Jun Li
Assistant Professor of Human Genetics
Research Assistant Professor, Center for Computational Medicine and Biology
Thinking big
In the field of human genetics, much progress has been made by small lab groups working on narrowly-defined problems, piecing together information on particular processes or diseases. While many researchers continue that important work, some are also banding together with scientists from different institutions and different disciplines to collaborate on long-term, large-scale research.
Jun Li is one such scientist. He's involved in one of the nation's largest collaborative cancer research initiatives, The Cancer Genome Atlas Project. Funded by the National Cancer Institute and the National Human Genome Research Institute, the project is a comprehensive, coordinated effort to systematically explore the whole range of genomic changes involved in many types of human cancer and to quickly communicate the findings to the research and clinical communities.
"It's the right approach for this particular problem," says Li, who also is a research assistant professor with the Center for Computational Medicine and Biology. "We've been fighting the war on cancer for more than 35 years, and some observers say we've failed, or at best fought to a stalemate. Patient survival has improved, mostly due to better care, but cancer incidence is about the same, and for the most severe types of cancer, people die just as quickly. What's exciting now is that large-scale genome sequencing and other advanced technologies allow us to look at the genetics and the molecular features of tumors from a comprehensive standpoint."
The consortium's first study, a whole-genome analysis of glioblastoma (a particularly deadly form of brain cancer), turned up three previously unknown mutations associated with the disease and yielded other insights that could lead to new diagnosis and treatment strategies. It was noteworthy not only for the results but also for the methods, which involved pulling together and integrating multiple types of data generated by several different analytical techniques from investigators at 18 institutions and organizations.
Li's role in the project is coming up with the statistical techniques to standardize and rigorously analyze the disparate data. After completing the glioblastoma study, the consortium now is performing the same sort of analysis on ovarian cancer. Next up: lung and breast cancer.
"It's exciting, because we're getting answers on some tumor types that, once they are replicated in other studies, will represent major progress in the war on cancer," says Li.
And though he's big on "big science," Li hasn't lost sight of the need for the kinds of smaller-scale studies that have helped U-M achieve its reputation for excellence in human genetics research.
"Global scale projects are not the answer to everything," he says. "To understand what the data mean, to understand how the statistical results play out in real biology, you still need to do smaller-scale validation, which takes years of hard work in the laboratory. We need to strike a balance, to bridge the two worlds, and being involved in the Cancer Genome Atlas Project, as well as being a principal investigator on my own small team at U-M is helping me think about ways of doing that."
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