The mutations provide the potential for highly-targeted cancer therapies, as receptor tyrosine kinases can be targeted by either small molecules or antibodies. Results from the study will be published this week in the Proceedings of the National Academy of Sciences (PNAS). Researchers from the University of California, San Diego also contributed to the project.

Using high throughput DNA sequencing, researchers conducted the first comprehensive DNA sequence analysis of the receptor tyrosine kinase gene family in glioblastomas, an aggressive form of brain cancer. Recent studies have shown receptor tyrosine kinases to be cell regulators responsible for rapid cell growth in cancers, including colorectal, lymphoma, breast, and ovarian cancer.

"We have developed and applied high throughput DNA sequencing technologies and bioinformatics tools to peer into the genomes of glioblastomas in a manner that was previously unattainable," noted Robert L. Strausberg, Ph.D., deputy director of J. Craig Venter Institute and vice president of Human Genomic Medicine, J. Craig Venter Institute.

Researchers sequenced genes from 19 glioblastoma tumors from eight females and 11 males ranging in age from 7 to 77 years and analyzed them against healthy DNA samples. The bi-directional dideoxy sequencing of 20 receptor kinase domains and their adjacent regions revealed novel somatic mutations in fibroblast growth receptor 1 (FGFR1) and frameshift mutations in growth factor receptor alpha (PDFGRA).

"Having identified these previously unknown mutations in key cancer causing genes, we will hopefully enable the development of small molecules and antibodies to regulate their abnormal function and thus inhibit the growth of cancerous cells," explained Andrew Simpson, Ph.D., associate director-programs at Ludwig Institute for Cancer Research. "This collaborative study exemplifies exactly what our coalition was formed to do -- leverage our individual institution's expertise to collectively discover new druggable targets through genome sequencing and functional genomic analysis."

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