Shelly Gunn, M.D., Ph.D.
Tumor sequencing at the time of diagnosis can give significant insight for successful cancer treatment.
There are huge benefits to genomic tumor assessment, both for better treatment now, and later, if first-line treatments fail. But I don’t think many cancer patients—and even some physicians—fully understand how important tumor sequencing can be to successful cancer treatment. Yet.
This is not surprising. Outside of a few tests for breast cancer, we really didn’t have the tools to do this sequencing even just five years ago. The first major breakthrough that I saw in clinical practice was for metastatic melanoma, a very rare clinical scenario where the incidence is maybe 10,000 cases a year. Suddenly in August 2011, there was a machine I could put in my lab, and in one day obtain results of a molecular test that had a tremendous impact on treating the patient, according to whether the tumor was BRAF positive or BRAF negative.
From that time on, there has been an increasing number of solid tumors where we can test for a genetic biomarker that indicates a specifically targeted treatment, such as the FDA-approved testing for EGFR in non-small-cell lung cancer and KRAS in colorectal cancer.
Single gene testing just isn’t adequate anymore, especially with the growing numbers of targeted therapies, both currently FDA-approved and in the pipeline. If a lung tumor isn’t being driven by EGFR, then you immediately want to know whether ALK is involved, and if not ALK then what about ROS, MET, PIK3CA, etc. We need to be looking at multiple genes during our diagnostic testing, not just a few select biomarkers.
Having your tumor sequenced at the time of diagnosis can give valuable guidance for choosing the right course of treatment, but many physicians only turn to large gene panels as a last resort, when the patient’s tumor hasn't responded to conventional therapy or becomes metastatic. Multiplex gene testing is still something of a controversial topic.
One point of controversy is clinical. Clinicians often don’t want too much information early on because it complicates their treatment planning. As a physician, once you know something, you become responsible for that information. It’s great to have a comprehensive test that provides all this detail about the tumor genetics, but the clinician is left having to figure out what this means for treatment. That may just be too much information at a time that’s not helpful, when you just need to implement a treatment plan.
There are computational tools coming online that can help interpret this avalanche of molecular information and give clinicians an easy-to-understand roadmap for each patient’s treatment.
The second controversial issue is who’s going to pay for it? Insurance companies are slowly coming to understand the benefits of paying for a more extensive test. Genetic testing is perceived as expensive, but it’s really no more expensive than the CAT scans and MRIs that are already commonly used serially throughout a course of treatment. I also think payers will soon come to understand that comprehensive gene testing saves money, using a patient’s biomarkers to avoid unnecessary courses of truly expensive “standard therapies” that would be ineffective or even toxic to the patient.
There is also something of a metaphysical controversy surrounding genetic testing. Is it possible, some people ask, that we might learn too much about the patient’s genome and inherited genetic defects?
One way to avoid this issue might be to run a targeted panel, where the genes on the panel have been carefully selected for the role they play in tumor formation, tumor treatment, or drug metabolism. If a biomarker isn’t potentially actionable for cancer treatment planning, it shouldn’t be on the panel.
Of course, what clinicians need to know genetically isn’t always specific to the tumor. Drug metabolism genes, for example, are germ-line markers, which can be tested in tumor samples but are really from the patient’s germ line. I know of one recent instance where the patient turned out to be positive for G6PD (glucose-6-phosphate dehydrogenase). This was extremely helpful information for her and her doctors, because that biomarker is predictive of an adverse reaction to oxidants, a class of drug that can induce a highly oxidated state. Here’s a situation where the clinician was looking for treatment decision support, and computational analysis provided not only some targeted markers but also treatment decision support to say that she has an inherited G6PD mutation that she needs to know about.
Sometimes a targeted panel is just not enough. Another case was referred by a clinician who was asking why a patient was not responding to the Coumadin she was on, in addition to all of the other questions about her tumor. Computational analysis of her genetics showed she had a Factor V Leiden mutation that was causing her not to respond to Coumadin. It can actually be very helpful clinically to have this more general information, but a highly targeted panel would not have identified this issue because it would have been designed not to provide information about genes that didn’t directly help with treatment decisions in an oncology patient.
Our understanding of cancer genetics is growing at a tremendous rate, so I imagine that things that seem controversial now will quickly become accepted practices. I and others have been predicting a shift in how we think about genetic testing, as people discover it makes more sense to get as many answers as possible at diagnosis, even if you don’t act on it at the time of diagnosis. You then have the information if you need it. I think every new cancer patient should have their tumor genome sequenced at the time of diagnosis.
This article was originally published in the September 10 issue of Clinical OMICs. For more content like this and details on how to get a free subscription to this digital publication, go to www.clinicalomics.com.