October 15, 2019
OICR Biostatistics Training Initiative Fellow and newly-minted PhD, Dr. Osvaldo Espin-Garcia, dedicates his career to cutting-edge clinical cancer research
For Dr. Osvaldo Espin-Garcia, an industry-based job wouldn’t suffice. Having already worked in banking, insurance and telecommunications, Espin-Garcia found that his skills in statistics could be applied to a field that he was much more passionate about. For him, that was health research.
Combining his skills in math with his interest in health, Espin-Garcia left his job in Mexico and moved to Canada to pursue the University of Waterloo’s Master of Mathematics program. His strong academic performance secured him an internship at the Princess Margaret Cancer Centre (PM) where he found his niche in statistical genetics.
“Despite advancements in sequencing technologies, the path between a new -omics discovery and applying that discovery in the clinic remains cumbersome and often costly, especially in large-scale studies,” says Espin-Garcia, who recently completed his PhD at the University of Toronto’s Dalla Lana School of Public Health. “We can use statistical techniques and tools to design better trials and make sense of this sequencing data in more efficient ways.”
Espin-Garcia’s internship laid the foundations for his PhD research, where he developed statistical methods and analysis tools to examine the data from genome-wide studies – studies that look at the entire set of genes across many individuals.
In these studies, researchers often examine a sample subset of patient genomes from a large group of patients. These samples are often selected randomly, but Espin-Garcia’s methods allow researchers to select these patients in a “smarter” way.
“Choosing patients randomly is an inefficient way to perform post-genome-wide studies since this strategy fails to incorporate the information that is already available,” says Espin-Garcia. “Our methods allow us to select subgroups of patients whose data will give us rich insights into challenging research questions. That’s what I’m here for, I’m here to help address important and challenging questions in health.”
For this work, Espin-Garcia was awarded a Biostatistics Training Initiative (BTI) Fellowship, which helped him fast-track the development of his methods and the completion of his PhD.
Now, as a Senior Biostatistician at PM, he is specializing in gastrointestinal cancer studies and continues to develop and apply new tools to support the clinical cancer research community.
“I am grateful for the support I’ve received throughout my training to build my collaborative relationships with clinicians and scientists and learn from incredible mentors,” says Espin-Garcia. “I look forward to supporting more cutting-edge clinical cancer research in the future.”
BTI, a training program co-led by OICR, the University of Waterloo and McMaster University, has supported numerous fellows, like Espin-Garcia, and other studentships over the last decade.
July 23, 2019
Biostatistics Training Initiative (BTI) alumnus brings on new BTI trainee to study Canada’s largest population health dataset using today’s top technologies
Recently, circulating tumour DNA (ctDNA) – DNA released from cancer cells that freely circulates in the blood – has garnered much attention not only as an alternative to traditional tissue biopsies, but as a potential blood-based biomarker for early cancer diagnosis.
The ability to detect the earliest blood-borne traces of cancer largely rests in our ability to determine which molecular markers indicate that a cancer is developing – or which patterns in ctDNA can predict whether a cancer will grow. Dr. David Soave sees this as a mathematical challenge that, if solved, could have huge impact for better predicting and diagnosing a wide variety of cancers.
“To find cancer earlier or predict who will develop the disease, we need to carefully compare human samples from those who will develop cancer and samples from those who won’t,” Soave, an Assistant Professor at Wilfrid Laurier University and OICR Associate, says. “This type of challenge requires new statistical models, methods and computational techniques that can decipher large, complex and high-dimensional data.”
Last year, the Canadian Partnership for Tomorrow Project (CPTP) unified the data from several provincial longitudinal health studies into a national cohort consisting of more than 325,000 participants who are voluntarily donating their health and biologic samples to research. As some CPTP participants will develop disease and others will not, this dataset provides an unprecedented resource for researchers like Soave to discover the earliest traces of cancer that appear several months to years prior to an initial diagnosis.Continue reading – Blood samples, biostatistics and a fresh perspective: The makings of a cancer prediction machine
April 9, 2018
Dr. Gregory Pond, Jenna Sykes, Dr. Richard Cook, Yonathan Brhane, Dr. Wei Xu.
Cancer researchers often confront quantitative challenges and puzzles that are best addressed by biostatisticians – specialists in a field for which there is a growing demand. In a 2008 survey of Ontario oncologists, eight in 10 respondents identified the lack of trained biostatisticians as a factor limiting their progress in cancer research. OICR has recently renewed funding for the Biostatistics Training Initiative (BTI) following a successful review. With this funding, the BTI will continue to benefit Ontario’s cancer research community and develop the next generation of cancer biostatisticians. The BTI is run in partnership with in the University of Waterloo and McMaster University.