Advanced techniques examining single cells are revolutionizing basic biology as well as our understanding of health and disease. This rapid development in isolation and analysis is showing promise and expanding applications. However, before biomarker
analysis from single cells can be integrated into diagnostic and therapeutic use, hurdles including validation, interpretation, and method standardization must be addressed.
At Cambridge Healthtech Institute’s 2nd Annual Single Cell Analysis symposium, innovators and early adopters present single cell omics case studies for diagnostic and therapeutic applications in genomics, transcriptomics, and proteomics. Overall,
this symposium will share new methods and biological insights to continue accelerating single cell omics.
Final Agenda
Thursday, March 14
7:00 am Registration Open and Morning Coffee (Continental Foyer)
8:25 Chairperson’s Opening Remarks
Sandrine Dudoit, PhD, Professor, Department of Statistics, Division of Epidemiology and Biostatistics, School of Public Health, University of California, Berkeley
8:30 Single Cell Analysis of Smooth Muscle Cell Phenotypic Modulation in vivo Reveals a Critical Role for Coronary Disease Gene TCF21 in Mice and Humans
Robert Wirka, MD, Instructor, Department of Medicine, Stanford University
We used single cell RNA sequencing to characterize the phenotype of smooth muscle cells (SMCs) during atherosclerosis in mouse and human arteries and found that these cells transform into unique fibroblast-like cells, or “fibromyocytes.” Loss
of TCF21, a causal CAD gene, inhibited this process in mice and TCF21 was associated with transition of SMCs to fibromyocytes in human coronaries. TCF21 expression was also associated with decreased CAD risk in humans.
9:00 Statistical Methods and Software for the Study of Stem Cell Differentiation Using Single Cell Transcriptome Sequencing
Sandrine Dudoit, PhD, Professor, Department of Statistics, Division of Epidemiology
and Biostatistics, School of Public Health, University of California, Berkeley
I discuss statistical and computational issues that have arisen during a collaboration with the UC Berkeley Ngai Lab concerning the analysis of olfactory stem cell fate trajectories in mice. These issues include experimental design, exploratory data analysis
(EDA) of scRNA-Seq reads, quality assessment/control (QA/QC), normalization to account for nuisance technical effects, cluster analysis to identify novel cell types, cell lineage and pseudotime inference, and differential expression analysis to identify
genes involved in the differentiation process.
9:30 Breast Cancer Metastasis in Single Cell Resolution
Devon A. Lawson, PhD, Assistant Professor, Department of Physiology and Biophysics, Chao Family
Comprehensive Cancer Center, School of Medicine, University of California, Irvine
Using machine learning, we developed a predictive logistic regression model to classify individual cells based on the metastasis-associated gene signature. This model was able to accurately predict cell identity (>85%) and predict patient outcomes
in large patient datasets. Future studies will focus on biological interrogation of metastasis-associated pathways, and evaluation of the utility of metastasis-associated signatures as predictive biomarkers in patients.
10:00 Biology at True Resolution: Accelerating Discovery with 10x Genomics’ Single Cell Solutions
Brian R. Fritz, PhD, Senior Marketing Manager, AMR, 10X Genomics
10:30 Coffee Break in the Exhibit Hall with Poster Viewing
11:15 Introducing Inertial Microfluidics for High-Throughput Droplet Barcoding for Single Cell RNA Sequencing
Hui-Sung Moon, PhD, Principal Researcher, Samsung Genome Institute, Samsung Research Institute
for Future Medicine, Samsung Medical Center
Droplet-based single cell sequencing provided a promising tool with higher throughput than other single cell technologies. However, despite the high frequency of droplet generation, the co-encapsulation rate of barcoded bead and cell is still low, so
it limits the throughput. We introduced hydrodynamic technique into droplet-based single cell sequencing platform to significantly improve the throughput and yield. At the same time, we suppressed the barcoding error due to multi-beads-in-droplets
through deterministic encapsulation.
11:45 10X Platform for Immune Profiling
Zora Modrusan, PhD, Principal Scientist, Genentech
Single cell RNA sequencing (scRNA-seq) has been used to reveal cellular heterogeneity of tumor microenvironment and composition of immune infiltrates in order to improve diagnosis, prognosis and response to cancer immunotherapies. We employed 10x Genomics platform to examine cell diversity and immune repertoire in tumor samples from treatment-naïve cancer patients, and further characterized patterns of clonal expansion in different T cell types to gain better insight into their significance in antitumor response.
