#1CYTEK TRANSCEND THE CONVENTIONAL Investor and Analyst Day Dr. Wenbin Jiang, CEO June 22, 2022#2Safe Harbor Statement This presentation and the accompanying oral presentation contain forward-looking statements within the meaning of the Private Securities Litigation Reform Act of 1995, including, among others, statements regarding the size and growth of the cell analysis market; Cytek's anticipated total addressable market; Cytek's vision and business and operational strategy; Cytek's prospective products; Cytek's business development plans and opportunities; Cytek's goals, market opportunities and competitive position; and Cytek's financial guidance, including its expectations that full year 2022 revenue will be closer to the high end of the range of $160 million to $168 million. Forward-looking statements are neither historical facts nor assurances of future performance. Instead, they are based on our current expectations and projections about future events and financial trends that we believe may affect our financial condition, results of operations, business strategy, and financial needs. All statements other than statements of historical facts contained in this presentation, including, without limitation, statements The words "may," "will," "expect," "anticipate," "aim," "estimate," "intend," "plan," "believe," "is/are likely to," "potential," "continue" and other similar expressions are intended to identify forward-looking statements, although not all forward-looking statements contain these identifying words. Forward-looking statements are subject to numerous risks and uncertainties that could cause actual results to differ materially from currently anticipated results, including but not limited to risks relating to market conditions; the ongoing COVID-19 pandemic; supply chain risks and Cytek's dependence on certain sole and single source suppliers; competition; market acceptance of Cytek's current and potential products; Cytek's ability to manage the growth and complexity of its organization; Cytek's ability to maintain, protect and enhance its intellectual property; and Cytek's ability to continue to stay in compliance with its material contractual obligations, applicable laws and regulations. Information on these and additional risks and uncertainties and other information affecting Cytek's business and operating results is contained in Cytek's Quarterly Report on Form 10-Q for the quarter ended March 31, 2022, and in its other filings with the Securities and Exchange Commission. These forward-looking statements speak only as of the date hereof. Except as required by applicable law, Cytek does not plan to publicly update or revise any forward-looking statements contained herein, whether as a result of any new information, future events, changed circumstances or otherwise. No representations or warranties (expressed or implied) are made about the accuracy of any such forward-looking statements. Certain information contained in this esentation and statements made orally during this presentation relate to or are based on studies, publications, surveys and other data obtained from third-party sources and Cytek's own internal estimates and research. While Cytek believes these third-party sources to be reliable as of the date of this presentation, it has not independently verified, and makes no representation as to the adequacy, fairness, accuracy or completeness of, any information obtained from third-party sources. While Cytek believes its internal research is reliable, such research has not been verified by any independent source. Cytek's estimates are derived from publicly available information, management's knowledge of the Cytek's industry and management's assumptions based on such information and knowledge, which they believe to be reasonable. This data involves a number of assumptions and limitations which are necessarily subject to a high degree of uncertainty and risk due to a variety of factors. This presentation contains adjusted EBITDA, adjusted gross profit and adjusted gross profit margin, financial measures that are not in accordance with Generally Accepted Accounting Principles (GAAP). Reconciliations of adjusted EBITDA, adjusted gross profit and adjusted gross profit margin to the most comparable GAAP measures are included at the end of this slide presentation. We present adjusted gross profit and adjusted gross profit margin because we believe they are frequently used by analysts, investors and other interested parties to evaluate companies in our industry and it facilitates comparisons on a consistent basis across reporting periods. Further, we believe it is helpful in highlighting trends in our operating results because it excludes items that are not indicative of our core operating performance. Cytek, Full Spectrum Profiling, FSP, Northern Lights and cFluor are trademarks or registered trademarks of Cytek Biosciences, Inc. Other trademarks appearing in this presentation are the property of their respective holders. CYTEK TRANSCEND THE CONVENTIONAL 2#3Analyst / Investor Day Agenda Welcome | Dr. Wenbin Jiang, CEO Market Overview | Mark Herberger, Sr. Director, Marketing. Aurora at the NIH | Dr. Bill Telford, NIH/NCI (by video) High Dimensional Cell Sorting | Kevin Weller, Ohio State Aurora Empowering Immunological Research | Dr. Anna Belkina, Boston University 10:30 10:45 Cytometry in Leukemia & Lymphoma | Dr. Franklin "Buddy" Fuda, UTSW 9:00 - 9:15 9:15 - 9:45 9:45 10:00 10:00 10:15 10:15 10:30 10:45 10:55 10:55 11:25 11:25 11:35 11:35 11:45 11:45 - 12:00 12:00 - 12:30 CYTEK TRANSCEND THE CONVENTIONAL Break Product and Technology Overview | Dr. Ming Yan, CTO and Mark Herberger Financial Overview | Patrik Jeanmonod, CFO Business Strategy and Conclusions | Dr. Wenbin Jiang Q&A Hors d'oeuvre and Social 3#4Cytek's Leadership Team Wenbin Jiang, Ph.D. Chief Executive Officer LIGHTSPEED BANDWIDTH> Cosemi LUMENTUM Valerie Barnett General Counsel Dermira FLUIDIGM Maria Jaimes, M.D. VP, Applications BD CYTEK TRANSCEND THE CONVENTIONAL WILSON SONSINI Ming Yan, Ph.D. Chief Technology Officer BD Ne Photonics llen Poirson, Ph.D. SVP, Marketing and Corporate Development SONY Acculmage twoXAR BIOTECHNOLOGY Connie Wedel Chief People Officer Binding Site ARGEN Paul Goodson Head of Investor Relations Invitrogen living science sequenom. XOMA Mark Edinger VP, Scientific Affairs Patrik Jeanmonod Chief Financial Officer CORE COVANCE BRANDS BDQ²Solutions® Mark Herberger Sr. Director, Marketing BD BIO RAD Thermo Fisher SCIENTIFIC Melik Ulusu VP, Operations & Integrated Supply Chain BD PerkinElmer Todd Garland Chief Commercial Officer BD CareFusion CardinalHealth Ken Riley General Manager BD INTUITIVE SURGICAL Dave Kennedy VP, Global Sales & Service SARTORIUS amnis 4#5Cytek Highlights Patented, transformative FSP platform, delivering deep insights, high-throughput and ease-of-use Enabling broad applications in discovery, translational and clinical CYTEK TRANSCEND THE CONVENTIONAL 汩 Addresses unmet needs and provides highly intuitive and flexible customer experiences Diversified customer base with accelerating publications. Global scale and reach, with uniquely diversified geographics 5#6Global Scale and Reach with Diversified Revenue Mix Since launch of Aurora Series in 2017 900+ Customers 500+ Employees 150+ Biopharma Companies 40+ Countries WW Applications, Service & Sales % Revenue by Industry 51% 49% CYTEK TRANSCEND THE CONVENTIONAL Seattle Fremont (Headquarters). San Diego Academic and Government-Owned Institutions ■ Pharmaceutical and Biotechnology Companies, Distributors and CROS Bethesda Amsterdam % Revenue by Region USA 58% ΕΜΕΑ 25% Wuxi Shanghai APAC 17% Tokyo#7Investing to Capture the Cell Analysis Opportunity Broad Customer Base and Global Presence Strong Financial Profile* Validated Technology Platform * 1,226 Units Placed 740 Publications *Units as of 3/31/22 Publications as of June '22 CYTEK TRANSCEND THE CONVENTIONAL 900+ Customers 40+ Countries $139M $18M TTM Revenue/ A-EBITDA $362M $0M Cash/Debt * Data as of 3/31/22 CE-IVDD Tonbo Cell Sorter Reagents Northern Lights Aurora 238 2022 2021 2021 2020 2018 2017 7#8Our FSP Platform Allows Us to Address the Broader Cell Analysis Market $1.0B Single Cell Analysis $1.6B Cell Counting & QC CYTEK TRANSCEND THE CONVENTIONAL $8B Initial TAM (Cell Analysis Market in 2019 Addressable by Flow Cytometry) $1.9B Cell Proliferation $3.0B Cell ID $1.1B Cell Structure $1.3B Target ID $1.3B Cell Interaction $8B Additional TAM (Cell Analysis Market in 2019 Not Currently Addressable by Flow Cytometry) $2.4B Cell Viability $2.4B Cell Signaling $23B Long-Term TAM (Total Cell Analysis Market in 2024) Marine Biology Water Supply Contamination 8) Alternative Biofuels#9Today's Focus Areas Where Flow Cytometry fits in Research, Clinical, Diagnostics, and Other Areas 4 Real World Examples of Cytek's Use in Research and Clinical CYTEK TRANSCEND THE CONVENTIONAL Market Segments, Sizes, and Growth Rates Our Financial Profile and Business Drivers What our Technology Enables: Why Customers Choose Cytek Our Business Strategy and Objectives Reagents - Markets and Opportunities The Reasons Cytek Can Become #1 in Cell Analysis 9#10CYTEK TRANSCEND THE CONVENTIONAL (R) Investor and Analyst Day Market Overview Mark Herberger, Sr. Director Marketing June 22, 2022 10#11Why Flow Cytometry? A Transformative Platform Technology Infectious diseases Autoimmune diseases Normal CYTEK TRANSCEND THE CONVENTIONAL XXXXXX Autoimmune disease Immune regulation 548 Environment 248 Exhaustion Abnormal Senescence Bulk Tumour Distant metastasis Single cell analysis Immuno-Oncology Cancer cell clone 1 Cancer cell clone 2 CAF O Endothelial cell Macrophage NK T-cell B-cell ¹} Cell sorting XM - Malignant Str Stromal Immune DOMO Xpl Genomics MIN ANNUN VINN Trascriptomics Proteomics 11#12Cytek Technology Enables Applications JCI insIGHT Cell # Publications Publications by Application Q3 '18 CYTEK TRANSCEND THE CONVENTIONAL 3% 2% 12% 2% # 3 6 Q4 '18 Cancer Research The Foundational Cancer Journal Driving Transformative Science 12% 9% 9 13% Q1 '19 AAGR Volume 7 American Association 13% 11 21% Q2 '19 Dec 201 Volume 3 24 5% Tumor-specific MHC-Il expression drives a unique pattern of resistance to immunotherapy 18 Insight.j.org Q3 '19 25 Q4 '19 The Journal of Immunology Auto-immune disorder COVID-19 Drug discovery Genomics Oncology Immuno-oncology Immunology Immunotherapy Infectious disease Inflammation Neurobiology Transplantation Viral infection 45 Q1 '20 70 Q2 '20 nature INSIDE GREEN FLUORESCENT PROTEIN The vibration that powers the classic gene expression marker PANDEMIC FLU In the lab with HIN1 DUAL ROLE FOR UNIVER Towards a new social contract THE ORIGINS OF SPEEC FOXP2 and the chimp-human divide 111 172 NATURE JOBS Distant learning Advances AAAAS 242 Q3 '20 Q4 '20 Q1 '21 325 JANUARY 201 Q2 '21 414 Q3 '21 516 Q4 '21 652 740 Q1 '22 Q2 '22 12#13Market Forces and Needs Shaping Cell Analysis Research Emergence of high dimensional characterization & functional assays ● ● ● The rise of immunotherapy, tum or microenvironment, infectious disease studies (COVID) In 2021 Flow Cytometry accounted for the largest share of -29% of the global cell analysis market Target customers Academic Institutions Pharma & Biotech R&D CYTEK TRANSCEND THE CONVENTIONAL Translational CRO focus on cell markers and biomarkers leads to new clinical applications Comprehensive Panels, New Fluorochromes Instrument Characterization, Optimization, Standardization Panel Construction, Optimization, Validation, Automation Data Analysis, Automated Analysis, Cloud-based Target customers CRO, Pharma, Specialty labs Performance (quality), price, IVD, customer service are fundamental needs ● ● ● ● ● Clinical ● Validated applications & assay kits Understanding and adjusting to changing clinical regulations EU IVDR May 2022 (replacing IVDD) Laboratory Developed Tests (LDT) VALID Act proposed in US congress to replace 510 K and LDT with new category Target customers Reference labs, hospital labs Developing country clinical labs 13#14Cytek Plans to Expand the Market and Capture Share Customer Segment Application(s) Competitors Market CAGR CYTEK TRANSCEND THE CONVENTIONAL Academic Research Immuo profiling Immuno-Onc, Immunology BD, Danaher, Cytek, Thermo, Agilent, Cytof, Miltenyi, Sony ~10-12% Translational Pharma / BioTech / CRO Dendritic cells, Car-T, Vaccine development & trials, Receptor Occupancy Assays BD, Danaher, Miltenyi, Agilent, Cytek -12-15% Cytek Market Share Expected to Increase Clinical Reference labs, hospitals MRD, IO, LDT, Immunotherapy monitoring BD, Danaher, Cytek ~5-8% 14#15A Selection of Application Areas for FSP CYTEK TRANSCEND THE CONVENTIONAL Immuno-oncology blood 803 EMERGING DIAGNOSTIC TOOLS AND TECHNIQUES | NOVEMBER 5, 2020 One Tube 24 Color Full Spectral Flow Cytometry and Multi-Dimensional Software to Study the Maturation Pattern and Antigen Expression of the Myeloid Man Chen Wang MD Mining Fun Wang Mewel Gong Juny Zhen Xuying W Kun Zhan Pehua Lu MO Pathology & Laboratory Medicine Division Haber Yanda Ludaper hospital Langlang, China Pathology & Labiry Medicine Din Habe Yands Lu Dapel Heng Chi "Pathology & Laboratory Medicine Dion Hebel Yande Ludope Hospital, Langtang China Yand LuDepe H Langling China 13:13 httpdol.org/10.1182/blood-2020-140000 Introduction Flow cytometry(FC) plays an important role in the diagnosis of hematologic diseases and the study of cell maturation Spectral multicolor flow cytometry(MFC) has shown an advantage over traditional FC that more fuorescent markers could be detected simultaneously, more antigen combinations could be made and the expression of cells could be scrutinized. However, published studies focused on lymphocyte subsets and the differentiation between hematogones and B-acute lymphoblastic leukaemia/ymphoma(ALL) meal residual disease (MRO) detection, and the there are few studies on myeloid development and expression. Besides, more powerful and cutting-edge software are needed for complicated combinations from SMFC because traditional dot plots are unable to meet the demand of analysis. Here we design a one-tube 24-color panel combining with the multidimensional data analysis software to study the expression and maturation of normal