a subset of TNBC patient samples. The group investigated further and found a common trait between the cell lines that were sensitive to the drug – they had high levels of a protein called RB1. This indicates that patients with TNBC and high levels of RB1 may, one day, benefit from this drug.
“Having access to diverse cell models of triple-negative breast cancer allows us to distinguish where the potential drug will work, and where it won’t,” says Lupien. “Without this broad spectrum of samples, we might have missed the subset of triple-negative breast cancers that respond to our compound.”
Collectively, this study suggests that clinical evaluation of targeting GLUT1 in certain patients with TNBC is warranted.
“The more we understand about the molecular complexity of cancer cells, the more we can target with precision,” says co-lead of the study Dr. Cheryl Arrowsmith, Chief Scientist for the Structural Genomics Consortium Toronto laboratories and Professor of Medical Biophysics at the University of Toronto. “And the more we can build up a pharmacy of cancer drugs matched to specific changes in the cancer cell, the greater the chance of a cure.”
Read UHN’s Media Release.
July 24, 2020
OICR research leads to new pancreatic cancer clinical trial with aim to change the standard of care for patients
New pancreatic cancer trial, NeoPancONE, launches across Canada
Adapted from Pancreatic Cancer Canada’s press release.
OICR’s PanCuRx team and collaborators have launched NeoPancONE, a Phase II clinical trial that will evaluate a potentially curative treatment strategy for operable pancreatic cancer. The trial, which is supported by Pancreatic Cancer Canada, will recruit patients at 10 cancer centres across the country to evaluate the effectiveness and feasibility of peri-operative chemotherapy – chemo treatment before and after surgery.
Typically, only 50 per cent of pancreatic cancer patients receive chemotherapy after surgery due to a range of personal and health reasons. NeoPancONE will help evaluate whether chemotherapy treatment before surgery can help extend the lives of these individuals.Continue reading – OICR research leads to new pancreatic cancer clinical trial with aim to change the standard of care for patients