Carolyn Peluso, Ph.D.
. . . in a lab far, far away a postdoc sits nestled in among the test tubes and large, glass sequencing plates. Tapping his pen in time to the soulful sound of the Doobie Brothers, he analyzes 100 base pairs of hard-earned sequencing data, and dreams of an easier way. Years from now, as he tells his graduate students this story, they will unkindly cluck and roll with laughter. That hard-working post-doc of yesteryear was dreaming of next-generation sequencing, but he could never anticipate how it would revolutionize the way we approach cancer research and drug discovery.
Next generation sequencing refers to the high-throughput sequencing techniques that followed first generation Sanger sequencing. These technologies have led to the formation of large-scale sequencing initiatives that have generated a vast amount of actionable data. One such initiative is the Cancer Cell Line Encyclopedia (CCLE). The CCLE is a collaborative effort between Novartis and the Broad Institute that has released mutation data for 1,651 genes for nearly 1,000 cell lines. The CCLE research group used this data set to compare the copy number, expression pattern, and mutation frequency of tumor cell lines with primary tumors and showed that tumor cell lines are reasonably representative of their in vivo counterparts. Additionally, they used the sequencing data to predict that tumor cell lines harboring particular mutations are sensitive to specific classes of drugs1.
Researchers are using this information, and the data from similar initiatives, to build better models to support basic research, and better platforms for screening potential drug candidates. ATCC is contributing to this effort by generating “sets” of tumor cell lines (the ATCC® Tumor Cell Panels) that are annotated with mutational data, and arranged by tumor type, such as Pancreatic (TCP-1026™), Lung (TCP-1016™), and Breast (30-4500K™), or by commonly mutated genes like APC, EGFR, and BRAF.
Alone, these tools have the power to accelerate the research, development, and screening phase of drug discovery. The long-term hope, however, is to couple whole-genome sequencing to the transcript and epigenetic information from a single tumor sample. Having such information at their disposal, researchers will be able to develop better classifications for human cancers, and better, more personalized treatments. So, when they stop laughing, those graduate students should take a minute to thank their advisor. The long hours he spent in the lab, struggling for every base pair and thinking about a better way, were setting the stage for them to make huge strides towards a cure for cancer.
1. Barretina, et al., (2012) Nature 483: 603-607
