A conversation with leading Canadian oncologist Dr. Janessa Laskin

Personalized OncoGenomics, probing an individual’s genome for bespoke cancer treatment, is a reality for a select group of patients with incurable cancer in British Columbia. The project, known as POG, now in its seventh year and offered through BC Cancer, has vaulted its clinical leader, Dr. Janessa Laskin, into the forefront of international discussion on the future of this revolutionary approach to cancer.

A medical oncologist at BC Cancer, Vancouver, Dr. Laskin has drawn at least four conclusions from her ground-breaking work with POG, a novel collaborative research project between clinical oncologists and the Michael Smith Genome Sciences Centre in Vancouver:

• Cancer is a disease of the genome

• Genomic technology can help us better understand cancer biology, behaviour and response to therapy

• Genome/transcriptome data can be used to identify novel treatment strategies

• Such comprehensive data can make a difference in clinical care for the individual and this knowledge can be translated to help patients on a global scale

POG is the only project of its kind to accept adult and pediatric patients with all types of advanced cancer for evaluation in such extensive detail. As of August 2019, 1,068 patients have been enrolled in the study since the program’s launch. Whole-genome and RNA sequencing is done on biopsied cancer cells taken from every patient, generating enormous amounts of data which are then subjected to thorough analysis and discussion by researchers and clinicians. Their combined effort is focused on generating hypotheses about what might be driving a particular person’s cancer to grow uncontrollably and to exploit those vulnerabilities with drug treatments. Of the cases completed, over 80 per cent of the time the genomic/transcriptomic data generated potentially clinically actionable drug targets that could often be aligned to actual treatments for the individual patient.

POG considers cancer a disease of genetic mutations with drivers that are individual to the persons affected. Using a patient’s analyzed genomic and transcriptomic (RNA) data, POG can search for drug treatments – some of which may be off label or approved for other diseases – with potential to contain or neutralize the drivers.

Conventionally, cancer has been approached as a disease differentiated by its site of origin and it has been treated according to standards, based on what has helped others affected in the same way. In some respects, it has been a one-size-fits-all approach.

“Unfortunately,” Dr. Laskin has acknowledged, “we know that this strategy can only help some patients, which means that many people endure potentially toxic and ineffective treatments. POG is about trying to identify the right treatment for the right person at the right time; we are still in the discovery phase but POG has had its share of fascinating success stories as well as disappointments, as outlined in a 2017 episode of The Nature of Things, broadcast by CBC.”

Yet even at this early trial stage, the concept behind POG is considered promising enough that many observers in the cancer field expect it to eventually provide more options to patients, for whom the traditional approach has been unsuccessful, and to present scientists and clinicians with new, fruitful lines of inquiry for more effective cancer treatments.

Dr. Laskin stopped at Genome Atlantic on a visit sponsored by Sanofi-Genzyme, Genome Atlantic, Integrated Microbiome, Illumina and Dalhousie University. She was in Halifax to speak to the local medical and research cancer community about POG.  To mark the visit, we asked her five questions:

Do you find oncologists and cancer researchers open to the idea that cancer is a disease of the genome or do they need convincing?

At this point I think there is a general agreement that the unregulated cell growth that defines cancer is driven by something wrong at the genome or transcriptome level. We have clear examples of success when we are able to identify and target these specific abnormalities and many of these are now integrated into the standard of care for testing and treating certain types of cancers. Lung cancer with EGFR mutations, melanoma with BRAF mutations would be examples of this integration of genomic technology directly into mainstream care. However, it is also clear to clinicians and researchers that this is still a wide-open space and there are many aspects that are as yet unclear and many of these likely lie in the space around the genome such as epigenetics, proteomics, and so on.

It has been found that chemotherapy changes the genome. Is this conclusion an obstacle or an opportunity for improved cancer based on the POG approach?

We have a lot to learn about the untreated cancer genome, so the changes after chemo- or radiation therapy pose an additional important challenge. We have demonstrated many of these changes over time with serial biopsies and analyses; this is one of the most interesting aspects of the research aspect of POG. In the future I am hopeful that we can learn how to harness the power of this sort of knowledge; by understanding how a cancer might evolve in the face of a specific treatment perhaps we can guide it in a direction that would allow a treatment we could anticipate and therefore take advantage of.

