Due to either staff turnover or increased testing demand, your clinical genomics laboratory is expanding. You need your new personnel trained and ready to perform at the same high level as the rest of your staff as soon as possible.
You know that the best training programs are guided ones, with samples and workflows similar to those your new staff members will encounter on a day-to-day basis.
Are your remnant patient samples up to the task?
Clinical NGS tests may be powerful diagnostic tools for your molecular pathology laboratory, but they remain complex amalgamations of different hardware, reagents, and software systems — often from several different vendors and with different levels of quality. Only one of these critical reagents or systems has to fail or underperform in an assay to cause performance drift.
If you don’t catch assay drift quickly enough, it can lead to assay failures such as false positives or unexpected changes to assay performance — such as those that impact limit of detection (LoD).
How can your lab protect itself better? Avoid these two common mistakes:
Common Lab Mistakes,
Downtime can be devastating to a clinical testing laboratory. The timely return of test results is critical for effective patient care. Any delay can hurt your lab’s reputation and prompt your customers to seek testing services elsewhere.
Unfortunately, any clinical testing laboratory using sophisticated next-generation sequencing or other genetic analysis technology will suffer downtime sooner or later.
The question is, how fast can you recover?
What Causes Downtime?
There are myriad factors that could cause your laboratory to cease operations:
- Simple operator error - anything from a sample mix-up to a PCR contamination - can cause a downstream problem that can take days or weeks to identify and correct.
- Poorly-performing vendor supplied reagents, kits, instruments, or software.
Operators Are Human; Mistakes Can and Do Happen
As it makes its way through your lab, a patient sample interacts with a wide range of operators, materials, and instrumentation. Mistakes can creep in at any point along this process, including:
- Labeling and accessioning.
- The use of particular reagents.
- The setting of instrument parameters.
- The informatics pipeline.
When an error does occur, it can take a long time and a lot of effort to determine root cause and take action to fix it. Without an appropriate reference standard, the problem becomes more complex, as the number of potential causes increases exponentially.
Here is an example:
In the course of patient care, formalin-fixation and paraffin-embedding (FFPE) of biopsy tissue samples are routinely performed, where these samples can be analyzed by histology and archived to link the sample with clinical long-term follow-up. With the development of advanced NGS-based oncology gene panels, it is becoming increasingly important to consider pre-analytic variables when extracting nucleic acids from FFPE-treated samples. This post covers frequently asked questions (FAQs) around the extraction of nucleic acids from FFPE samples for downstream NGS analysis.
next gen sequencing,
FFPE Tissue Kit,
On January 23-25, 2017 the Precision Medicine World Congress was held in Mountain View, California. The PWMC conference kicked off with Dr. Keith Yamamoto, Vice Chancellor for Science and Policy and Strategy UCSF, with Dr. Robert Califf, FDA Commissioner in a “fireside chat” format. Dr. Califf has been with the FDA for 2 years, has served as Commissioner for 11 months, but has resigned as of January 20th 2017. One of his important parting thoughts presented was how the FDA has been re-energized by the 21st Century Cures Act to hire new scientific talent to implement the President’s Precision Medicine and Cancer Moonshot plans.
limit of detection,
Precision Medicine World Congress,
During my time spent in academia, I studied in a laboratory focused on molecular switches. Although cellular signaling cascades appear as nothing more than incomprehensible spiderwebs when viewed graphically, the concept is very straightforward: certain molecules can act to regulate cellular processes by functioning like electrical switches. Just as light switches in your home complete or break a circuit to control the flow of electrical current, molecular switches such as Ras GTPases (PDF) control whether certain signals can elicit a cellular response.
New Reference Material,
Variant Allele Frequencies,
Hypertrophic Cardiomyopathy (HCM) is a disease where the heart muscle is enlarged and a significant cause of sudden cardiac death, and is frequently asymptomatic. HCM is commonly caused by a mutation in one of nine heart muscle genes that comprise the sarcomere, and occurs at a prevalence of about 1 in 500 in the general population. HCM is the leading cause of cardiac death in young athletes in the United States.
Clinical genetic testing for mutations in the HCM-related genes has been ongoing for over a decade; the GeneTest.org database reveals 105 laboratories offering some version of genetic testing. While knowledge of prevalent pathogenic variants are available, the majority of variants remain private (that is, unpublished and not widely available). The move to NGS-based gene panels for HCM testing has lead to new challenges for test development, validation and routine quality control due to the inherent scarcity of samples, the cost of including numerous single mutations from these individual samples, and the lack of these materials for laboratories without a long history of testing.
next gen sequencing,
Clinical Genetic Testing,
multiplexed referenence materials,
Previously, we wrote about some of the Quality Control challenges that clinical laboratories performing Next Generation Sequencing (NGS) face towards ensuring their assays are safe and effective for guiding medical management decisions. Reliable access to high quality reference materials is necessary to help overcome these challenges; however, it is not sufficient. Insights that reference materials provide into the health of an NGS assay are only as good as laboratories’ ability to use their QC data effectively.
With limited time and resources to collect, organize, access, and analyze QC metrics, laboratories may frequently rely on reference materials as binary indicators of Pass/Fail: As long as the expected endpoint results are obtained, an assay is considered to be performing well. The drawback of this approach is that it is reactive, rather than proactive: A sufficient number of failures must occur within a given timeframe before a troubleshooting investigation is performed. By the time a problem is recognized, resources have been wasted and turnaround times (TAT) delayed; in some cases, fidelity of patient results may even have been put at risk. Additional time and costs are then incurred as the investigation proceeds.
Specimen analysis by NGS yields a wealth of information in addition to endpoint variant calls that is indicative of assay performance. Data such as nucleic acid quantity and quality at different steps throughout the workflow (PDF) and sequencing library characteristics are generated every time a reference material is tested. However, these data must be carefully tracked and trended to allow use as highly informative QC parameters. For clinical laboratories whose primary focus is on patient testing and reporting, granular QC metrics may not be captured and reviewed as part of routine test monitoring.
Sequencing quality control,
next gen sequencing,
Since the introduction of the GS20 in 2005 by 454 Life Sciences, Next Generation Sequencing (NGS) has found many applications in clinical diagnostics. As a result of this transition from the long-held gold standard, Sanger sequencing, the primary challenge for clinical laboratories has shifted from data acquisition to ensuring these tests are safe and effective for guiding medical management decisions.
Many laboratories struggle to gain a thorough understanding of the analytic performance characteristics of their NGS tests. The difficulty arises from the fact that these assays are comprised of highly complex, fragmented workflows, and have many different intended uses. However, across the various practices currently used for NGS assay development, validation, and performance monitoring, there is a common goal: results must be as accurate, precise, and consistent as possible.
next gen sequencing,
If you took a university introductory statistics course, you may have learned the distinction between accuracy and precision. It may likely have been presented with an archery analogy, where ‘Accurate’ was represented by arrows loosely clustered around the target’s bull’s-eye, ‘Precise’ was shown as a tight grouping displaced from the center, and ‘Accurate and Precise’ was depicted as what every archer aims for, a tight grouping directly at the bull’s-eye. Suddenly, words that are used interchangeably in everyday conversation took on dramatically different meanings.
Tumor Mutation Mix,
Sequencing quality control,
Good Manufacturing Practices,