New approach to analyzing tumor genome promises expanded results
Researchers have created a promising new method to accurately and, in some cases, more comprehensively analyze and interpret DNA sequence information from cancer patients. They have developed an algorithm that sorts out genomic mutations and variations and ranks them according to their clinical and biological relevance to a patient's cancer.
The findings eventually may help guide individualized patient treatment or enrollment in clinical trials that test a therapy aimed at a particular genomic alteration. The scientists reported their results May 18, 2014, in the journal Nature Medicine. Their work is supported by the Clinical Sequencing Exploratory Research program at the National Human Genome Research Institute (NHGRI), and the National Cancer Institute, both part of the National Institutes of Health, in addition to other organizations.
Investigators at Dana-Farber Cancer Institute in Boston, the Broad Institute in Cambridge, Mass., and elsewhere focused on the problem of how the clinician might best use the large amounts of data in a cancer patient's protein-coding exome, the portion of the genome where many key cancer-related genes are located. Initially, they showed that two different tumor sample storage methods produced comparable DNA sequencing information - an important step that may enable genomic profiling to become a more accessible tool for clinicians evaluating cancer patients. The researchers then surveyed established cancer databases, studied the medical literature and spoke to experts to develop a database of 121 tumor genomic alterations that could have therapeutic, prognostic and diagnostic implications for cancer patients.
The researchers subsequently devised an algorithm called the Precision Heuristics for Interpreting the Alteration Landscape (PHIAL), which uses information about a patient's genomic alterations and asks a series of questions to determine which of them might be clinically or biologically important. To validate the tool, they tested its use in previous exome sequencing studies of 511 cancer patients. In 80 percent (408/511) of the patients, PHIAL identified more than 1,800 alterations in the 121 genes and detected potentially important but less common genomic alterations in small subsets of individuals. In a separate study, the algorithm identified 29 genes in 16 current patients that might influence clinical decision-making. In one such case, this system helped connect a patient to a clinical trial.
Van Allen, et al. Whole-exome sequencing and clinical interpretation of formalin-fixed, paraffin-embedded tumor samples to guide precision cancer medicine. Nature Medicine. 2014. [Full Text]
Lucia Hindorff, Ph.D., program director in NHGRI's Clinical Sequencing Exploratory Research program, Division of Genomic Medicine
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Last updated: May 19, 2014