This is part 2 of 2 of the MRD blog post. (Click here for part 1). In this section, we will discuss how to overcome some of the most common challenges of MRD testing. Overcoming the Challenges In order to mitigate sequencing errors, methods using Molecular Barcodes (MBCs), Unique Molecular Identifiers (UMIs), etc. (which are essentially all the same) may be used, where each starting molecule is sequenced many times. The MBCs are then used to generate consensus sequences from sequences that were likely obtained from the same starting molecule. The assumption is that errors appear due to somewhat stochastic processes and that the consensus sequences will likely be correct. This requires many observations of the same starting molecule, so it will be recommended to generate 10-fold more sequences than there are molecules. Therefore, with 8,000 genomic equivalents, we might want to target a sequencing depth of 80,000. This is a reason why using 10-fold more input ccfDNA may not necessarily be a good thing (in addition to having to obtain a 10-fold larger liquid biopsy) since we may have to increase sequencing depth accordingly to 800,000, which could increase the cost of sequencing 10-fold, which could reduce the likelihood for payment and running the assay profitably.

Part 1 of 2   Background Measurable Residual Disease (MRD) monitoring – for purposes of this blog – will be the act of looking for somatic variants in a liquid biopsy sample by analyzing circulating cell-free DNA (ccfDNA). This is done to monitor the disappearance of a metastatic solid tumor during treatment and to follow any future reemergence of that cancer. Analyzing ccfDNA assumes that circulating tumor DNA (ctDNA) will be present, and the median ctDNA frequency in patient samples across cancers seems to be around 0.5 to 1 %. Thus, the median variant allele frequencies (VAFs) of the somatic variants will start around this range, and the goal of MRD monitoring is to be able to detect them at much lower VAFs. This can be challenging and if we are going to design an assay for MRD monitoring, then we need to be aware of them and overcome them.

Overview Tumor mutational burden (TMB) is a measurement of the number of mutations carried by a tumor cell genome. By comparing DNA sequences from a patient’s healthy tissue and tumor cells, and using a number of complex algorithms, scientists can determine the number of acquired somatic mutations present in tumors but not in normal tissues.1 NGS is the primary method employed to measure TMB, either through targeted panels or whole exome sequencing (WES);2 the latter is considered the gold-standard measurement today.

The plans for this year’s NIPT and PGT conferences, like many others, were quickly derailed by the COVID-19 pandemic. The ESHG and ESHRE Annual Meetings were moved to virtual space and even though the format was a new experience, the science did not disappoint. Here we will share some of the highlights from the sessions.

    Tumor profiling assay workflows start from a tissue biopsy sample that is formalin fixed and paraffin embedded (FFPE), a process that introduces various kinds of damage in the nucleic acids in the tissue specimen. Reference materials that closely mimic the damage profile of patient FFPE samples are lacking. Depurination, depyrimidination, deamination, oxidation, nicks, and double strand breaks may be found in DNA extracted from FFPE tissue, despite the use of extraction kits that attempt to repair some of this damage. We have developed a formalin-damaged, multiplexed biosynthetic reference material, Seraseq® Compromised FFPE Tumor DNA, as well as a companion wild-type (WT) material, Seraseq Compromised FFPE WT, to mimic the damage found in patient samples that can be used to assess the entire tumor profiling workflow. We compared the performance of these reference materials in downstream assays to that of FFPE material with minimal DNA damage such as the Seraseq FFPE WT (DNA/RNA) RM product.

 

  A staffing crisis may be looming in the nation’s clinical testing laboratories, and many labs are already facing the problem. Labs are understaffed, while the demand for clinical testing is only going up. Turnover is high among lab technicians, as burnout and job dissatisfaction leads them to seek employment elsewhere or abandon their lab tech careers altogether. For lab directors, frequent turnover, diminished staffing, and employee unhappiness are vexing issues. A staff of motivated, qualified, and experienced technicians is one of the keys to generating the high volume of accurate, reportable results clinicians and healthcare organizations demand. How can you hold on to your best technicians while getting your newest team members up to the same skill level quickly? As we’ll see, an efficient and effective training program is essential. Well-trained technicians are more likely to stay in their jobs. New technicians perform at a higher level sooner when their labs prepare them for the variations they’ll encounter when working with real patient samples.

  What is a clinical laboratory director’s worst nightmare? That’s an easy one. The thought that, somehow, an inaccurate testing result has escaped their lab and convinced an unsuspecting clinician to make a poor patient care decision. So much of modern medical care is grounded in treatment decisions based on diagnostic testing results. According to one review of the data, 98 percent of in-patient populations get lab tests. False negatives can delay life-saving and life-improving patient care. False positives can cause patients to undergo unnecessary treatment, which can result in needless psychological, physical, and financial distress. No wonder lab directors are troubled by the possibility, no matter how small, of reporting inaccurate results - critical patient care decisions hang in the balance. (Not to mention the professional reputations of lab directors, the reputations of their labs and hospitals, and the trust of patients and clinicians.) To prevent errors in testing and reporting, quality control is a must. You need to be confident every time you report a result that your assays are working the way they are intended. Here are four tips for optimizing quality control to ensure accurate results in your clinical lab:

  Proficiency testing under CLIA is no joke. Failed tests lead to costly downtime for equipment and personnel as labs troubleshoot to find the source of an error. In the case of proficiency testing (PT), failures lead to time invested in corrective-action measures, and in the worst case, cease-testing directives from regulatory authorities. A failed CLIA proficiency test — multiple failures, especially — is the ultimate black mark not only on the career of a lab director but on the reputation of a clinical lab.  The key to CLIA confidence is the same simple approach you took to ace your exams back in college: preparation. If you run your assays through their paces on a regular basis, and you use high-quality third-party controls to root out any weak points in your testing protocol and train your lab staff, CLIA proficiency testing will be a breeze.

Do you consider yourself a control freak? And by control, we mean quality control - the procedures and materials implemented to ensure test accuracy and precision. Most importantly, having the proper controls in place provides confidence in the accuracy of your tests and the reported results, reducing the risk of generating false-positives or false-negatives. A strong quality program has the added benefits of reducing both the amount of valuable staff time expended on troubleshooting, as well as costly instrument and assay downtime.