Saturday, 12 March 2011

OICR's Genomics Pathway-Sequencing Project Highlights Genomic Data's Steady March Into Clinics

OICR's Genomics Pathway-Sequencing Project Highlights Genomic Data's Steady March Into Clinics

The Ontario Institute for Cancer Research has kicked off a project that promises to address some key informatics challenges related to clinical sequencing.
Lincoln Stein, platform leader of informatics and biocomputing at the OICR, described the project in a presentation at the fourth Summit on Translational Bioinformatics in San Francisco this week.
Stein said that the project, conducted in partnership with Canada's Princess Margaret Hospital and dubbed the Genomics Pathway Sequencing project, or GPS, will sequence genes in normal and tumor samples excised from patients.

“The biggest challenge,” Stein said, “is trying to keep the amount of information in this report to a minimum without keeping potentially important information back [from physicians].”

For each individual, OICR researchers will sequence about 1,000 cancer-related genes in control and tumor samples and attempt to identify mutations that are of immediate relevance to the patient’s cancer care, or that are targeted by drugs that are currently being tested in trials.
The genes in the study — which include the usual suspects such as KRAS, p53, and B-Raf — were selected based on suggestions from oncologists in the Toronto area as well as data stored in knowledgebases at the Memorial Sloan Kettering Cancer Center, the Wellcome Trust Sanger Institute, and the National Cancer Institute.
To sequence patient samples, OICR will use Pacific Biosystems' single-molecule sequencing as a first step to discover novel mutations. It will then sequence known mutations on Sequenom's MassArray platform. The sequence variants will be confirmed using a Sanger sequencer housed at the clinical sequencing lab at Princess Margaret hospital.
Stein explained that the OICR selected the PacBio system because “it allows us to do very long reads at high coverage … currently 1,000-base-pair reads in a circular consensus, which gives high accuracy for targeted genes.”
In addition, he said, the platform has a rapid turnaround time, taking only “15 minutes per run to completely analyze … a single typical gene.”

Kevin: fascinating! Would their's become the de facto standard for clinical sequencing?

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