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Flow Cytometry

Flow Cytometry

Day 1  |  Day 2 


4:00-5:00 Conference Registration

5:00-6:00 Grand Opening Reception in the Exhibit Hall



7:00 am Conference Registration and Morning Coffee

7:30-8:15 Breakfast Presentation (Opportunity Available)

Contact Katelin Fitzgerald, Manager, Business Development,
at 781-972-5458 or


Flow Cytometry Data Analysis

(Joint Session with High-Content Data Analysis Meeting)

8:30-8:35 Chairperson’s Opening Remarks

8:35-9:00 Image Analysis and Structure/Localization Relationships for Small Molecule Probes in Live-cells

Kerby A. Shedden, Ph.D., Associate Professor, Statistics, College of Literature, Science & Arts, University of Michigan

Images of cells incubated with fluorescent small molecule probes can be analyzed to assess whether probes enter cells, and how the probes distribute within the cells that they enter. When images are available for a chemically diverse collection of probes, it becomes possible to ask whether particular chemical substructures -- “optical address tags” -- are associated with specific patterns of sub-cellular distribution. A number of interesting statistical questions arise in attempting to do this. Imaging artifacts must be identified and compensated for, distribution patterns must be quantified, and multivariate relationships between image properties and chemical structures must be discovered. I will discuss our recent work in this area, focusing on two issues: (i) how complex image features should be, and how many spatial scales are informative; (ii) what information is contained in the variation in sub-cellular patterns observed across multiple cells exposed to the same probe?

9:00-9:25 Automated High-Dimensional Flow Cytometric Data Analysis

Philip L. De Jager, M.D., Ph.D., Assistant Professor, Neurology, Harvard Medical School

9:25-9:50 An Open Source Software Framework for High-Throughput Flow Cytometry Data Analysis

Ryan Brinkman, Ph.D., Senior Scientist, Terry Fox Laboratory, BC Cancer Agency; Assistant Professor, Medical Genetics, University of British Columbia

High-throughput FCM (HT-FCM) is poised to reshape dramatically biomedical research by increasing the efficiency of an already widely adopted research and clinical tool. However, accelerating data collection requires a similar increase in the ability to analyze data, and successful management of the information generated by HT-FCM techniques requires highly automated methods to extract the relevant information from the large volume of data generated by the measurement of complex treatment-response patterns. This talk will review the development of an integrated computational infrastructure supporting high throughput data quality analysis, normalization, automated gating and sophisticated visualization.

9:50-10:15 FLOCK: A Density-Based Clustering Method for Automated Cell Population Identification in High-Dimensional Flow Cytometry Data

Richard H. Scheuermann, Ph.D., Chief, Division of Biomedical Informatics; Director, Division of Translational Pathology, John H. Childers Professorship in Pathology, Department of Pathology, University of Texas Southwestern Medical Center

Historically, investigators have analyzed flow cytometry (FCM) data using two-dimensional dot plot visualization and manual gating to identify and compare specific cell populations between samples. However, this approach is subjective and does not scale as the number of parameters detectable with different fluorochrome reagents increases. We have developed an analytical system, FLOw Clustering without K (FLOCK), which utilizes a density-based, data-driven approach for automated population discovery in multidimensional FCM data. Because FLOCK is not constrained by any underlying distributional assumptions, it is compatible with unique features of FCM data, including irregular distributions and sparse populations.

10:15-11:15 Networking Coffee Break with Exhibit and Poster Viewing


Technology Showcase: Flow Cytometry and Beyond

11:15-12:30 pm Sponsored Presentations (Opportunities Available)

Contact Katelin Fitzgerald, Manager, Business Development,
at 781-972-5458 or kfitzgerald@healthtech.com.

12:30-2:00 Lunch on your own


Flow Cytometry for Clinical and Diagnostic Applications

2:00-2:05 Chairperson’s Opening Remarks

2:05-2:30 The Application of Best of Breed Data Warehousing Practices to Support the Integrated Analysis and Dissemination of Flow Cytometric Data across Multiple Clinical Trials

David Parrish, Executive Director, Bioinformatics, The Immune Tolerance Network

Knowledge management and discovery within the biological sciences relies heavily on data sets that have been cleaned, validated, and consolidated from disparate sources. Such information processing is typically not part of the day-to-day transactional or operational systems, which were designed for the collection of data. The transition from an operational systems approach to a discovery-based system requires both a logical and physical conversion of raw data into models and structures that support analytical tools and techniques; this process is often referred to as data staging or transformation. The complexity of this transition is dependent on the nature of the data being incorporated, diversity and number of data feeds, and the end goals of the system. This is specifically challenging in flow cytometry analysis where the measures and interpretations are dependent on reagent definition and technologist expertise. However, the application of structured and rigorous data management practices coupled with an understanding of the idiosyncrasies of the data and concepts within the domain area has allowed us the creation of an automated and robust system for the collection, storage, analysis and delivery of flow cytometric data as part of an integrated clinical trials warehouse. In this presentation we will describe our approach to establishing this data warehousing approach, leveraging commercial tools and best practices, and detailing the unique difficulties associated with Flow Cytometry data.

