Liquid biopsy requires better standardization to realize all the new possibilities for studying metastasis, heterogenicity, treatment efficacy, and disease recurrence. Furthermore, it is critical for clinicians to have confidence in liquid biopsy data to diagnose and treat patients. This is only achievable when consistent and high-quality data is generated at research and all clinical centers. The Liquid Biopsies course at EMBL Advanced Training Centre provides a unique practical training in best practices and pitfalls on the complete liquid biopsy workflow, from sample preparation to data analysis. The course is targeted for clinical laboratory and research scientists interested in learning all aspects of liquid biopsy testing.
A Panel of Experts Discusses Best Practices for Clinical NGS Quality Management in the Rapidly Evolving Field of Clinical Genomics
There is that old adage that says the only thing that is constant is change. This is one of those universal truths we have all come to accept. Heck, even Dunkin' Donuts, widely credited as being the inventor of the word “Donut,” is dropping the word from their brand name. Blasphemy! But that is for another blog...
As seen in the original “The Matrix,” Morpheus offers Neo two pills - a blue one and a red one. Take the blue pill and you continue right where you left off. But take the red pill and suddenly your outlook on things will change and new possibilities emerge.
As Immunotherapy Use Rises, Critical Gaps Remain in Harmonizing Tumor Mutational Burden Measurements
A consortium of industry experts has combined forces to solve TMB challenges.
Recent clinical studies of immuno-oncology (I-O) checkpoint inhibitors have indicated that the tumor burden in a cancer patient’s genome may be predictive of positive response to I-O therapies such as Keytruda® and Opdivo®. The tumor mutational burden (TMB), that is, the number of mutations per megabase of sequenced tumor sample as determined by whole exome sequencing (WES), is currently the most promising biomarker for cancer patient selection and stratification in many clinical trials. Numerous clinical studies are underway to elucidate and validate the role of TMB in I-O treatment decision making and therapeutic response.
A recent study, published in the Journal of Molecular Diagnostics, describes a new, more sensitive Hepatitis B Virus (HBV) assay1. This study, led by Song-Mei Liu, MD, PhD, of the Center for Gene Diagnosis, Zhongnan Hospital of Wuhan University in China, is particularly exciting because the new assay can be used to diagnose hepatocellular carcinoma (HCC) at an earlier stage and to manage antiviral HBV treatments more effectively. It also highlights the way innovative molecular diagnostics can play a synergistic role with the development of new pharmaceutical therapeutics.
One of several important steps in next-generation sequencing (NGS) is tuning the many options provided by mutation callers. Providing values for options configures the signal to noise ratio of the impending mutation calls. In theory, providing values that increase the stringency of mutation calls will reduce the number of false positive calls and thus enrich for true positives. In practice, increasing stringency can eliminate true positives.
Microsatellites are simple tandem repeats that are present at millions of sites in the human genome. Microsatellite Instability (MSI) is defined as a change of any length due to either insertion or deletion of repeating units in a microsatellite within a tumor compared with normal tissue.1 The molecular mechanism for the change in repeat length is slippage of nascent DNA strand with respect to the template strand during replication followed by failure to recognize the mismatch due to deficiency in mismatch repair genes.
In a recent post, we discussed key considerations for designing a robust next-generation sequencing (NGS)-based lung cancer assay. Putting those plans into action in the development phase brings forth a new set of challenges. Through our experience developing NGS reference materials and the relationships we’ve built with assay developers of all stripes, we’ve identified those important factors and ways to navigate them. But before you begin designing and optimizing your assay, you should become very familiar with binomial and Poisson distributions and their use because the outcome of many analytical steps can be modeled and explained with them.
On April 4th, 2018, a new outbreak of Ebola Virus Disease (EVD) occurred in Equateur Province in the Democratic Republic of the Congo. As of June 10th, there have been a total of 55 EVD cases and 28 deaths with a case fatality rate of 50.9%. Although the outbreak remains active, public health authorities have expressed cautious optimism because there have been no new cases in two of the three affected areas (Bikoro and Wangata zones) since May 17th, 2018 and the rate of new cases in the third affected zone (Iboko) has slowed.1