and malignant myeloid cells including minus subgroups. We hope to improve the sensitivity of MRD by FC and explore more information about myeloid diseases, finally promote the development of anficial intelligence(Al) in clinical FC diagnosis Methods: the one-tube 24-color panel was designed according to our experience and Euroflow recommendation, it is composed of backbones including CD45 and myeloblast markers CD34, CD117 and HLA-DR, adding myeloid markers CD33. CD13, CO371. CD1S, CD64 CD11c/CD14, CD36 and CD11b, routine leukaemia associated immunophenotyping(AIP) or different from normal(DFN) markers CYTEK TRANSCEND THE CONVENTIONAL Immuno-deficiencies PLOS ONE OND RESEARCH ARTICLE Natural killer cell phenotype is altered in HIV-exposed seronegative women Nancy Q Zhao Elane Vendrame Anne-Maud Fair, Christof Saker Thanay Rangana Mary Annie Claude Labbe, Femend Goedo, Johanne Poudrier Susan Holmes, Michel Roger Cas Published September 1, 2020 ps dol org/10.1371/joumal pone 0238347 Alastad Materias and methods Rendh Discussion Supporting inalin Adm Palaces Reader Comments Figures Authors Metrics Comments Media Coverage Abstract Highly expregative HESN) individuals presenta unique setting to study mechanisms of protection against HIV acquistan As natural kler (K) cell activation and function have been implicated as a corelate of protection in HESN individuals, we ought to better understand the features of NK calls that may confer protection. We used mass cytometry phenotypically proe NK cells from a cohort of Berinese sex workers and healthy controls. We found at Nata from HESN saman had increased asprassion of NA NK30 ULRB1, as wet as the Fc receptor CO16, and decreased expression of DNAM, CO ssments of NK cels om haathy donors again and Nodd Usino hectatel te Signed 14 teas autologous HIV infected CD4" Tools, wo and Siglec- cells had improved functional activity Further we found that NK calls from HESIN wameended towards increased antibody-dependent cellular cytotoxicity (ADCC) activity activity correlated with increased CD18 expression Overall, we idently features of NK oss in HESN women that may contribute to protection from HIV infection Follow up studies with largar cohorts are wenanted to conkm these findings Figures BERGARAGE 555555555 ... Flow Cytometry Cell Analysis Allergy & Immunology Androgen receptor signaling promotes Treg suppressive function during allergic airway inflammation Vive D. Gandhi, Jacqueline-Yvonne Cephus,' Allison E. Norlander,' Nowrin U. Chowdhury,² Jian Zhang,¹ Zachary J. Ceneviva, Elie Tannous,¹ Vasiliy V. Polosukhin, Nathan D. Putz,' Nancy Wickersham,' Amrit Singh, Lorraine B. Ware,' Julie A. Bastarache,¹ Ciara Peebles ,12 and Dawn C. Newcomb¹2 Shaver, Hong Wei Chu, R. Stokes Authorship note: VDG and JYC contributed equally to this work. Published January 13, 2002- More info View PDF Women have higher prevalence of asthma compared with men. In asthma, allergic airway inflammation is initiated by IL-33 signaling through ST2, leading to increased IL-4, IL-5, and IL- 13 production and eosinophil infiltration. Foxp3 Tregs suppress and ST2- Trega promote allergic airway inflammation, Clinical studies showed that the androgen dehydroepiandrosterone (DHEA) reduced asthma symptoms in patients, and mouse studies showed that androgen receptor (AR) signaling decreased allergic airway inflammation. Yet the impact of AR signaling on lung Tregs remains unclear. Using AR-deficient and Foxp3 fate- mapping mice, we determined that AR signaling increased Treg suppression during Alternaria extract (Alt Ext; allergen) challenge by stabilizing Foxp3+ Tregs and limiting the number of ST2- ex-Trege and IL-13- Th2 cells and ex-Trega. AR signaling also decreased Alt Ext-induced ST2+ Tregs in mice by limiting expression of Gata2, a transcription factor for ST2, and by decreasing Alt Ext-induced IL-33 production from murine airway epithelial cells. We confirmed our findings in human cells where 50-dihydrotestosterone (DHT), an androgen, decreased IL-33-induced ST2 expression in lung Tregs and decreased Alt Ext-induced IL-33 secretion in human bronchial epithelial cells. Our findings showed that AR signaling stabilized Treg suppressive function, providing a mechanism for the sex difference in asthma. Infectious Disease RESEARCH ARTICLE Successful treatment of COVID-19 with remdesivir in the absence of humoral immunity > Matthew S Buckland, James Galloway, Caoimhe Nic Fhogartaig, Luke Meredith, Nicholas M. Provine, Stuart Bloor, Ane Ogbe, Wioleta M. Zelek, Anna Smielewska, Anna Yakovleva, Tiffeney Mann, Laura Bergamaschi, Lorinda Turner, Frederica Mescia, Erik J.M. Toonen, Carl-Philipp Hackstein, Hossain Delowar Akther, Vinicius Adriano Vieira, Lourdes Ceron-Gutierrez, Jimstan Periselneris, Sorena Kiani- Alikhan, Sofia Grigoriadou, Devan Vaghela, Sara E. Lear, Estee Torok, William L Hamilton, Josh Quick, Joanne Stockton, Peter Nelson, Michael Hunter, Tanya I Coulter, Lisa Devlin, John Bradley, Ken Smith, Willem Ouwehand, Lise Estcourt, Hell Harvala Simmonds, Dave Roberts, lan Wilkinson, Nick Screaton, Nick Loman, Paul Lyons, Rainer Doffinger, Paul Morgan, lan Goodfellow, Paul Klenerman, Paul Lehner, Nick Matheson, James Thaventhiran Human Publications Successful treatment of COVID-19 with remdesivir in the absence.... Immunotherapy blood advances IMMUNOBIOLOGY AND IMMUNOTHERAPY | SEPTEMBER 8, 2020 Charge-altering releasable transporters enable phenotypic manipulation of natural killer cells for cancer immunotherapy Aaron J. Wilk, Nancy Lynn-Benner Weidenbacher, Rosemary Vergara, Ole A. W. Haabeth, Ronald Levy, Robert M. Waymouth, Paul A. Wender, Catherine A. Blish Human Blood Adv (2020) 4 (17): 4244-4255. https://doi.org/10.1182/bloodadvances 2020002355 Publications Charge-altering releasable transporters enable phenotypic manipulation of natural killer cells 15#16Application of FSP in Myeloid Disorders in L/L YOONESTE bloodⓇ 803.EMERGING DIAGNOSTIC TOOLS AND TECHNIQUES | NOVEMBER 5, 2020 One Tube 24 Color Full Spectral Flow Cytometry and Multi-Dimensional Software to Study the Maturation Pattern and Antigen Expression of the Myeloid Man Chen, Hui Wang, MD, Minjing Fu, Aixian Wang,"¹ "1 +1 2.1 Meiwei Gong, Junyi Zhen, Xueying Wu, Kun Zhao, Peihua Lu, MD5 ¹Pathology & Laboratory Medicine Division, Hebei Yanda Ludaopei hospital, Langfang, China "Pathology & Laboratory Medicine Division, Hebei Yanda Lu Daopei Hospital, Beijing, China *Beijing Ludaopei Hospital, Beijing, China *Pathology & Laboratory Medicine Division, Hebei Yanda Ludaopei Hospital, Langtang, China Hebei Yanda Lu Daopei Hospital, Langfang, China Blood (2020) 136 (Supplement 1): 13. http://doi.org/10.1182/blood-2020-140600 Introduction Flow cytometry(FC) plays an important role in the diagnosis of hematologic diseases and the study of cell maturation. Spectral multicolor flow cytometry (SMFC) has shown an advantage over traditional FC that more fluorescent markers could be detected simultaneously, more antigen combinations could be made, and the expression of cells could be scrutinized. However, published studies focused on lymphocyte subsets and the differentiation between hematogones and B-acute lymphoblastic leukaemia/lymphoma(ALL/LBL) minimal residual disease (MRD) detection, and there are few studies on myeloid development and expression. Besides, more powerful and cutting-edge software are needed for complicated combinations from SMFC because traditional dot plots are unable to meet the demand of analysis. Here we design a one-tube 24-color panel combining with the multidimensional data analysis software to study the expression and maturation of normal and malignant myeloid cells including minus subgroups. We hope to improve the sensitivity of MRD by FC and explore more information about myeloid diseases, finally promote the development of artificial intelligence(Al) in clinical FC diagnosis. Methods: the one-tube 24-color panel was designed according to our experience and Euroflow recommendation, it is composed of backbones including CD45 and myeloblast markers CD34, CD117 and HLA-DR, adding myeloid markers CD33, CD13, CD371, CD15, CD64, CD11c,CD14, CD36 and CD11b, routine leukaemia associated immunophenotyping(LAIP) or different from normal(DFN) markers CYTEK TRANSCEND THE CONVENTIONAL Published by Pathology Laboratory at Ludaopei Hospital, Chinal Spectral multicolor flow cytometry (SMFC) has shown an advantage over traditional FC that more fluorescent markers could be detected simultaneously, more antigen combinations could be made, Precise diagnosis through deep cellular level correlation A one-tube 24-color panel was designed according to our experience and Euroflow recommendation • Offers more cellular information that is unmatched by traditional FC ● ● tSN-2 a b sample 1-20 Healthy Control FCM MRD:0 a: b: sample 21 FCM MRD:0.23% blast cells,No special gene C: sample 22 FCM MRD:4.39% blast cells,FLT3:10.8%, WT1:6.86 sample 23 FCM MRD:30.31%blast cells,6.47%normal mast cells, sample 24 FCM MRD:0.29%blast cells, 16.49%basophils, BCL-ABL:23.40 d: + d A Selection of Application Areas for FSP CYTEK tSN-1 16 danc#17Application of FSP in Multiple Myeloma Diagnostics High-parameter and Effective Multiple Myeloma Diagnostic Panel on the Cytek NL- CLC Improves Sample Efficiency Li Xiong¹, Wen Du2,3, Yao-Kun Ma¹, Lei Qin¹, Qing Yuan¹, Yu Liu¹, Shi- Ying Xu¹, Juan-Hua Zheng¹, Xiao-Jian Xu¹, Fang-Ying Shang¹, Shi- Ang Huang2,3, Jin-E Zheng 2,3 1Flow cytometry laboratory, Wuhan Kindstar Medical Laboratory Co., Ltd, Wuhan, China 2Center for Stem Cell Research and Application, Institute of Hematology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China 3Biological Targeted Therapy, Key Laboratory in Hubei, Wuhan, China CYTEK TRANSCEND THE CONVENTIONAL ● ● ● ● Presented by Kindstar Medical Laboratory, China at ICCS 2021 Compared the antigen expression and diagnostic results obtained from the Cytek NL-CLC vs. the widely used BD FACS Canto flow cytometer Converted four 6-, 7- color tubes to one 23-color tube Found no significant difference in detection accuracy between the instruments. • However, Cytek NL-CLC has many advantages including more detection parameters in a single tube, lower compensation interference, easier processing with small-volume samples Established a new standard 23-color panel for highly accurate detection of MM A Selection of Application Areas for FSP CYTEK Results wwwwww (1) Both Cylek NL-CLC full-spectrum flow cytometer and BD FACSCanto II flow cytometer could effectively classify cells from all bone marrow samples (Figure 1). There was no significant difference in cell ratios between the two cytometers (differences < 7.1%). A B P M 2 BACA Figure 1. The Cell population distribution in bone marrow samplec defeated by different panels (A: Cytak 28-oollor panel; B: BD 3-0olor panal). Abnormal plasma balls are colored in red. wwwwww. danc 17#18Flow Can Now Analyze 50 Parameters Cyto-Feature Engineering: A Pipeline for Flow Cytometry Analysis to Uncover Immune Populations and Associations with Disease Amy Fox¹, Taru S. Dutt', Burton Karger¹, Mauricio Rojas?, Andrés Obregón-Henao¹, G. Brooke Anderson³ & Marcela Henao-Tamayo¹ Flow cytometers can now analyze up to 50 parameters per cell and millions of cells per sample; however, conventional methods to analyze data are subjective and time-consuming. To address these issues, we have developed a novel flow cytometry analysis pipeline to identify a plethora of cell populations efficiently. Coupled with feature engineering and immunological context, researchers can immediately extrapolate novel discoveries through easy-to-understand plots. The R-based pipeline uses Fluorescence Minus One (FMO) controls or distinct population differences to develop thresholds for positive/negative marker expression. The continuous data is transformed into binary data, capturing a positive/negative biological dichotomy often of interest in characterizing cells. Next, a filtering step refines the data from all identified cell phenotypes to populations of interest. The data can be partitioned by immune lineages and statistically correlated to other experimental measurements. The pipeline's modularity allows customization of statistical testing, adoption of alternative initial gating steps, and incorporation of other datasets. Validation of this pipeline through manual gating of two datasets (murine splenocytes and human whole blood) confirmed its accuracy in identifying even rare subsets. Lastly, this pipeline can be applied in all disciplines utilizing flow cytometry regardless of cytometer or panel design. The code is available at https://github.com/aef1004/cyto-feature_ engineering. CYTEK TRANSCEND THE CONVENTIONAL ● ● ● Flow cytometers can now analyze up to 50 parameters (antigens, size, granularity, cytokines, transcription factors, etc.) per cell and millions of cells per sample Conventional flow cytometry data analysis uses manual gating of cells on 2D plots to distinguish populations 1-2 dimensions at a time; this makes it both subjective and time consuming (up to 15 hours per experiment) Better methods are therefore critically needed to take full advantage of this powerful technology. Data Cleaning I 30-06 26-06 16+06 FSC-H 0+0+00 20-06 FSC-A 36+05 Singlets 20+06 10+06 Density Leukocytes De+00 00-00 5-05 40-06 30-06 24-06 16-06 De 00 24+06 FSC-A Live 43% de+00 50-04 Zombie NIR-A 40-06- Se+00 20+08 10-06- 000- 40+06 3+06 20-06 -10-04 000 10:00- Ce+00- Feature Engineering 40+06- 3 06- 2006- FMOS fe 00- De-00- 10+04 0+00 CD3 CD4 -10-04 0-00 CD8 2404 26+04 COLE 20-04 coun Visualization Phenotype Identification Population Correlation Cell Percentage Pop38 0.4- 0.2- 0.0- Hypothesis Testing Population and CFU Correlation Pop3 ²=0.688 Pop27 Q090348 0.25 3 = 0.70 0.25 0.50 Pop32 A Selection of Application Areas for FSP CYTEK 0.50 0.75 0.75 18 danc#19Application of FSP in Immunology Development of a 43 color panel for the characterization of conventional and unconventional T-cell subsets, B cells, NK cells, monocytes, dendritic cells, and innate lymphoid cells using spectral flow cytometry Fairooz Sahir, Jericha Miles Mateo, Martin Steinhoff, Kodappully Sivaraman Siveen X First published: 18 December 2020 | https://doi.org/10.1002/cyto.a.24288 | Citations: 