January 10, 2020
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
March 19, 2019
Collaborative research group performs the most comprehensive analysis of curable prostate cancer to date, finds key connections between different data types
As cancer researchers delve deeper into different omics studies, and technologies enable their ability to do so, it is becoming increasingly important to understand how these areas of research are interconnected. Previous studies across multiple omes – such as the genome, proteome, transcriptome or epigenome – have led to important discoveries in colorectal cancer and ovarian cancer, but prostate cancer remains largely unresolved. Researchers from the Canadian Prostate Cancer Genome Network (CPC-GENE) set out to unravel some of these mysteries.
In the most recent CPC-GENE study, published today in Cancer Cell, the research group integrated multiple levels of omics analyses to better understand the biology of intermediate-risk prostate cancer – a type of cancer in which it is notoriously difficult to predict and treat accordingly. A better understanding of this disease could lead to improved tests that can determine which tumours are aggressive and require aggressive treatment, while helping spare those whose cancer will never become aggressive the negative side effects of treatment.
“We cannot overlook the important information that we gain from looking at the bigger picture,” says Julie Livingstone, bioinformatician at OICR and co-author of the study. “In this case, this means looking at prostate cancer from multiple angles – or multiple omes – to potentially find new markers of aggressive disease.”
The study explored 76 prostate cancer tumours and found new combinations of information that could act as a better predictor of a patient’s chance of relapse than any single piece of information alone. More specifically, they identified that the combination of protein and methylation data could, on average, predict the severity of a tumour better than looking at just the proteins – the proteome – or just the methylation patterns – the methylome – alone.
“Integrating datatypes is anything but straightforward, but it illuminates interesting aspects about prostate cancer that we haven’t seen before,” says Livingstone. “In the future, we intend to pursue our multi-omic investigation and translate this understanding into better tools to inform treatment selection for men with this disease.”
Find out more about research from the CPC-GENE project on OICR News.
March 13, 2019
Researchers begin to unravel why some prostate tumours can be seen with magnetic resonance imaging and others go undetected
Determining whether a patient with prostate cancer requires aggressive therapy or active surveillance is a growing challenge for the healthcare system. Blood tests can detect early signs of prostate cancer, but these tests can lead to many unnecessary and painful biopsies for patients whose disease never becomes aggressive.
Multi-parametric magnetic resonance imaging (mpMRI), a type of non-invasive imaging technique, has the potential to help determine which patients require biopsies and which can be spared possible negative side effects, such as bleeding, pain and infection. Some tumours are visible by mpMRI while some are not, yet it’s not well understood if this visibility can predict a tumour’s aggressiveness.
Researchers at OICR have teamed up with clinicians from the University of California, Los Angeles to investigate the molecular properties of MRI-visible and MRI-invisible tumours. In their recent study, published in European Urology, they found that visible tumours have similar features to aggressive tumours and discovered new features that may be contributing to the disease’s aggression.
“Even if two tumours are similar in size and in similar positions, one still may be MRI-visible and one may be MRI-invisible,” says Kathleen Houlahan, PhD Candidate at OICR and lead author of the study. “We wanted to see if this visibility could help us determine if a cancer is aggressive, so we took the first step towards unraveling the relationship between a patient’s MRI results and the molecular characteristics of their tumour.”
Recent commentary on the study highlights Houlahan’s work as an “initial foray” into the intersection of radiology, pathology and genomics, but recognizes the limited size of her exploratory study. Recent MRI-focused clinical trials will provide larger datasets for further investigation.
“If we can better understand why some tumours show and some don’t, we could potentially use imaging to predict the course that a patient’s disease will take,” says Houlahan. “Ultimately, we hope that this technique can help reduce unnecessary prostate biopsies and ensure that the men who need treatment get the treatment they need.”
March 12, 2019
The Global Alliance for Genomics and Health publishes new guidelines for comparing a patient’s test results to a reference human genome
Finding the difference between a patient’s DNA sequence and a reference sequence – also known as variant calling – is central to cancer research, but approaches to variant calling differ from lab to lab. Comparing – or benchmarking – one lab’s approach to another lab is important to the development of new sequencing and analysis tools, yet there are no widely-accepted standards for benchmarking variant calls.
