Endometrial cancer is the most common gynecologic malignancy in the United States and both the incidence and associated mortality are rising. When detected early, endometrial cancer survival rates are dramatically improved. Despite this, no screening methods have been developed which can effectively detect either pre-malignant lesions or early-stage cancers. We conducted a prospective study to analyze the effectiveness of molecular analysis of uterine lavage fluid, taken at the time of evaluation for a definitive tissue-based diagnosis, to assess the use of targeted next generation sequencing (NGS) for detecting endometrial carcinomas. The women in this study were primarily either experiencing abnormal uterine bleeding or had abnormal pelvic ultrasound findings and were being evaluated by hysteroscopy and curettage for a tissue diagnosis. We detected somatic mutations in all women who were later diagnosed with endometrial cancer, even microscopic stage IA, grade 1. In addition, we also identified that half of the women in our study who did not have clinical evidence of cancer, nonetheless possessed a significant landscape of driver mutations. Our findings therefore suggest the apparently inimicable possibilities of a genomics- based approach for endometrial cancer screening and the discovery of prevalent driver mutations in clinically-defined non-cancerous tissue.

Microorganisms growing in biofilm phenotype are the cause of chronic infections.  Several universal properties of biofilm communities are they are overwhelmingly polymicrobial, difficult to culture (viable but not culturable), and the individual constituents are very tolerant of antimicrobial agents, especially antibiotics.  Just like in medical imaging utilizes multiple technological platforms such as ultrasound, magnetic resonance or x-ray, microbial identification requires multiple technologies and methods.  However, when dealing with biofilm phenotype microorganisms, molecular methods are superior.  Molecular methods have the ability to identify microorganisms with very high sensitivity, specificity and also can be quantitative.  Utilizing a quantitative PCR methodology, specific targets can be identified as present/not present but also an absolute quantitative determination for each target present can be made.  This allows for the determination of “bacterial load”.  Sequencing platforms can reveal crucial relative quantification of the different microorganisms present, allowing for the determination of dominant microbes.  Timely and accurate diagnostic information of microorganisms, which are the primary cause of the chronic infection, are essential for improving outcomes.  PCR information can be returned rapidly, allowing the clinician to rule out antibiotic resistant microbes which allows for the selection of appropriate empiric antibiotics.  Sequencing data, which returns several days later, allows for great sensitivity and specificity in the identification of microorganisms while also providing the information on what is dominant within the community.  Antibiotic therapy can then be tailored to the chronic infection.  Molecular diagnosis also provides a way to assess the efficacy of treatment.  Chronic infections are more prevalent and costly than heart disease, cancer, diabetes or any other disease in our healthcare system.  Molecular methods for identifying microorganisms provide a powerful diagnostic tool for the management of chronic infections. 

Genomics and metagenomics have become ubiquitous research efforts.  Here we will show details of the development of physical, computational, and even space-based standards for metagenomics, as part of the International Metagenomics and Microbiome Standards Alliance (IMMSA).  Also, pilot data will be shown for enabling patients to become more involved in their ‘omics data, including an integrative genomics view of entire cities (based on our MetaSUB project) that leverages longitudinal metagenome and microbiome profiles of the world’s subway systems and cites, including the 2016 Rio Olympics. All of these methods and molecular tools work together to guide the most comprehensive, longitudinal, mutli-omic view of integrated genomics with the NASA Twins Study and new technologies to mine, engineer, and sequence DNA in for long-term human space travel.

Lyme disease is a common tick-transmitted infection caused by spirochetes in the Borrelia burgdorferi sensu lato complex. Borrelia burgdorferi is the primary cause of Lyme disease in the United States, while B. burgdorferi, B. garinii and B. afzelii cause Lyme disease in Europe. Although Lyme disease is primarily diagnosed using clinical and serologic criteria, molecular testing may play an important adjunctive role in detection and have contributed greatly to our knowledge of Lyme disease epidemiology. Molecular tests also increase our ability to detect the presence of co-infecting organisms and allow for detection of previously unknown organisms, such as Borrelia mayonii. This presentation will provide an overview of the available molecular methods for diagnosing Lyme disease and discuss future applications of these technologies.

The presentation will describe the principles of the ultra-sensitive single-molecule array (Simoa) developed by Quanterix and the application of the Simoa technology to the development of a toolbox of CNS biomarkers. The presentation will include several case studies across CNS diseases, ranging from traumatic brain injury to Alzheimer's Disease

In spite of the huge potential impact of microbiome science, current measurement capabilities are insufficient, particularly for translating discoveries and correlations observed in the lab into commercially viable products and services that improve our quality of life. Data are difficult to compare between experimenters, laboratories, or institutions. Emerging capabilities (e.g., next generation sequencing, metabolomics) are new and not fully characterized for microbiome investigations. Reference samples (i.e., for calibration or quality control) that mimic the complexity of naturally occurring communities are not available. Bioinformatic analysis packages and reference databases remain incomplete.  At NIST, we are improving microbiome science and supporting the National Microbiome Initiative by developing standards for microbiome measurements that will enable federal, academic, and industry labs to reliably reproduce and advance each other's results. Microbiome standards will support research investigations and commercial translation of microbiome science by providing measurement assurance tools: standardized protocols, reference materials, validated measurements and critically evaluated reference data.

