Researchers at the Mayo Clinic in Scottsdale, Ariz., and at the nearby Translational Genomics Research Institute in Phoenix are moving clinicians one step closer to using whole-genome sequencing as a diagnostic tool. The team successfully sequenced tumor and normal cells from a male patient with pancreatic cancer, making him the first patient at the Mayo Clinic to undergo whole-genome sequencing. After comparing both sequences — which totaled more than 6 billion bases — clinicians and researchers were able to pinpoint genetic changes that were crucial in tailoring a more effective treatment plan for the patient. According to Mitesh Borad, an assistant professor at the Mayo Clinic, this study not only revealed useful discoveries that could make a difference in a single patient's recovery, it also demonstrated that whole-genome sequencing can be utilized in the clinic in a timely fashion.
"Our work demonstrates that turnaround can be achieved in a timeline that is conducive to point-of-care application of results — roughly six to eight weeks," Borad says. "Whole-genome sequencing had long been identified as a potential game-changer, but cost and time limitations had prevented its application in a comprehensive fashion," he adds. But even with clinicians' concerns over cost and turnaround time on the decline, regulatory hurdles — such as Clinical Laboratory Improvement Amendments considerations — remain. "Despite these concerns, utilization of this approach are clearly the way forward, and it is only a matter of time before whole- or targeted-genome sequencing becomes routine in the clinical sphere, ranging from primary care to specialty areas such as oncology." As part of this study, Borad and his colleagues also report their detection of several previously unrecognized polymorphisms in a number of proteins implicated in pathways amenable to therapeutic intervention.
In addition to the pancreatic case study, the Mayo Clinic-led team also used whole-genome sequencing on an acute myelogenous leukemia patient, in whom they found a novel mutation in IDH1. In their subsequent analysis of 187 additional samples, the team found 15 other AML cases with this mutation. "We have more demand for this sort of technology than available capacity, especially with regards to trained professionals in the sphere of genomic bio-informatics," Borad says. "Hopefully, the availability of next-generation bioinformatic tools will allow for this piece of the process to become largely automated in the future. Scaling up and streamlining to further reduce timelines and cost will be key priorities as well."