Precision medicine for cancer patients may not always be so precise
USC researchers create an online tool that minimizes inaccurate results due to inadequate genetic population data
A new study finds that precision medicine for oncology genetic testing to determine the best drug treatment for each cancer patient is not always so precise when applied to people of non-European descent.
In precision medicine for oncology, scientists identify mutations that transform healthy cells into tumor cells. In an ideal world, they would then be able to compare genetic variations from the tumor to the patients normal tissue. However, a normal tissue sample is often not available. So scientists use a stand-in: population databases that filter out benign genetic changes from those that may cause cancer.
Patients whose tumor-cell sequencing cannot be compared to their normal-cell sequencing run the risk of being misdiagnosed, researchers said.
The field of precision medicine isnt taking into account population differences. The approaches being used are imprecise when you look at very specific populations, said John Carpten, one of the studys lead authors and director of the Institute of Translational Genomics at the Keck School of Medicine of USC.
The study, published Oct. 19 in the journal BMC Medical Genomics, found that precision medicine using a tumor-only approach to guide therapeutic intervention is less precise for people whose ancestors are from Latin America, Africa and Asia.
You might be getting the wrong therapy simply because of our lack of understanding of the genetic architecture of your ancestry, said David W. Craig, the studys senior author and vice chair of the Keck School of Medicines Department of Translational Genomics. These findings argue that were really not doing a very good job of doing precision medicine for many populations.
A multi-pronged problem
Many hospitals, especially in underdeveloped nations, collect tumor tissue for research purposes without collecting normal tissue for comparison. Without normal cell samples, it is difficult to determine which mutations potentially cause cancer and which are benign variants in the human genome.
It is very difficult to identify a somatic, or potentially cancer-causing, variant when you don’t have a germline, or normal, sample, said Rebecca Halperin, an assistant research professor of the Arizona-based Translational Genomics Research Institute (TGen) and the studys other lead author.
The other part of the problem is that most of the tens of thousands of individuals worldwide who have undergone whole-genome sequencing the spelling out of the nearly 3 billion chemical bases in their DNA are of European descent. This creates a bias in existing databases, which are used to exclude potentially inaccurate results called false-positive variants.
European ancestry turns out to be among the least diverse genetically. This population, particularly Scandinavians, has the fewest genetic variants, the study said.
There is a need to sample more people from more diverse parts of the world, Carpten said.
People whose ancestry can be traced to less developed parts of the world areas that have experienced the most rapid population increases in recent history have the most genetic variants. Bangladeshi people, for example, possess one of the worlds most diverse genomes.
The scientific community is beginning to see the shortfalls of precision medicine, said Rick Kittles, a premier scientist in population genetics and cancer.
This study provides insight on the lack of genetic data from diverse populations and its impact on the value and utility of precision medicine.
This study goes beyond the barriers to participation and provides insight on the lack of genetic data from diverse populations and its impact on the value and utility of precision medicine, said Kittles, a founding director of the Division of Health Equities at City of Hope. There is still much work to be done in order for all communities to benefit from precision medicine.
Lighting up the problem areas
USC and TGen are trying to move precision medicine forward. To help researchers sort out potentially inaccurate results, USC and TGen researchers created a computational tool called LumosVar: Lumos means light and Var refers to genetic variance. LumosVar lights up the genomes potentially cancer-causing genetic mutations.
Simply sequencing more individuals from various populations is not enough, Craig said. We really need access to the cells that were passed on from previous generations. But when those arent available, we need better tools. LumosVar is one such tool.
Craig and Halperin are the co-creators of LumosVar, an open-source tool to search for potentially cancer-causing mutations.
The study was funded by The Ben & Catherine Ivy Foundation and the Multiple Myeloma Research Foundation.