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St. Jude's Leukemia Researcher Receives ABI Sequencing Prize

NEW YORK (GenomeWeb News) – Applied Biosystems announced today that St. Jude's Children's Research Hospital pathology researcher Charles Mullighan is the recipient of the company's "What Would You Do with a $10K Genome" grant, which will support his research on acute lymphoblastic leukemia.

Under the program, Mullighan will collaborate with researchers from ABI to sequence normal tissue, leukemia cells at diagnosis, and relapse samples from five pediatric patients at St. Jude. The researchers plan to generate 60 gigabases or 750 million tags of sequencing data in an effort to identify SNPs, large and small insertion/deletions, translocations, and copy number variants associated with ALL, a white blood cell cancer.

ABI, now a subsidiary of Life Technologies following its merger with Invitrogen, will perform sample processing, data generation, and primary data analysis on the SOLiD 3. The project is aimed at uncovering structural variations and other genomic changes associated with ALL in order to understand genomic changes associated with relapse and identify new therapies for the disease.

The "What Would You Do with a $10K Genome" program was developed to motivate new research using genomic technologies as ABI closes in on a $10,000 human genome. Mullighan, who received the first prize award at the annual Advances in Genome Biology and Technology meeting in Marco Island, Florida, was selected from more than 200 applicants.

"The comprehensive identification of genetic changes in tumor cells is a major goal of cancer research, and this grant provides a tremendous opportunity to look across the genome and identify all coding mutations in this disease," Mullighan said in a statement. "Ultimately, our aim is to use this genetic information to identify new pathways and targets for therapy in relapsed acute lymphoblastic leukemia."

Mullighan and his co-workers published a study in the New England Journal of Medicine last month which used microarrays, transcription profiling, and selective re-sequencing to reveal copy number changes associated with ALL relapse. Others recently published a paper using a similar approach to find germline SNPs that can help predict ALL treatment response.

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