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.