MetroFlow 2024 Annual Meeting
Thursday, November 14, 2024
at Kean University, Union, NJ
(1 stop on NJ transit from Newark Penn Station)
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Click here important info on parking and directions
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Register now at EventBrite!​
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For CMLE and CE Credits please download these forms (1,2,3), complete, and email to MetroflowCMLE@gmail.com​​
Agenda
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8:30AM - 9:30AM
Registration & Breakfast
(Virtual broadcast will begin starting at 9:20AM)
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9:30AM - 9:40AM
Welcome & Announcements
Christina DeCoste
Director, Flow Cytometry Resource Facility at Princeton University &
President, MetroFlow Steering Committee
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9:40AM - 10:20AM
High-dimensional cytometry in the spectral era: new metrics to achieve a 50-color panel
Florian Mair, PhD
Scientific Director of Cytometry Facility
ETH Zurich
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10:20AM - 11:00AM
Do more with Less: Improving High Parameter Cytometry Through Overnight Staining
Oliver Burton, PhD
Senior Scientist
University of Cambridge
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11:00AM - 11:30AM
Break w/Corporate Members
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11:30AM - 12:00PM
Development of a customizable mouse backbone spectral flow cytometry panel to delineate immune cell populations in normal and tumor tissues
Rui Gardner, PhD
Core Head
Flow Cytometry Core Facility at Memorial Sloan Kettering Cancer Center
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12:00PM - 12:30PM
Balancing More Colors with Data Integrity
Kelly Lundsten
Director of Strategic Product Development
FluoroFinder
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12:30PM - 1:45PM
Lunch & Corporate Member Visits
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1:45PM - 2:30PM
Applications of machine learning in clinical flow cytometry
Paul D. Simonson, M.D., Ph.D.
Assistant Professor of Clinical Pathology and Laboratory Medicine
Weill Cornell Medicine
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2:30PM - 3:15PM
Using OMIP-069 as a case study to review the considerations to effectively implement HDF assays in support of clinical trials
Luis A. Mendez MS
Director, Flow Cytometry
Merck
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3:15PM - 3:45PM
Break w/Corporate Members
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3:45PM - 4:15PM
Rewards and Challenges in the Academic Core Facility Environment: Perspectives From the Columbia Stem Cell Initiative Flow Cytometry Core Team
Mike Kissner, Director of Operations
Chris Wu, Flow Cytometry Specialist
Columbia Stem Cell Initiative, Columbia University Irving Medical Center
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4:15PM - 5:15PM
Improving resolution and unveiling biology with spectral flow cytometry
Bob Balderas
Distinguished BD Fellow
BD Life Sciences–Biosciences​
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5:15PM - 5:30PM
Business Meeting
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5:30PM - 6:30PM
Wine and Cheese Networking
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Abstracts
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High-dimensional cytometry in the spectral era: new metrics to achieve a 50-color panel
Florian Mair, PhD, Scientific Director of Cytometry Facility, ETH Zurich
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To understand the function of the immune system in human tissue samples it is imperative to capture as much information as possible from often size-limited tissue biopsies. To do so, we have developed the first 50-color spectral flow cytometry panel to comprehensively study the functional state of the human immune system in PBMCs and tissue samples. The panel contains lineage markers for all major immune cell subsets, and an extensive set of phenotyping markers focused on the activation and differentiation status of the T cell and dendritic cell (DC) compartment. To establish such a complex panel, we utilized a new metric termed unmixing spreading error, that evaluates the fluorochrome-specific increase in background that is inherently generated when unmixing highly complex panels. In this presentation we show the systematic workflow we used to develop the panel and how we evaluated panel performance.
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Do more with Less: Improving High Parameter Cytometry Through Overnight Staining
Oliver Burton, PhD, Senior Scientist, University of Cambridge
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Recent advances in flow cytometry have allowed high-dimensional characterization of biological phenomena, enabling breakthroughs in a multitude of fields. Despite the appreciation of the unique properties of antigens and fluorophores in high-parameter panel design, staining conditions are often standardized for short surface stains, regardless of antibody affinity or antigen accessibility. Here, we demonstrate how increasing antibody incubation times can lead to substantial improvements in sensitivity, maintaining specificity, and reducing background, while also significantly reducing the costs of high-parameter cytometry panels. Furthermore, overnight staining reduces the influence of interexperimental variability, assisting accurate pooling over experiments over extended time courses. We provide guidance on how to optimize staining conditions for diverse antigens, including how different fixation strategies can affect epitope accessibility. Overnight staining can thus substantially improve the resolution, repeatability, and cost-effectiveness of high-parameter cytometry.
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Development of a customizable mouse backbone spectral flow cytometry panel to delineate immune cell populations in normal and tumor tissues
Ana Longhini, PhD, Scientific Assistant Director, Flow Cytometry Core Facility at Memorial Sloan Kettering Cancer Center
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This talk will explore the development of a 14-marker backbone spectral flow cytometry panel, designed to comprehensively profile immune populations across diverse murine tissues, including tumors. With the flexibility to incorporate 7 additional fluorochromes tailored to specific research needs, this panel offers a versatile solution for immuno-oncology researchers. Attendees will gain insights into how this customizable backbone panel not only enhances resolution and consistency across different cytometers and tissues but also serves as a practical guide for developing similar high-parameter panels in diverse research contexts.
