Speaking from the White House podium in June 2000, former U.S. President Bill Clinton said triumphantly, “Without a doubt, this is the most important, most wondrous map ever produced by humankind.” The map he spoke of was the draft human genome—an assemblage of DNA fragments that many believed would lead to a new era in health care—one characterized by personalized medicine.
Though his words may have been hyperbole, there is no doubt that sequencing the human genome was a significant step toward personalized medicine, not because scientists had revealed the human genome, but because they had proven the ability to do so. In publishing this wondrous map, scientists demonstrated they could be genetic cartographers.
We no longer think of DNA in terms of maps, but the basic concept—that a series of data points can coalesce into an informative picture—forms the basis of genetic profiling. Using next-generation sequencing (NGS), researchers and clinicians can collect immense amounts of genetic data from patients that can then be used to better understand, and potentially treat, ailments. This is particularly true in oncology where tumor genetic profiling is used to identify mutations that may be leveraged for more effective care.
It’s been more than 20 years since Clinton’s aspirational speech, and in that time, we’ve learned that pictures built with DNA are far from complete.
Expanding a narrow focus
Malignant transformation and evolution can be driven by a wide range of factors that span the central dogma. However, current tumor profiling is predominantly focused on DNA, and specifically on tumor DNA. As sequencing technology has only recently become widely available, this narrow focus is understandable. However, this narrow focus risks missing critical data.
For example, assays that focus only on tumor data are at a substantial risk of erroneously identifying positive variants. Recent studies suggest that tumor profiling has the potential to identify actionable variants—those mutations that affect the potency of specific therapeutics—in up to 24 percent to 36 percent of patients. However, some studies suggest that roughly 14 percent to 27 percent of the identified variants in tumor-only panels may also be present in non-malignant cells, meaning they’re not tumor specific. These false positives can mislead efforts to identify malignant cells, confounding assessments of therapeutic efficacy.
For this reason, more accurate profiles require sequencing data from both tumor and normal tissue in each patient (so called paired tumor-normal sequencing). Not only can this help identify false positives, but in some instances, it can reveal therapeutically relevant mutations that may have otherwise been overlooked. For example, in recent studies 13 percent to 16 percent of cancer patients were found to have pathogenic variants in their normal tissue. And nearly one third of those patients had their clinical management or therapy altered as a result of the discovery of those variants.
Whole exome sequencing provides comprehensive tumor profiles
Still more comprehensive profiles can be built by incorporating broader sequencing (such as through whole exome sequencing, or WES). Rather than narrowly focusing on genes that are associated with the suspected tumor, WES enables an unbiased search for mutations across the tumor’s exome, ultimately contributing to a more comprehensive picture of the patient’s specific tumor type. Conducting WES on a patient up front has the further advantage of allowing them to be considered for sequence-driven therapies that are new or in clinical trials without the need for additional testing.
Identifying structural variants in tumors
Whether using WES or gene panels, tumor genomic profiles remain severely limited when it comes to identifying structural variants, particularly those that result in gene fusions.
Gene fusions can result from structural variations, as well as aberrant RNA processing. Such events may lead to chimeric proteins that drive tumorigenic phenotypes (such as EWS/FLI1 fusions in Ewing sarcomas). Not only are these fusion events important for understanding tumor evolution, but they may provide novel therapeutic targets. Detecting fusions with targeted sequencing is far from trivial, though, as it requires a prohibitively expensive probe-tiling design (such that all possible introns and junction points are accounted for).
Therefore, including RNA sequencing data in tumor profiling can be invaluable, enabling easier detection of known and novel fusion transcripts. Multiple studies have demonstrated increased identification of actionable variants in patient cohorts when both transcriptomic and genomic data are combined during tumor profiling. And for every advance in actionable variant identification, access to personalized medicine expands.
Understanding how to best treat a patient requires comprehensive profiling
The evolution of tumor genomic profiling continually reminds us that personalized medicine is possible and may even be critical for many patients. But it also makes it clear that DNA sequencing has its limits. To build a future in which personalized medicine is the new standard of care, we will need to go beyond sequencing tumor DNA. We will need to construct a composite picture of human health and disease from an individual’s comprehensive profile—including whole exome, RNA, and tumor, as well as healthy tissue, sequences.