July 16, 2022
Mayo Clinic researchers have identified disparities in the genomic data included in The Cancer Genome Atlas (TCGA). The study was published in the March 2022 edition of the Journal of the National Cancer Institute. This research and efforts like it are the first steps toward identifying gaps and areas for improvement and working toward equitable individualized medicine for all.
"As a researcher, I often hear from clinicians about personalized medicine and designing solutions that are tailored for each patient," said Yan W. Asmann, Ph.D., a bioinformatician at Mayo Clinic in Jacksonville, Florida, and senior author of the study. "Each patient is different and that includes genetics and genomics differences between race."
The gaps discovered in TCGA impact ancestrally African patients at higher rates than those of other ancestries. Aaron S. Mansfield, M.D., is an oncologist at Mayo Clinic in Rochester, Minnesota. He noticed these gaps in his practice, leading him to look further into the issue and connecting him with Dr. Asmann's work analyzing TCGA.
"When the genomic information came back, some patients didn't have any actionable mutations amenable to treatment with targeted therapy, but lots of variants of unknown significance were identified. Anecdotally, patients of European ancestry seemed to have fewer variants of unknown significance," said Dr. Mansfield.
Analyzing TCGA
For this study, genetically inferred African and European ancestry were used rather than self-reported ancestry from TCGA participants, but this inference confirmed reported race with very few exceptions. Researchers compared the quality of both germline and tumor exomes between ancestrally African and European patients for seven cancers.
Each cancer analyzed had at least 50 self-reported Black patients. Exomes were analyzed for sequencing depth, tumor purity, and qualities of germline variants and somatic mutations. For six of the seven cancer types reviewed, ancestrally African exomes were covered at a statistically significant lower sequencing depth than ancestrally European exomes. These six include breast, prostate, lung, uterine, kidney and colon cancers.
"There are holes in the depths of coverage, and those gaps impact people of African ancestry more than others," said Dr. Mansfield. "Part of this we now understand."
The researchers used breast cancer as an example to demonstrate the potential cause. According to the report, the ancestral difference likely resulted from different exome capture kits used to sequence exomes in different temporal batches. The older kits were sequenced at higher depths regardless of ancestry. At the time of earlier batches, ancestrally European patients were overrepresented leading to higher depths of coverage among those exomes.
"Every patient's genome is compared against the human reference genome," Dr. Asmann explains. "The reference genome itself, however, has racial bias because it came from patients mostly of European ancestry."
The researchers further evaluated factors contributing to sequencing depth including tumor purity, capture kit, sample collection and sequencing centers. Due to missing values among these variables, the factors were evaluated separately instead of by a single statistical model.
Working toward individualized medicine
The first step in creating more equitable individualized medicine is finding the gaps, which was a primary goal of this study. While the field is going in the right direction, there is still much work to be done.
"A single change in DNA can be the trigger that takes a premalignant lesion to cancer," said Dr. Mansfield. "For some drugs, a single change in DNA can predict which of them will work."
If one of the metrics is significantly inflated or incorrectly called abnormal, it can negatively impact a clinician's therapeutic recommendations. Accurate metrics and individualized data can help clinicians find the therapies that will be most valuable for their patients.
"With the available therapies that are FDA approved, you need this level of precision to make the right choices," said Dr. Mansfield. "You want the utmost accuracy of every DNA base to make sure you understand what is or is not changed between the tumor and germline."
Dr. Asmann points out other applications of accurate genetic data including drug response and creation of personalized neoantigen vaccines. She, Dr. Mansfield and their colleagues are working on a digital solution to address these gaps at a clinical level.
In the meantime, the most accurate way to sequence a patient's cancer can be to sequence both the patient's tumor and normal cells. Clinically this can be more difficult and more expensive to do. While it is not standard of care, it can help provide a more accurate comparison between a patient's tumor and their own genetic information.
For more information
Wickland, et al. Lower exome sequencing coverage of ancestrally African patients in The Cancer Genome Atlas. JNCI: Journal of the National Cancer Institute, 2022; doi: djac054
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