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Fluorophores for Spectral Cytometry
Kelly Lundsten, Director of Strategic Product Development, FluoroFinder
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As spectral flow cytometry takes us to >30 parameters, we should take a moment to answer the age-old question of whether more is better. From an assay perspective, we’ll discuss how fluorophores are changing to meet the needs of stability in spectral flow cytometry. We’ll also look at efforts to standardize immunophenotyping, ontologic naming and analysis of human peripheral blood.
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Applications of machine learning in clinical flow cytometry
Paul D. Simonson, M.D., PhD, Assistant Professor of Clinical Pathology and Laboratory Medicine, Weill Cornell Medicine
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Flow cytometry data are already digitized, and hundreds if not thousands of example cases of common diseases are found in the data repositories of most clinical flow cytometry laboratories. This provides a wealth of information and opportunity for developing artificial intelligence and machine learning algorithms to assist in the evaluation of flow cytometry data for diagnosis and to create efficiencies in workflows. I will discuss example applications (primarily those developed by myself and group members) including use of supervised machine learning to identify diagnoses, supervised machine learning to automate flagging cases for expedited review (with example of flagging cases for adding antibody panels for distinguishing chronic lymphocytic lymphoma from mantle cell lymphoma), and prediction of various associated disease features (e.g., mutation status). I will discuss the utility of using interpretability algorithms to better understand the functioning of the algorithms. Finally, I will end with some discussion of validation for clinical use.
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Using OMIP-069 as a case study to review the considerations to effectively implement HDF assays in support of clinical trials
Luis A. Mendez MS, Director, Flow Cytometry, Merck
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Flow cytometry is currently going through an exciting period. The introduction of full spectrum cytometry to the community is allowing scientists to explore cells in a very comprehensive manner at the single-cell level. With full spectrum flow cytometry, one is no longer bound to a panel that is limited by the number of detectors and filter sets as one would be with traditional flow cytometry, but only to one’s imagination and careful placement of available fluorophores. Recent publications (OMIP-069) using this technology have reported up to 40-colors in a single panel. Having this ability to tag cells with 40 different markers/specificities is revealing novel biology and a better understanding of cells, their numerous cell subsets, the presence/role of these cell subsets in disease, and how these cell subsets respond to various therapeutics. In Pharma and Biotech, this strategy has already been widely adopted by our Discovery colleagues and these teams are benefiting by realizing a wealth of data early-on to precisely move forward with novel and promising therapeutics. Given this scenario, those in clinical flow cytometry need to take pause here and ask, is clinical flow cytometry ready for biomarker plans that require high-dimensional flow cytometry? This is a good question and worthy of the considerations to effectively adopt high-dimensional flow cytometry into the clinical space. Some of the early challenges that will need to be considered are where to develop the assays, such as in-house or externally, what instrument(s) to leverage, sample handling, marker/sample stability, data handling and storage, data analysis (hierarchical vs. AI/ML), compute environment, and reporting. This talk will highlight many of these considerations and provide some pointed recommendations that will be of value to those involved with clinical flow cytometry.
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Rewards and Challenges in the Academic Core Facilty Environment: Perspectives From the Team
Mike Kissner, Director of Operations
Chris Wu, Flow Cytometry Specialist
Columbia Stem Cell Initiative, Columbia University Irving Medical Center
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The academic core facility is a unique environment which combines aspects of collaboration, scientific methodology and technology, and customer service in a centralized hub around the institution’s research interests and culture. The core facility is poised to make significant impacts on scientific research at its institution and beyond and thus can be an extraordinarily rewarding experience for its staff. At the same time, such a complex operation presents notable challenges. In this talk, we will speak about the journey of the establishment and growth of the Flow Cytometry Core Facility in the Columbia Stem Initiative at the Columbia University Irving Medical Center from the perspectives of two team members, Michael Kissner, Director of Operations, and Christopher Wu, Flow Cytometry Specialist. We will highlight the aspects of their operation that have allowed it to successfully support the research at Columbia University. We will also speak about past and ongoing challenges and will share our experiences and thoughts about how to handle them. Our aim is to provide insight into the core facility through our specific and unique experiences and hope that attendees will find our discussion helpful to understand how this impactful and critical resource operates.
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Improving resolution and unveiling biology with spectral flow cytometry
Bob Balderas, Distinguished BD Fellow, BD Life Sciences–Biosciences​
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Since the efforts associated with the sequencing of the human genome, biomedical research has continued to evolve in the measurement of the underlying molecular and physiological mechanisms of complex biological systems and networks. Tools for molecular and cell analysis have continued to evolve to address these new challenges and opportunities in many different biological fields. Flow cytometry, the tool of the trade of today’s immunologists, is a highly multi-parametric platform, capable of high speed quantitative assessment of cells and other particles, at the single cell level. Today, as we continue to innovate on our flow cytometry platforms, which are capable of reaching up to 50 parameters, flow cytometry is opening a range of new applications stemming from opportunities presented by the advancements of genomics, proteomics, systems immunology and biology. Today, with the introduction of new high parameter spectral flow cytometry platforms, the development of a large array of new fluorochromes on the Blue and Yellow Green lasers and the completion of 2 studies for both mouse and human receptor density and expression, this year saw the demonstration of highly sensitive 50 flow cytometry panel. In this presentation we will discuss a systematic strategy for successful panel design for high parameter multicolor assays. To facilitate the wide-spread implementation of such a panel design process across different human samples, the establishment of a defined list of critical factors was needed. In this presentation we will define the approaches to build high valued panels with uncompromised biology by utilizing the a new set of colors, combined with critical biological antigen density data to support a fast an effective approach to panel design that works for both spectral and conventional flow cytometry.
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