12:15 pm Selected Poster Presentation: Bacterial Single Cell Whole Transcriptome Amplification in Microfluidic Platform Shows Gene Expression Heterogeneity
Yuguang Liu,
PhD, Post-doctoral Research Fellow, Department of Surgery, Center for Individualized Medicine, Mayo Clinic & Foundation
12:30 Session Break
12:40 Luncheon Presentation: NGS Barcoding Technologies, CRISPR and Expression Profiling for Single Cell Genetic Analysis
Alex Chenchik, President and CSO, Cellecta
Clonal barcodes, or UMIs, can be combined with Perturb-Seq and single cell analysis techniques to generate important insights. Cellecta will discuss work we are doing to develop an integrated platform that combines CRISPR sgRNA screens with single
cell genetic analysis.
1:15 Session Break
1:55 Chairperson’s Remarks
Ryan Kelly, PhD, Associate Professor, Chemistry and Biochemistry, Brigham Young University
2:00 Near-Infrared Nanocrystals for Imaging Cells with Minimal Phototoxicity
Bruce E. Cohen, PhD, Staff Scientist, The Molecular Foundry, Lawrence
Berkeley National Laboratory
Multiphoton techniques that convert low energy excitation to higher energy emission are widely used in live cell imaging to limit cellular photodamage. Here, we report protein-sized alloyed upconverting nanoparticles (aUCNPs) that can be imaged as
single particles at laser intensities 8-10 orders of magnitude lower than needed for standard 2-photon fluorescence probes. Protein-sized aUCNPs can be imaged through several millimeters of tissue in live mice using NIR lasers weaker than standard
laser pointers.
2:30 Single Cell Delivery of Payloads Utilizing Controllable Silicon Nano-Needles
Anil Narasimha, PhD, CSO, Mekonos, Inc.
We have created a new platform to deliver molecules into cells utilizing controllable silicon nano-needles. Using our single cell platform, we can deliver payloads at high efficiency and low toxicity in fragile cell types for applications such as
gene therapy, basic research, and drug discovery.
3:00 Mass Cytometry and Measurement of Global Immune Competence
Holden T. Maecker, PhD, Professor (Research), Microbiology
& Immunology, Stanford University School of Medicine
Mass cytometry, or CyTOF, is a version of flow cytometry that uses heavy metal ion labels in place of fluorochromes, with readout by time-of-flight mass spectrometry. This allows for many more labeled antibodies to be used in combination, with much
less spillover between detection channels. Our lab uses CyTOF to analyze PBMC from patients undergoing cancer immunotherapy in order to define metrics of immune competence that may be necessary for immunotherapy success.
3:30 Refreshment Break and Poster Competition Winner Announced in the Exhibit Hall
4:15 Mass Spectrometry-Based Proteomic Analysis of Single Mammalian Cells
Ryan Kelly, PhD, Associate Professor, Chemistry and Biochemistry, Brigham Young University
Human tissues contain a variety of cell types and subtypes with distinct functions, and understanding heterogeneity at the single cell level is of great interest for biomedical research. Mass spectrometry-based proteomic analyses can quantify thousands
of proteins, but the extension to single cells has been ineffective due to protein losses during preparation. We have developed novel sample processing and analysis workflows that overcome these losses and enable in-depth, quantitative and label-free
proteome profiling of single mammalian cells.
4:45 Characterizing Heterogeneity via Single Cell Receptor Quantification
Princess Imoukhuede, PhD, Associate Professor, Department of Biomedical
Engineering, Washington University in St. Louis
While there are a plethora of data available on protein expression (e.g., Western blots), much of these data report relative protein amounts or qualitative descriptions of protein presence. Unfortunately, there are few quantitative data available.
Our work aims to overcome these challenges by leading efforts to sensitively measure both plasma membrane protein concentrations and in so doing, provide metrics for understanding heterogeneity.
5:15 PANEL DISCUSSION: The How and the Why of Single Cell Analysis
Moderator:
Ryan Kelly, PhD, Associate Professor, Chemistry and Biochemistry, Brigham
Young University
Panelists:
Bruce E. Cohen, PhD, Staff Scientist, The Molecular Foundry, Lawrence
Berkeley National Laboratory
Princess Imoukhuede, PhD, Associate Professor, Department of Biomedical
Engineering, Washington University in St. Louis
Holden T. Maecker, PhD, Professor (Research), Microbiology
& Immunology, Stanford University School of Medicine
Anil Narasimha, PhD, CSO, Mekonos, Inc.
Additional Panelists to be Announced
Higher-throughput single cell isolation technologies are being developed for imaging, mass spectrometry, payload delivery, and sequencing applications. Understanding cell heterogeneity is revolutionizing our understanding of health and disease.
However, much needs to be accomplished before this knowledge can be integrated into applied therapies and diagnostics. Learn from this panel of experts as they share how we study single cells and where this knowledge can be applied.