With the exception of the Microbiome Quality Control (MBQC), very little has been published on best practices and reference standards for microbiome and metagenomic studies. As evidenced by recent publication trends, researchers are moving the field toward commercial development at a rapid pace.  If these analyses are to ever evolve into reliable assays (e.g. for clinical diagnostics), the measurement process must be regularly assessed to ensure measurement quality.  A key aspect of this validation is the routine analysis of reference materials as positive controls. A reference material (RM) is any stable, abundant, and well characterized specimen that is used to assess the quantitative and/or qualitative validity of a measurement process. The focus will be on the use of whole cell microbial reference materials to characterize metagenomic analyses from start to finish.  We’ll discuss 3 key categories (environmental samples, in vitro models for microbial ecosystems, pure microbial isolates) of reference standards and the challenges in characterizing those standards.

Genomics and metagenomics have become ubiquitous research efforts.  Here we will show details of the development of physical, computational, and even space-based standards for metagenomics, as part of the International Metagenomics and Microbiome Standards Alliance (IMMSA).  Also, pilot data will be shown for enabling patients to become more involved in their ‘omics data, including an integrative genomics view of entire cities (based on our MetaSUB project) that leverages longitudinal metagenome and microbiome profiles of the world’s subway systems and cites, including the 2016 Rio Olympics. All of these methods and molecular tools work together to guide the most comprehensive, longitudinal, mutli-omic view of integrated genomics with the NASA Twins Study and new technologies to mine, engineer, and sequence DNA in for long-term human space travel.

As next generation sequencing has lowered the price of DNA sequencing orders of magnitude below what it cost to create the first consensus human genome, the sheer diversity of human sequence between individuals has become more and more apparent. This diversity is not only seen in single nucleotide variants but also deletions/duplications, insertions/deletions, and copy number variants.  Sorting the wheat from the chaff when performing molecular diagnostics of single-gene (Mendelian) disorders such as Hereditary Breast and Ovarian Cancer, Hypertrophic Cardiomyopathy, Hereditary Spastic Paraplegia, Cystic Fibrosis, is an enormous challenge because very serious medical decision making rests on a correct interpretation of the clinical meaning of variants, both in affected individuals and when sequencing is used for screening purposes.  The American College of Medical Genetics and the Association of Molecukar Pathologists took a first major step when they proposed that variant interpretations fall into one of five classes:  Benign, Likely Benign, Likely Pathogenic, Pathogenic, and Variant of Uncertain Significance (VUS). The also proposed a set of criteria to apply to guide the placement of any variant into on of these buckets. This proposal has improved the rigor and reproducibility of variant interpretation but much remains to be done to make variant interpretation more accurate and scalable if we are to deploy genomics more widely in medicine.

Lyme disease is a common tick-transmitted infection caused by spirochetes in the Borrelia burgdorferi sensu lato complex. Borrelia burgdorferi is the primary cause of Lyme disease in the United States, while B. burgdorferi, B. garinii and B. afzelii cause Lyme disease in Europe. Although Lyme disease is primarily diagnosed using clinical and serologic criteria, molecular testing may play an important adjunctive role in detection and have contributed greatly to our knowledge of Lyme disease epidemiology. Molecular tests also increase our ability to detect the presence of co-infecting organisms and allow for detection of previously unknown organisms, such as Borrelia mayonii. This presentation will provide an overview of the available molecular methods for diagnosing Lyme disease and discuss future applications of these technologies.

The presentation will describe the principles of the ultra-sensitive single-molecule array (Simoa) developed by Quanterix and the application of the Simoa technology to the development of a toolbox of CNS biomarkers. The presentation will include several case studies across CNS diseases, ranging from traumatic brain injury to Alzheimer's Disease

Screening for cervical cancer represents one of the greatest successes achieved in disease prevention. Cytology has been central to cervical cancer screening programs for over 50 years and has contributed to the 70% decline in rates of cervical cancer in the developed world.³ By the 1990’s, HPV was recognized as a single, necessary cause of cancer of the cervix that was detected in 99.7% of cases of cervical cancer.⁴ Therefore, tests that detect infection with these high-risk HPV genotypes are now being used increasingly in cervical cancer screening programs.  The 2007 Consensus Guidelines for the Management of Women with Abnormal Cervical Cancer Screening Tests⁶ recognized the utility of using a combination of cervical cytology, tests for HPV, and genotype-specific HPV testing for women undergoing screening for cervical cancer. These guidelines were subsequently revised and now recommend the combination of cytology and HR HPV testing (cotesting) as the preferred method of screening in women ≥30 years, with HPV 16/18 genotype–specific testing an added option to triage women with negative cytology to colposcopy.⁷ Most recently, the FDA approved the use of the cobas HPV Test as the first-line primary screen and interim guidance for this screening strategy has been issued and supported by 3 professional societies.

