Next generation sequencing for clinical tumor profiling can be considered to have four levels of analysis beginning with the conversion of raw data into sequencing data (FASTQ), alignment and variant calling (BAM, vcf),  annotation (filtered vcf), and interpretation (clinical report). Over the past few years the path of the first three of these steps have been extensively discussed and published, while the latter of interpretation, or clinical reporting, remains much less so. There are likely many reasons for this discrepancy, including intellectual property, but foremost is the lack of involvement of clinicians in the actual clinical reporting process. At the root cause of this issue is the lack of established clinically oriented knowledge informatics databases at the variant level. This talk will provide a background on the use of one or more knowledge informatics databases at the variant level that allows for the involvement of clinicians in the actual clinical reporting process beyond the typical analytical phases of analysis.

After years of improved cancer therapy, we still struggle to understand malignancies. A major obstacle is our lack of understanding of cancer complexity and its microenvironment. In the last years, we and others developed tools to uncover the transcriptomes of patient-derived single cells. This cutting-edge approach, complimented with other technologies, is central in understanding tumors by creating detailed atlases.

Infectious disease detection is of critical importance in today’s pandemic-stricken world. Clinical metagenomics with next generation sequencing uniquely addresses the challenges of pathogen detection and surveillance using breakthrough technologies such as the Explify® Platform from IDbyDNA. Explify converts sequencing data to insight by applying robust bioinformatics and machine learning, and can be applied to unbiased shotgun sequencing, focused amplicon sequencing, or syndrome-based target enrichment to identify various pathogen types within a single sample.

SHERLOCK is a method for single molecule detection of nucleic acid targets and stands for Specific High Sensitivity Enzymatic Reporter unLOCKing. It works by amplifying genetic sequences and programming a CRISPR molecule to detect the presence of a specific genetic signature in a sample, which can also be quantified. When it finds those signatures, the CRISPR enzyme is activated and releases a robust signal. This signal can be adapted to work on a simple paper strip test, in laboratory equipment, or to provide an electrochemical readout that can be read with a mobile phone.

Instruments ranging from the venerable GeneXpert to ones just coming on the market allow fairly rapid NAAT pathogen detection, but they are based on disposable cartridges and a permanent (and relatively expensive) instrument. Our lab has been developing instrument-free disposable NAAT devices that retain the advantages of the instrumented systems, but free the user from the need for purchasing a permanent instrument (and the upfront cost that incurs).

GeneChip Resequencing microarrays have been advanced for infectious disease agent detection and identification from Ebola to Zika. Next-generation sequencing with the highly mobile and cost-effective nanopore sequencing device is challenging the supremacy of the microarray in rapid point-of-need pathogen detection. This talk will present results of side-by-side application of these two platforms for detection in pathogen-spiked blood samples and compare their performance.

As part of the Multiplex Panel session, this talk will focus on multiplex testing for the laboratory diagnosis of meningitis and encephalitis as compared to standard-of-care testing. The potential benefits and limitations of panel testing for meningitis and encephalitis compared to standard-of-care testing will be discussed. The potential approaches to maximize testing yield will also be discussed.

The BioFire FilmArray Pneumonia Panel (PP) detects 15 common bacterial pathogens semi-quantitatively (copy # from 104 to 107), 3 atypical pneumonia bacteria, 8 viruses, and 7 antimicrobial resistance markers by multiplex PCR in about 1 hour in the laboratory. Results of our 396-patient study suggest PP detects more bacterial isolates than conventional microbiology, and the copy number correlates with outcome variables, such as ICU length of stay, temperature, and white cells in the BAL. Results reported in a 3-4 h timeframe after a BAL could potentially improve both antibiotic choice and de-escalation in critically ill intubated patients.

Non-alcoholic fatty liver disease (NAFLD) affects approximately 25% of adults and 10% of children in the U.S. and is associated with obesity, type 2 diabetes mellitus, dyslipidemia and hypertension. Severe clinical outcomes include decompensated cirrhosis and hepatocellular carcinoma. The current diagnostic standard for non-alcoholic steatohepatitis (NASH), the more advanced form of NAFLD, is based on liver biopsies. Early diagnosis of the higher risk individuals is paramount. Representation and active engagement of scientific experts from all stakeholder groups in a non-competitive environment increases clarity and standardization while decreasing uncertainty. Lessons learned will be summarized.

Breast cancer screening by mammography, which began in the U.S. about 40 years ago, has led to significant increases in the incidence of early-stage breast cancers, including ductal carcinoma in situ (DCIS), also called precancer or stage 0 disease. However, the expected reciprocal decrease in subsequent late-stage breast cancers was not found. It is now clear that some screen-detected breast “cancers” are indolent lesions without significant malignant potential.

Metagenomic next-generation sequencing (mNGS) is a transformative technology for infectious disease diagnosis as it enables detection of nearly all pathogens – viruses, bacteria, fungi, and parasites – in a single assay. Here we will discuss the integration of multiple approaches to enhance the clinical utility of body fluid mNGS, including nanopore sequencing, CRISPR-Cas12-based pathogen detection, complementary host response analyses, and simultaneous diagnosis of cancer.

Initial efforts for applying metagenomic next-generation sequencing (mNGS) for infectious disease diagnostics have focused on pathogen detection. However, we can also gain information on antimicrobial resistance markers, virulence factors or even host biomarkers associated with different disease states. In this presentation, we will discuss the challenges of using mNGS for detection of antimicrobial resistance genes to predict phenotypes and discuss the current status of mNGS for detection of antimicrobial resistance.