The 8th Annual Ohio River Valley Cytometry Association Meeting
was held in conjunction with the
Great Lakes International Imaging and Flow Cytometry Association (GLIIFCA) 27th Annual Meeting
on September 28th-30th, 2018, at the Marriott River Center, Covington, KY.
See the meeting program for complete presentation and poster abstracts.
2018 Carleton and Sigrid Stewart Lecture
Vincent Shankey, PhD
Shankey Biotechnology Consulting
I have spent the past ~20 years working on analyzing cell populations from complex mixtures, including our published research on signal transduction pathways utilized by different human bone marrow cell populations as they differentiate from CD34+ down the myeloid differentiation pathway to mature granulocytes, monocytes or erythrocyte precursors. This project included the development of fixation and permeabilization techniques for whole bone marrow (or peripheral blood), and modifications of this technique to allow staining of cell surface plus intracellular (signaling) epitopes. In addition, we needed to carefully design and validate all of the reagents used in these studies (frequently measuring 4 independent signaling pathways plus 6-10 cell surface CD’s to monitor myeloid differentiation pathways). Finally, the daunting task of data analysis for these studies demonstrated to me that descriptive, “gating” dependent data analysis approaches to convert complex (flow) data into information with statistical significance is limiting the impact of cytometry to basic science. While much of this research is aimed at helping to develop a fundamental understanding of the biological complexity of heterogeneous cell populations, some work has focused on specific clinical problems (e.g. measuring ZAP-70 protein expression in CLL; Cytometry 70B:259-269, 2006). Much of my research from 2001-2013 was performed as part of a unique industrial-academic research program that I convinced Beckman Coulter (my employer) to invest in as a mechanism to advance “Signaling Cytometry”. This program produced 7 patent applications and over 12 joint-publications. Throughout much of my scientific career, I have placed a significant emphasis on education. In addition to my teaching responsibilities at Loyola and later teaching at the University of Miami (which included one of my favorite talks to the Bioengineering students on “Is the cell a digital or an analog machine?”), in the past 20 years, I have lectured and participated in workshops nationally and internationally, including multiple US-Indian and ASEAN Flow Cytometry Workshops I have had the privilege in participating (lectures and wet workshops) at most of the National Flow Cytometry courses held at either Bowdoin College, or Los Alamos Laboratory (now at UNM) for the past 15 years. My chair at Loyola repeatedly cautioned me that these activities would not contribute to grants, publications or promotion and tenure. But it does contribute to developing the critical resource of the next generation of scientists.
Flow Cytometry and Small Molecule Drug Development in Pharma: if Flow is so Good, How is Pharma using it?
Pharma is facing increasing challenges: the cost to develop and market new small molecule drugs is steadily growing, increasing numbers of currently marketed pharmaceuticals are coming off-patent, and there is a rising societal pressure to lower the price of prescription drugs. A recent paper (DOI: 10.1056/NEJMp1500848) indicates that the current cost to develop a single new drug is approaching $2.6 billion, up from $800 million estimated in 2003. In this same time period, most large Pharma companies have significantly reduced R&D funding and decreased their research staff. Anecdotal evidence suggests that the majority of cell-based assays performed during drug development employ image analysis and that many of these image-based assays use whole field/population signal averaging rather than single-cell analyses. Published data also show that the majority of image-based tests used by Pharma operate measuring 2-3 independent features. The status of flow cytometry in Pharma is less clear, as the industrial R&D groups may not publish their most valuable data. That said, published studies show the use of up to 4-6 dimensions in flow cytometry based drug-development assays. With limited exception, computational analysis of the results is generally limited to uncomplicated univariate or bivariate techniques.
During the past five years, I worked with a start-up CRO (AsedaSciences) to develop multi-parametric flow-based assays for early assessment of compound risk. The screen employs state-of-the-art hardware such as auto-samplers, robotic liquid handling systems, and multiparametric flow cytometry. Simultaneously measuring multiple cellular responses across a range of compound concentrations, the measured biological features are organized in tensors of numerical values, jointly describing dissimilarities between controls and measured samples in biological feature space. The resultant tensors characterize the tested compounds and can be compressed, compared, and used as inputs for predictive machine learning algorithms. This approach departs from the tradition of representing compound “toxicity” as EC50 (logarithm of half maximal effective concentration) for each individual phenotypic marker. Instead, the method integrates all measurements to produce single values representing the likelihood of specific cellular stress. Abandoning the univariate cell-stress/compound toxicity metric via EC50 and adopting a genuinely multivariate representation of cell responses facilitates assignment of probabilistic scores to compound-cell interaction fingerprints. This provides a framework for quantitative evaluation and validation of assay performance via sensitivity and specificity measures typically used for diagnostic tests. Using this approach, the assay recognizes ~50% of compounds present in the test database which “failed” (included compounds that failed for multiple reasons in more advanced stages of development , e.g. organ-specific toxicities, DILI, toxic metabolites, efficacy, etc.). The assay also offers remarkable precision (positive predictive value) of 98%. The described work demonstrates an example of a broader philosophy of cellular-stress testing, emphasizing simplicity and reproducibility paired with sophisticated computational analysis and machine learning. I will argue that the future of drug development will depend on the broader use of massively parallel and machine-learning-aided screening systems, coupled to well validated and reproducible assays. This philosophy emphasizing single cell analysis implicitly relies on cell population heterogeneity to characterize compounds in early phases of drug development and differs dramatically from costly and complex tissue and animal models.