5:45 Reception in the Exhibit Hall with Poster Viewing
6:45 Close of Day
Friday, March 15
8:00 am Registration Open and Morning Coffee (Continental Foyer)
8:25 Chairperson’s Remarks
Adrian Bot, MD, PhD, Vice President, Translational Sciences, Kite, a Gilead Company
8:30 High-Dimensional Profiling of Human Antigen-Specific T Cells: Asking T Cells What They “See” in Cancer
Yannick Simoni, PhD, Research Fellow, Vaccine and Infectious Disease Division,
Fred Hutchinson Cancer Research Center
The utility of high-dimensional mass cytometry analysis together with rapidly evolving computational analysis tools will be discussed. For T cell antigen specificity, this analysis can be performed in conjunction with a highly multiplexed
method based on peptide-MHC tetramers. Application of these approaches to identify and phenotypically profile virus and cancer-specific T cells will be described. In addition to the possibility of finding novel therapeutic targets, a long-term
goal of this work is to discover more accurate biomarkers of clinical outcomes.
9:00 Generation of Engineered Pluripotent Cell-Derived T Cells as a Cornerstone Approach for Off-the-Shelf Cancer Immunotherapy
Bahram (Bob) Valamehr, PhD, MBA, Chief Development
Officer, Fate Therapeutics, Inc.
I describe the creation of a universal CAR-T cell completely absent of TCR expression from renewable master pluripotent cell line, and how this reduces cost and improves patient accessibility through a true off-the-shelf approach. Additionally,
I discuss i) engineering CAR into the TRAC locus for improved product quality and efficacy; ii) targeting antigen escape through a secondary antibody-dependent mechanism; and iii) development of a cellular platform to enable multiplex
engineering in a single cell.
9:30 Single-Cell Optical Analyses for the Characterization and Development of Immunomodulatory Therapies
Andrea Pomerantz, PhD, Investigator III, Microscopy and Biophotonics (MiBs), Analytical Sciences and Imaging, Novartis Institutes for BioMedical Research, Inc.
In support of the development of new immunomodulatory therapies at NIBR, we are implementing microfluidic and confocal imaging approaches for interrogating single immune cell / target cell interaction dynamics. We have also developed single-cell
imaging flow cytometry assays for CAR-T cell therapies in order to gain a detailed understanding of factors driving the safety and efficacy of these transformative therapeutics.
10:00 Functional Capacity of Immune Cells as Measured by Single Cell Proteomics Predicts Clinical
Outcome Across IO Therapies
Will Singleterry, Director, Business Development, Isoplexis
Using single cell proteomics to measure the functional capacity or ‘fitness’ of immune cells has correlated with and been predictive of clinical outcome in CAR-T, TIL, Cancer Vaccine and Checkpoint Inhibitor therapy.
This talk will review several of these data sets and discuss applications of IsoPlexis’ single cell technology
10:30 Coffee Break in the Exhibit Hall with Poster Viewing
11:15 FEATURED PRESENTATION: High-Resolution Characterization of CAR-T Cell “Fitness” to Aid Process Optimizations and Clinical Development
Adrian Bot, MD, PhD, Vice President, Translational Medicine, Kite, a Gilead Company
A major advantage of T cell products based on primary lymphocytes is their composition, comprising multiple subsets that may complement each other functionally towards mediating clinical outcomes. Based on a range of methods including single
cell analysis, we are advancing a systematic approach to characterize product T cell fitness that integrates three key attributes: their intrinsic expansion capability, polyfunctionality, and dose of specialized cells in the product infusion
bag.
11:45 Single Cell Mass Cytometry and AI-Guided Analysis to Predict Therapeutic Response and Monitor and Direct Clinical Trials
Carsten Krieg, PhD, Assistant Professor of Immunology, Microbiology & Immunology and Dermatology, Medical University
of South Carolina
Immunotherapy has revolutionized oncology but not everyone responds to therapy or relapses under therapy. We developed a workflow based on high-dimensional single cell mass cytometry combined with augmented intelligence (AI)-supported bioinformatics
to analyze liquid blood biopsies to a) predict immune response to immunotherapy and b) monitor and direct clinical trials. The generated cellular maps, so-called “immune instagrams”, might help in stratifying patients prior
to immunotherapy, choosing the right therapeutic combination, and supporting clinical trial decisions.
12:15 pm Circulating T Cell Subpopulations Correlate with Immune Responses at the Tumor Site and Clinical Response to PD1 Inhibition in Non-Small Cell Lung Cancer
Nataly Manjarrez-Orduño, PhD, Clinical Mechanisms Lead, Bristol-Myers Squibb
Analysis of peripheral blood of cancer patients showed that peripheral T cell subpopulations inform about the state of the anti-tumor immune response and identify potential blood biomarkers of clinical response to checkpoint inhibitors in
melanoma and NSCLC.
12:45 Close of Symposium