2 Funding information: Hamad Medical Corporation, Grant/Award Numbers: MRC-03-19-039, IRGC-04-51- 17-151, IRGC-03-NI-17-071 E SECTIONS PDF CYTEK TRANSCEND THE CONVENTIONAL TOOLS SHARE Abstract Although many flow cytometers can analyze 30-50 parameters, it is still challenging to develop a 40+ color panel for the phenotyping of immune cells using fluorochrome conjugated antibodies due to limitations in the availability of spectrally unique fluorochromes that can be excited by the commonly used laser lines (UV, Violet, Blue, Green/Yellow-green, and Red). Spectral flowcytometry is capable of differentiating fluorochromes with significant overlap in the emission spectra, enabling the use of spectrally similar fluorochrome pairs such as Brilliant Blue 515 and FITC in a single panel. We have developed a 43 color panel to characterize most of the immune subsets within the peripheral immune system, including conventional T cells, unconventional T cells such as invariant natural killer T cells (INKT), Gamma delta (yo) T-cell subsets (TCR V82, TCR VY9) and mucosal-associated invariant T cells (MAIT), B-cell subsets, natural killer (NK) cells, plasmacytoid dendritic cells, dendritic cell subsets, hematopoietic progenitor cells, basophils, and innate lymphoid cell (ILC) subsets (CD117, CRTH2). The panel includes surface markers to analyze activation (CD38, HLA-DR, ICOS/CD278), differentiation (CD45RA, CD27, CD28, CD57), expression of cytokine and chemokine receptors (CD25, CD127, CCR10, CCR6, CCR4, CXCR3, CXCR5, CRTH2/CD294), and co-inhibitory molecules and exhaustion (PD-1, CD223/LAG-3, TIGIT), which enables a deep characterization of PBMCs from peripheral blood. Cells were analyzed on a 5-laser Cytek Aurora and data analysis was done using Flowjo. This panel can help to make a thorough interpretation of immune system, specifically when specimen quantity is low. The panel has not been completely optimized but would rather act as a guide toward the development of a ● Scientists developed a 43 color panel to characterize most of the immune subsets within the peripheral immune system, including conventional T cells unconventional T cells ● ● ● ● B-cell subsets natural killer (NK) cells dendritic cells A Selection of Application Areas for FSP CYTEK hematopoietic progenitor cells basophils Innate lymphoid cell Cells were analyzed on a 5-laser Cytek Aurora and data analysis was done using Flow Jo. This panel can help to make a thorough interpretation of immune system, specifically when specimen quantity is low. 19 danc#20Adjacent Markets: The Power of "AND" Flow cytometry is often used with and enables downstream or companion technologies CYTEK N.CLC Flow Cytometry Analysis Cytek Instruments & cFluorTM Reagents CYTEK TRANSCEND THE CONVENTIONAL Flow Cytometry Sorting --- SH Next Gen Sequencing 10x illumina GENOMICS High Content Imaging Molecular Biology THE TIMANT ------- ADVANCED SCIENCE Full Paper Open Access Ⓒ+ The Beneficial Role of Sunitinib in Tumor Immune Surveillance by Regulating Tumor PD-L1 Hui Li, Xinwei Kuang, Long Liang. Youqiong Ye, YongChang Zhang, Jialu Li, Fangyu Ma. Juan Tao, Guang Lei. Shuang Zhao. Juan Su. Nong Yang. Cong Peng. Xiaowei Xu ... See all authors ✓ First published: 27 November 2020 | https://doi.org/10.1002/advs.202001596 ADVANCED SCIENCE NEWS www.advancech ciencenews.com B E dumis Ubeg24) Down2743 Averige b Durilish (AME 2 my LCH GAPON A375 Open Access ADVANCED SCIENCE www.advancediscience.com A335 Sk-mel28 Sunitin-p Su-25 Surtis-Sult 52 942 LC 942 LCON Skers-28 FR, Gung OMGO-ITN-y Scie 30-10-29 20#21Multicolor Flow Combined With Next Gen Sequencing Combining these technologies improves the ability to predict leukemia relapse after therapy ELSEVIER Allogeneic: Adult Multicolor Flow Cytometry and Multigene Next-Generation Sequencing Are Complementary and Highly Predictive for Relapse in Acute Myeloid Leukemia after Allogeneic Transplantation Biol Blood Marrow Transplant 23 (2017) 1064-1071 ¹ Bone Marrow Transplant Service, Memorial Sloan Kettering Cancer Center, New York, New York 2 Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, New York * Leukemia Service, Memorial Sloan Kettering Cancer Center, New York, New York 4 Memorial Sloan Kettering Center for Hematologic Malignancies, New York, New York Article history: Received 13 January 2017 Accepted 12 March 2017 Biology of Blood and Marrow Transplantation journal homepage: www.bbmt.org Bartlomiej M. Getta ¹.*, Sean M. Devlin 2, Ross L. Levine 3,4, Maria E. Arcila 5, Abhinita S. Mohanty 5, Ahmet Zehir 5, Martin S. Tallman ³, Sergio A. Giralt ¹, Mikhail Roshal 6 Diagnostic Molecular Pathology Laboratory, Memorial Sloan Kettering Cancer Center, New York, New York * Department of Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, New York Key Words: Minimal residual disease Flow cytometry Next-generation sequencing Acute myeloid leukemia CYTEK TRANSCEND THE CONVENTIONAL ASBMT American Society for Blood and Marrow Transplantation Cross Mark ABSTRACT Minimal residual disease (MRD) in acute myeloid leukemia (AML) is typically measured using multiparam- eter flow cytometry (MFC). Detection of leukemia mutations using multigene next-generation sequencing (NGS) can potentially be used to measure residual disease. We used a targeted 28-gene NGS panel to detect muta- tions and different-from-normal 10-color MFC to measure MRD in AML patients before allogeneic hematopoietic stem cell transplantation (HCT). Residual disease was defined when any abnormal blast population was de- tected using MFC and when any leukemia allelle was detected with a variant allele frequency (VAF) 25% using NGS. We tracked the clearance of leukemia alleles between AML diagnosis and immediately before HCT and found that mutations in DNMT3A, TET2, and JAK2 were less likely to be cleared than NPM1, JDH 1/2, and FL13- ITD. Despite varying sensitivities, the concordance rate of residual disease detection before HCT using the 2 assays was 44 of 62 (71%) evaluable cases. Discordance could be explained by residual mutations in DNMT3A and TET2 that were not detected by MFC and presence of residual leukemia mutations with VAF below the established thresholds for mutation calling. Presence of flow MRD and residual mutations immediately before HOR HCT using the 2 assays was associated with relapse risk (MFC: hazard ratio, 4.62; 95% confidence interval [CI], 1.32 to 16.09; P=.016 and NCS: hazard ratio, 4.35; 95% CI, 1.63 to 11.6; P=.003) and survival (MFC: hazard ratio, 2.44; 95% CI, 1 to 5.97; P=.05 and NGS: hazard ratio, 2.1; 95% CI, 97 to 4.55; P=.059) after HCT. Re- sidual disease detected concurrently by MFC and NGS conferred the highest relapse risk compared with patients who were either negative by both assays or had discordant status (overall, P = .008). Although MFC is univer- sally applicable, a multigene NGS approach to measuring residual disease in AML provides additional information on differential clearance of disease alleles and can assess clonal architecture before transplantation. ©2017 American Society for Blood and Marrow Transplantation. Published by Elsevier Inc. All rights reserved. Minimal Residual Disease (MRD) Predicting 4-Year Relapse for Acute Myeloid Leukemia (AML) MFC NGS 73% 52% 50% 21#22Cytek Commercial and Reagent Strategy Establish credibility H Academic Labs ● Instruments at top research universities across US, Europe and Asia Over 1200 instruments installed globally CYTEK TRANSCEND THE CONVENTIONAL Cutting-Edge Applications ● Focus on ● Immunotherapy Immuno-oncology Immune-profiling CAR-T cells >700 publications in many application areas Position the platform Pharma, Biotech & CROS ● Instruments at top pharma and CRO companies Cytek cFluor reagents and panels Cytek Continued Progress Translate applications into Clinical Space ● ● ● Immunotherapy monitoring Minimal Residual Disease Infectious diseases Expanded KOL partnerships & collaborations / LDT support Transforming Cytek to a Solutions Provider Kits & Panels ● ● Clinical & Research assays IVD product registrations completed or in process 22#23KOL Profiles Bill Telford, Ph.D. NIH / NCI, Head of Core Flow Cytometry Facility ● More than 20 years experience in flow cytometry More than 100 publications in immunology and cytometry Domestic and international teaching experience in flow cytometry Research on hardware and wetware R&D, including novel laser technology CYTEK TRANSCEND THE CONVENTIONAL Kevin Weller Co-Director Flow Cytometry, The Ohio State University and Associate Director for Peletonia's Immune Monitoring & Discovery Platform Cutting edge flow cytometry advances in reagents and instrumentation at BD Trained hundreds of researchers to use and maximize results from flow cytometry Anna Belkina, MD, Ph.D. Asst. Professor, Pathology & Laboratory Medicine, Director, Flow Cytometry Core Lab, Boston University ● ● Spectral cytometry applications in immunology and stem cell research Designed the opt-SNE algorithm for visualizing multidimensional cytometry datasets Focused on the intersection of immunology and computational biology Buddy Fuda, MD Professor of Pathology at the University of Texas Southwestern ● Medical director, clinical flow cytometry labs for UTSW Hospital and Parkland Memorial Hospital Numerous flow cytometry related academic publications and lectures International Clinical Cytometry (ICCS) committees 23#24CYTEK TRANSCEND THE CONVENTIONAL (R) Investor and Analyst Day Flow Cytometry in Oncology Dr. Bill Telford, NIH / NCI June 22, 2022 24#25NCI Flow Cytometry Core Laboratory William Telford, Ph.D. National Cancer Institute, National Institutes of Health ● ● 2000 ml A research core laboratory providing state-of-the- art flow and image cytometry services to NCI investigators. Building specialized instruments and improving flow cytometry technology is a big part of what we do. Our internal research and development program is guided and influenced by the scientists we serve.#26NCI Flow Cytometry Core Laboratory While a research-oriented shared resource facility, we support both basic and clinical research projects within the National Cancer Institute. • Clinical trial support is a major component of our mission - not diagnostic analysis for patient care, but high-level analysis of patient response to therapies. • Recovery of the immune system following allogeneic bone marrow transplantation, CAR-T and TCR based immunotherapies. ● • High-dimensional immunophenotyping - up to high-20 and low-30 immune cell markers. • Identification of immune cell subsets in tumors, both circulating and solid. • Some cancer cell analysis aimed at biochemical mechanisms. Fluorescent protein and physiological marker analysis. Cell sorting is a major focus of our group. When a research group analyzes a cell sample, they will soon want to physically separate it for further analysis. ● We need to provide cell sorting capability that matches our analysis-only capabilities.#27What do we analyze by flow cytometry? Our lab analyzes virtually many potential fluorescent targets Using antibodies, FPs and biosensors, we can target almost many cellular characteristics (and there are thousands)... Extracellular and intracellular receptors. Thousands now known for the immune system alone. Immunophenotyping. Expressible fluorescent proteins (FPs). Gene expression, tracking, organelle labeling. Physiological markers. Fluorescent biosensors for membrane electrical potential, pH, DNA content. While fluorescent immunolabeling is the dominant, it is often combined with FPs and physiological markers. Complex high- dimensional labelings are now the norm. Full spectrum analysis is essential for this. AUNUNUA Unununu Unununu MICE EXPRESSING GFP 401#28Spectral flow cytometry Traditional flow cytometers use single lasers to excite a fluorochrome, and detects fluorescence in narrow bandwidths using dichroic mirrors, filters and PMTs. cyan laser Spectral flow cytometry collects 488 nm fluorochrome data as complete spectra using multichannel PMTs or multiplex APD or SiPM arrays. Rather than compensation, it uses spectral unmixing or deconvolution to separate fluorescent probes (similar to confocal microscopy). D V16 V15 V14 V13 V12 V11 V10 V9 Detectors V8 V4 V3 DS DS 10⁰- SSC 10- PerCP Cy5.5 488 10 710/50 PE 680LP 552 LP 575/26 PE TxRed ultraviolet 355 nm 610/20 595 LP 635 LP 670/30 505 LP Spectral flow uses all lasers to excite all fluorochromes (not just the most optimal one) and collects the full spectra of each fluorochrome from all laser sources. The data is far more granular and allows better spectral separation that traditional compensation. 750 LP PE-Cy5 530/30 √3 VA √5 AF488 Her 780/60 Hempty, PE-Cy7 Positive Alexa Fluor 488 (Cells) violet 405 nm cell number Channel M AF488 fluorescence (530/30 nm) blue 488 nm Alexa Fluor 488 yellow 561 nm red 640 nm#29Traditional flow cytometry The traditional approach ... expand the dichroic / filter single detector model. Complexity, size and cost become prohibitive and detection efficiency suffers. BD Biosciences FACSymphony A5 A5 BD FArder Research Product $1 50 BUV395 PE-CF594 PE-eFluor610 PE-TxRed PI UV Laser 355nm G BUV496 Green Laser 532nm Cyan Laser 488nm E FITC BB515 GFP 00 E BUV661 00 E PE-Cy5.5 PerCP BB660 BUV737 B PE-Cy7 B PerCP-Cy5.5 PerCP-eFluor710 BB700 BUV805 08 B D A BYG790 BUV563 BB790 PE-Cy5 F BB630 PE DAPI BV421 Pacific Blue V450 eFluor450 G Red Laser 628nm Violet Laser 405nm BV605 Qdot 605 eVolve 605 APC eFluor 660 Ax647 00 E BV711 Qdot 700 Ax700 APC-R700 BV750 B B APC-Cy7 APC-eFluor 780 Ax780 BV650 Qdot 655 eVolve 655 BV786 Qdot 800 F BV510 The traditional approach as reached its practical limit for high-dimensional analysis.#30Spectral flow cytometry Full spectrum flow cytometry provides many advantages over traditional cytometry Dramatically improved ability to separate the signals from fluorescent probes with similar (but non-identical) spectra. This allows us to analyze many more fluorescent probes (and cell markers) simultaneously. More than 40 marker analysis is now practical (and has been reported). Improved quality of signal separation. While spectral cytometry is not strictly more sensitive than traditional techniques, improved signal separation improves data quality. Some interesting advantages derive from these improvements... Spectral cytometry is more "forgiving" of less-than-optimal fluorochrome selections. Many older fluorochromes previously less useful for flow cytometry now have new potential. The variety of fluorescent probes now usable for cytometry is greatly increased. Virtually any visible fluorochrome can be used. Spectral analysis allows improved subtraction of cellular autofluorescence, improving detection sensitivity, particularly in difficult cell types like myeloid lineages and tumors.