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​Register here!

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Thursday, October 20th


Kean University

NJ Center for Science, Technology & Mathematics

Union, NJ​

This year's meeting will hybrid in-person/virtual


MetroFlow 2022 Annual Meeting


Please fill out these forms for CMLE and CE credit (1,2,3)


In person Registration and Breakfast


Welcome & Introduction


"High-speed Image-enabled Cell Sorting"

Diana Ordonez Ph.D.

Head of the Flow Cytometry Core Facility ISAC SRL Emerging Leader 2022-2025 



Coffee Break with Corporate Members


"Computational cytometry analysis with FlowSOM, PeacoQC and CytoNorm"

Dr. Sofie Van Gassen Ph.D.

Department of Applied Mathematics, Computer Science and Statistics, Ghent University, Ghent, Belgium
Data Mining and Modeling for Biomedicine group, VIB Center for Inflammation Research, Ghent, Belgium.


"Measurement Assurance for Rare Event Analysis"

Virginia Litwin Ph.D.

Research Scientist

Charles River Laboratories


Lunch & Corporate Member Visits


"Single-cell Genomics and Why Flow Cytometry is More Important than Ever”

Peter A. Sims Ph.D.

Associate Professor of Systems Biology

Columbia University


Coffee Break with Corporate Members


"Using flow cytometry and FACS to identify mechanisms of metastasis in clinical specimens and to generate Cas9-expressing patient-derived xenografts for functional genomics in vivo."

Álvaro Quintanal-Villalonga Ph.D.

Assistant Attending Biologist, Lab co-director

Department of Medicine, Memorial Sloan Kettering Cancer Center


"A method for rapid flow-cytometric isolation of endothelial nuclei and RNA from archived frozen brain tissue"

Patrick Murphy Ph.D.

Associate Professor

Department of Cell Biology, Center for Vascular Biology and Calhoun Cardiology Center, University of Connecticut Medical School


MetroFlow Business Meeting & Elections


Wine & Cheese Social



"High-speed Image-enabled Cell Sorting"

Diana Ordonez Ph.D.

Have you ever looked at a cell under a microscope and thought how exciting it would be to isolate and characterize it? Have you ever wondered what’s really behind those anonymous dots in a flow cytometer plot?. Then you should join this talk in which I will present a novel image-enabled cell sorting (ICS) platform that combines the spatial resolution of a fluorescence microscope with the speed and sensitivity of flow cytometric cell sorting. This technology, developed at BD Biosciences and tested by EMBL researchers, can be used for the rapid identification, isolation, and molecular characterization of cells with unique (sub)cellular phenotypes. Join to get an overview of its advantages and applications and to know how ICS can help to accelerate your research.

"Computational cytometry analysis with FlowSOM, PeacoQC and CytoNorm"

Sofie Van Gassen Ph.D.

The amount of data collected with cytometers keeps increasing. With studies measuring up to 40 markers, millions of cells per sample and up to thousands of samples, manual gating of all data becomes infeasible. In this talk, I will present the algorithms our team has developed to help with these challenges and some specific use cases where we have made use of them. FlowSOM is a clustering algorithm, able to return a high-quality clustering similar to a manual gating. However, every clustering algorithm needs good quality input data. Therefore, we also developed two preprocessing algorithms: PeacoQC and CytoNorm. PeacoQC evaluates the stability of each sample during the acquirement, while CytoNorm is able to align samples across multiple batches. I will share some tips and tricks on how to use these and caveats to look out for.

"Measurement Assurance for Rare Event Analysis"

Virginia Litwin Ph.D.

Translational and clinical science is defined as the pathway to accelerated scientific advances from the bench-to-the-bedside. Flow cytometry continues to play an increasingly important role in the translational pathway from basic research, to clinical research ,to drug discovery and development, to patient care and treatment. This is partly due to the success of immunotherapies and cell-based therapies.

Rare event analysis in flow cytometry, defined as the measurement of cellular subsets present at very low frequencies, is widely used at at all stages of the translational pathway. The measurement CD34+ hematopoietic stem cells, paroxysmal nocturnal hemoglobinuria (PNH), and measurable residual disease (MRD) in blood cancers are examples of rare event assays used in clinical laboratories. In research and drug development settings, the measurement of intracellular signalling events (i.e., protein phosphorylation) and intracellular cytokines are some of the more common rare event assays.

Factors influencing measurement assurance in quantitative flow cytometry include the instrument and assay as well as the processes surrounding monitoring, reporting, and documentation of both the instrument and the assay. When measuring and reporting rare events, each of these factors has unique requirements, and enhanced importance. This presentation will address aspects to consider when designing and validating methods which report rare subsets. Emphasis will be placed on the impact of instrument set-up and panel design/optimization on the validation of the assay specificity and sensitivity. Case studies demonstrating how the application of a lower limit of quantification (LLOQ) can improve the translatability of the assay will be presented. In addition, considerations for reporting data, near or below the LLOQ ,will be discussed.

