HPC Enables Genome Analysis Used to Alter Course of Patient’s Cancer Treatment

Research at the Washington University School of Medicine in St. Louis has shown how sequencing cancer patients’ genomes can yield important personalized insights into the nature of each patient’s individual condition.  In a case described below, rapid turn around of this analysis allowed doctors to alter the course of a cancer patient’s treatment.  This rapid turn around was enabled by high-throughput sequencing technology backed by The Genome Institute‘s High Performance Computing (HPC) resources to iteratively analyze over 90 billion data points.

As reported by The Genome Institute at Washington University in St. Louis:

In one case, sequencing the genome of a 39-year-old woman with acute myeloid leukemia (AML) uncovered a novel genetic mistake, leading doctors to change the course of her treatment. Instead of a stem cell transplant, which had been recommended because standard testing indicated poor survival odds, she was treated with a targeted chemotherapy regimen and is now in remission.

Left Tim Ley and Rick Wilson looking at a flow cell in the genome sequencing lab.

Dr. Timothy Ley, left, and Dr. Richard Wilson and colleagues have shown the power of sequencing cancer patients’ genomes as a diagnostic tool. CREDIT: Robert Boston

The sequencing of this patient’s cancer genome was done in around seven weeks.  As the sequencing was done, massively parallel DNA sequencing machines cranked out streams of data directly to The Genome Institute’s storage arrays.  As each batch of sequencing was completed, the Institute’s automated Laboratory Information Management System (LIMS) triggered a round of computational analyses to run on internal HPC resources.  The results provide important metrics to lab staff and are also automatically passed on to an automated secondary analysis pipeline.  This pipeline launches a number of other jobs in parallel to provide input to the research team.  From there, researchers begin to analyze the data and launch other batches of computational jobs as needed.

With job prioritization, careful attention to detail and on the order of ten thousand CPU core hours and tens of terabytes of stored and intermediate data, the Institute was able to use HPC to keep up with the massive data rates needed to do this thorough analysis and quality checking and to get this data back to the patient’s doctors for critical treatment decisions.

See the resources below for more information about how genome sequencing is helping to impact personalized medicine:

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