#31DC1555 KRC Arno versus spectral analysis Aurora analyzer Option 3B SSC-H 3.0M- 2.0M- 1.0M- 0 0 1.0M CD3 PECY5 CD4 QD655 Mloid cells 9.72 wwwphecytes 47.2 HLA-DR PECY7 CD14 QD800 2.0M FSC-H 3.0M CD56 BV421 CD45 eFluor 450 CCR7 BV605 CD19 StarBright Violet 610 4.0M Comp-BV421-A :: CD56 SSC-H CD2 BV711 CD8 QD705 CD45RA AF488 CD20-biotin streptavidin-QD525 Comp-B/605-A : CD20 10° 105 104 4.0M- 3.0M 2.0M- 1.0M- 0 10° -10 monocytes -104 -104 -104 104 Comp-Odot 800-A CD14 0 0 CD19+ CD20+ 51.7 10 Comp-eFluor 450-A: CD45 0 CD56+ 65.0 CD45+ 99.3 10 10 B cells Comp-StarBright Vio 610-A 105 108 Comp-EV711-A :: CD2 Comp-BV711-A :: CD2 Comp-Qdot 705-A :: CD8 10 10⁰ 105 -1042 105 103 -104 NK cells CD56+ 86.4 -104 CD3- CD2+ 7.74 -10" -104 B 0 Cono-BV421-A: CD56 0 ™™|™||||| 0 104 CD3+ CD2+ 75.1 DN 14.5 104 Comp-PE-Cv5-A: CD3 CD4 T cell CD8+ 32.8 105 104 105 Comp-Qdot 655-A :: CD4 10° 10 A T 108 107 Fluorochromes intentionally chosen for close spectral proximity. 10⁰ Comp-Alexa Fluor 488-A :: CD45RA Comp-Qdot 525-A : Comp-Qdot 525-A :: CCR7 105 104 10° -104 12-color panel comparison between spectral and fluorescence lifetime cytometry. CD4 T naïve cells -104 -104 -104 CD4+CD45RA+ 28.4 104 Comp-Odot 655-A 0 0 CD4+ CCR7+ 44.1 104 Comp-Odot 655-A CD4 CD8+ CCR7+ 36.3 CD4 104 105 10° Comp-Odot 705-A :: CD8 10 10 |||||||||||||| 105 108 Comp-Alexa Fuor 488-A :: CD45RA Comp-PE-Cy7-A :: HLA-DR Comp-PE-Cy7-A: HLA-DR 108 -104 10 10⁰ 104 -104 10 105 -104. CD8+ CD45RA+ 17.0 CD8 T naïve cells 10 -104 -10" 0 Comp-Odot 705-A :: CD8 10 CD4+ HLA-DR+ 3.34 CD8+ HLA-DR+ 5.91 זיזו 0 Comp-Qdot 655-A CD4 104 105 104 10° 105 Comp-Qdot 705-A: CD8 10 108 10⁰#32BV421 and SuperBright 436 by spectral cytometry 120 100 % Normalized Excitation/Emission 80 60 40 20 S 300 10⁰. 10- 10³. 10*- 10¹- 10²- BV421 BV421 400 ultraviolet 355 nm UVI SuperBright 436 ↓↓ SuperBright 436 ✓² √² √² VA √5 vo v² V8 Brilliant Violet 421 Emission Super Bright 436 Emission 500 violet 405 nm 3 32 V3 VA VS VG VI V8 V9 V10 VIT VIZ VIS VIA VIS VIC B1 B2 B3 B4 B5 BG BT Channel Positive Super Bright 436 (Cells) Positive BV421 (Cells) VID B¹ B2 B3 BA BS BE Channel blue 488 nm 600 Two fluorochromes that are VERY similar spectrally but can be distinguished by spectral cytometry. Not possible by traditional cytometry. yellow 561 nm al al RRS red 640 nm 700 SuperBright 436 10⁰ 800 10⁰ zoom out zoom in BV421 10² Alejanju konsulent fa 0.97 900 10⁰#33Cytek Aurora 27 colors One of our users (Natalia Schneider-Nunez, Chris Kanakry Lab, ETIB-CCR-NCI) is designing a 27-color panel for murine B/T/NK/myeloid cells. UV BUV395 CD317 BUV496 CD24 BUV563 F4/80 BUV615 B220 BUV661 CD11b BUV737 CD45.1 BUV805 CD8 violet BV421 CD135 PacBlue CD80 BV510 Ter119 and L/D Aqua BV570 NK1.1 BV605 CD86 BV650 1-A/I-E BV711 CD172a BV786 XCR-1 green-yellow PE CD207 PE-CF594 CD103 PE-Cy5 Thy1.2 PE-Cy7 PD-L1 red APC CD45.2 AF647 CD1d AF700 H2Kb APC-Cy7 CD40 blue FITC CD11c SB550 CD4 PerCP Gr-1 PerCP-Cy5.5 CD64 ▬▬▬▬▬▬▬▬ BUV395 BUV496 BUV563 BUV615 BUV661 BUV737 BUV805 BV421 Pacific Blue BV510 BV570 BV605 BV650 BV711 BV786 FITC Spark Blue 550 PerCP PerCP-Cy5.5 PE PE-CF594 PE-Cy5 PE-Cy7 APC Alexa Fluor 647 Alexa Fluor 700 APC-Fire 750 Complexity Index: 11.52 0.07 0.34 1 0.23 0.07 0.04 0.02 0.03 0.11 0.06 0.03 0.06 0.01 0.01 0.01 0.01 0 0.04 0.09 0.38 1 0.02 0.02 0.05 0.31 0.03 0.01 0.02 0.11 0.36 0.06 0.08 0.01 0.01 0.23 1 0.34 0.09 0.02 0.01 0.04 0.08 0.13 0.5 0.11 0.06 0.03 0.01 0.01 0.12 0.12 0.02 0.01 0.03 0.01 0 1 0.03 0.13 0.01 0.01 0.11 0.04 0.02 0.04 0.09 0.39 1 0 0 0.36 0.09 0 0 0 1 0.39 0 0 1 0 0.06 0.5 0.24 0.14 0.04 0.02 0.02 0.16 0.34 1 0 0.01 0.11 0.34 0.29 0.06 0.02 0.01 0.16 0.15 0.55 0.38 0.05 0.02 0.02 0.01 0.01 0.24 0.34 0.17 0.04 0.01 0 0.09 0.18 0.04 0.03 0.44 0.21 0.05 0.01 0.02 0.01 0 0 0 0.01 0.03 0.18 0.4 0.32 0.06 0.01 0.06 0.17 0.46 0.15 0.05 0.02 0.07 0.07 0.41 0.71 0 0.03 0.44 0.24 0.03 0.01 0 0 0.01 0.78 1 0 0.01 0.21 0.61 0.16 0.03 0.01 0 0.31 0.11 0.04 0.01 0.01 0.14 0.29 0.46 0.23 0.07 0.02 0.02 0.05 0.25 0.18 0.24 0.61 0.3 0.04 0.17 0.05 0.04 0.02 0.01 0.03 0.04 0.23 0.36 0.11 0.03 0.13 0.11 0.18 0.26 0.54 0.01 0.01 0.01 0.07 0.26 0.38 0.1 0.09 0.08 0.07 0.08 0.18 0.44 0 0 0.02 1 0.78 0.16 0.16 0.07 0.13 0.09 0.08 0.02 0.02 0.01 0 0.05 0.3 0.46 0.12 0.01 0 0.01 0.04 0.05 0.16 0.08 0 0.02 0.17 0.84 0.22 0.03 0 0.01 0 0.02 0.05 0.21 0.21 0.08 0.06 0.04 0.04 0.07 0.15 0.48 1 0.02 0.12 0.09 0.02 0.01 0 0.01 0.02 0.03 0.09 0.05 0.03 0.02 0.01 0 0.01 0.05 0.78 0.22 0.02 0 0 0.04 0.44 0.53 0.07 0.02 0.01 0.02 0.01 0.02 0.03 0.1 0.21 0.01 0.01 0.04 0.06 0 0 0.02 0.15 0.33 0.23 0.01 0.12 0.18 0.05 0.01 0.01 0.01 0.02 0.05 0.3 0.24 0.16 0.08 0.03 0.01 0.71 0 0 0.01 0.02 0.04 0.25 0.43 0.22 0.04 0.01 0.01 0.06 0.1 0.23 0.46 0.33 0.12 0.02 0.08 0 COO 0 0 0 www. Con 0 BV711 0 0 1 1 0 0.04 0.06 0.15 0.36 0.26 0.05 0.01 0.01 0.43 0.4 0.03 0.16 0.46 0.05 0.84 0.78 0.44 0.15 0 0.02 0.02 0.05 0.11 0.38 0.21 0 0.01 0.22 0.32 0.01 0.03 0.12 0.16 0.22 0.22 0.53 0.33 0 1 0 0 0.02 0.01 0.01 0 0 0.34 0.15 0.07 0.11 0.08 0.06 0.03 0.05 0.01 0 0.01 0 0 1 Spark Blue 550 0 0 0.04 0.07 0.18 0.4 0.56 0.22 0.01 0.07 0.8 0 0.02 0.03 0.03 0.1 0.16 1 0.02 0.05 0.13 0.33 0.22 0.04 0 0.01 0.02 0.14 0.18 0.02 0 0.01 0.01 0.04 0.14 0.44 0.11 0 0.01 0.01 0.02 0.05 0.19 0.23 PE-CF594 0.55 0.41 0.18 0.07 0.04 0.09 0.3 0.06 0.04 0.09 0.06 0.01 0 0.02 0 0.01 0.01 0.71 0.26 0.08 0.04 0.05 0.24 0.1 0.07 0.46 0.27 0.08 0.02 0.05 0.01 0.01 0.01 0 0 PE-Cys PE-Cy7 0 0 0.54 0.18 0.07 0.03 0.16 0.23 0.18 0.22 0.39 0.17 0.03 0.13 0.02 0.04 0.02 0 0.06 0.27 0.39 0.17 0.05 0.01 0.05 0.17 0.36 0.31 0.43 1 0 1 0 0 0.44 0.15 0.02 0.08 0.46 0.4 0.05 0.17 0.25 0.03 0.33 0.14 0.14 0.05 0 0 0 0 0 0 1 0 0 0.48 0.01 0.03 0.33 0.56 0.01 0.05 0.14 0.1 0.22 0.18 0.44 0.19 Alexa Fluor 647 Alexa Fluor 700 0 0 0 0.01 0.09 0.46 0.22 0.05 0.01 0 0.1 0.24 0.06 0.05 1 0.43 0.11 0.03 0.04 0.01 0.01 0 0 0 0.01 0.01 0.08 0.03 0.02 0.07 0.23 0 0.06 0.15 -Fire 750 0 0.01 0.12 0.22 0 0.01 0.03 0.16 0.04 0.02 0.11 0.23 0.71 0.02 0.01 0.1 0.05 0.02 0 0 0 0 0 1 0.08 0.07 0.24 0.17 0.07 0.02 0.01 0 0.01 0 0 0 0 0 0 0 0 0 0.01 0.08 0.17 0.25 0.14 0.03 0.02 0.07 0.78 0.67 0.11 0.51 1 0.13 0.54 0.36 0.21 0.08 0 0 0.8 0.06 0.36 0.78 0.13 0.36 0.26 0.17 0.06 0.05 0.31 0.67 0.24 0.35 0.3 0.38 0.15 0 0.02 0.13 0.24 0.03 0.07 0.13 1 0.06 0.03 0.09 0.28 0 0.51 0.07 0.19 0.06 0.04 0.02 0.01 0.36 0.35 0.04 0.19 0.54 0.06 1 0.88 0.47 0.18 0 0.26 0.3 0.01 0.06 0.36 0.03 0.88 1 0.53 0.18 0.01 0.17 0.38 0.01 0.04 0.21 0.09 0.47 0.53 1 0.38 0 0.02 0.08 0.28 0.18 0.18 0.38 1#34side scatter hCD3 PE-CF594 The simple 12 color T regulatorv cell panel below (designed not for low spectral overlap but to test fluorochromes spectrally close to CF-5 and R-PC) show that these probes can be reasonably combined with spectrally similar fluorochromes. 4.0M- 3.0M- 2.0M- 0 1.0M CD3+ -104 Lymphocytes. 66.2 forward scatter 0 2.0M 3.0M hCD19 APC 4.0M hCD14 PE-Cy5 hCD4 R-PC -104 0 104 CD45+ hCD45 PerCP 105 CD4+ CD8+ 104 -10* hCD8 CryptoFluor-5 10 hCD25 APC-Cy7 hCCR7 PerCP-Cy5.5 -104 104 hCD127 PE-Cy7 104 hCD127 PE-Cy7 -10° 10° Above. Resting human PBMCs labeled with the 12 indicated antibodies and analyzed on a Cytek Biosciences Aurora. Right. Spectral indices matrix. Complexity index was 11.41. These results indicate that both CryptoFluor-5 and R- phycocyanin can be used as fluorochromes in high- dimensional labeling panels for spectral cytometry (although conjugation conditions need to be optimized). These PBs can are not tandem dyes, making them potentially more spectrally uniform options. hCD25 APC-Cy7 -104 hCCR7 PerCP-Cy5.5 BUV563 BV605 PerCP PerCP-Cy5.5 PE CryptoFluor-5 PE-CF594 R-PC PE-Cy5 PE-Cy7 APC 0 APC-Cy7 Complexity Index: 11.41 104 BUV563 1 10 BV605 PerCP CYTO 20 VIRTUAL INTERACTIVE 21 JUNE 7-10 hCD45RO BUV563 PerCP-Cy5.5 ______ _ -10% 105 108 hCD45RA PerCP-Cy5.5 PE 0.03 0.19 0.82 1 0 CryptoFluor-5 0 PE-CF594 104 0.29 0.41 0.29 0.23 0.67 1 R-PC 0.19 0.38 0.39 0.33 0.42 0.83 PE-Cy5 0.16 0.04 0.03 0.42 0.29 0.19 0.07 0.05 0.01 0.02 0 0.16 1 0.23 0.19 0.21 0.41 0.38 0.26 0.18 0.03 0.12 0.02 0.04 0.23 1 0.82 0.07 0.29 0.39 0.56 0.81 0.12 0.38 0.07 PE-Cy7 0.06 0.23 0.33 0.52 0.69 0.24 0.35 0.16 0.42 0.21 0.07 0.06 1 0.67 0.42 0.15 0.11 0.03 0.04 0.01 APC 0.07 0.26 0.56 0.52 0.15 0.53 0.53 1 APC-Cy7 0.83 0.53 0.44 0.08 0.21 0.03 0.05 0.18 0.81 0.69 0.11 0.44 0.52 0.85 1 1 0.53 0.52 0.08 0.19 0.02 0.01 0.03 0.12 0.24 0.03 0.08 0.08 0.14 0.14 0.85 0.14 0.74 0.15 0.14 0.52 0.09 1 0.06 0.3 0.02 0.12 0.38 0.35 0.04 0.21 0.19 0.74 0.52 0.06 1 0.18 Telford, DeLonge, Int Veldt, Kapoor, Hawk and Morseman (CYTO 2021) 0.02 0.07 0.16 0.01 0.03 0.02 0.15 0.09 0.3 0.18 1#35"New" fluorochromes Old fluorochromes previously not applicable for flow cytometry are now being reassessed, expanding the "palette" of fluorescent tags for high-dimensional labeling. Original Articles Cryptomonad Algal Phycobiliproteins as Fluorochromes for Extracellular and Intracellular Antigen Detection by Flow Cytometry Cytometry 44:16-23 (2001) 2 William G. Telford,¹* Mark W. Moss,2 John P. Morseman, and F.C. Thomas Allnutt² ¹Department of Experimental Transplantation and Immunology, Medicine Branch, Division of Clinical Sciences, NCI-NIH, Bethesda, Maryland 2Martek Biosciences Corporation, Columbia, Maryland Received 12 July 2000; Revision Received 5 December 2000; Accepted 14 January 2001 R-phycocyanin (R-PC). Isolated from red algae (C-PC from cyanobacteria). AEX = 533, 544 nm, λEM = 646 nm CryptoFluor-5 (CR-PE555, phycoerythrin 555) Isolated from photosynthetic protozoans Chroomonas sp., Chroomonas ovata. AEX = 566 nm, λEM = 598 nm Stanford University Columbia Biosciences#36Cytek Biosciences Aurora CS cell sorter Cell sorting is a major focus of our group. When our users analyze a cell population, they will soon want to sort it! These cells can be put back into culture, analyzed for proteomics, genomics, etc. Traditionally, the capabilities of cell sorters lag behind analyzer development. Most manufacturers maximize their analyzer capabilities first, then build their sorters. The Cytek Aurora CS cell sorter has the same analyzer optical "front end" as the analyzer. (5 lasers, 64 detectors, 40+ color analysis capability, real-time spectral unmixing for sorting). Once our users have optimized their cell analysis experiments, they can immediately transfer them to a cell sorter for physical separation. CYTEK 52#37Cytek Biosciences Aurora CS cell sorter Extensive sensitivity evaluations have shown that the Aurora analyzer and Aurora CS have virtual identical sensitivity, intensity and and linearity profiles. Aurora CS Aurora analyzer Count 300 200 100 150- 100 50 10 ™™T||| 10 10¹ Comp-B2-A 107 Comp-B2-A Clontech / Takara acGFP microspheres (6 populations) 10⁰ 10⁰ B2 detector QC presets minus 0% 10° 150 100- 50 100 80 10 10² 10" Comp-B2-A 104 Comp-B2-A 10 10 B2 detector minus 35% 10° 10 Count 150 100 50 120- 90 60 30 10² 10² 10 Comp-B2-A 104 Comp-B2-A 10⁰ 10 B2 detector minus 70% 10 Count Count 80 60 Clontech Takara mCherry microspheres (6 populations) 10² 10² 10³ 104 Como-VG3-A 10³ All 10 10 Comm.VG3.8 10 108 10 YG3 (615 nm) QC presets Count 300 Spherotech PE MESF microspheres (5 populations) 200- 150- 100 10² 10² 104 Comp.YG1-A 10+ Comp-YG1-A 105 10° m 10 10 10 R1 (660 nm) QC presets#38Cytek Biosciences Aurora CS cell sorter Acquisition Sorter Acquisition and Sort Controls 8 UNSORTED: Previewing Acquisition Flow Rate: 2 Sample Return Sort Stream Controls Threshold Count: 319,325 Record Event Rate: 2,970 Nozzle Settings *100 µm K00119 2.16.22 Drop Delay (0.1 us) 11,168 DDF (Hz) Pause Sort Amplitude. Plate Voltage (V) Pressure (psi) Drop Center Actual Chamber Light Sample Input Settings Temperature (°C) Disabled 311 317 Stop Restart ■ Stop Sort Stream Status A Quick Stop 8 26560 53018 Sample Mixing 3000 18.3 Sort Monitoring: Drop Interval Off On On 15: 15 Collection Device Options Collection Device Tube Plate Sort Stream Adjuster Aim Settings: 100um K00119 4 way 50 Tube and Plate Details FAR LEFT Enable In The Collection Device Options Tube Size 5 ml Lock Aim Targets Sort Mode Purity MIDDLE LEFT Population RA+ CD127 hi CD25 lo Count MIDDLE LEFT Sort Rate (e/s): Sort Efficiency (%): Active Tubes FAR LEFT Drop Charge Starting Volume (µl) 0 Count: < -102 > Stopping Volume (%) 100 Aborts Sort Abort Rate (e/s): Sort Abort Count: 5 Continuous S 31 82 3,021 6 1072 LEFT MIDDLE LEFT Count Drop Charge Population RA+CD127 hi CD25 hi LEFT Count: Starting Volume (ul). Sort Rate (e/s): Sort Efficiency (%): LEFT Drops: 1st Stopping Volume (%) 100 -46 > Center Stream Optimization Aborts A Sort Abort Rate (e/s): Sort Abort Count: RIGHT 14 MIDDLE RIGHT 2nd Test Sort 3rd Sort Block Stage A DEFLECTION PLATES ON CENTER Live View FAR RIGHT 0 4th Deflection Plates 16 Aspirator Buckets RIGHT Drop Charge 46 > Open Autis Drop Delay MIDDLE RIGHT Drop Charge 100 >> A m Sort Control Report Live View Adjust Sort Stream Save Save As DX#39Cytek Biosciences Aurora CS cell sorter Human PBMCs, 14 color panel (T cell subsets including naïve/memory and Treg) Sorting for CD4+ and CD8+ populations UNSORTED CD8+ CD45RA+ SORTED Percentage target population 2.9% CD8+ CD45RO+ SORTED Percentage target population 3.2% side scatter side scatter side scatter OM- 4CM- CM- 1.0M 2.0M Lymphocytos 68 8 1.0M forward scatter 2.0M 1.0M Lymphocytes 792 3.0M 2.0M 3.0M forward scatter 4.0M 3.0M 4.0M 4.0M forward scatter SSC-A 4CM- 3 CM- 2 CM- side scatter H 10M- 4.0M- 3.0M- 1.0M- -104 CD45+ Dalle 99 2 side scatter A CD45+ cels 99.8 10 10 side scatter A CD45+ colo 100 10" 10⁰ m side scatter A Como-Alexa Fluor 488 side scatter A side scatter A T D 59.5% CD3+CD2- 59.5 hCD45 eF450 10 10² ID CD3+ CD2- 97.4 97.4% 104 hCD45 eF450 10° CD3+CD2- 99.4 99.4% 10° hCD45 eF450 Comp-Odot 655-A CD8 hCD2 AF488 hCD2 AF488 CD8+ 48.3 €48.3% CD4+ 45.0 45.0% 10 