By Monica Heger
Dana-Farber Cancer Institute's Belfer Institute of Applied Cancer Science and Sanofi-Aventis have entered into a collaboration and license option agreement to identify and validate oncology targets.
The researchers will use sequencing technology at various stages in the collaboration, including target identification and validation, preclinical testing in animal models, and eventually in clinical trials, Lynda Chin, the Belfer Institute's scientific director, told In Sequence.
Under the terms of the agreement, Dana-Farber will receive $33 million in upfront research funding for a minimum of three years from the company, and will be entitled to preclinical, clinical, and commercial milestone payments and royalties on sales of any commercial products that may result from the collaboration. Sanofi-Aventis, meantime, will have exclusive access to "certain components of a transformative cancer target identification and validation platform," according to a release.
Chin said that the team will leverage data from the National Institutes of Health's Cancer Genome Atlas, the International Consortium on Cancer Genomics, and other public data. Belfer Institute researchers have also contributed data on glioblastoma to the TCGA project, including the analysis of copy number alterations, gene expression, and methylation aberrations in over 200 glioblastomas.
For the current project with Sanofi-Aventis, Chin said the details are still being finalized, but that sequencing would play an important role.
"It's not a collaboration that's set out to sequence tumors, but it is cancer genomics as a whole, and sequencing technology will certainly be leveraged," she said. "In the closer time frame, genomic information will be a big part of target identification."
Initially, she said the researchers would likely do targeted resequencing studies in large numbers of samples across a range of cancer types. Because there will be many potential candidates, focused, targeted resequencing of candidate genes across a large number of samples will help increase the "statistical power to determine how prevalent a mutation is in a particular subtype," she said.
The researchers will likely use the Illumina platform for sequencing, Chin said, although she said they were not committed or linked to any particular platform. "We'll be keeping watch on the technology, particularly given the applications we are looking to use it for," she said. "Different purposes of the study may dictate a different platform."
Belfer researchers collaborate with, the Dana-Farber Cancer Institute, the Dana-Farber Harvard Cancer Center, the Broad Institute, as well as other commercial organizations. And sequencing for the project could be done through any of these collaborations, Chin said.
Chin also was not able to specify which types of cancer the researchers would be studying, but she said they were not limited to any particular type and would look at more than just the "big tumor types." She added that, over time, "cancer will more and more be defined by its genetic events, rather than cell lineage," so it will be important to study all different types of cancer.
The major goal for the first year of the project is to "enlist novel targets into the drug discovery pipeline." She said the team wants to "very rapidly define what we call the clinical path hypothesis — [identifying] tumor types and subtypes where the novel target may be the most important." This is different from the traditional drug-discovery paradigm, where researchers develop a drug and then try to identify the cancer subtype in which it will work best. "The sooner we define that clinical path hypothesis, the more efficient the drug-discovery process will be. And that's a place where cancer genomics will play an important role," Chin said.
Eventually, she said, the collaborators expect to use sequencing in preclinical work, studying tumors and drug response in mouse models, for instance. For these types of studies, researchers would likely be doing a combination of either whole-genome or whole-exome sequencing, depending on the resources available, and also transcriptome and methylome sequencing.
Studying model systems, such as mice, will be important for gaining a "dynamic view of the genome," Chin said. Researchers will be able to sequence the genome, transcriptome, and methylome at various stages of disease progression, and also at various stages post-treatment, to help determine drug response and to characterize subtypes for which the drugs are most successful. These types of studies are harder to do with human samples, because it can be difficult to obtain samples at all those various stages, she said.
Chin added that this type of collaboration, as well as the use of sequencing technology, will both help speed up the process of drug development and further the understanding of the complex biology of cancer.
"Rather than handing a drug target off to a drug developer, it's important that we come together to understand the biology," she said. Cancer drug development has about a 90 percent failure rate, from target discovery to bringing a drug through US Food and Drug Administration approval. Leveraging sequencing technology to gain a better understanding of the biology and to determine the important pathways in cancer should help improve that rate, she said.