With the rise of next-generation sequencing (NGS) technology, multigene panel testing is expanding so rapidly that clinical practice is racing to keep pace. And questions within genetic tests have expanded along with it, making definitive answers more challenging to come by. The amount of information being published by the research community is virtually exploding in this area, and wading through all this literature is a daunting task. Why? Because this vast landscape of emerging-disease associations is constantly evolving, and it takes time for new findings to be replicated and become definitive.
Meanwhile, physicians are asking broader, less-defined questions to find out if a patient has any hereditary variants (mutations) associated with a particular class of diseases.
Hutton Kearney, Ph.D., leads the Hereditary section of the Genomics Laboratory in Mayo Clinic’s Department of Laboratory Medicine and Pathology (DLMP).
“When your clinical question is more exploratory in nature, and you broaden your search to large, comprehensive panels, or entire exomes or genomes, rather than targeting specific variants, it becomes impossible to limit your return of results to just those pieces of information that are absolutely clear,” she says. “Nearly every nook and cranny of our genome can be revealed to a laboratory, and much of it is not yet curated for disease relevance.”
Then there are the differences between labs and their approach to result filtering, prioritization, and interpretation, which contributes to how test results arrive in the physician’s hands. For example, some labs return an often-lengthy list of detected variants, where others report only findings with definitive clinical relevance. But most laboratories strive to find middle ground, returning both clinically relevant and the most compelling research targets encountered.
“Some physicians, especially those who are more research-oriented, really appreciate an exhaustive list of findings,” says Dr. Kearney. “There are other physicians who feel burdened by that amount of information, and they expect the lab to sift through and return only those findings that have clear clinical relevance. Making that decision as a laboratory is really difficult if you don't have an intimate relationship with your physician and a clear understanding of the clinical question and patient’s medical history.”
Mayo Clinic Laboratories, being a large reference lab that receives hereditary genetic test orders from all over the world, strives to cultivate close relationships with every type of physician so as to better understand and serve their varying needs. This kind of support is invaluable, considering Mayo Clinic Laboratories offers a broad and comprehensive selection of panels and genome-wide exploratory assays.
“We work very hard to find an appropriate balance in our clinical reports, returning variants with definitive literature to support the clinical relevance, as well as those with emerging understanding, that we think might yield clarity with a little more exploration,” says Dr. Kearney. “And the genetic counselors in our group do a terrific job of supporting physicians, especially those who order genetic testing less frequently, when uncertain findings are encountered.”
This kind of counseling support helps physicians avoid misinterpretation of results, such as over-interpretation of a variant of uncertain clinical significance, which might lead to unwarranted medical intervention or predictive testing in family members.
Or, a patient might be given false assurances, according to Jessica Balcom, a certified genetic counselor who manages the Hematopathology-Oncology Genetic Counseling unit in DLMP.
“A patient may be inappropriately counseled after a negative result that their risk for a particular disease is completely eliminated, when in fact the test may have ruled out only a portion of genetic causes of disease, and only a subset of overall risk,” says Balcom.
“For example, a patient testing negative for genetic risk factors for breast cancer would still have a baseline risk for breast cancer and should adhere to recommended general population screening measures such as routine mammogram. It would be inappropriate to counsel this patient that they have no risk and are completely off the hook for screening.”
NGS technology has proven quite important to both somatic and hereditary oncology testing. But its full potential in these clinical areas continues to unfold, as do the complexities. Benjamin Kipp, Ph.D., consultant at Mayo’s Department of Medical Genetics and the Division of Anatomic Pathology, points out some contrasts between these two types of testing:
“Although similarities exist between hereditary and somatic NGS testing, there are nuances associated with somatic testing that can make it more challenging to detect somatic (acquired) variants than germline (hereditary) ones,” he says. “Germline alterations generally occur in all the cells of the body (rare exceptions exist) so every cell analyzed should show the genetic abnormality if present. Whereas somatic changes, as in cancer, may occur only in tumor cells that are often mixed with non-cancer cells in the specimen provided to the laboratory. Cancers can also show tumor heterogeneity, which means not all cancer cells necessarily show the same genetic abnormality throughout the entire tumor.
“In addition, the sample primarily used for cancer testing is formalin-fixed, paraffin-embedded (FFPE) tissue, and the processing of this tissue can cause damage to DNA/RNA, making it more difficult to test. As a result, different laboratory protocols and bioinformatics pipelines are often needed for somatic and germline testing to assure patients get accurate results.”
DNA from tumor tissue (somatic) is geared at clarifying diagnosis, prognosis, and treatment options for the cancer, based on the genetic profile of that tumor (i.e., mutations that arose in that tumor), according to Balcom. “But a small subset of patients who develop cancer are identified at higher risk for hereditary cancer syndrome, and may be referred for genetic testing for that reason,” she says.
“In this case, the testing is looking for a germline mutation that’s inherited or present from birth in all cells of the body. We want to see if a germline mutation could have predisposed that patient to develop cancer, puts them at higher risk for additional cancers, and if it could pose a risk to other relatives.”
Another ongoing question with any area of genetic testing is: how hard do you look? How big of a “net” should you cast when answering a clinical question based on an affected family member’s genetic risk or symptoms? And when is it more appropriate to analyze small as opposed to large gene panels, whole exomes, or whole genomes?
These different testing options can be generally categorized as “disease-specific” smaller panels versus “non-disease specific” large panels, according to Dr. Kipp. “If you are testing a patient suspected of having, for example, Lynch syndrome, it makes sense to test that patient with a hereditary colon cancer panel because you know what disease you’re targeting and the genes associated with that diagnosis,” he says. “The benefits of using disease-specific panels are that they are generally cheaper, have better turnaround time, and there is less chance of identifying variants of unknown significance.”
On the other hand, if one is assessing a patient whose symptoms or phenotype are not specific to a diagnosis, then using a broader or larger “net” (e.g., exome) may be the preferred approach. “Large panel testing increases the chance of finding a disease-causing alteration in a less commonly altered gene that may not be interrogated with a disease-specific panel,” says Dr. Kipp.
Balcom further explains, saying, “This ‘broad net’ exploratory testing approach, using genomic testing strategies—whole exome or whole genome sequencing approaches—generally comes into consideration for patients who have a complex clinical presentation that doesn’t obviously point to a specific diagnosis.”
Because of the sheer amount of genetic data returned from broader testing, there’s a much more involved process of bioinformatics filtering, which is needed to prioritize the most relevant findings for further in-depth analysis. Balcom continues: “There are also going to be regions of the genome that aren’t as well covered by sequencing. This testing is to some extent sacrificing depth for breadth. So it’s not always going to be the best bet for every patient testing scenario to jump right to that broad testing.”
When it comes to casting this larger “net,” Mayo has an advantage because of its talented bioinformatics team. “We have very creative and comprehensive test validation paradigms,” says Dr. Kearney, “where we challenge classes of variants in different genomic contexts and we extrapolate from the measured performance to predict the ability of our tests to detect all types of potential variants that might be encountered in clinical testing. I think Mayo excels at that.”
However you slice it, the pros and cons of these testing strategies are nuanced and complex. Dr. Kipp summarizes the genetic testing landscape thusly: “There is currently not a one-size-fits-all NGS test for all patients.”