Join Fluidigm and Visiopharm at the Imaging Mass Cytometry Summit for a demonstrtaion of the uitility of Visiopharm’s Phenotyping and Deep Learning toolbox for advanced multiplex phenotype analysis of Hyperion Imaging System multiplexed data sets.

We will provide an overview of Visiopharm’s flexible and intuitive Deep Learning and Advanced Phenotyping solutions to provide a comprehensive analysis of highly multiplexed IMC datasets. Specifically, we will demonstrate Visiopharm’s approach to and scope of cell segmentation and phenotyping algortithm development using real world IMC examples.

• • Tissue mining to enhance anlysis

• • Cell segmentation by deep learning

• • Robust multiplex phenotyping

• • Integration supported phenotyping

Brit Boehmer, Account Executive, Sales US, Visiopharm

Brit Boehmer is an Account Executive for the US West based in Denver, CO. He has a master’s and Ph.D. in physiology from Oklahoma State University and completed postdoctoral research in reproduction, nutrition and fetal growth. Brit joined Visiopharm in 2020 and supports clients with pre-sale APP development and advice on image analysis and histopathology workflows.

• • Discover how the Visiopharm platform can be used for multiplex analysis

• • Review an example analysis of an mIF 8plex image

• • Learn how the new Visiopharm Data Insights tool can be used for exploring image objects

• • See an example analysis of a Fluidigm Hyperion CyTOF image covering tissue and cell segmentation using AI deep learning, phenotyping and an example tumor microenvironment region analysis

Dr Fabian Schneider, PhD, Service Project Lead, Visiopharm

Dr Fabian Schneider is part of Visiopharm’s R&D and Product Management team, responsible for phenotyping products as well as service projects for custom APP development. Fabian has over 10 years of international experience in cancer biology and immuno-oncology, working in academic research labs, clinical research teams and computational pathology groups in both academia and biopharma. Fabian received his Dr phil. nat. in Cell Biology in 2011 from the Johan Wolfgang Goethe University Frankfurt, Germany.

Quantitative histological analyses are used to infer pathological diagnoses and identify biological drug targets in human and laboratory animal samples. Each histological sample often include millions of cells imposing a need for automated unbiased quantitative analysis to replace manual assessment.

We have trained a convolutional neural network that can identify individual nuclei inferred from DAPI fluorescence, allowing automated quantitative analysis of various fluorescent marker levels in nuclei. We used this convolutional network to assess proliferation from nuclear Ki67 fluorescence and apoptotic DNA fragmentation from terminal deoxynucleotidyl transferase dUTP nick end labelling (TUNEL) at a single cell level in human kidney biopsies. Upon retraining, the convolutional neural network was adaptable to identify nuclei from pancreas emphasizing the versatility of the network. Taken together, these results demonstrate an AI-based automated method for quantifying fluorescence levels of various markers in diverse tissues such as kidney and pancreas.

Tobias Højgaard Dovmark, Research Scientist, Novo Nordisk

As a research scientist at Novo Nordisk, Tobias Højgaard work with image analysis of histological samples. He has previously worked for Visiopharm as an image analysis specialist. He has a PhD in Physiology, Anatomy and Genetics from University of Oxford and an M.Sc. in Molecular Biomedicine from the University of Copenhagen.

Dr Fabian Schneider, PhD, Service Project Lead, Visiopharm

Dr Fabian Schneider is part of Visiopharm’s R&D and Product Management team, responsible for phenotyping products as well as service projects for custom APP development. Fabian has over 10 years of international experience in cancer biology and immuno-oncology, working in academic research labs, clinical research teams and computational pathology groups in both academia and biopharma. Fabian received his Dr phil. nat. in Cell Biology in 2011 from the Johan Wolfgang Goethe University Frankfurt, Germany.

Immunotherapy has transformed the treatment of metastatic and recurrent solid tumors but is challenging in that only a minority of patients respond. Therapies that rely on immune activation, such as checkpoint inhibitors, have been shown to be especially difficult due to the complex and heterogeneous immune escape mechanisms which can develop in each patient. Therefore, development of robust biomarkers coupled with spatial analysis of tissue is key for enabling rational patient selection and the design of precise combination therapies.

The use of multiplex immunohistochemistry/immunofluorescence (mIHC/IF) provides much needed insight into cellular composition, cellular functions, and cell-cell interactions. Importantly, recent studies have used mIHC/IF to explore specific immune cells as part of the tumor immune microenvironment (TME) and found that it is helpful for clinical prognosis and efficacy prediction in patients with cancer.

In this presentation we will show a streamlined unique workflow supporting whole slide imaging of an 8-plex mIF and H&E fusion on a single tissue slide for a comprehensive tissue immunophenotyping analysis.

• • The utility of a high throughput, high-plex (Immuno-8) staining and mIF assay development for scientists and clinicians

• • Demonstrate how advanced AI-driven image analysis can be applied to discover cell types, populations and morphological context

• • Discuss how whole slide image analysis of the tumor microenvironment can provide insight into specific cancer types

Fabian Schneider, PhD, Service Project Lead, Visiopharm

Dr. Fabian Schneider is part of Visiopharm’s R&D and Product Management team, responsible for phenotyping products as well as service projects for custom APP development. Fabian has over 10 years of international experience in cancer biology and immuno-oncology, working in academic research labs, clinical research teams and computational pathology groups in both academia and biopharma. Fabian received his Dr phil. nat. in Cell Biology in 2011 from the Johan Wolfgang Goethe University Frankfurt, Germany.

Angela Vasaturo, PhD

Associate Director, Biomarker Strategy and Applications

Only a small subset of patients with clear cell Renal Cell Carcinoma (ccRCC) respond to immunotherapy with checkpoint inhibitors. Research has shown that additional mechanisms of inhibition prevent the majority of patients from successful treatment. Recent studies into the inhibitory role of macrophages portend that these cells are associated with lower survival rate in several different cancer types. In this webinar, Immunologist Prof Dr Elfriede Nößner will present her research on specific macrophages in RCC (“ercDCs”) which are associated with poor outcome and their potential as new targets in immune therapy.

Presented as a LabRoots webinar on January 19, 2021.

• • What is known about the role of macrophages in immuno-oncology in general and in RCC specifically

• • What are “ercDCs” and how do they interact with T-Cells in RCC?

• • Which possibilities exist to manipulate the ercDCs?

Dr Elfriede Nößner, Head of Immunoanalytics, Helmholtz Zentrum München, German Research Center for Environmental Health

Dr. Elfriede Noessner is professor at the Ludwig-Maximilians-University of Munich (LMU) in Munich, Germany, and employed by the Helmholtz Zentrum Munich, where she is the Head of Immunoanalytics Research Group. She is board certified in immunology by the German Society of Immunology. She spent 5 years at Stanford University. Her research topics include the biology of HLA proteins and the antigen presentation; the activation, maintenance and control of T cell responses; and the modulation of T and NK cells, as well as dendritic cells and macrophages in tissue milieus, including cancer.