Researchers have developed a cancer genetics database that may help personalize treatment, according to a study conducted at the Cancer Genome Project at the Wellcome Trust Sanger Institute.
The researchers, who will conduct a 5-year study, hope to find the best combinations of treatments for a wide range of cancer types. To determine the most effective drug or combination of drugs in the lab, researchers will expose approximately 1,000 cancer cell lines to 400 anticancer treatments, alone or in combination. Each cell line has been genetically fingerprinted and researchers will design clinical studies in which treatment will be selected based on a patient’s cancer mutation spectrum.
In an initial dataset of responses from 350 cancer samples to 18 anticancer treatments, researchers reported the data confirms several genes that predict therapeutic response in different cancer types.
Continue Reading
“It is very encouraging that we are able to clearly identify drug-gene interactions that are known to have clinical impact at an early stage in the study,” said Ultan McDermott, MD, Faculty Investigator at the Wellcome Trust Sanger Institute. “ It suggests that we will discover many novel interactions even before we have the full complement of cancer cell lines and drugs screened.”
The authors explained that further results from the study should, over the 5-year period, provide information about interactions between mutations and drug sensitivities most likely to translate into benefit for patients.
“We need better information linking tumor genotypes to drug sensitivities across the broad spectrum of cancer heterogeneity, and then we need to be in position to apply that research foundation to improve patient care,” said Professor Daniel Haber, Director of the Cancer Centre at Massachusetts General Hospital and Harvard Medical School. “The effectiveness of novel targeted cancer agents could be substantially improved by directing treatment towards those patients that [the] genetic study suggests are most likely to benefit, thus ‘personalizing’ cancer treatment.”