"Single-cell Genomics and Why Flow Cytometry is More Important than Ever”

Peter A. Sims Ph.D.

The last ten years have seen a dramatic increase in the scalability of single-cell genomics with the development of microfluidic and molecular barcoding technologies. These tools offer highly multiplexed quantification of RNA, DNA, and protein in tens of thousands of individual cells. They have also made flow cytometry and fluorescence activated cell sorting (FACS) more important than ever. In this presentation, I will describe recent technological advances in single-cell genomics. I will also demonstrate how conventional, flow-based single-cell analysis enables protocol optimization, sample preparation, and orthogonal validation for single-cell genomics across many fields including cancer, immunology, and neuroscience.

"Using flow cytometry and FACS to identify mechanisms of metastasis in clinical specimens and to generate Cas9-expressing patient-derived xenografts for functional genomics in vivo."

Álvaro Quintanal-Villalonga Ph.D.

Lung tumors are among the top prevalent tumor types and are responsible for most cancer-related deaths. Among them, small cell lung cancer (SCLC) is the most aggressive lung cancer subtype with a strong metastatic capacity. Little is known about the molecular biology of SCLC tumors, due to the limited accessibility to clinical specimens amenable for molecular analysis. SCLC subtypes have been defined by differential expression of ASCL1, NEUROD1, and POU2F3 (SCLC-A, -N, and -P, respectively), with potential subtype-dependent therapeutic implications. However, to date no targeted therapy is available for these. The only therapeutic option for SCLC is classic chemotherapy, with very limited efficacy due to the rapid development of resistance, leading to extremely poor survival. The identification of mechanism of metastasis, the main cause of death for patients with SCLC, and of novel therapeutic approaches in this setting, are prioritary unmet clinical needs. To decipher the biology of SCLCs, we leveraged FACS to perform single-cell RNA sequencing in 21 human SCLC tumors. We observed that SCLC subtypes are not static but rather plastic, with some SCLC cells exhibiting intermediate or admixed subtype phenotypes. We also discovered a universal small intra-tumoral population characterized by high PLCG2 expression and stem-like, pro-metastatic features. PLCG2 expression induced pro-metastatic features in vivo and in vitro and importantly, the abundance of this intra-tumoral population strongly predicted worse survival in patients with SCLC. On the other hand, aiming to find a novel therapeutic target for SCLC tumors, we performed CRISPR Cas9 knock out screens in SCLC models that revealed XPO1 (Exportin 1) inhibition as a mediator for chemotherapy sensitization in SCLC. Through the use of FACS, we generated Cas9-expressing patient-derived xenografts (PDXs), allowing the performance of functional genomics in vivo in the preclinical models that most closely resemble the behavior of tumors in the patient. With these, and performing flow cytometry analysis, we genetically validated that knock out of XPO1 sensitized SCLC tumors to chemotherapy. Treatment with the exportin 1 inhibitor selinexor exhibited high synergy in vitro with either cisplatin or irinotecan, chemotherapeutic drugs used in treatment-naïve and chemotherapy relapsed SCLC tumors, respectively. Consistently, selinexor dramatically sensitized treatment-naïve and chemotherapy relapsed SCLC PDXs to cisplatin and irinotecan, respectively, with manageable toxicity profiles at the drug concentrations tested. Mechanistic studies revealed that selinexor was able to abrogate the induction of the AKT/mTOR pathway, upregulated by SCLC cells as a cytoprotective and anti-apoptotic mechanism against chemotherapy, thus strongly sensitizing SCLC tumors to therapy. Overall, these results describe a novel mechanism of metastasis in SCLC and provide preclinical rationale for the combination of selinexor with chemotherapy in the treatment of SCLC tumors.

"A method for rapid flow-cytometric isolation of endothelial nuclei and RNA from archived frozen brain tissue"

Patrick Murphy Ph.D.

Endothelial cells are important contributors to brain development, physiology, and disease. Although RNA sequencing has contributed to the understanding of brain endothelial cell diversity, bulk analysis and single-cell approaches have relied on fresh tissue digestion protocols for the isolation of single endothelial cells and flow cytometry-based sorting on surface markers or transgene expression. These approaches are limited in the analysis of the endothelium in human brain tissues, where fresh samples are difficult to obtain. Here, we developed an approach to examine endothelial RNA expression by using an endothelial-specific marker to isolate nuclei from abundant archived frozen brain tissues. We show that this approach rapidly and reliably extracts endothelial nuclei from frozen mouse brain samples, and importantly, from archived frozen human brain tissues. Furthermore, isolated RNA transcript levels are closely correlated with expression in whole cells from tissue digestion protocols and are enriched in endothelial markers and depleted of markers of other brain cell types. As high-quality RNA transcripts could be obtained from as few as 100 nuclei in archived frozen human brain tissues, we predict that this approach should be useful for both bulk analysis of endothelial RNA transcripts in human brain tissues as well as single-cell analysis of endothelial sub-populations.

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