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Genomics core team members discuss strengths of model that places data sharing front and centre within research community

In this blog, Dr. Trevor Pugh and Neil Winegarden discuss their contributions to the Terry Fox Program Project Grant “Delineating Therapeutic Opportunities in Triple-Negative Breast Cancer,” launched in 2016 and led by Dr. Mathieu Lupien at the Princess Margaret Cancer Centre.  A scientist at Princess Margaret Cancer Centre, Dr. Pugh is an assistant professor of medical biophysics at the University of Toronto and is also a member of three other TFRI research teams: The TFRI’s pan-Canadian immunoTherapy NeTwork, (iTNT) and multiple myeloma group, as well as a 2017 New Investigator Award. Winegarden is the core’s operations manager and technical lead. Here they discuss the project and the role and importance of the core to its success in finding new treatments.

Trevor Pugh
Dr. Trevor Pugh speaks at a recent TFRI event. 


Trevor Pugh: My role in the Core is more of the scientific director of the Genome Centre, and Project 1 within the PPG is focused on improving immunotherapy for patients treated with triple-negative breast cancer. My most recent interest is single-cell analysis of primary biopsies from patients. We’re very interested in what the cells are in individual biopsies. Our goal is to say, “Here are specific genes that express proteins in tumours that we can inhibit with drugs,” or to see if there are elements in the microenvironment in all the known tumour cells that could also be targeted. That’s really the aim of Project 1, and those ideas don’t really go anywhere without the technology available through the Genomics Core.”

Neil Winegarden: We are pretty full-featured in terms of doing some of the classical things, like exome sequencing and RNA sequencing, but some of the newer technologies we have around single-cell genomics and single-cell epigenomics are of particular interest. My role is chiefly is to deal with the operations; to bring in and integrate new technologies and to help evangelize the Centre. Currently we are heavily focused on bringing in a broad portfolio of single-cell genomics technologies as well as some functional genomics technologies.

Trevor Pugh: I’m definitely most excited about single-cell RNA sequencing and its potential. At one time, we used to take a lump of tissue, grind it up and infer the presence of different populations, and do the average of all the cells. Now, with the single-cells technologies we literally take one cell into an oil droplet, do all the molecular biology in that droplet, and when we sequence all of the resulting DNA and RNA that all gets assigned to a single cell. So rather than taking the average across all tissues we can now say this cell expresses these genes, these cells do not. This is a whole new look at what used to be very complicated tumour tissues. Our biggest challenge is that a tumour is not just cancer cells; it’s a mixture of cancer cells, infiltrating immune cells, and blood vessels. It’s very challenging for us to deconvolute using just whole tissue sections - but that’s really much less of a problem now with single-cell analysis.

Neil Winegarden: The other thing beyond the single-cell level is some of these functional genomic assays that we are starting to bring in as well, which allow us to look at what we call synthetic lethalities. We can couple the results of these assays to drug screens and start to really understand the molecular mechanisms underlying how cells respond to drug treatments. I think for triple-negative breast cancer this is going to be incredibly important. We’re trying to understand therapeutic modalities that are going to work in these cancers.

Trevor Pugh: That’s what is really exciting about this project, and being in the Terry Fox Program: these four projects within the PPG are really quite different. It’s a nice opportunity for us to generate data using these new platforms, but also then compare them using epigenetic data, mouse xenographs, as well as all the other data that has been generated from these other four projects. It’s been great to have this centralized Core that’s actually quite well connected to all the core leaders in the other projects as well.

Neil Winegarden: We have a large data-sharing component within the Core itself, thanks to our bioinformatics colleagues and the bioinformatics group headed by Carl Virtanen. The idea is to set up a centralized server to make the data navigable by everyone involved in the project and to also capture some patient data. The data is all secure and, in the hospital, we don’t have names or identifying information, but clinical data are actually very important for us to interpret why a mouse xenograph won’t respond or why a cell line genome looks a certain way.”

Trevor Pugh: Dr. Mathieu Lupien leads this whole thing and it’s a very diverse group. he’s really helped us put data sharing front and centre for everyone in the group. It’s great for us, because we learn about all these other research areas we didn’t even know existed! Especially getting close to the patient-derived data, which is kind of a new area for most of the basic researchers.  It really helps us to think about trying to design our experiments in a more clinically oriented way.

Neil Winegarden: We want to encourage data sharing across centres, and focusing on collaborative research, not just in Toronto but also across Canada. We’re very good at generating data. The challenge now is data aggregation. That’s something we’re really trying to solve at least locally in our Cores:  putting all that data in a standardized place and sharing it out but also trying to connect a little more internationally.

Trevor Pugh: To really, truly understand things like triple-negative breast cancer, we need to work collaboratively with multi-disciplinary teams and multi-faceted research. The only way to do that is to bring in a lot of people, share the data, and make sure that everyone sees what’s been going on. And that’s something I’ve been a proponent of outside of this initiative.

The second thing is that the Core model does make lot of sense. We’ve got some revolutionary new technologies that are out.  They’re expensive to set up, they’re hard to maintain without dedicated personnel, and by combing resources and centralizing into a Core, we can spend more of the money generating data rather than setting up the machines to generate data. I believe this is something that’s going to be very successful because we can have a dedicated team of people who know how to run this stuff. Then bring in more researchers who can take advantage of that. I think this is going got be a very strong model going forward.

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