To develop these standards and address common benchmarking challenges, a group of stakeholders from government agencies, academic bioinformatics groups, sequencing technology developers and other organizations around the world gathered to create the Global Alliance for Genomics and Health (GA4GH) Benchmarking Team. They’ve recently published their best practices for benchmarking genome sequencing results in Nature Biotechnology.
“Technology is improving rapidly, but we’ve lacked ways to know the strengths and weaknesses of new sequencing and genome analysis methods,” says Dr. Justin Zook, lead author of the study from the National Institute of Standards and Technology. “This paper gives people tools to develop accurate sequencing tests for precision medicine.”
The adoption of these practices – and their continual improvement – can also help facilitate collaboration between research and clinical laboratories while improving the performance of shared tools and methods.
The framework was developed in part by Dr. Paul Boutros and his lab members at OICR, who have used crowdsourcing to develop benchmarking foundations for individual variants as well as broader genetic variation.
Read more about this benchmarking work on Genome Web.
September 20, 2018
Today, OICR’s Dr. Paul Boutros was named the 2018 winner of the Bernard and Francine Dorval Prize. The award is part of the Canadian Cancer Society’s Awards for Excellence in Cancer Research.
July 10, 2018
Researchers further clarify the role of epigenetic proteins in the development of breast cancer, and discover that inhibiting these proteins could prevent the disease in women at high risk.
May 17, 2018
Dr. Michael Fraser, Director of the Prostate Program in the Computational Biology group at OICR, has been named a 2018 NextGen Star by the American Association for Cancer Research (AACR). Awarded to only eight researchers around the world, AACR’s NextGen Stars program recognizes outstanding early-career scientists who have made significant contributions to cancer research.
April 19, 2018
Largest-ever study of its kind uses a tumour’s past to accurately predict its future
Toronto (April 19, 2018) – Findings from Canadian Prostate Cancer Genome Network (CPC-GENE) researchers and their collaborators, published today in Cell, show that the aggressiveness of an individual prostate cancer can be accurately assessed by looking at how that tumour has evolved. This information can be used to determine what type and how much treatment should be given to each patient, or if any is needed at all.
The researchers analyzed the whole genome sequences of 293 localized prostate cancer tumours, linked to clinical outcome data. These were then further analyzed using machine learning, a type of statistical technique, to infer the evolutionary past of a tumour and to estimate its trajectory. They found that those tumours that had evolved to have multiple types of cancer cells, or subclones, were the most aggressive. Fifty-nine per cent of tumours in the study had this genetic diversity, with 61 per cent of those leading to relapse following standard therapy.
September 25, 2017
Since mitochondria are inherited maternally, it may strike some as an odd place to go looking for connections to prostate cancer. But recently an international research team explored that relationship by looking at how the small amount of DNA contained in mitochondria, a cellular structure, is involved in prostate cancer.
March 16, 2017
Genetic tests are being used more commonly in the diagnosis of many types of cancer. However, there currently isn’t a highly accurate test that can identify men with aggressive forms of prostate cancer, making it more difficult to choose the most appropriate course of treatment.
January 10, 2017
Prostate cancer is the most common cancer in Canadian men, but there is still no one-size-fits-all strategy for treating the disease. Currently it is difficult to choose exactly the right type and amount of treatment for each individual because it is hard to accurately assess how aggressive the cancer is. Researchers are now a step closer to bringing a powerful new prognostic tool into clinical use.
January 9, 2017
Findings published in renowned journal Nature
January 9, 2017 – TORONTO, ON – The Canadian Prostate Cancer Genome Network (CPC-GENE) has published findings from the world’s most comprehensive genetic analysis of prostate cancer tumours in the journal Nature. Led by Drs. Robert Bristow of the Princess Margaret Cancer Centre and Paul Boutros of the Ontario Institute for Cancer Research, CPC-GENE has uncovered the full set of mutations that can occur in the most common cancer in men. By fully cataloging these mutations, the CPC-GENE team was able to create a new signature that predicts at an early stage whether a prostate cancer tumour will become aggressive or not, allowing for personalized treatment.