CD8+ 99.2 hCD3 BUV395 CD4+ 0.82 10⁰ 99.2% hCD3 BUV395 CD8+ 99.7 99.7% CD4+ 0.24 10 10⁰ hCD3 BUV395 108 hCD8 QD650 hCD8 QD650 CD8+ CD45RA+ 35.3 CD8+ CD45RO+ 39.2% www. -10° CDB+ CD45RA+ 92.6 10% hCD4 R-PC CD8+ CD45RO+ 6.41 CDB+ CD45RA+ 0.31 10° CD8+ CD45RO+ 0 :35.3% 98.6% 10 hCD4 R-PC 96.6% 10° 10 hCD4 R-PC unlabeled Alexa Fluor 488 hCD2 PE hCD56 R-PC hCD4 PECY7 hCD45RA APC hCD19 APCCy7 hCD45RO eF450 hCD45 BV605 hCD20 BV650 hCD25 QD655 CD8 BV711 hCD127 QD800 hCD14 BUV395 hCD3 BUV661 hCCR7 Sort purity 96.6% = Actual yield (actual over calculated) 70.3% Sort purity= 98.6% While still being fully optimized, we now have spectral cell sorting capability, a necessity for our group. = Actual yield (actual over calculated) = 71.3%#40CYTEK TRANSCEND THE CONVENTIONAL Investor and Analyst Day High Dimensional Cell Sorting Kevin Weller, Ohio State University June 22, 2022 40#410 CG с High Dimensional Sorting for Discovery Kevin P. Weller Associate Director - PIIO Co-Director - Flow Cytometry Share Resource Pelotonia Institute for Immuno-Oncology The James THE OHIO STATE UNIVERSITY COMPREHENSIVE CANCER CENTER G A CG T G G C TA G A A T C G CT A G C C G с G C G T G G C T A T A A T C G G C Seq 11 A TOUT 101001 1000 10001 11010101011100 01011 001 1010001 10001 1010001 10001 10001 11101010 A T G T T A G G C 50 40 10 100- 100- 90- 80- 70-> 10 C A A T G T T A ww 20 C G The Ohio State University Comprehensive Cancer Center - Arthur G. James Cancer Hospital and Richard J. Solove Research Institute 01011001 1010001 10001 1010001 10001 10001 11101010 Seq 12 40 30- G 20 80- 60 70- 20- GG F CT 30 8 V 2 8 8 ← A 1 Seq1 B 1 B GT 8 1 8 1 18 3 ४ 8 11 www WW GIG 1 al 1 8 1 G 8 8 T TA CA G C 011100 01011 001 1010001 10001 1010001 10001 10001 11 1010101011100 01011 001 1010001 10001 1010001 10001 10001 11 1010101011100 01011 001 1010001 10001 1010001 10001 10001 11 1010101011100 01011 001 1010001 10001 1010001 10001 10001 11 101010 |||| |||| 8 T A TO G G € T A 1 1 -" Seq 2 50 1 1 60- $ 1 ww 8 70- TIGCNO C A TA C G 1 C 80- 1 ************* 90 ** T 100- COG G 8 1 10 8 1 -05 -09 1 4 -06 061 A C TAA 1011100 01011 001 1010001 10001 1010001 10001 10001 11 1010101011100 01011 001 1010001 10001 1010001 10001 10001 11 101010101110001011 001 1010001 10001 1010001 10001 10001 11 101010 Seq 3 8 TA 8 02 -08 <<-06 is <-001 G#42011100 01011 001 1010001 10001 1010001 10001 1000111 101010101110001011 001 1010001 10001 1010001 10001 10001 11 10101010110001011 001 1010001-1000 1010001 10001 10001 11 101010101110001011001 1010001 10001 10100 10001 1000111101010 Our Mission - PIIO A comprehensive bench-to-clinical- trial research initiative that will accelerate advanced immunotherapies that harness the immune system to fight cancer Founded in April 2019 with a starting donation of $102 million 42 CYTEK TRANSCEND THE CONVENTIONAL 80 The Jame B ALL PR Pona 0 es The James THE OHIO STATE UNIVERSITY COMPREHENSIVE CANCER CENTER#43011100 01011 001 1010001 10001 1010001 10001 1000111 101010101110001011 001 1010001 10001 1010001 10001 10001 11 10101010110001011 001 1010001-1000 1010001 10001 10001 11 101010101110001011001 1010001 10001 10100 10001 1000111101010 43 ● The IMDP is a key part of the bench Build a leading immune monitoring platform for supporting 10 research from discovery to translation, using state-of-the-art technology, robust informatics, strong expertise and exceptional customer service A Shared Resource to provide 10 researchers with the best laboratory equipment for discovery and immune monitoring As much of a 360 degree view of the immune system as we can provide CYTEK TRANSCEND THE CONVENTIONAL 0 es The James THE OHIO STATE UNIVERSITY COMPREHENSIVE CANCER CENTER#44011100 01011 001 1010001 10001 1010001 10001 1000111 101010101110001011 001 1010001 10001 1010001 10001 10001 11 10101010110001011 001 1010001-1000 1010001 10001 10001 11 101010101110001011001 1010001 10001 10100 10001 1000111101010 44 The PIIO was built for this The PIIO has over 100 members with broad specialization Emphasis on bioinformatics, the first IO Database is already accruing We are planning large experiments with teams (5- 10) investigators with different interests and expertise Currently optimized high dimensional (35+ biomarkers) panels are being customized based experimental goals Get as much information from precious patient samples as possible CYTEK TRANSCEND THE CONVENTIONAL 0 es The James THE OHIO STATE UNIVERSITY COMPREHENSIVE CANCER CENTER#45011100 01011 001 1010001 10001 1010001 10001 1000111 101010101110001011 001 1010001 10001 1010001 10001 10001 11 10101010110001011 001 1010001-1000 1010001 10001 10001 11 101010101110001011001 1010001 10001 10100 10001 1000111101010 45 ● New Opportunities Previous generations of sorting equipment were limited by biomarker numbers (10-15) Other high dimensional platforms limited: Mass Cytometry cell destruction FACS - not yet reaching stated potential (25-30 commonly reported) Current high dimensional panels are translating well to the CS sorting platform Constructing a discovery pipeline... CYTEK TRANSCEND THE CONVENTIONAL 0 es The James THE OHIO STATE UNIVERSITY COMPREHENSIVE CANCER CENTER#4646 CYTEK TRANSCEND THE CONVENTIONAL 410001 10001 11 101010101110001011 001 1010001 10001 10100 10001 10001 Let's do everything 0 es The James THE OHIO STATE UNIVERSITY COMPREHENSIVE CANCER CENTER#47011100 01011 001 1010001 10001 1010001 10001 1000111 101010101110001011 001 1010001 10001 1010001 10001 10001 11 10101010110001011 001 1010001-1000 1010001 10001 10001 11 101010101110001011001 1010001 10001 10100 10001 1000111101010 47 Single Cells/Team Science CYTEK TRANSCEND THE CONVENTIONAL Tumor/Blood/Tissue Process and sort Revie - M 0 es The James THE OHIO STATE UNIVERSITY COMPREHENSIVE CANCER CENTER#48011100 01011 001 1010001 10001 1010001 10001 1000111 101010101110001011 001 1010001 10001 1010001 10001 10001 11 10101010110001011 001 1010001-1000 1010001 10001 10001 11 101010101110001011001 1010001 10001 10100 10001 1000111101010 48 Class Cell Type Subtypes Granulocytes Neutrophils CD16 and CD66b or CD15/SSEA1+ Myeloid-Derived Suppressor Cells (MDSCS) Eosinophils CD193 and Siglec-8 and CD16- Basophils FceR10 and CD117- Activated CD63 and CD203c Mast cells FceR10' and CD117+ and Tryptase Activated CD203c CYTEK TRANSCEND THE CONVENTIONAL Cell Signar Plasmacytoid Dendritic Cells (pDCs) Monocytic (M) MDSCS CD15-and CD14' and HLA-DR- Myeloid Cells CD14-and HLA-DR- CD83 Polymorphonuclear (PMN) MDSCs CD15 and CD11b- HLA-DR and CD123* Activated Conventional Dendritic Cells (CDCs) Activated CD83+ CD11c and HLA-DR Cell Signaling Macrophages CDC1s (excel at cross- presentation) XCR1 or CLEC9A CDC2s CD1c or SIRPO Monocytes CD68 and HLA-DR and CD11c M1-like CD86'or CD80° or INOS CM2-like CD163 or CD206 Activated CD69 or CD25+ Leukocytes Central Memory CD45RO" and CD62L or CCR7 CD45+ CD14 and HLA-DR and CD206 and CD86- Th9 PU.1 and T Cells Tfh Bcl-6° and CXCR5 and IL-21- Th22 AHR and IL-22 Cytotoxic Granzyme or Perforin Effector CD45RA" and CD62L-or CCR7- CD3 Cytotoxic T Cells CD8+ NKT Cells Helper T Cells (Th) CD4+ Th1 T-Bet' and IFNY Th2 GATA-3-and Th17 RORyt and IL-17- Treg FoxP3 and CD25+ Naive CD45RA and CD62L or CCR7" Progenitor Exhausted TCF1/TCF7* and PD-1 and TIM-3 CD56 and CD3 Type II NKT Type I NKT (INKT) TCR Va24 V$11 Lymphoid Cells Effector Memory CD45RO and CD62L™ or CCR7- NK Cells Terminally Exhausted Tox/Tox2" and PD-1 and TIGIT- CD56 and CD3 PB Immature/ Regulatory NK Cells CD56 and Cell SignaCD16-and TECHTOI NCR Activated CD69 B Cells PB Cytotoxic NK Cells CD56 and CD16 Cytotoxic Granzyme ar Perforin CD19 Plasma Cells Naive IgD-and CD27- Switched Memory IgD-and CD27 Unswitched Igo and CD27 Key BCMA or CD138 *positive/high expression "negative/low expression Functional State Markers rev. 02/26/21 © 2003-2021 Cell Signaling Technology, Inc. es The James THE OHIO STATE UNIVERSITY COMPREHENSIVE CANCER CENTER#49011100 01011 001 1010001 10001 1010001 10001 1000111 101010101110001011 001 1010001 10001 1010001 10001 10001 11 10101010110001011 001 1010001-1000 1010001 10001 10001 11 101010101110001011001 1010001 10001 10100 10001 1000111101010 49 Single Cells/Team Science CYTEK TRANSCEND THE CONVENTIONAL Tumor/Blood/Tissue Process and sort - Single Single Cell Genomics Single Cell Proteomics es Single Cell Functional Screening 0 The James THE OHIO STATE UNIVERSITY COMPREHENSIVE CANCER CENTER#50Composite 50 μm DAPI Combine with Spatial information CD8 PD1 51570 Gzm B T-bet FoxP3 CD3#51Cell Y Position 12400- M1 M6 M7 M10 M11_082318_Ms Bladder Tumor_[36504,12853].im3 - Nearest PD-1+ to each CD8a+ 12800- 13200- 13600 Examples of spatial maps for a given pair of biomarkers 35500 DAPI (DAPI) CD3 (Opal 520) CD8a (Opal 690) MX1 (Opal 620) PD-1 (Opal 570) TCF1 (Opal 540) Tim3 (Opal 650) Autondon cenco CYTEK TRANSCEND THE CONVENTIONA 36000 36500 Cell X Position Phenotype CD8a+ PD-1+ 37000 200 μm 3750 Cell Y Position M1 M6 M7 M10 M11_082318_Ms Bladder Tumor_[36504,12853].im3 - Nearest TCF1+ to each CD3+ 12400- 12800- 13200- 13600- 35500 (DAPI) CD3 (Opal 520) CD88 (Opal 69 MX1 (Opal 620d) PD-1 (Opal 570) TOF1 (Opal 540) Tim3 Opal 650) ramofitorcence 36000 36500 Cell X Position Phenotype CD3+ TCF1+ 37000 200 μm. AKOYA BIOSCIENCES 3750#52011100 01011 001 1010001 10001 1010001 10001 1000111 101010101110001011 001 1010001 10001 1010001 10001 10001 11 10101010110001011 001 1010001-1000 1010001 10001 10001 11 101010101110001011001 1010001 10001 10100 10001 1000111101010 52 ● ● Single Cells/Team Science The experiments are designed and funded by multiple labs thereby distribution the costs Very costly becomes relatively affordable Each sorted cell population is selected for a specific expert on the project based on their interest Multiple publications and or single high-impact publications each experiment Every data set gets added to a mineable. database New downstream technologies will be added as they are developed Unused cells can be banked 0 The James THE OHIO STATE UNIVERSITY COMPREHENSIVE CANCER CENTER#534.0M- 3.0M- 2.0M- 1.0M- 0+ 0 1.0M T All Events G 2.0M FSC-A 8 1 G Healthy Donor 3 on Aurora - Y0245 Scatter 3.0M 4.0M Segl 5 r 8 Am 4.0M- 3.0M- 2.0M- 1.0M- 0+ 0 Singlets 1.0M Scatter 2.0M FSC-A 3.0M G 4.0M AMA CD45 BV510-A 10º- 10¹- 10- 10¹. 10 Live 45+ Singlets 10° 10² Viability dye LIVE DEAD Blue-A Seg 2 M www A 10⁰ CD8 Super Bright 436-A CD8+ 988 Live 45+ 10* CD4 APC-Fire810-A 10₁ GTG 10⁰ Seq 3 G C CD8 Super Bright 436-A CD8 Super Bright 436-A CD8 Super Bright 436-A CD8 Super Bright 436-A CD8 Super Bright 436-A 10. 105 10¹- 03 10° 105. 10* - 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03 10- 10'- 10- 03 10- 10'- 10* 03 10. 10º - 10- 03 0 0 "M 0 0 Live 45+ 0 ייה חיי ןװװוי 10* 10³ 10€ NKG2A BUV615-A Live 45+ 10⁰ 105 NKG2D BV480-A Live 45+ 10* 105 T-bet BV786-A Live 45+ 10⁰ 105 Lag3 PE-Cy5-A Live 45+ 106 106 10° 104 10³ KIR2DL1 APC-Cy7-A 10° CD8 Super Bright 436-A CD8 Super Bright 436-A CD8 Super Bright 436-A CD8 Super Bright 436-A CD8 Super Bright 436-A 10° 105- 10*- 03 10° 10³ 10- 03 10. 10³- 10² 10- 03 10. 10- 10*- 03 10- 10º- 10*- 0 03 Live 45+ 10* 10³ CD11b BUV661-A Live 45+ 0 10* 0 10⁰ 105 CD45 BV510-A Live 45+ CD8+ CD45RO BB515-A Live 45+ 106 10° 105 10° 0 104 105 106 EOMES PE-Cy5.5-A Live 45+ 10* 105 10° CD4 APC-Fire810-A CD8 Super Bright 436-A CD8 Super Bright 436-A CD8 Super Bright 436-A CD8 Super Bright 436-A CD8 Super Bright 436-A 10 10- 10- 03 10 10³ 10*- 10 10³- 10- 10 10- 10- 03 10 10- 10- 0 03 0 10⁰ -10* 0 10* 105 ICOS Alexa Fluor 488-A Live 45+ M 0 Live 45+ 0 10* 10⁹ PD1 BUV737-A Live 45+ 10* 105 CD3 BV570-A Live 45+ 10° 10⁰ Kirg1 PE-Cy7-A Live 45+ 10* 105 106 10€ 10³ 105 AF-A#544.0M- 3.0M- 2.0M- 1.0M- 0▬▬▬▬▬▬▬ 1.0M 0 All Events T G 2.0M FSC-A 8 1 G Healthy Donor 3 on Aurora CS - S0108 Scatter T 3.0M 4.0M Segl 5 3.0M r 2.0M- 1.0M- 0+ 0 8 Am Singlets 1.0M Scatter 2.0M FSC-A 3.0M 4.0M G CD45 BV510-A AMA 10- 10⁰- 10- 10¹- 0 -10° Singlets 10 10⁰ Viability dye LIVE DEAD Blue-A Seg 2 M ז"ייי ז www 10⁰ A CD8 Super Bright 436-A CD8+ 988 Live 45+ 10 CD4 APC-Fire810-A 10² GTG 10 Seq 3 G CD8 Super Bright 436-A CD8 Super Bright 436-A CD8 Super Bright 436-A CD8 Super Bright 436-A CD8 Super Bright 436-A 10⁰ 105 10- 0 -10 10⁰ 105 10- 05 -10ª 10⁰ 105 10- 05 -10* 10⁰ 10⁰ 10- OE -10 10⁰ 10- 05 -10⁰ 0 0 0 Live 45+ 0 Trinny 10* 105 10° Ki-67 BUV395-A Live 45+ 10* 10³ CD69 BUV805-A Live 45+ 0 10* 105 10 CD25 Super Bright 600- Live 45+ 10 10* 105 105 CD45RA Alexa Fluor Live245+ THE TI 10* TOX APC-A 105 10° CD8 Super Bright 436-A CD8 Super Bright 436-A CD8 Super Bright 436-A CD8 Super Bright 436-A 10- 105 10- OE -10* 10° 10- 10- 05 -10* 10⁰- 10²- 10- OE -10 10⁰ 10- 10- 03 -10 10² 105 10- 05 -10 Sho 0 10* 10³ 105 Viability dye LIVE DEAD Libyas+ 0 0 0 Live 45+ 0 10* 105 CD62L BV421-A Live 45+ 10* 10³ 105 TIGIT BV650-A Live 45+ 105 10* 10⁰ 10³ CD28 PerCP-Cy5.5-A Live 45+ 10* 105 10° Bcl2 Alexa Fluor 647-A CD8 Super Bright 436-A CD8 Super Bright 436-A CD8 Super Bright 436-A CD8 Super Bright 436-A CD8 Super Bright 436-A 10⁰ 105 10- 0 10 10⁰ 105 10- 05 10 10⁰ 10 10¹- -10* OE 10€ -104 105 10- 10* OF 105 10- -10* -10 0 10* 105 OE 0 0 Live 45+ 0 T 10⁰ CCR7 BUV496-A Live 45+ 105 CD8 Super Bright 436-A Live 45+ 105 10° www Tim3 BV711-A Live 45+ 10⁰ 105 10⁰ 10* TCF1 PE-A Live 45+ mm 105 10° THE FITTI 0 10* 10³ 106 CD27 spark NIR 685-A CD8 Super Bright 436-A CD8 Super Bright 436-A CD8 Super Bright 436-A 10° CD8 Super Bright 436-A 10³- 10- 05 10- 10° 10³ 10 05 10⁰ 10³ 10mm 0 10- OE -10* 10° CD8 Super Bright 436-A · 10° 10¹- OF 10* 10⁰ 105 10- 05 -10₁ 8 0 Live 45+ 0 10* 105 KIR3DL1 BUV563-A Live 45+ m 0 10* 105 105 FoxP3 eFluor 450-A Live 45+ 10* 105 CD56 BV750-A Live 45+ 106 10* 105 CTLA4 PE-Dazzle594-A Live 45+ THE TH 10€ 10⁰ 10* 105 10° GzmB Alexa Fluor 700-A CD8 Super Bright 436-A CD8 Super Bright 436-A CD8 Super Bright 436-A 10⁰ 105 10¹- 0 10¹ 10⁰ 10³ 10¹- 05 10* 10⁰ 105 10¹- OE -10* 10 105 10¹- 05 10⁰ 105 10¹- ON -10ª 0 0 0 0 0 Live 45+ 104 105 10⁰ NKG2A BUV615-A Live 45+ 10* 105 NKG2D BV480-A Live 45+ 10* 105 T-bet BV786-A Live 45+ 10⁰ Lag3 PE-Cy5-A Live 45+ 10⁰ 10* 105 10° m 104 105 10⁰ KIR2DL1 APC-Cy7-A CD8 Super Bright 436-A CD8 Super Bright 436-A CD8 Super Bright 436-A CD8 Super Bright 436-A 10⁰- 10³- 10- 05 -10¹. 10"- 105. 10¹- 05 10. 