Apart from cases of remission, how does POG know if it has improved the condition of its patients, given that all the participants have been diagnosed with terminal cancer.  In other words, how does POG evaluate success?

This is an important question that everyone in the “precision” medicine field is grappling with; if you are treating each individual how do you know they would not have done just as well with a standard or different therapy? There have been many approaches to this in clinical trials, comparing how a person did on the previous treatment is the most common method. For POG we have been more focused on development of a process to create meaningful analyses and testable hypotheses so we have not yet focused on this sort of clinical value.

We do have some early data with matching cohorts of patients who have not had treatment informed by POG and we do find that patients treated based on POG information do at least as well if not better; but these are early days and the study was not designed to answer that specific question. It is definitely something we are motivated to address, and we work closely with our Health Economics team to try to measure and understand the value of this sort of data. And “value” can mean many things, not just financial but also the utility of having more information and a biological rationale to choose treatments.

We do think that in time finding the right treatment for each person will be more effective care, though it may not be less expensive. If people are living longer, they will need to be on treatment for longer.

The POG project has been running for seven years now. Has the program provided enough proof of concept yet, to be considered worthy for adoption into the health care system?  If not, what stands in the way?

POG has been an innovation and discovery project, we would not envision that POG as it currently exists would be the right answer for every person with cancer. It is clear that more information is helpful for treatment planning and to understand cancer biology and evolution. Once we have sequenced tens or hundreds of thousands of these individual cases, I think we will have a much better idea of what sort of patient requires each level of testing. And as we acquire this experience, the technology will change, and we need to adapt along with it.

Much as you might not have envisioned a smart phone when you bought your first cell phone, your needs changed as the technology evolved. For now, funding is a significant issue, we need to amass enough data to understand the best way to include genomic technology into care.

What is next for the POG project?

We have a number of exciting projects on the go. We are about to launch a trial using POG data to identify markers for immunotherapy. This is an area of great need because there are no reliable markers for these drugs currently, and they are costly and often toxic. We have been doing some innovative work in pancreas cancers, understanding that there are some niche populations in this devastating cancer that can be selected out by POG-like analysis.

Our next goal is to work close with the Marathon of Hope Cancer program in collaboration with the Terry Fox Research Institute, to bring cancer genomics to all Canadians. We have a novel program to generate information more rapidly for clinical use while selecting some genomes for more in-depth analysis. We are committed to collaborations and data sharing, and we hope to bring our experience into the field, to pave the way for other researchers and clinicians.

Genomics is the future, and the future is hope.

JD Irving Ltd., also known as JDI, the Canadian forestry company based in New Brunswick, is leaping ahead with genomic selection, a technology that promises so much efficiency, it could eventually eclipse conventional tree breeding practices.

Josh Sherrill, JDI’s genetics and forest productivity leader, said the company’s participation in a recent research project, dubbed FastTRAC, for Fast Tests for Rating and Amelioration of Confers, with a focus on Norway and white spruce, “allowed JDI to move to the front of the pack and gain experiences with genomic selection that many industry players around the world have not benefited from.”

At the company’s six-hectare, second generation white spruce seed orchard in Parkindale, N.B., JDI has been using genomic predictions, based on diagnostic tools developed during FastTRAC, to cull what Mr. Sherrill described as “the least desirable parents” for new white spruce. “By using genomics, we were able to do this several years earlier than we normally do,” he said. The estimated time saving was eight years, compared to traditional methods that require more tree growth before field test data can be collected and analyzed.

Indeed, with genomic profiles, the genetic value of a tree can be estimated while it is still a seedling, reducing the need for field evaluation. By contrast, conventional breeding practices can require growers to wait up to 20 years before some economically and environmentally important traits can be assessed in the field. FastTRAC showed genomic selection, which can predict the breeding value of a candidate tree for many traits of interest using its genomic profile, will reduce the timeline for the selection of enhanced reforestation stock by 20 to 25 years in spruces.

Moreover, genomic predictions have enabled JDI to more reliably select trees with the best traits for industrial use and employ them more often for breeding.

