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.”
August 28, 2020
OICR-supported researchers and collaborators discover indicators in the blood that may predict which patients will respond to the immunotherapy drug, pembrolizumab
Adapted from UHN’s Media Release.
Immunotherapy can shrink tumours and prolong survival for certain cancer patients, but clinicians don’t yet know which patients will benefit from these treatments. OICR-supported researchers and collaborators at the Princess Margaret Cancer Centre have made a discovery that could help identify those patients who may benefit and match them with potentially life-saving therapies.
In their study, recently published in Nature Cancer, the research group found that the changing levels of tumour fragments, or circulating tumour DNA (ctDNA), in a patient’s blood can be used to predict whether they will respond to the immunotherapy drug pembrolizumab.
The study lays the foundation for researchers to develop an easy, non-invasive and quick blood test to determine who will benefit from the drug and how well their disease is responding to treatment.
“While we have known for some time that cancer disease burden can be monitored by measuring tumour DNA in the blood, we are excited to report that the same concept can be applied to track the progress of patients being treated with pembrolizumab,” says co-first author Cindy Yang, PhD Candidate in Dr. Trevor Pugh’s lab at the Princess Margaret Cancer Centre and OICR. “This will hopefully provide a new tool to more accurately detect response and progression in patients undergoing immune checkpoint inhibitor therapy. By detecting progression early, patients may have the opportunity to undergo subsequent lines of treatment in a timely fashion.”
The benefits of blood tests
Conventionally, imaging scans – such as computerized tomography (CT) scans – and other methods are used to monitor a patient’s cancer. This study suggests a simple and quicker blood test as an alternative to these scans.
“Although important, computerized tomography (CT) and other scans alone will not tell us what we need to know quickly or accurately enough,” says senior author Dr. Lillian Siu, Senior Scientist and medical oncologist at the Princess Margaret Cancer Centre.
Dr. Scott Bratman, radiation oncologist and Senior Scientist at the Princess Margaret Cancer Centre and co-first author of the study, points out that it may take many months to detect whether a tumour is shrinking with various imaging scans.
“New next-generation sequencing technologies can detect and measure these tiny bits of cellular debris floating in the blood stream accurately and sensitively, allowing us to pinpoint quite quickly whether the cancer is active.”
This study represents one of the many emerging applications of using ctDNA to guide treatment decisions. It is one of the first to show that measuring ctDNA could be useful as a predictor of who responds well to immunotherapy across a broad spectrum of cancer types.
The prospective study analyzed the change in ctDNA from 74 patients, with different types of advanced cancers, being treated with pembrolizumab. Of the 74 patients, 33 had a decrease in ctDNA levels from their original baseline levels to week six to seven after treatment with the drug. These patients had better treatment responses and longer survival. Even more striking was that all 12 patients who had clearance of the ctDNA to undetectable levels during treatment were still alive at a median follow-up of 25 months.
Conversely, a rise in ctDNA levels was linked to a rapid disease progression in most patients, and poorer survival.
“Few studies have used a clinical biomarker across different types of cancers,” says Siu, who also co-leads OICR’s OCTANE trial. “The observation that ctDNA clearance during treatment and its link to long-term survival is novel and provocative, suggesting that this biological marker can have broad clinical impact.”
Innovation and translation
This study is part of a larger flagship clinical trial, INSPIRE, which has enrolled more than 100 patients with head and neck, breast, ovarian, melanoma and other advanced solid tumours. INSPIRE brings together researchers from many disciplines to investigate the specific genomic and immune biomarkers in patients that may predict how patients will respond to pembrolizumab.
INSPIRE is made possible by collaborations across institutes and industries with expertise from those applying genomics to research and those applying genomics in the clinic.
“INSPIRE is an incredibly collaborative initiative that is a blend of big genomics – looking at large trends across many individuals – and highly-personalized genomics – looking at mutations within each patient sample,” says Pugh, co-senior author, Senior Scientist at Princess Margaret and Senior Investigator and Director of Genomics at OICR. “This is a modern approach to the translation of clinical genomics.”
“As a PhD student, this project gave me the unique opportunity to work in a highly collaborative intersection with industry, clinical, and academic partners,” says Yang. “It is very exciting to see translational research in action.”
Read the UHN Media Release.
July 27, 2018
Over the past decade, OICR’s laboratories have procured state-of-the-art equipment and developed leading-edge technologies to help answer pressing cancer research questions. The effective and proper use of advanced laboratory tools is dependent on specialized knowledge and skills on the part of the operator. OICR’s platform for laboratory training, BioLab, is ensuring that Ontario’s cancer researchers have the knowledge they need to explore the full potential of some of the province’s most advanced cancer research equipment.