2:30-2:55 Flow Cytometry Assay to Measure Receptor Occupancy on Monocyte in Human Blood

Dianna Wu, Ph.D., Principal Scientist, Clinical Biomarkers, Bristol-Myers Squibb Co.

2:55-3:20 Laser Rastering Flow Cytometry: Cell Analysis at New Orders of Magnitude

Giacomo Vacca, Ph.D., Advanced Research & Development Program Manager, Abbott Hematology

Laser Rastering is a novel concept that turns conventional flow cytometry principles on their head. A tight laser beam spot is scanned at high speed across a wide core stream, getting around a critical bottleneck imposed by conventional hydrodynamic focusing. We have prototyped and developed a cell analyzer capable of interrogating more than 300,000 cells per second, depending on the type of assay. I will describe the concept, the current state of research and development, and some possible applications that leverage the new capabilities made possible by this technical advance.

3:20-4:15 Networking Refreshment Break with Exhibit and Poster Viewing

4:15-4:40 Flow Cytometry: A Multipurpose Technology for a Wide Spectrum of Global Biosecurity Applications

Babetta Marrone, Ph.D., Scientist, Research & Development Manager, Bioscience Division, Los Alamos National Laboratory

Flow cytometry and cell sorting have a wide variety of applications in biosecurity and public health, ranging from environmental surveillance of pathogens, to disease diagnosis and the development of vaccines and therapeutics for prevention and control of infectious diseases.  Features of flow cytometry such as high sensitivity, throughput, and sampling statistics, and an extensive array of available reagents enable direct measurement of pathogen characteristics, or effects of pathogens on host cell responses.  The full spectrum of possible applications of flow cytometry technology to global biosecurity challenges has not yet been realized.  A critical review of existing and potential applications will be presented.

4:40-5:05 Flow Cytometry Can Diagnose Classical Hodgkin Lymphoma in Lymph Nodes with High Sensitivity and Specificity

Jonathan Fromm, M.D., Ph.D., Assistant Professor, Laboratory Medicine; Associate Director, Hematopathology Laboratory, University of Washington

Classical Hodgkin lymphoma (CHL) is diagnosed by morphology, as attempts to identify the neoplastic Hodgkin and Reed-Sternberg (HRS) cells of CHL by flow cytometry (FC) have been unsuccessful. Our initial 10-color FC experiments demonstrate that: 1) L1236 cells (HRS cell line) express CD15, CD30, CD40, CD71, and CD95, but not CD5 and CD20; 2) L1236 and HRS cells bind to T cells; 3) HRS cells can be identified by FC (89% sensitivity, 100% specificity in 89 tissues); and 4) flow sorting confirms that these populations are HRS cells. In a second series of 420 tissues, FC diagnostic sensitivity and specificity were 88.7% and 100%, respectively. This assay can now be used to routinely diagnose CHL.

5:05-5:30 Flow Cytometry for Translational Applications: Multiparameter Analysis of Epithelial Tissues

Vera S. Donnenberg, Ph.D., Assistant Professor, Surgery and Pharmaceutical Sciences; Director, Basic Research, Heart-Lung Esophageal Surgery Institute, University of Pittsburgh School of Medicine

I will describe the complete procedure for the detection of tumor cell subsets in dissociated epithelial tissues including: 1) Preparing single cell suspensions from tumor and normal tissue specimens; 2) An efficient method to perform cell surface marker staining on large numbers of cells; 3) Flow cytometer setup and controls; 4) Simultaneous detection of surface proteins and DNA content in rare cell subsets; and 5) Data acquisition and analysis.

5:30 Close of Day

For more information, please contact:
Julia Boguslavsky, Executive Director, Conferences
Cambridge Healthtech Institute
E-mail: juliab@healthtech.com

For sponsorship information, please contact:
Katelin Fitzgerald, Manager, Business Development
Cambridge Healthtech Institute
Phone: 781-972-5458; E-mail: kfitzgerald@healthtech.com

Download Conference & Course Catalog

CHI Catalog March 2018 - August 2018 Cover