“Both these applications will result in increased growth and other quality traits in the seedlings we plant,” Mr. Sherrill said. “These applications are intended to grow our wood supply for our sawmills and pulp mills. That means more jobs and economic development throughout the supply chain from the forests to the consumer.”

While genomics is not new, it is a relative newcomer to the world of forestry and to conifers in particular. “JDI had followed developments in the research and only recently, through development of genomic selection methods, has the technology advanced to the point where it could be evaluated for an applied industrial tree improvement program,“ explained Greg Adams, a forestry consultant with a long association with JDI. Essentially, he said it was the advanced state of genomic selection that piqued JDI’s interest in the project.

For more than 30 years, before entering the consultancy business, Mr. Adams ran JDI’s tree improvement program. He also represented JDI on the FastTRAC team, a research partnership that included the Canada Research Chair in Forest and Environmental Genomics at Laval University; Forest Products Innovations, the world’s largest private non-profit forest research centre;  the New Brunswick Tree Improvement Council, the Canadian Wood Fibre Centre; the Quebec Ministry of Forestry of Forests, Wildlife and Parks; and Natural Resources Canada. Funding came from Genome Canada and Génome Québec, through the Genomic Applications Partnership Program (GAPP). The province of New Brunswick was also a contributor, while  Genome Atlantic provided support and assisted with co-funding.

 “This effort was certainly among the first in North America to apply genomic selection in applied tree improvement programs,“ said Mr. Adams.

 “Tree growth rate and stem quality are important traits in selection programs and are easily assessed in field tests,” he said. “Other traits, such as wood properties and pest resistance, are more difficult and expensive to assess but also important for long-term value. Genomic selection offers significant potential to address these difficult-to-assess traits.”

“The FastTRAC project was highly successful,” said Mr. Adams.  Originally, the plan was to test genomic selection results against available data as a proof-of concept. The results proved so encouraging, the research effort expanded to include the New Brunswick Tree Improvement Council’s entire second-generation white spruce population. “This provided growth and wood quality predictions used in orchard management and brought increasing efficiency of breeding to the next cycle,” said Mr. Adams. “Further to this, genotyping from the FastTRAC project has also been used to build genomic selection models related to spruce budworm resistance.” The genotyping process examines DNA for variants tied to the unique traits of an organism.

As an industry participant, JDI helped shape the project’s goals to have practical application for the forestry business. The company also supplied some financial backing, and most importantly, provided access to several decades worth of genetic data. “The field data is essential to any program hoping to integrate molecular genetics into applied tree improvement, Mr. Adams stressed.

Back at JDI’s white spruce seed orchard, where Mr. Sherrill oversees the application of the genomic tools for genomic selection developed by FastTRAC, he said, “We implemented quickly but have proceeded carefully. In the seed orchard, we could have removed more parents but we were conservative. As we gain confidence in genomic selection, we will rely more heavily on it and make increasingly bolder decisions.”

He said, “Currently we are working on validation of the FastTRAC models using field data. This will help us to adjust our level of reliance over time and make improvement to the methodologies.”

The results of the first FastTRAC project are “quite encouraging,” he said, and “the usefulness of the information means that breeding programs will be different going forward. The new normal for breeding will be genomics-informed, and as we build confidence there is the potential for breeding to be genomics-led.”

In the meantime, a follow up proposal, FastTRAC 2, is shaping up to focus on genomic selection for red and black spruce, conifers that JDI also plant and count on for raw material. The two species are the most planted in eastern Canada.

Due to the success of the first FastTRAC, the new proposal has attracted greater investment from New Brunswick and Nova Scotia tree improvement participants. FastTRAC 2 proposes to create genomics technologies that can stock future tree plantations with seedlings capable of withstanding the effects of climate change and minimizing the impact on Atlantic Canada’s forestry sector.

Taking the long view of genetic selection, Mr. Sherrill says that “beyond creating predictive models for additional species, we expect there will be opportunities to refine and build on existing methods and practices. For instance, our rich genetic marker data could be used to better understand genetic diversity and help us optimally manage our breeding populations.”

The FastTRAC team was named the 2019 recipient (Collaboration category) of the prestigious Canadian Forest Service Merit Award. Congratulations to the team on this recognition!