The numerous guideline changes have presented challenges to both laboratories and clinicians. For laboratories, decisions needed to be made regarding which HPV assay to run and how to re-organize resources and workflow to accommodate changing guidelines. For clinicians, choosing the optimal screening strategy and then understanding how to manage the results has become a difficult task.

Today we will try to simplify approaches to cervical cancer screening and management by reviewing the role of HPV genotyping in risk management. Cytology and HPV genotyping results can be used to quantify risks so that we can identify women at the highest risk of having or developing cervical disease and conversely, to identify women at the lowest risk. By utilizing this risk assessment approach, laboratorians and clinicians will better be able to choose the most efficient screening methodology and also more easily manage results that are often confounding and confusing.

A recent clinical trial of the AR inhibitor enzalutamide in patients with TNBC included an exploratory endpoint using RNA sequencing to identify a genomic signature of patients likely to respond to treatment. Tumor samples were collected from all patients enrolled in the single-arm, open-label phase 2 trial. The primary endpoint was clinical benefit rate at 16 weeks (CBR16). Samples were assayed by whole transcriptome RNA-sequencing and divided into a training and blinded validation cohort for model development and evaluation. The gene expression model of enzalutamide sensitivity demonstrated strong association with progression free survival (HR = 0.40, Wald p = 0.0001).  This signature is being used to select patients enrolling in a phase 3 trial of enzalutamide in patients with advanced TNBC. Biological associations and translation of the assay for clinical use will highlighted.

Endometrial cancer is the most common gynecologic malignancy in the United States and both the incidence and associated mortality are rising. When detected early, endometrial cancer survival rates are dramatically improved. Despite this, no screening methods have been developed which can effectively detect either pre-malignant lesions or early-stage cancers. We conducted a prospective study to analyze the effectiveness of molecular analysis of uterine lavage fluid, taken at the time of evaluation for a definitive tissue-based diagnosis, to assess the use of targeted next generation sequencing (NGS) for detecting endometrial carcinomas. The women in this study were primarily either experiencing abnormal uterine bleeding or had abnormal pelvic ultrasound findings and were being evaluated by hysteroscopy and curettage for a tissue diagnosis. We detected somatic mutations in all women who were later diagnosed with endometrial cancer, even microscopic stage IA, grade 1. In addition, we also identified that half of the women in our study who did not have clinical evidence of cancer, nonetheless possessed a significant landscape of driver mutations. Our findings therefore suggest the apparently inimicable possibilities of a genomics- based approach for endometrial cancer screening and the discovery of prevalent driver mutations in clinically-defined non-cancerous tissue.

This presentation describes the new process by which the Centers for Medicare and Medicaid Services (CMS) will establish the prices the Agency pays for clinical diagnostic laboratory tests.  This revolutionary approach was
mandated by Congress in the clinical laboratory provisions contained within Section 216 of the Protecting Access to Medicare Act of 2014.  In his talk Dr. Klein will discuss this legislation, accompanying CMS regulations, and their
potential impacts on the laboratory industry

Microorganisms growing in biofilm phenotype are the cause of chronic infections.  Several universal properties of biofilm communities are they are overwhelmingly polymicrobial, difficult to culture (viable but not culturable), and the individual constituents are very tolerant of antimicrobial agents, especially antibiotics.  Just like in medical imaging utilizes multiple technological platforms such as ultrasound, magnetic resonance or x-ray, microbial identification requires multiple technologies and methods.  However, when dealing with biofilm phenotype microorganisms, molecular methods are superior.  Molecular methods have the ability to identify microorganisms with very high sensitivity, specificity and also can be quantitative.  Utilizing a quantitative PCR methodology, specific targets can be identified as present/not present but also an absolute quantitative determination for each target present can be made.  This allows for the determination of “bacterial load”.  Sequencing platforms can reveal crucial relative quantification of the different microorganisms present, allowing for the determination of dominant microbes.  Timely and accurate diagnostic information of microorganisms, which are the primary cause of the chronic infection, are essential for improving outcomes.  PCR information can be returned rapidly, allowing the clinician to rule out antibiotic resistant microbes which allows for the selection of appropriate empiric antibiotics.  Sequencing data, which returns several days later, allows for great sensitivity and specificity in the identification of microorganisms while also providing the information on what is dominant within the community.  Antibiotic therapy can then be tailored to the chronic infection.  Molecular diagnosis also provides a way to assess the efficacy of treatment.  Chronic infections are more prevalent and costly than heart disease, cancer, diabetes or any other disease in our healthcare system.  Molecular methods for identifying microorganisms provide a powerful diagnostic tool for the management of chronic infections.