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X-MAN to the rescue
October 2010
by David Hutton  |  Email the author
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CAMBRIDGE, U.K.—The Wellcome Trust Sanger Institute and Horizon Discovery are teaming up to translate the abundance of new information on human genetic variation into more effective treatments for cancer, as part of a three-year collaboration between the two Cambridge-based organizations that began in July.

In the collaboration, Horizon will make available to the Sanger Institute's Genomics of Drug Sensitivity in Cancer project its unique resource of more than 200 genetically defined X-MAN in vitro human cancer models, which harbor known cancer-causing mutations, for sensitivity profiling against a panel of clinical and preclinical anti-cancer drugs. Matthew Garnett, a scientist in the Cancer Genome Project at the Sanger Institute, says this will work well to complement Sanger's current bank of non-isogenic human cancer cell lines—gathered in collaboration with Massachusetts General Hospital Cancer Center as part of Genomics of Drug Sensitivity in Cancer.

"Horizon will supply a portfolio of isogenic human cancer models generated using its novel GENESIS gene-targeting technology, wherein a pair of cell lines are created in which one line harbors a specific cancer causing mutation and the other is a perfectly matched control cell line," says Horizon Discovery CEO Chris Torrance, noting that his company's rapidly expanding list of more than 60 clients in academia, biotech and pharma are now using such genetically defined human disease models to address several key bottlenecks in the development of targeted cancer medicines.

Torrance says the terms are open access, meaning data will be made public as it is generated for the benefit of the entire research community.

Together, the Sanger and Horizon models will, it is hoped, help design clinical trials that target cancer therapeutics to patient populations that are most likely to respond, based on definitive and predictive biomarkers of either drug response or drug resistance.

"This a key need to maximize the efficiency of developing novel personalized medicines that are designed to target the root genetic causes of cancer," Torrance says. "Cancer, we now know, is at its heart a genetic disease. Horizon is using the data generated by the Sanger Institute and other genome centers around the world to create X-MAN cell lines, or more colloquially; 'patients-in-a-test- tube,' that will allow researchers to understand how cancer genes work (or not) and develop new treatment strategies."  

As the Sanger-Horizon collaboration moves forward, Garnett notes there will be some hurdles to overcome.

"Working with a large cell line collection represents a significant technical challenge," he explains. "Another significant challenge is correlating large drug sensitivity data sets with the genetic features of the cancer models."

The challenges, Garnett adds, will be small bumps in the road and his team is ready to tackle them head- on.

"We have built a dedicated multidisciplinary team including biologists, clinicians, computer biologist and biostatisticians to facilitate the analysis and interpretation of our research," he notes.

Torrance notes that the collaboration will also address another real challenge as researchers move forward, which is to increase the diversity of cancer genes that are currently being addressed by the drug discovery community.  

"Only a few cancer genes or pathways are being addressed at the moment because they are either quite prevalent and/or drugable," he says. "Consequently, we will need to find drugs to less common defects and targets downstream of undrugable cancer genes in order to build a sufficiently large tool box of drugs to combine and provide lasting remissions from this disease."

One way to achieve this is to get more "bang from your buck" on drugs already proven to possess safety and efficacy in humans, he notes.  

"Although designed to a specific target, drugs will often have other 'off-targets' some of which may be useful," Torrance concludes. "The only way to determine if they are useful is to profile them on a wide range of patient-relevant disease models to see if unexpected patient-types benefit. This will also happen in this program as approved drugs are also being tested for potential new uses."
 
 
Code: E101017

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