By: Christie Rizk – Feburary 14, 2018
SAN FRANCISCO (GenomeWeb) – Using gene expression data from pediatric tumor samples, researchers at the California Kids Cancer Comparison (CKCC) project have been able to match 100 percent of their samples to possible treatments for the patients, according to Project Leader and University of California, Santa Cruz Biomolecular Engineering Professor David Haussler.
The project was first funded by the California Initiative to Advance Precision Medicine in August 2015 to build on the UCSC Treehouse Childhood Cancer Project, which was established to enable the sharing of genomic data from various kinds of pediatric cancer from hospitals and cancer centers.
At the Molecular Medicine Tri-Conference in San Francisco today, Haussler gave an update on the CKCC’s progress, noting that its approach of primarily using gene expression data to match patients whose cancers come back, who have proven resistant to treatment, or who have little or no treatment options to therapies that may help them live longer or better lives, has been successful even beyond the initial goals of the project itself.
Out of 146 samples that passed CKCC quality control measures, the project’s researchers found treatments they could present to clinicians for all of the samples, significantly exceeding the initial goal of finding treatment leads for 20 percent of the samples, Haussler said. Further, he added, 79 percent of the treatment leads were found by an automated analysis workflow developed by CKCC researchers, while only 21 percent of the matches had to be determined manually by CKCC data analysts.
CKCC has also built a gene expression map for many types of pediatric cancers, which contains about 11,340 vectors of RNA expression, Haussler said. The gene expression analysis workflow is done in two parts. In the first step, pediatric tumors are molecularly classified based on an analysis of their gene expression. And in the second step, targeted therapies are identified as treatments that could be considered for a given patient, based on the increased expression of druggable gene targets in the patients’ tumors.
“We now know so much about the genome that we can go beyond standard of care in these cases,” Haussler said.
[ Read More ]