Genetic testing and gene sequencing represent a paradigm shift in testing, but labs still have some time to develop a winning strategy for adapting to the new direction in which the field is heading.
The continuing drive toward personalized and precision medicine, combined with the declining cost of genomic sequencing, has led to greater use of genetic testing, most notably in oncology. But there's a problem: Analyzing individual patient samples for specific mutations is time-consuming and not overly efficient when it comes to determining the best treatments for patients.
So, there is a need to speed up the sequencing process, especially as the demand for genetic testing increases, putting pressure on labs to provide accurate, rapid results. In response to this demand, many labs are expected to turn to next-generation sequencing (NGS). NGS, also known as high-throughput sequencing, makes it possible to sequence millions of small DNA fragments simultaneously instead of individually.
NGS can sequence a significant number of base pairs, unlike the standard Sanger sequencing method. Instead of examining single genes, NGS examines several genes simultaneously, yielding diagnostic, prognostic, and predictive (therapeutic) answers more efficiently.
Preparation is key
The challenge many labs face is how to prepare for the expected increase in molecular genetic testing demand, which is notable right now in oncology and has already emerged in other diseases as well. For example, NGS eventually may be used for newborn metabolic screening or to test for germline-based inherited diseases. So, many labs will need to harness NGS to stay competitive.
Currently, the use of genetic testing in labs is not widespread. This means labs and pathology groups have time to develop a genetic testing strategy and figure out how to incorporate genetic testing and NGS into their testing menus.
Labs may find that they don't have important resources that would enable them to offer accurate genetic testing and gene sequencing services. With several sequencing platforms available, labs must determine which one is best for them, based on their potential demand, and undertake a demand-supply analysis. Beyond that, they must have staff with the proper expertise, supported by the necessary IT infrastructure.
"The cost of genetic sequencing has gone down dramatically," said Dr. Dhananjay Chitale, vice chair of anatomic pathology at Henry Ford Hospital in Detroit, in an interview. "And the technology has evolved in such a rapid fashion that from a small amount of nucleic acid from clinical samples, we are able to get high-quality sequencing results."
Much has been learned in the past 15 years through research, and it is now possible to use genetic information in the clinical arena, he added, referring to somatic mutations in oncology settings. Chitale acknowledged the tremendous potential for NGS in germline testing as well.
NGS eventually will evolve into routine testing at many labs, such as for routine blood work, through "out-of-the-box technology," even for small-footprint labs, Chitale noted. He cited small gene panels as one example of NGS usage.
"The price for NGS will continue to decline, making it affordable for more than just large research institutions to perform molecular genetic testing," he said.
Examining demand and capabilities
To create a proper genetic testing strategy, labs should first determine their customer demand for genetic testing, according to Chitale. They should then establish whether they have the required internal expertise and capabilities, including pathologists trained in molecular genetic pathology who can interpret complex test results and translate the data into usable information for clinicians, he explained.
Starting with technologists at the bench level, labs must determine if they're able to do the molecular genetic assay setup and the complex testing necessary. They need doctorate-level staff to oversee operations and conceptualize with pathologists and oncologists to design and validate the needed sequencing assays, such as gene-specific or large gene panels, Chitale said.
IT for data-driven processes
Another important issue, according to Chitale, is IT infrastructure, and the question for many labs is whether they have adequate storage and connectivity. Labs must determine their internal storage capabilities and decide if they are going to outsource HIPAA-compliant data storage. To support the IT efforts, labs might have to hire staff trained in bioinformatics and computational, molecular, and genetic science.
"These scientists have information and training to apply their computational skills to build the informatics support for a lab," he said.
Reflecting on the changes, Chitale noted that this differs from what labs traditionally have done in the past. A health system's labs can perform about 7,500 NGS tests annually, which equates to about 10 TB worth of data, he said.
"It's a heavy data-driven process -- a computational-heavy paradigm shift for clinical pathology laboratories," he emphasized.
Several NGS sequencing platforms are commercially available. To select the most appropriate ones, labs should calculate test volume and consider the type of patient population they will be testing -- for example, different tumor types (lung, breast, or colorectal cancer). Labs need to avoid having too much capacity; otherwise, it will become expensive to run tests, Chitale noted.
Follow the money
When business planning for a molecular laboratory, it's crucial to check the Current Procedural Terminology (CPT) codes, which will drive how much money will come into the lab. The current codes are mostly based on testing individual genes, but Chitale expects the codes in a few years to be bundled for panel-based testing, in which several genes are tested simultaneously.
With bundling, reimbursements will decline, but that will force labs doing molecular genetic testing to move from older sequencing platforms to NGS and panel-based testing, he indicated.
As genetic testing becomes more mainstream, NGS will play a greater role in advancing clinical diagnosis and precision medicine. And as NGS adds knowledge to the clinical decision-making process, it promises to benefit patients and improve health outcomes.