Actionable Physician Reports
“Our goal is to develop actionable sequencing reports for physicians,” says Rong Chen, Ph.D., assistant professor and director of clinical genome sequencing, Icahn School of Medicine at Mount Sinai. “These reports indicate which drugs would most likely benefit a particular patient, which drugs would have toxicities, and which clinical trials might enroll the patient.”
Dr. Chen’s team builds a decision tree for each FDA-approved treatment as well as drugs that have not yet been approved but appear to have potential benefits, as indicated by molecular network information or in vitro or in vivo studies. A sophisticated Hadoop-based search engine combs though vast amounts of publicly available knowledge and integrates information at the DNA, RNA, and protein levels.
“While the bioinformatics workflow to generate driver mutation analysis is very involved, the resulting report should be tailored to the physician’s workflow,” continues Dr. Chen. “We received a lot of feedback from oncologists on how to provide the most useful information and layouts. In the future, we hope to automate the process to reach a critical mass of physicians and then start receiving their feedback regarding success of the suggested treatment.”
Dr. Chen recognizes that genome interpretation may be confounded by inaccuracies that arise from the sequencing process itself or related procedures such as alignment, variant calling, and functional annotation. Dr. Chen’s team deploys multiple strategies to address the known causes of error. These include sequencing on two different platforms and utilizing multiple variant callers and sequence aligners. In addition, the team manually reviews the most important calls and checks raw reads of known driver mutations to avoid false-negative calls. “Mistakes are unacceptable,” insists Dr. Chen. “Treatment outcomes depend on accurate information.”
Dr. Chen’s group continues to develop methods to integrate and translate various molecular measurements in the public repositories into biomarkers for the diagnosis of disease. For example, the group’s ActiVar database contains 110 million distinct variants; 600,000 genome, exome, and genotyping data points; and manually curated human genetics papers.
Dr. Chen’s latest initiative, the Resiliance Project, aims to find secondary mutations that “balance” the disease-causing mutations. It aims to find individuals with catastrophic genetic mutations that somehow remain healthy, presumably via protections afforded by yet undiscovered genetic or environmental factors.
The Resiliance Project is the first systematic attempt to recruit “unexpected heroes” —people willing to donate their DNA in order to further research into mechanisms of disease prevention. “This project takes full advantage of all our previous experience in generating the highest quality sequencing and annotation workflow,” concludes Dr. Chen.