Mayo Clinic Cancer Researchers Targeting Racial Disparities in Genomic Data

Yan Asmann, Ph.D. (left), and Aaron Mansfield, M.D. Courtesy of Mayo Clinic.

Standing at the forefront of Mayo Clinic’s genomics advancements, Yan Asmann, Ph.D., and Aaron Mansfield, M.D. are working to tailor the diagnosis and treatment of certain cancers to a person’s unique genomic makeup.

As a bioinformatician, Dr. Asmann is pursuing individualized therapeutic cancer vaccines that target a person’s distinctive tumor characteristics.  Dr. Mansfield, a medical oncologist, is on a quest to discover biomarkers to predict which patients with cancer could benefit from immunotherapy, a treatment that can stimulate the body’s immune system to attack cancer cells. But beyond their pioneering research, Dr. Asmann and Dr. Mansfield are also leading a major effort to reduce racial disparities in genomic data representation. They say a lack in quantity and quality of diverse genomic data in public research databases used by the global scientific community is hindering the scientific understanding of genomic links to diseases in all populations and escalating healthcare inequities. “We’re on the frontlines of seeing a critical need to address data disparities between racial groups, particularly people of African ancestry. That’s why we’ve launched the Mayo Clinic Data Disparities Project,” says Dr. Asmann, who works at the Mayo Clinic Center for Individualized Medicine in Florida.  “This Data Disparities Project addresses a significant need to study the disparities in cancer research. Our results could potentially lead to an immediate pathway to changing practice with how germline (normal cells) and tumor genomes are sequenced and analyzed in racial minorities to improve treatment selections,” says Dr. Mansfield, co-director of Mayo Clinic Precision Cancer Therapeutics in the Center for Individualized Medicine and Chair of Data Safety and Monitoring in Mayo Clinic Comprehensive Cancer Center.

Breaking Down Barriers to Individualized Medicine

Racial and ethnic minorities often experience cancer disparities in the U.S. with higher disease prevalence, shorter survival times, and higher death rates with many cancer types, according to the National Institutes of Health. These disparities are believed to arise from an interconnection of non-biological (socioeconomic, environmental, and behavioral) and biological factors (genetic and genomic features). The researchers are hopeful they can help address the biological factors to improve healthcare for more people.

The Data Disparities Project is built on a foundation of two recently published studies by Dr. Asmann and Dr. Mansfield. In one study, they found that the quantity of African ancestry patients’ tumor mutations is overestimated, which could lead to inaccurate treatment strategies.  The other study found lower sequencing data quality for ancestrally African patients in the Cancer Genome Atlas, which is one of the largest and most widely used cancer sequencing projects.

At the heart of the Data Disparities Project, Dr. Asmann and Dr. Mansfield are creating a highly detailed genomic map that reveals precise locations where genetic differences between patients with African and European ancestries are difficult to determine. The team is developing analytic solutions to mitigate these data disparities.  With this comprehensive disparity map, the scientists also plan to investigate genetic variations that affect drug safety, drug response, and therapy management. Furthermore, they will work to recommend new sequencing guidelines for identifying clinically notable tumor mutations in patients of different ancestries.

Bridging the data divide

As discoveries driven by genomic data continue to advance individualized medicine, the researchers emphasize that addressing data disparities has taken on an urgent importance. “We’re working to clear a path to a future where every patient fully benefits from individualized medicine,” Dr. Asmann says. “But first we must understand the genomic links to diseases across all populations.”

This article originally published on the Center for Individualized Medicine blog.

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