10⁰- 10³- 10¹- 10² OE -104 10- 10- 10¹- 05 10ª 10⁰- 10³- 10¹- 05 -10 0 0 Live 45+ CD8+ 0 10* 105 10 CD11b BUV661-A Live 45+ In 0 10⁰ 10* 105 CD45 BV510-A Live 45+ 105 CD45RO BB515-A Live 45+ EOMES PE-Cy5.5-A Live 45+ 10⁰ 10⁰ 10* 105 10 10⁰ 105 10 CD4 APC-Fire810-A CD8 Super Bright 436-A CD8 Super Bright 436-A CD8 Super Bright 436-A CD8 Super Bright 436-A CD8 Super Bright 436-A 10⁰ 105 10- 0 10¹ 10⁰ 105 10- 0 10* 10⁰ 105 10- OE -10 10⁰ 10- 10¹- 0 10 10⁰ 105 10- OE 0 -10* 0 10* 105 ICOS Alexa Fluor 488-A Live 45+ -10ª 0 Live 45+ 0 10* 105 PD1 BUV737-A Live 45+ 10* 105 CD3 BV570-A Live 45+ 10⁰ 10⁰ 0 10* 105 10* 105 10² Kirg1 PE-Cy7-A Live 45+ AF-A 105 "TE 105#55011100 01011 001 1010001 10001 1010001 10001 1000111 101010101110001011 001 1010001 10001 1010001 10001 10001 11 10101010110001011 001 1010001-1000 1010001 10001 10001 11 101010101110001011001 1010001 10001 10100 10001 1000111101010 4.0M- 3.0M- 2.0M- 1.0M- 0 0 T All Events O 1.0M G 2.0M FSC-A 8 1 G Aurora CS Data from 'Patient 1 3.0M Scatter 4.0M Segl 5 r 4.0M- 3.0M- 2.0M- 1.0M- 8 Am 0- 0 Singlets 1.0M Scatter SA 2.0M FSC-A 3.0M G CD45 BV510-A 4.0M AMA 10⁰- 10⁰- 10⁰- Singlets 10⁰ 10² Viability dye LIVE DEAD Blue-A Seg 2 M www 10° A CD8 Super Bright 436-A 03 CD8+ 988 Live 45+ 10* 10⁰ CD4 APC-Fire810-A GTG 10* 8 Seq 3 CD8 Super Bright 436-A CD8 Super Bright 436-A CD8 Super Bright 436-A CD8 Super Bright 436-A CD8 Super Bright 436-A 10⁰ 10³ 10ª- 0 -10 105 10- 10* 05 10⁰ 10- 10¹- -10g Tering trining 0 10* 105 10° 0 -104 10⁰ 10² 10ª- 05 -10* 10 105 10ª- 0 05 Live 45+ 10* 10⁰ Ki-67 BUV395-A Live 45+ CD69 BUV805-A Live 45+ 105 0 10⁰ 10 10° CD25 Super Bright 600- Live 45+ 0 10* 105 105 CD45RA Alexa Fluor LIVE²25+ G C -10NG HAN FINN 105 105 0 10* TOX APC-A CD8 Super Bright 436-A CD8 Super Bright 436-A 10⁰ 105 10- 05 -10ª 10° 10. 10. 0 -10² 10 10³- 10* 05 -10¹ 10⁰ 10. 10ª 0E -10ª 10³ 10. 05 -10° 10* 10³ 10° Viability dye LIVE DEAD LiByas+ 0 0 0 Live 45+ ▬▬▬g T 10⁰ 105 0 CD62L BV421-A Live 45+ 10° SAN CASIN 10° 10⁰ 10° TIGIT BV650-A Live 45+ 10* 105 CD28 PerCP-Cy5.5-A Live 45+ 105 10* 105 106 Bcl2 Alexa Fluor 647-A CD8 Super Bright 436-A CD8 Super Bright 436-A CD8 Super Bright 436-A CD8 Super Bright 436-A CD8 Super Bright 436-A 10- 105. 10- 05 10* 10° 10' 10. 05 10- -10ng ringer 10- 10- 05 -10* -10⁰ 0 104 10¹ 10° CD8 Super Bright 436-A Live 45+ 10%- 105. 10. 03 -10* 10. 105 - 10- 05 0 10* 0 Live 45+ B 10³ CCR7 BUV496-A Live 45+ 0 10° 10€ 105 Tim3 BV711-A Live 45+ 10° 10* 10⁰ 10⁰ TCF1 PE-A Live 45+ -10 TT TIng 10⁰ CD27 spark NIR 685-A 0 10* 105 T CD8 Super Bright 436-A CD8 Super Bright 436-A CD8 Super Bright 436-A CD8 Super Bright 436-A CD8 Super Bright 436-A 10⁰ 10³- 10ª- 05 10₁ 10". 10*- 05 -10ª 10° 10² - 10. 03 10⁰ 105. 10- 05 -10¹ 10 105. 10- 05 -10⁰ י שני ניחן 0 mm Live 45+ -m. --- 10* 10³ 10 KIR3DL1 BUV563-A Live 45+ 0 0 10¹ 105 FoxP3 eFluor 450-A Live 45+ eng 0 10ª 0 This m 10ª CD56 BV750-A Live 45+ 10⁰ mm F 10 105 CTLA4 PE-Dazzle594-A Live 45+ 10 106 10* 10³ 10⁰ GzmB Alexa Fluor 700-A CD8 Super Bright 436-A CD8 Super Bright 436-A CD8 Super Bright 436-A CD8 Super Bright 436-A CD8 Super Bright 436-A 10⁰- 10³ - 10- 05 -10. 10- 10- 10- 05 10- 10- 10- 05 -10mg termnny teren 0 10⁰ 10² 10 -10 10⁰- 10- 10- 05 -10 105- 10- 05 ווו מיירי ש'T 0 Live 45+ 10* 10³ 10% NKG2A BUV615-A Live 45+ 0 NKG2D BV480-A Live 45+ www. 0 10€ 10º 10 T-bet BV786-A Live 45+ 0 10€ 105 10° Lag3 PE-Cy5-A Live 45+ -10 mm 105 10° 104 KIR2DL1 APC-Cy7-A CD8 Super Bright 436-A CD8 Super Bright 436 CD8 Super Bright 436-A 10- 10³- 10* 05 10. 10. 10° 10- 05 -10. 10- 10²- 10² 10- 05 -10 10- 10³- 10- 05 10* 105- 10- 0 05 0 Live 45+ mm 10* 10³ CD11b BUV661-A Live 45+ 0 10€ 10⁰ 105 CD45 BV510-A Live 45+ 10º CD45RO BB515-A Live 45+ www CD8+ 10* 105 EOMES PE-Cy5.5-A Live 45+ -10TTIN 0 10 10 10 ™ 106 104 105 CD4 APC-Fire810-A 10⁰ CD8 Super Bright 436-A CD8 Super Bright 436-A CD8 Super Bright 436-A CD8 Super Bright 436-A 10⁰ 10- 10ª- 05 -10° 10⁰ 10⁰ 10- 05 -10 10" 10³- 10- 05 -104 10⁰ 105 10ª- 03 -10 10- 105 10ª- 03 0 0 Live 45+ 0 THE FIN 10⁰ 10³ PD1 BUV737-A Live 45+ 10⁰ 105 CD3 BV570-A Live 45+ 0 10ª 10º 10⁰ ICOS Alexa Fluor 488-A Live 45+ 10* 10³ Kirg1 PE-Cy7-A Live 45+ 10⁰ 10 AF-A 105 -10 m ring 0 104 105 10⁰#56011100 01011 001 1010001 10001 1010001 10001 1000111 101010101110001011 001 1010001 10001 1010001 10001 10001 11 10101010110001011 001 1010001-1000 1010001 10001 10001 11 101010101110001011001 1010001 10001 10100 10001 1000111101010 CD45RA Alexa Fluor 532-A 4.0M 3.0M- 2.0M- 1.0M- 04 0 10⁰- 10- 10*- 10. 1.0M All Events T 2.0M FSC-A Singlets Scatter 3.0M 10* 10⁰ 10² Viability dye LIVE DEAD Blue-A CD8+ 10 10² CD45RO B8515-A G 4.0M 10⁰ 4.0M- 3.0M- G r 2.0M- 1.0M- CD8 Super Bright 436-A 04 10² 0 10- Singlets 1.0M CD8+ 2DL1+ Scatter 2.0M FSC-A Live 45+ 2030+ 3.0M CD4 APC-Fire810-A P5 10² 10³ KIR3DL1 BUV563-A AMMA 3DL1+ 10° 4.0M G All Events 34c Panel Sort AMA Populatior clinical trial-E Scatter Singlets G Live 45+ CI E -- CD45 BV510-A CD45 BV510-A 3.0M- CD45RA Alexa Fluor 532-A 2.0M- 1.0M- CD45RA Alexa Fluor 532-A 10- 10⁰- 10- -10° 10 4.0M 2.0M 3.0M- 0 1.0M- 10- 10². -10* -10° 10- 10- 04 -Live 15 1.0M RA RA-RO 0 0 All Events 2.0M 10* 10⁰ Viability dye LIVE DEAD Blue-A CD8+ Al RA-RO 28 20 FSC-A Singlets RO+ 1.0M 2.0M 10* 10⁰ All Events 3.0M FSC-A Singlets RO. 3.0M Scatter 10" 10* 105 10⁰ Viability dye LIVE DEAD Blue-A CD8+ 10³ CD45RO BB515-A 10* Scatter 4.0M 10 4.0M 4.0M- 3.0M- 2.0M- CDB Super Bright 436-A 1.0M- KIR2DL1 APC Cy7-A CDB Super Bright 436-A KIR2DL1 APC-Cy7-A 0+ 0 10. 4.0M- 10- 3.0M- 2.0M- 1.0M- 0 0 10- 10"- 03 10⁰- 10- Singlets 1.0M CD8+ 2011+ 0 10' Singlets 1.0M CD8+ 2DL1+ 10⁰ 10¹ Scatter 2.0M FSC-A Live 45+ 10 CD4 APC-Fire810-A P5 2030+ 10* 10 Scatter 2.0M FSC-A Live 45+ 3.0M 2D3D+ 10* CD4 APC-Fire810-A P5 3.0M 10% 10³ KIR3DL1 BUV563-A 3DL1 10" 3DL1+ 4.0M 4.0M 10⁰ All Events vents Population Hierarchy clinical trial-post sort-RA+ Scatter Scatter Singlets Live 45+ Singlets Live 45+ CDB+ CD8+ P5 RA+ RA. RA-RO- Population Hierarchy clinical trial-post sort-RA RO RO+ RO- 2011- 2D3D+ 3DL1+ RA-RO- 2DL1+ 2D3D+ 3DL1+ % Parent 0.07 97,21 99.22 80.16 0.26 100.00 98.82 0.19 95.07 0.00 0.35 % Parent 0.00 0.00 100.00 96.05 0.93 21.43 97.70 0.00 97.83 95.76 7.14 Ⓒ 33.33 Ⓒ 4.0M- 3.0M- 2.0M- 1.0M- D4SRA Alex CD45 BV510-A 0 0 10- 10⁰- 10- 10¹- 08 10's 10⁰- 10- 10- 4.0M- 3.0M- CD45RA Alexa Fluor 532-A 2.0M- 1.0M- 10² 10' 0 0 10- 10²- 1.0M 10¹- -Live 16+ RA+ RA-RO- RA All Events 10⁰ 10⁰ Viability dye LIVE DEAD Blue-A CD8+ T 1.0M 2.0M FSC-A Singlets RA-RO- RO+ 3.0M 10* 10⁰ All Events 2.0M FSC-A Singlets RO Scatter 3.0M 10* 10³ CD45RO BB515-A 10° 10* 10⁰ Viability dye LIVE DEAD Blue-A CD8+ 4.0M 10° Scatter 10° 4.0M 10 4.0M- 3.0M- 2.0M- 1.0M- CDB Super Bright 436-A KIR2DL1 APC-Cy7-A 10- 0- 0 4.0M- 3.0M- 10² 2.0M- CD8 Super Bright 436-A 1.0M- KIR2DL1 APC-Cy7-A 10º- 10'- 10⁰ Singlets 10⁰- 1.0M CD8+ 0 04 T 0 1.0M 20L1+ CD8+ Singlets 2DL1+ 0 Scatter T 2.0M FSC-A Live 45+ 10" CD4 APC-Fire810-A P5 2030 10 3.0M Scatter 2.0M 3.0M FSC-A Live 45+ 2D3D+ 10* CD4 APC-Fire810-A P5 10⁰ 3DL1+ 10 10¹ KIR3DL1 BUV563-A 10" 4.0M 10° 10 3DL1+ 10° vents 4.0M Scatter vents Population Hierarchy clinical trial-post sort-RO+ Singlets Scatter Live 45+ P5 Singlets F Live 45+ RA RA-RO- P5 RO. 2DL1 2030- 3DL1+ CD8+ RA RA-RO- 2DL1+ 2030- % Parent 3DL1+ 100.00 86.06 97.77 96.57 Population Hierarchy clinical trial-post sort-DL1+ 97.04 0.00 0.61 87.80 0.00 N/A N/A N/A % Parent 100.00 92.47 97.54 97.95 1.77 81.82 9.09 0.00 96.95 91.38 0.00 0.00 Ⓒ CD4S BV510-A CD45 BV510-A 4.0M- 3.0M- 2.0M- 1.0M- 0 10⁰- 10⁰- -10⁰ 10- 10¹- 10 0 4.0M- 3.0M- 2.0M- 1.0M- 10- 10' 0 10- 10*- 10 10. 10² 0 10² 10²- -Live 45+ 1.0M 0 RA+ RA-RO 1.0M 10* 10 Viability dye LIVE DEAD Blue-A CD8+ RA+ All Events RA-RO- 2.0M FSC-A Singlets 10⁰ 10⁰ RO+ 10* All Events 2.0M 3.0M 10³ FSC-A Singlets RO 3.0M Scatter 10* 10⁰ Viability dye LIVE DEAD Blue-A CD8+ 10 10* 10⁰ CD45RO 88515-A 10⁰ Scatter 4.0M 10 10 4.0M CD8 Super Bright 436-A FSC-H 3.0M- 2.0M- KIR2DL1 APC-Cy7-A KIR2DL1 APC-Cy7-A 0+ 0 10- 10¹- CD8 Super Bright 436-A 10*- 10'- 4.0M- 3.0M- 2.0M- 1.0M- 0+ 10- 10⁰. 10. 0 10- 10⁰ 10¹ 10- 0 Singlets 10² 1.0M CD8+ 2DL1+ Singlets 1.0M CD8+ 2DL1+ Scatter 10² CD4 APC-Fire810-A P5 2.0M 3.0M FSC-A Live 45+ 10 2D3D+ 10* Scatter 2.0M 10* 10 FSC-A Live 45+ 10 3.0M CD4 APC-Fire810-A P5 2D3D+ 10* 10° KIR3DL1 BUV563-A 10⁰ 3DL1+ 10⁰ 3DL1+ 10 4.0M 4.0M vents Scatter vents Population Hierarchy clinical trial-post sort-KIR DP Singlets Scatter Live 45+ CD8+ Singlets P5 Live 45 CD8+ RA+ P5 RA-RO- RO+ 2DL1+ 2D3D+ 3DL1+ RA+ RA-RO- RO+ 2DL1+ 2D3D+ % Parent 3DL1+ 100.00 30.36 94.12 Population Hierarchy clinical trial-post sort-Kir 3+ 62.50 0.00 N/A N/A N/A 90.00 0.00 100.00 0.00 % Parent 100.00 56.25 100.00 61.11 9.09 100.00 0.00 100.00 0.00 0.00 81.82#57011100 01011 001 1010001 10001 1010001 10001 1000111 101010101110001011 001 1010001 10001 1010001 10001 10001 11 10101010110001011 001 1010001-1000 1010001 10001 10001 11 101010101110001011001 1010001 10001 10100 10001 1000111101010 57 Thanks! JA CYTEK TRANSCEND THE CONVENTIONAL PELOTONIA A PELOTONIA PELOTONIA PELOTONI PELOTONIA ELOTONIA PELOTONIA PELOTONIA PELOTONIA #ONE GOAL PELOTONIA PELOTONIA PE DI PELOTON ONI PELOTONIA PELO https://www.pelotonia.org/profile/KW 0281 PELOTONIA IIA TONIA ΌΝΙΑ LOTO PELOTO PELOTONIA PELOTONIA ΤΟΝΙΑ PELOTONIA T-REX PELOTONIA PELOTONIA PE PE PELOTONIA #ONE GOAL, PE OTONIA PE PEL The James THE OHIO STATE UNIVERSITY COMPREHENSIVE CANCER CENTER#58CYTEK TRANSCEND THE CONVENTIONAL Investor and Analyst Day Aurora Empowering Immunological Research Dr. Anna Belkina, Boston University June 22, 2022 58#59Full spectrum cell analysis reveals novel immune phenotypes in health and disease BOSTON UNIVERSITY Anna C. Belkina, M.D., Ph.D. Assistant Professor Department of Pathology Boston University School of Medicine Director Flow Cytometry Core Facility fc cif#60Introduction Assistant Professor of Pathology and Laboratory Medicine at Boston University School of Medicine My work is focused on chronic inflammatory processes in the context of variety of conditions: HIV · Diabetes/obesity Aging and 'inflammaging' Bioinformatic approaches to study single cell data Visualization of flow cytometry data structure Multivariate analyses of mixed datasets ● Director of the Flow Cytometry Core Facility Multiple instruments including 5L Cytek Aurora (spectral applications)#61Immune system is known to be incredibly complex, but you would never suspect that if you look at the immune cells under the microscope... SA STRATIFIED SQUAMOUS (Knized) This composed of several cel shapes. At the baal leyen they are besar colar, hd are formed a flased squats cells as they approach the face. This in the epiderms of skin Hamer 320X SIMPLE COLUMNAR creped eta al cross found in the digestive wat and every ofwgland Cated cum ne the fallopian tube TRANSITIONAL pince of fod spam lise esceps that the ended which allows for Epithelial tissues SIMPLE CUBOIDAL ical spherical acid Found in kidney tubules, ducts of gland and ad face of orary Kibyle 3100% STRATIFIED COLUMNAR e conta one more of cells and a basal layer of condal Food 120x Hum kito GLANDULAR esocrines This is prad though dacts into the digestive to the le of the holy Found in C 268 STRATIFIED CUBOIDAL y congioed of slims of beidd el is found in the acts of b vary, and mammary gland Human wow gland 1240X PSEUDOSTRATIFIED actually a single ter of all and short et All allsch the hemen borine of the team 530X GLANDULAR (docrine) has and homes into the Hood Found the thindadmale puters, and sof Langor oc Hum 2 a Lymphocyte 50#62However, immune cells are extremely diverse! Protein 'fingerprints' that define diverse types and functions of immune cells Monocytes CD14+ CD16 +/- CD11b+ HLA DR +/- CD33+ CD86 +/- Cytotoxic T Cells CD8+ Effector Memory Cells NK T Cells Human Blood Cells T Cells CD3+ Helper T Cells CD4+ Lymphocytes Double Negative Cells CD8- CD4- Effector Memory Treg Cells Cells TCR yo T Cells Non T Cells CD3- B Cells NK Cells Dendritic Cells CD20-CD56- HLA DR+ mDCs pDCs#63Multiparameter measurements allow us to detect the exact 'fingerprint' that correlates with disease X Immune feature: with no correlation with weak correlation O with strong correlation to outcome. ts % RA- % RA-57+ % RA-57+ 27 + % RA-57+ 27 + 28+ X X X Disease X X X Disease X Xx#64We need to assay these proteins in a single measurement + identify and measure other biomarkers of disease ➤For clinical trials Monocytes CD14+ CD16 +/- CD11b+ HLA DR +/- CD33+ CD86 +/- For basic and translational research Effector Memory Cells CCR7 +/- CD45RA +/- I For clinical diagnostics Cytotoxic T Cells CD8+ Effector Memory Subsets CD27 +/- CD28 +/- CD95 +/- PD-1 +/- CD127 +/- CD57 +/- HLA DR +/- CD38+/- CCR6 +/- CXCR3 +/- CD161 +/- CXCR5 +/- ICOS +/- NK T Cells CD56+ CD16 +/- NK T Cell Subsets CD8 +/- CD57 +/- CD28 +/- CD27+ CD161 +/- CCR5 +/- PD-1 +/- CD95 +/- Human Blood Cells T Cells CD3+ Helper T Cells CD4+ Lymphocytes Cells CCR7 +/- CD45RA +/- | Effector Memory Subsets CD27 +/- CD28 +/- CD95 +/- PD-1 +/- CD127 +/- CD57 +/- HLA DR +/- CD38+/- CCR6 +/- CXCR3 +/- CD161 +/- CXCR5 +/- ICOS +/- Double Negative Cells CD8- CD4- Effector Memory Treg Cells CD25+ CD127⁰⁰ Treg Subsets CD45RA +/- HLA DR +/- CD27 +/- CCR6 +/- PD-1 +/- CD161 +/- CCR7 +/- CXCR5 +/- TCR yo T Cells TCR yd+ | TCR yo T Cell Subsets PD-1 +/- CD95 +/- CD161 +/- CD28 +/- CD56 +/- CD57 +/- CD127 +/- CD27 +/- Non T Cells CD3- B Cells NK Cells Dendritic Cells CD20-CD56- HLA DR+ CD20+ CD19+ CD16+/- CD56+ B Cell NK Cell Subsets Subsets IgD+/- CD27 +/- CD38+/- CCR5 +/- CXCR3 +/- CXCR5 +/- CD24 +/- CD8 +/- HLA DR +/- CD33+/- CD27 +/- CD57 +/- CD161 +/- CD86 +/- mDCs CD123- CD11c+ CD16 +/- CD38 +/- CXCR3 +/- CD86 +/- CD95+ pDCs CD123+ CD11c- CD16 - CD95 +/- CD86 +/- CD38+ CXCR3 +/-#65HIV: a problem even when virus is undetectable Despite successful viral suppression via anti-retroviral therapy, HIV+ individuals have an elevated risk of Serious Non-AIDS (SNA) events: cardiovascular atherosclerosis Diseases associated with normal aging neurocognitive degeneration diabetes mellitus cancer osteoporosis liver (cirrhosis) frailty pneumonia SNAs afflict older HIV+ individuals at higher rates than the age-matched general population AIDS Patient Care STDS, 2013. 27(1): p. 5-16. SNAs occur at younger ages in HIV+ vs uninfected controls Clin Infect Dis, 2011. 