SU2C Innovator Grants Fund Big, Bold Ideas
December 7, 2009
William Pao, M.D., Ph.D., associate professor of Medicine, Vanderbilt-Ingram Cancer Center, has been awarded a grant from Stand Up to Cancer (SU2C) to study molecules that could speed up the search for new cancer drugs and targets. He is one of 13 young cancer investigators to earn a grant from SU2C. Over a three-year period, each investigator will receive up to $750,000 from SU2C’s Innovative Research Grants program, which supports the next generation of cancer research leaders.
SU2C raises funds to hasten the pace of groundbreaking translational research that can bring new therapies to patients and save lives. The effort kicked off in September 2008 with a live television broadcast featuring Hollywood stars, network news executives and celebrity athletes.
The new grants support high-risk, high-reward research from young investigators. Scientists from the American Association of Cancer Research (AACR) helped select the grant recipients.
“I am very grateful to be selected for this award,” said Pao, Ingram Associate Professor of Cancer Research and assistant director of Personalized Cancer Medicine. “This grant will allow us to pursue some risky but promising research.”
This is Vanderbilt-Ingram Cancer Center’s second major SU2C grant. Earlier this year, Carlos L. Arteaga, M.D., director of the Vanderbilt-Ingram Breast Cancer Program, and Patty Lee, Patient Research Advocate, were chosen to participate in one of the SU2C Cancer Dream Teams investigating breast cancer.
Pao and his colleagues are studying kinases, molecules inside cells that are involved in telling a cell whether to proliferate. In cancers, these kinases can become aberrant so that they are stuck in the “on” position, telling cells to divide all the time.
“Mutant kinases are very druggable targets, so if you identify the right drug to turn off a specific mutant kinase, you can kill the tumor,” explained Pao.
The best example of this is in Chronic Myelogenous Leukemia (CML) for which there is a kinase called ABL, which is abnormally fused. The discovery of that kinase fusion led to the drug Gleevec, which revolutionized treatment for CML.
Pao and graduate student Juliann Chmielecki have found a way to speed up the search for kinase fusions.
“We devised an unbiased screening strategy to detect potential fusions involving any of the 90 tyrosine kinases in the human genome, using minimal amounts of starting tumor material,” said Pao. “This assay involves new technologies such as ‘exon capture’ and ‘next-generation’ sequencing. We showed that it works and are now ready to start screening tumors for novel fusions.”
Pao believes this focus on genetic profiling of tumors will lead to improvements in personalized medicine.
“We know from history that kinase fusions are likely to be important in cancer,” said Pao. “Many drug companies are developing kinase inhibitors, so there may already be a drug in development that would target a fusion we find. We could then prioritize patients who should receive that drug, based on the genetic profile of their tumor.”
Pao will study tumors that are especially resistant to treatment, like lung cancer tumors that are epidermal growth factor receptor (EGFR) negative and K-ras negative, and will collaborate with Arteaga on the study of triple negative breast tumors.
Zhongming Zhao, Ph.D., associate professor in Biomedical Informatics, and Peilin Jia, Ph.D., research fellow in the same department also are involved in the research. They have written computer algorithms to analyze the flood of sequencing data and to find candidate fusions for further study.
The investigators will be using next generation gene sequencing in their research. New sequencing, microarray, and small molecule screening technologies are resulting in exponential increases in the genomic data analyzed, stored and distributed. For example, just over the past year, 10 trillion base pairs of high-throughput sequence data were submitted to National Center for Biotechnology Information (NCBI) and placed in a new database (Sequence Read Archive) designed specifically for these types of data. To put that number in perspective, these data are already 40 times greater than the 250 billion base pairs that were deposited over the last 20 plus years in NCBI’s GenBank DNA sequence database.