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.
February 21, 2018
Investment supports emerging entrepreneurial scientists and critical proof-of-principle studies
TORONTO, ON (February 20, 2018) – FACIT, a business accelerator, announced four new recipients of funding through its Prospects oncology investment competition: Dalriada Therapeutics Inc. (“Dalriada”), 16-Bit Inc. (“16-Bit”), a cancer biomarker study at the Ontario Institute for Cancer Research (“OICR”), and a virus-based therapeutic under development at the Ottawa Hospital and the University of Ottawa. FACIT’s investments are imperative in bridging the capital gap often experienced by early-stage Ontario companies, helping corporations establish jobs and build roots in the province. The wide ranging scope of the innovations, which span therapeutics, machine learning and biomarker development, reflect the rich talent pool within the Ontario oncology research community.
October 4, 2017
New software uses machine learning to identify mutations in tumours without reference tissue samples
One of the main steps in analyzing cancer genomic data is to find somatic mutations, which are non-hereditary changes in DNA that may give rise to cancer. To identify these mutations, researchers will often sequence the genome of a patient’s tumour as well as the genome of their normal tissue and compare the results. But what if normal tissue samples aren’t available?
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
A team of researchers and clinician-scientists from across Canada have discovered a signature of 41 mutations that are common in prostate cancer and will help to prevent patients with non-aggressive disease from being overtreated. Dr. Paul Boutros, a Principal Investigator in OICR’s Informatics and Bio-computing Program and Co-Lead of the Canadian Prostate Cancer Genome Network (CPC-GENE), answered a few questions about how the signature was developed and its potential impact on patients.
October 28, 2016
Dr. Matt Cecchini was one of many pathologists and researchers, including 21 trainees, to attend the inaugural Pathology Matters meeting hosted by the Ontario Molecular Pathology Research Network (OMPRN). In this post he covers what he learned at the meeting, where the field is going and how that impacts his training and research.