53(11): p. 1120-6. Do HIV+ individuals age earlier or differently? Whether HIV causes SNAs through the same mechanism(s) as normal aging or through other processes is unclear...#66Our Previous Work Implicate y8 T cells as Inflammatory Driver in HIV, Aging Multivariate Computational Analysis of Gamma Delta T Cell Inhibitory Receptor Signatures Reveals the Divergence of Healthy and ART-Suppressed HIV+ Aging ***********‒‒‒‒‒‒‒‒‒‒ Anna C. Belkina¹2, Alina Starchenko³, Katherine A. Drake4, Elizabeth A. Proctor³, Douglas A. Lauffenburger, Nina Lin5t and Jennifer E. Snyder-Cappione¹,6*+ **************** CITRUS algorithm: CD8+ T cells TIGIT 16-color immunophenotyping (PBMCs) OMIP-037 (Belkina et al, 2017) Ce NK cells CD56+ CD16+ TIGIT on y8 T cells stratified subjects CD4+ T cells into HIV+ vs HIV- groups with 89% CV accuracy yo T cells TIGIT: druggable checkpoint inhibitor (tiragolumab) analyte conc. (ng/ml) 800- 600- % TIGIT+ y8 T cells tracked with plasma inflammatory markers 400- 200- 0 D-Dimer R²=1301 25 ******************* A 50 75 100 total % TIGIT+ 16 markers of inflammation in plasma 3.0x106- Riley M. F. Pihl¹, Alex Olson5, 1.5x10- **********‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒ 0.0+ 0 Fibrinogen R=.2098 25 50 75 100 total % TIGIT+ Scores on LV 2 (8.88%) 4 2 O 2 -3 -4 -6 -4 & ● Healthy young ● Healthy older ● HIV young ● HIV older -95% CL -2 0 2 Scores on LV 1 (17.66%) 4 6 IR signatures on y8 T cells and plasma markers stratify 4 groups of subjects in a PLS-DA multivatriate model#67CYTEK AURORA Multiparameter analysis of immune cells Reagents to distinguish multiple analytes simultaneously We switched to CYTEK spectral platform to generate larger datasets with better signal resolution Instrumentation to detect multiple reagents We use CYTEK spectral unmixing with integrated signal standardization + our own algorithmic tools Data analysis tools to evaluate the results#68opt-SNE algorithm enables high quality visualization of mega-scale datasets and serves as our staple tool for high parameter data analysis nature sq Automated optimized parameters for t-distributed stochastic neighbor embedding improve visualization and allow analysis of large datasets iD Anna C. Belkina, Christopher O. Ciccolella, Rina Anno, Richard Halpert, Josef Spidlen, iD Jennifer E. Snyder-Cappione ID "Standard" t-SNE COMMUNICATIONS 't-SNE for large data’ S opt-SNE algorithm#69V81 V82 Vy9 CD3 CD4 CD8 Spectral analysis reveals dramatic diversity of yå T cells in HIV, Aging opt-SNE algorithm integrates the spectral data CD27 CD16 CD56 CD45RA CD38 CD160 CD103 TIM-3 TIGIT PD-1 y8 T cell data from 96 subjects contain 40 distinct clusters / subtypes 29 24 45 2 23 28 26 38 17 8 20 19 22231 952 ∞ ∞ ∞ 9 27 10 22 1 11 16 24 5 44 32 13 41 43 42 31 30 6 21 100 14 12 80 18 60 4 25 40 20 0 ܚܝ 7353 7 33 15 3 CD3 FVd1 -Vd2 Vg9 -CD4 -CD8 CD45RA -CD27 -CD38 CD103 -CD16 CD56 TIGIT PD1 CD160 -TIM3#70V81 V82 Vy9 CD3 CD4 CD8 Spectral analysis reveals dramatic diversity of y8 T cells in HIV, Aging ≥50yo opt-SNE algorithm integrates the spectral data CD27 CD16 CD56 CD45RA CD38 CD160 CD103 TIM-3 TIGIT PD-1 y8 T cell data from 96 subjects contain 40 distinct clusters / subtypes Uninfected HIV+ <35yo#71Mapping the landscape of the lung in pneumococcal pneumonia nature D Antigen presentation by lung epithelial cells directs CD4+ TRM cell function and regulates barrier immunity Shenoy et al, 2022 COMMUNICATIONS Epithelial cells H+H Day: 0 1 ↓↓↓↓ T and B lymphocytes ● 7 Watch recovery from pneumonia & development of immunity ● + 8 10 14 24 ↓↓ ↓ ↓ 35 Spectral fingerprints of lung cells are generated on Cytek Aurora Measurement stability over multiple timepoints - critical for this project Recovery from pneumonia induces development of tissue resident memory CD4+ TRM cells, BRM cells, and antibody secreting plasma cells.#72Multiparameter measurements on immune cells CYTEK customizable standardized panels allow reproducible and easy-to-implement assays Moving forward, full spectrum cell analysis is the method of choice for single cells cell characterization. CYTEK spectral platform has become a de facto default tool for spectral cell analysis Instrumentation to detect multiple reagents Reagents to distinguish multiple analytes simultaneously Data analysis tools to evaluate the results#73CYTEK TRANSCEND THE CONVENTIONAL Investor and Analyst Day The Aurora Analyzer in Oncology Dr. Franklin "Buddy" Fuda, UTSW June 22, 2022 73#74Buddy Fuda Professor of Pathology Division of Hematopathology Director of Clinical Flow Cytometry University of Texas Southwestern Medical Center Dallas, Tx#75Disclosures ● I have no actual or potential conflicts of interest in relation to this presentation or program.#76My Background ● ● ● ● 20 Years in Clinical Practice Hematopathology and Flow Cytometry at the University of Texas Southwestern Medical center (UTSW) ● ● ● ● Director of two clinical flow cytometry laboratories and one immunology laboratory One of the largest university labs in the county Wide range of patient demographics with high variety of disease Continued in the tradition of excellence set forth by experts in the field such as Louis Picker, Steven Kroft and Nitin Karandikar Expertise in comprehensive and detailed analysis with a unique approach using various software programs including cluster analysis with Cytopaint Used as a reference laboratory for regional laboratories on particularly difficult cases Collaborated with other flow cytometry experts on essential projects such as ConTexFlo (10-year effort across 7-13 labs) building "standardized" screening tubes for high parameter testing Actively involved member, contributor and inspector on international education committees, quality standards committees, and regulatory committees for clinical flow cytometry#77Clinical Flow Cytometry Immunophenotype Flow Cytometry Neutrophil Monocyte Lymphocyte 104 10³ 10² CD3 APC -> 10¹ 109 101 CD4 PE -> 10⁰ Helper T-lymphocytes 10² 103 104 Normal Cell Populations VS Cancer Cell Populations Leukemias and Lymphomas#78How are Laboratories Graded? All Institutions 1. 2. 3. Sensitivity and Accuracy of Diagnosis Operating Expenses Turn Around Time Academic Institutions 1. 2. 3. 4. Sensitivity and Accuracy of Diagnosis Operating Expenses Turn Around Time Expertise in Field 1. Publications 2. National Prominence Setting Our Goals#79Correct Resources Impact Outcomes 1. 2. 3. 4. Instruments Performance ● ● ● Resources ● Reliability/Downtime (Service) Reagents ● Vendor Application Support Training Knowledge of Clinical Market Performance Supply Shipping Times Vendor Customers Service Big influence on Outcomes Quality of Product Efficiency of Operation#80Correct Resources 1. 2. 3. 4. Instruments Performance ● ● ● Resources ● Reliability/Downtime (Service) Reagents ● Vendor Application Support Training Knowledge of Clinical Market Performance Supply Shipping Times Vendor Customers Service Cytek Jeep Enthusiast A=▬▬▬▬▬▬▬ Customer service company Flow Cytometry Focused Match my passion Chrysler dealership Four Wheel Parts#81Flow Cytometry Systems Hardware/Instruments The Markers matter! Numbers Game The more per tube Conventional Clinical Flow Cytometer Up to 12 colors Most Clinical Labs 6-8 colors Conventional Flow Cytometer Reality Highest Expertise 10-14 colors Dirty! The more powerful the test The more cost effective the test Conventional Research Flow Cytometer Up to 30 colors Cytek High Parameter Testing Up to 40 markers Clean!#82Flow Cytometry Systems The Hardware/Instruments Conventional Flow Cytometer Porthole Windows Dee FARM COW!#83Examples: Operating Expense Comparisons Example 1 - Peripheral Blood screen Conventional 17 Unique Markers Tubes Total Markers Run Redundant Markers Unbillable Markers Cost Savings Unique Markers Tubes Total Markers Run Redundant Markers Unbillable Markers 2 Cost Savings 19 2 2 Example 3 - Lymphoid/Myeloid Bone Marrow Screen Cytek 28 Conventional 28 4 38 10 Cytek 17 10 1 17 0 0 1 tube (2 Markers) ~50% 2 29 1 2 tube (9 Markers) ~100% Example 2 Peripheral Blood Mycosis Fungoides Panel Conventional Cytek 20 20 Unique Markers Tubes Total Markers Run Redundant Markers Unbillable Markers Cost Savings Unique Markers Tubes Total Markers Run Redundant Markers Fewer Tubes = $$$ Unbillable Markers Example 4 - Acute Myeloid Leukemia Panel Conventional 31 Cost Savings 3 27 7 7 6 47 19 19 1 20 0 0 2 tube (7 Markers) ~75% Cytek 31 2 32 1 1 4 tube (18 Markers) ~200%#84Turn Around Time Acquisition Faster On Cytek Routine sensitivity each tube - 3 minutes Panel Peripheral Blood screen Peripheral Blood Mycosis Fungoides Panel Lymphoid/Myeloi d Bone Marrow Screen Acute Leukemia Panel Acquisitions Minutes per panel Conventional 6 12 18 Acquisition Minutes per panel Cytek 3 3 6 6 Acquisition Time Savings 100% 200% 200% 300% Acquisition Time Savings across 1,000 patients 50 hours 100 hours 100 hours 200 hours Panel Peripheral Blood Routine analysis each tube - 3 minutes Analysis Minutes per panel Conventional Analysis Minutes per panel Cytek screen Peripheral Blood Mycosis Fungoides Panel Lymphoid/Myeloi d Bone Marrow Screen Acute Leukemia Panel 6 12 Fewer tubes = Faster Less Resource Consumption Faster patient results 18 ● ● 3 3 6 6 Analysis Time Savings 100% 200% 200% 300% Analysis Time Savings across 1,000 patients 50 hours 100 hours 100 hours 200 hours#85Faster Turn Around Times ● Increased productivity • Flow cytometry lab Hematopathology work up Improved patient care Earlier diagnosis Earlier induction of treatment ● More cost-effective patient care • More specific therapeutic approach Reduced duration of inpatient hospital care ● Cytek system "No-brainer" But, does it actually work? True Testament What does the data look like in complex tissue? Can I identify a minute malignant population?#86105 104 CD19 cFluor BYG781-A > 300 103 0 -300 10⁹ 104 CD20 cFluor B515-A -> 300 103 -300 0 -180 0 180 103 CD5 cFluor BYG710-A Stage Stage Stage -200 0 200 103 CD10 cFluor R780-A -> 104 200k 250k 105 150k 100k 21 color tube Cytek 2200 CD34 cFluor BYG575. -2200 0 -300 300 103 CD20 cFluor B515-A → 0 104 105 105 104 r V547-A →> 1400 10³ CD43 cFluor V505-A 101 10² www.l -1100 1100 CD23 cFluor R659-A → 0 104 105 105 104 103 CD38 cFluor R668-A → 0 008- 105 104 10³ Ig Lambda cFluor B690-A →> 0 008- Plasma cells Hematogones Chronic Lymphocytic Leukemia/Small Lymphocytic lymphoma (CLL/SLL) CLL/SLL = 0.001% CD5(+), CD10(-), CD19(+), CD20(dim +), CD23(+), CD34(-), CD38(-), CD43(+), CD45(+), surface kappa(dim +), surface lambda(-) B-cells CLL/SLL -300 CD20 cFluor B515-A → 0 300 103 104 سلسل 101 10² 103 Ig Kappa cFluor R720-A → 104 105 105#87Successful Operation Academic Institutions 1. Accuracy of Diagnosis 2. Operating Expenses 3. Turn Around Time 4. Expertise in Field 1. Publications 2. National Prominence Achieve our goals FAN! #1#88What's that mean for Flow Cytometry ● Cytek revolutionizes flow cytometry • Unleashes the full potential of artificial intelligence Simplifies the technical component Opens new horizons for research and clinical practice ● ● • Meets new challenges brought about through advancements in clinical therapeutics#89What's that mean for Cytek • It takes the market share • Reference laboratories and University Laboratories Will switch to the latest technology • Private practice and small laboratories • Will establish in-house labs Flow cytometry is a high revenue generator Capture the professional component but outsource the technical component • Technical component is where most revenue lies Cytek simplifies the technical component ● • Out of the gate Early Builds a bond ● ● Superior product Superior customer service Longevity of relationship#90Cytek A Focused Flow Cytometry Company Machine, Reagent, Service §#91CYTEK TRANSCEND THE CONVENTIONAL (R) Investor and Analyst Day Break June 22, 2022 91#92CYTEK TRANSCEND THE CONVENTIONAL (R) Investor and Analyst Day Cytek Technologies and Products Dr. Ming Yan, Chief Technology Officer Mark Herberger, Sr. Director Marketing June 22, 2022 92#93Unmet Needs: High Dimensional Cell Analysis The complexity of the immune system requires to detect and purify the combinations of expressing numerous proteins, the functionally distinct cell subsets. To correlate a given immune response to disease and treatment ● Functional Assays ● ● ● ● ● ● ● High Content/High Throughput Clinical Assays Metabolomics Cytokine assays Proliferation Apoptosis/cell killing HD and Automated MRD HD and Automated L&L CYTEK TRANSCEND THE CONVENTIONAL Dimensionality Reduction High Dimensional Immune Characterization ● ● Nanoparticles ● Infectious Disease Tumor Vaccine response CAR-T ● Vaccine delivery Immunotherapy Environmental biology Multimeter Colors Trend of Multiparameter Cell Analysis 45 40 35 30 25 20 15 10 5 0 1980 Conventinal Flow 1990 2000 Year 2010 2020 2030 93#94Advancing Cell Analysis with Our Unique FSP Technology Cytek's FSP Technology Conventional 80 80 70 80 50 30 20 10 n 300 Ignored PE Channel Compensated CYTEK TRANSCEND THE CONVENTIONAL 7:00 FITC = Green!... or emission from 515-545 (530/30 BP) zul PE cFluor YG584 UV Channe Be Channe X/G Channels And Cha Unmixing algorithm ENTIRE emission spectrum is captured across the different module & stitched together to create a spectral signature that combines emission information of fluorochrome excited by all onboard lasers CD8 APC 13 å 꿈 APC Alexa Fluor 647 0 4.0M- 2.0M 1.0M- 0- NK cells Aurora Full Spectrum NK cells M 0 10 10³ CD56 Alexa 647 Non T cells THE Tong 10¹ APC 10⁰ Unmixing T cells 10ª CD3 FITC CD8 APC 10⁹ -10³ Alexa Fluor 647 -10* 10⁰ NK T cells NK T cells 0 101 CD56 Alexa 647 Our FSP platform was purpose- built to advance the next generation of cell analysis by delivering deep insights, high throughputs and ease of use FSP technology enables high sensitivity and high throughput without compromising data quality Allows use of many dyes simultaneously with optimal resolution, which is not possible with conventional cytometers FSP is able to extract autofluorescence to enhance resolution 94#95C Our FSP Technology is Powered by Patented Innovative Designs 4 CE BCTUR I APD DETECTOR MODULE DETAIL DE EXTCR2 DE EXCR DE ESTRA CYTEK AURORA CYTEK TRANSCEND THE CONVENTIONAL Maximize Resolution & Accuracy SUVEN VIRTONS LAGERS A WAPO DETECTOR MODULE VIOLET APD DETECTOR MODULE FLOW CELL BLUE APO DETECTOR MODULE SAMPLE