2018 ORVCA Local Speaker
Stephen N. Waggoner, PhD
Cincinnati Children’s Hospital Medical Center and University of Cincinnati
Born and raised in Frederick, Maryland, Dr. Waggoner began his research career with a high school internship in the laboratory of Joost Oppenheim and Zack Howard at the National Cancer Institute. After obtaining a BA in Biology and Chemistry at St. Mary’s College of Maryland in 2000, he pursued his interests in viral immunology by performing PhD studies in Microbiology at the University of Virginia. In the laboratory of Young Hahn, Dr. Waggoner revealed immunosuppressive interactions between the nucleocapsid protein of hepatitis C virus and human complement receptors that likely contribute to viral persistence and chronic infection. In 2007, Dr. Waggoner joined the laboratory of Raymond Welsh at the University of Massachusetts Medical School, where he studied innate immune responses during virus infection in mice. This work led to the discovery of crucial immunoregulatory functions of natural killer cells that determine the incidence and severity of infection-associated disease. Following promotion to Instructor in 2011, Dr. Waggoner was named a New Scholar of the Lawrence Ellison Foundation in 2012 and was further promoted to Assistant Professor of Pathology. In 2013, Dr. Waggoner joined the faculty at Cincinnati Children’s Hospital Medical Center and the University of Cincinnati College of Medicine Department of Pediatrics. As an Assistant Professor in the Center for Autoimmune Genomics and Etiology (CAGE), he heads a team of exceptional researchers focused on how the immunoregulatory functions of natural killer cells limit vaccine efficacy, prevent severe disease by enforcing tolerogenic mechanisms during infection, preserve immune structures that are vital for host defense during chronic inflammation, and curtail autoimmunity. The laboratory is supported by an NIH Director’s Pioneer and Avant-Garde Award that concerns innovative manipulation of the immunoregulatory functions of natural killer cells to enable development of an efficacious preventative vaccine for HIV, with specific consideration for how to address the impact of HIV/AIDS in the context of drug abuse. Additional funding support from the Ralph and Marion Falk Medical Research Trust fosters collaborative efforts between Dr. Waggoner’s laboratory and clinicians in the Division of Rheumatology to harness the immunoregulatory activity of natural killers as a transformative new therapy for systemic autoimmune diseases, including systemic lupus erythematosus. Dr. Waggoner also serves as Chair of the Cincinnati Children’s Medical Research Center Institutional Biosafety Committee.
Imaging Non-conical New Roles for Natural Killers in Health and Disease
Natural killer (NK) cells are conventionally valued for their ability to make interferon-gamma and to kill virus-infected or cancerous cells. Our work reveals new functional roles for NK cells in regulating the duration, robustness, and character of immune responses. On one hand, we show that NK cells respond to inflammation and immunopathology during chronic virus infection by up-regulating expression of BAFF (B-cell activating factor belonging to the tumor necrosis factor family) and concomitantly providing support to maintain marginal zone macrophages and B cells. Chronic infection in mice devoid of NK cells results in complete and sustained loss of the marginal zone, which is associated with increased susceptibility to secondary bacterial infection. These data reveal a crucial and previously unappreciated role for NK cells in sustaining immune function during chronic inflammation. In contrast, we find that NK cells can also suppress adaptive immune function via perforin-dependent cytolytic targeting of activated CD4 T cells. This activity constrains development of follicular helper T cell and germinal center B cell responses following immunization. The reduced magnitude of germinal center responses is linked to decreased vaccine-elicited antibody titers and limited affinity maturation of antibodies. NK cell suppression of the germinal center is associated with transient localization of NK cells in the splenic white pulp. This discovery reveals that targeting of NK cell immunoregulatory function may enhance efforts to promote vaccine-elicited production of high affinity antibodies against pathogens like HIV, for which we do not have effective vaccine regimens.