поспортоз RED AND DETECTOR MODULE YORK APP DETECTOR MODULE Optimized Signal-to-Noise Ratio B LTRAVIOLET CHANK-SI VIOLET CHANNELS BLUC C&CHANNELS SPECTROFLO DISPLAY YELLOW-GREEN RED CHANNELS OR CHANNELS High Resolution D 100 quantum efficiency (%) 10 0.1 200 PMT APD photodiode 400 600 800 wavelength (nm) Valuable Insights 1000 1200 A The fluorescence spectrum from each laser source is collected from multiple laser excitation B The fluorescence from each laser source is collected by each corresponding detector array module C Use of APD detectors maximizes sensitivity and enables broad wavelength responses D The combination of our patented optical design with APD detectors yields high- resolution data at an optimized signal-to-noise ratio 95#96Cytek's Core Instruments: Analyzer to Sorter >40 Colors from 3-5 Lasers CYTEK AURORA Aurora CYTEK TRANSCEND THE CONVENTIONAL Biopharma, CROS, Large Academic Labs High-End Market ? High-Throughput & Compact Northern Lights >24 Colors from 1-3 Lasers CYTEK KL-3000 Individual Researchers & Clinical Labs x Flexible & Intuitive Entry-Level Market jike Ultra-Sensitive Aurora Cell Sorter >40 Colors from 3-5 Lasers 00000 CYTEK Biopharma, CROS, Large Academic Labs Valuable Insights High-End Market 96#97We Provide an End-to-End Platform of FSP Solutions Aurora Cell Sorter Specificity CD3 CD14 CD45 Violet Instruments Fluorochrome cFluor V420 cFluor V450 cFluor V547 CYTEK TRANSCEND THE CONVENTIONAL 0 Specificity CD8 CCR7 IgD CD45RA CD19 CD25 Blue Northern Lights Han Fluorochrome cFluor B515 cFluor BYG575 cFluor BYG667 Automatic sample loader cFluor 8690 cFluor BYG710 cFluor BYG781 Specificity CD127 CD16 CD56 CD4 Viability CD27 Red Fluorochrome cFluor R659 cFluor R668 cFluor R720 cFluor R780 ViaDye Red cFluor R840 Services & Application Support Reagents and Kits 2000 CYTER FULL SPECTRUM 5-LASER CYTOMETRY AT A GLANCE CYTEK CYTEK SELAS Dimensionality Reduction CYTEK Data Acquisition and Analysis Software 97#98Cytek' FSP Platform versus Other Technologies Conventional Flow Cytometry Biomarkers / Parameters (>40 biomarkers)1 Sensitivity (nanoparticle detection) Throughput (>30K cell/second) Footprint (<150K cm ³) Sorting Capability Cost Performance² CYTEK TRANSCEND THE CONVENTIONAL CYTEK TRANSCEND THE CONVENTIONAL X X Spectral Flow Cytometry X X X X X 1. Based on peer-reviewed publications 2. Cost-to-Performance reflects performance based on accessible biomarkers, sensitivity, throughput and sorting capabilities, relative to costs associated with instruments, consumables, time, labor and ability to upgrade over time Mass Cytometry X X X X X 98#99Our FSP Technology Provides a Significant Reagents Sales Opportunity Cytek developed a set of spectral unique dyes based on full spectrum cytometry About 28 cFluor dyes with high parameter enablers have been commercialized We market cFluor 14 & 25 colors immunoprofiling kit Fluorescence spectrum of Cytek cFluor dyes can be stored in the instruments for ease of use and bundling with instruments Spectral unique dye - high parameter enabler Function assay dye CYTEK TRANSCEND THE CONVENTIONAL % NORMALIZED EMISSION 100 90- 0 Fluor V420 Fluor V450 Fluor V547 Fluor B515 Fluor BYG575 1 ViaDye Red cFluor Laser Violet Violet Violet Violet Violet Blue Blue Blue Blue Blue Blue Blue Blue Blue Blue Blue Yellow Green Red Red Red Red Red Red Violet Red cFluor cFluor V420 cFluor V450 cFluor V500 cFluor V570 cFluor V620 cFluor B518 cFluor B532 cFluor B548 cFluor BYG575 cFluor BYG610 cFluor BYG628 cFluor BYG666 cFluor BYG676 cFluor BYG680 cFluor BYG710 cFluor BYG781 cFluor YG584 cFluor R659 cFluor R667 cFluor R685 cFluor R720 cFluor R780 cFluor R810 Via Violet ViaRed 99#100Reagents & Kits Portfolio Cytek cFluor Reagents Cytek Aurora Cytek® Aurora, Aurora CS, and Northern Lights™ flow cytometers deliver powerful cell analysis and sorting canabilities hv leveraging Full Spectrum Profiling™ CYTEK TRANSCEND THE CONVENTIONAL CYTEK Cytek cFluor Dyes and Reagents High Parameter EnablersTM Empower Full Spectrum Profiling™ Cytek Northern Lights™ CYTEK TRANSCEND THE CONVENTIONAL In a world of ever expanding fluorochrome options, our field teams listened to users who expressed frustration at the time commitment needed to understand the Ⓡ Our reagents are fluorochrome conjugated antibodies used to identify cells of interest Our multi-color cFluor immunoprofiling kits and optimized multicolor immunofluorescence panel provide users with ready-to-use antibodies and protocols Class 1 single-color reagents currently sold in China with clinical studies underway for 6-color TBNK reagents for potential Class 3 registration CD-IVD single-color reagents & 6-color TBNK reagents self certified in Q2 for EU customers 100#101Cytek Bioinformatics Program Objectives Make it easier to do Flow: Easier for new customers to get started, and advanced users to scale to larger and more complex experiments. 訂 Enables better understanding of our customers' needs: Our software gives us deeper insights into customers' use cases and applications. CYTEK TRANSCEND THE CONVENTIONAL Accelerates reagent and instrument pull-through. Powerful and easy-to-use software gives faster time-to- insight and answers more scientific questions. Enhances and accelerates product development. We use the same software as our customers, aligning us with customer needs and reducing time-to-market. 101#102Cytek Al Expected to Speed Up the Clinical Adoption Collaboration of Al machine learning on automatic diagnosis of B-ALL MRD Increased accuracy with less laboratory time - Greater simplicity CYTEK TRANSCEND THE CONVENTIONAL 4.0M- 3.0M 2.0M- 1.OM- 10- 10⁰. 0 All Events P1 2.0M FSC-A Q1607 P3 10° CD38 Q1607 P Count 343 10 CD10 Pant 19.78 40M Q1607 P3 10 CD10 10" T 10° 10° 10⁰- Q1607 PI P2 2.0M FSC-A 10% 10" 10- LOM Q1607 P 10" CD38 Q1607 P3 10 CD10 Q1607 P 10" CD10 10⁰ 10" 10⁰ 10 10 38.47 10 01607 P2 CD64C 0 10⁰ CD38 10- 10"- 10¹ Q1607 P3 Q1607 P3 C010 01607 P CD34 01.0M 10⁰ Q1607 P 10 TT 3.0M SSC-A ros CD33 floor BYGGIO A 10- 10- 10- 101- 3.0M 2.0M- 1.0M TT . Q1607 P3 10⁰ CD38 Q1607 P3 10° CD10 Count 101 ent: 5.50 01607 P3 CD34 01607 P P3 Coup, 1835 CD19 10" 10 Manual Analysis with Spectro Flo Pakol 0.37 10 CYTEK TRANSCEND THE CONVENTIONAL Ⓡ A 10 10² e 2 M FSC-A 191 30 CD38 3M 4M 20 10 30 10 COLD 10 30 CD10 10 20% 100 30% 1M 2M PSCA 30° 30° CD38 C030 4M 101 10° 30 10 C030 8 30⁰ 10 10 10 30 101. 2 M 3M 4M SSC-A 20² 20 20 (338 10 10 COLO Al Analysis 10 10 CD34 30% 0 10 10 10 CD19 10 20 COME 10 10 10 CD19 Seamless Workflow to the Clinician with Immediate Data Read O 10 10 10 C034 102#103Advancing Technology through Collaborations Dr. Sylvain Simon of Fred Hutch Cyto 2022 Talk Nand City Ca har P Sep A 59-marker panel to decipher immune cell perturbations in immunotherapy-treated patients VERA TANG, ADJUNCT PROFESSOR, FACILITY MANAGER, FLOW CYTOMETRY CORE FACILITY. UNIVERSITY OF OTTAWA Optimization and quantification of small particle sensitivity on the Cytek Aurora platform using FCMPASS software. Multiple sites nano-particle standardization NIH University Ottawa Cytek Bethesda CYTEK TRANSCEND THE CONVENTIONAL Team CYTEK TRANSCEND THE CONVENTIONAL 刘艳荣 Multiple site collaboration in L&L MRD diagnosis and monitoring 研究员,硕士生导师。 现任北京大学血液病研究所血液細胞实验室主任。 1984年毕业于北京医科大学,曾在美国MD Anderson肿窗中心实验血液学实验室 进行博士后研究,擅长血液恶性肿瘤的免疫分型和基因诊断。曾获得国家自然科学 基金和国家“863项目”等多项研究基金。获卫生部科技进步三等奖。主编《实用 流式细胞术-血液病篇》和参与编写全国研究生统编教材《医学细胞生物学》等4部 专著,兼任中国免疫学会血液免疫分会常务委员,中国免疫学会血液免疫分会临床 流式细胞术学组主任委员,中国医药生物技术协会生物诊断技术分会生物檢測到原材 料标准化学组成员。中国生物学会细胞分析专业委员会(筹)发起人及主任委员, 中国国家自然基金评审专家,《中华血液学杂志》审稿专家及《中国实验血液学杂 志》编委 Al on clinical data analysis Q167H ܠܝ CON 101 103#104Cytek's Value Proposition to the Clinical Market CYTEK NL-3000 FSP CYTEK TRANSCEND THE CONVENTIONAL Advanced flow cytometry for disease screening, diagnosis and monitoring Benefits ▪ More informative antibodies in 1 tube ■ Eliminates redundant reagents Optimizes use of smaller amounts of patient specimen ■ Identifies tiny populations of abnormal cells Explore new cell maturation pathways and cell subtypes ▪ Improves overall laboratory efficiency ▪ Lowers costs. 104#105Cytek Supporting Laboratory Developed Test (LDT) Worldwide Project Cytek 20-color MRD kit Conversion of BD Canto L&L panels to NL-CLC Broad range of LDT panels Formal clinical study on two MRD panels: NL- CLC vs. Canto Testing Al data analysis 20C AML panel for publication to promote cFluor Custom reagent projects Evaluating Al algorithm for AML MRD diagnosis and analysis CYTEK TRANSCEND THE CONVENTIONAL Panels 20C AML MRD 10 panels, screening and diagnosis. Tested in >300 samples 23C MM, 23C ALL-CS, 16C ALL-IC, 22C L&L screening panel, AML CAR-T target panel 14C BLL MRD 20C AML MRD 20C AML MRD panel Assorted 10, Immunology, infectious disease AML MRD diagnosis Number of cFluors 20 16 cFluors 15-17 cFluors 14 cFluors 17 cFluors Varies due to clone and dye access >15 cFluors 105#106Next-Gen Clinical Flow Cytometry - Key Focus Points Next Generation Flow Cytometry: completely operator independent - removing bias, daily performance variability, and individual operators' variability. Result: improved results & data quality Instrument ● CYTEK TRANSCEND THE CONVENTIONAL ● Automation Characterization & Initialization Easy set up Optimization and standardization • Cocktail & Assay Preparation. Consistent construction, incubation, and sample processing times Constant temperature control and minimized light exposure ● ● Data Acquisition ● • Standardization & QC verification Assay & Acquisition worksheets Adjustment of acquisition gates ● Data Analysis & Reporting ● ● ● Cluster determination & visualization Reporting & Database export Cross-discipline data integration & correlation 106#107System Solutions Under Development at Cytek ● ● ● ● Advanced Instrumentation Automated processing Panels based on innovative cFluor reagents Application driven menu Automatic data analysis CYTEK TRANSCEND THE CONVENTIONAL YTEK misc Cytek Clinical System -->- Flow cytometer with loader option Automated Sample prep L&L DX, MRD, Immunodeficiency and immune monitoring assays Analysis Software with bi-directional LIS connectivity & barcoding 107#108CYTEK TRANSCEND THE CONVENTIONAL (R) Investor and Analyst Day Key Financial Review Patrik Jeanmonod, CFO June 22, 2022 108#109Strong and Growing Base of Instrument Placements 303 4Q19 CYTEK TRANSCEND THE CONVENTIONAL 376 1Q 20 447 2Q20 548 3Q20 657 4Q20 CAGR (Q4'19 - Q1'22) 86% 751 1Q21 855 2Q21 970 3Q21 1110 4Q21 1226 1Q22 109#110Quarterly Revenue and Adjusted Gross Margin % Q1-20 to Q1-22 ($MM) $18.0 $1.9 47% $16.1 Q1'20A $19.1 $1.7 CYTEK TRANSCEND THE CONVENTIONAL 43% $17.5 Q2'20A $25.1 $1.9 62% $23.2 Q3'20A Service Revenue $30.6 $2.0 64% $28.6 Q4'20A $24.3 $1.6 60% $22.7 Q1'21A $30.4 $1.7 Reconciliation of Non-GAAP figures are in the appendix 65% $28.7 Q2'21A Product Revenue $34.4 $2.2 64% $32.2 Q3'21A $38.9 $2.9 63% $36.0 Q4'21A Adj-GP $35.1 $3.6 61% $31.5 Q1'22A Q1-2022 Review • Revenue $35.1 million or + 44% YoY Cytek added another 116 instruments now total base at 1,226 ● ● Service revenue has more than doubled from the prior year on more instruments coming off warranty ● • Adjusted GP margin 61% compared to 60% in the first quarter of 2021 110#111Revenue & Adj. EBITDA Adj. EBITDA Tot. Revenue A-EBITDA % CYTEK TRANSCEND THE CONVENTIONAL -2% Q1 20 $(0.4) $18.0 Q1'20 $(0.4) $18.0 -2% 2% $0.4 Q2'20 Q2'20 $0.4 $19.1 $19.1 2% 28% $7.1 Q3'20 Q3'20 $7.1 $25.1 $25.1 28% Reconciliation of Non-GAAP figures are in the appendix 27% $8.3 Q4'20 $30.6 Q4'20 $8.3 $30.6 27% Tot Revenue 7% $1.8 $24.3 Q1'21 Q1'21 $1.8 $24.3 7% 15% $4.7 $30.4 Q2'21 Q2'21 $4.7 $30.4 15% A-EBITDA % $34.4 16% $5.5 Q3'21 Q3'21 $5.5 $34.4 16% $39.9 14% $5.5 Q4'21 Q4'21 $5.5 $39.9 14% $35.1 7% $2.2 Q1'22 Q1'22 $2.2 $35.1 7% 111#112Operating Expenses S&M Expenses (SMM) 19% $3.5 16% $3.1 15% 15% $3.8 $4.6 CYTEK TRANSCEND THE CONVENTIONAL 17% $4.3 18% 18% $6.6 $5.6 $8.3 20% $7.0 18% Q1'20 Q2'20 Q3'20 Q4'20 Q1'21 Q2'21 Q3'21 Q4'21 Q1'22 R&D Expenses ($MM) 17% $3.0 15% $2.9 20% $7.1 19% 14% 13% 16% 16% MM 8% 7% $2.5 $2.5 $2.6 $1.7 13% 14% $5.1 $3.4 $4.4 20% $6.2 $6.1 $8.0 Q1'20 Q2'20 Q3'20 Q4'20 Q1'21 Q2'21 Q3'21 Q4'21 Q1'22 % of Total Revenue G&A Expenses ($MM) 16% $4.0 13% $4.2 $7.5 $6.9 18% 1,5% 16% Q1'20 Q2'20 Q3'20 Q4'20 Q1'21 Q2'21 Q3'21 Q4'21 Q1'22 112#113Cytek Operating Stats Non-GAAP Target Operating Model ($ in thousands) Gross Margin % S&M % R&D % G&A % Adj. EBITDA Margin % Gross Margin Shift in product mix with higher margin reagents becoming a greater share of total revenue Benefit from economies of scale as Company grows Leverage global manufacturing capabilities CYTEK TRANSCEND THE CONVENTIONAL 1Q2020 47% 19% 17% 14% -2% 2Q2020 43% 16% 15% 13% 2% S&M 3Q2020 62% 15% 13% 7% 28% Increased publications improve brand recognition and lowers customer acquisition costs Key Improvement Drivers Improved variable costs to retain and service customers at scale Reconciliation of Non-GAAP figures are in the appendix 4Q2020 64% 15% 14% 8% 27% 1Q2021 60% 17% 20% 16% 7% R&D 2Q2021 65% 18% 20% 13% 15% ▪ Lower cost to develop new products by leveraging existing FSP platform ■ Talent diversification in other lower cost locations Lower fixed costs to operate at scale 3Q2021 64% 18% 16% 15% 16% ■ 4Q2021 63% 20% 16% 16% 14% G&A 1Q2022 61% 18% 19% 18% 7% Improved operating costs through system automation ■ Talent diversification in other lower cost locations 113#114Top Line Growth with Improved Operating Efficiencies (($) CYTEK TRANSCEND THE CONVENTIONAL Support 4 pillars strategy - with focus on top line growth, GP margin improvement and increased A-EBITDA $ value and as percent of total revenues Discipline in cost management Capex investment to support long term Cytek worldwide growth Re-affirming prior 2022 revenue guidance closer to the high end of the range $160 - $168m 114#115CYTEK TRANSCEND THE CONVENTIONAL (R) Investor and Analyst Day Business Strategy & Conclusions Dr. Wenbin Jiang, CEO June 22, 2022 115#116Cytek's Four Business Pillars Instruments Performance Intelligence Ease of use ● ● Compact Lowest cost CYTEK TRANSCEND THE CONVENTIONAL UNAVA FOOTNOTE Applications Enabler Panels/kits Flexibility Functionality/Purposes Volume/repeating UNNA Bioinformatics Storage Analysis Optimization Management Exchanges ● ● ● ● ● UNNA are are are Clinical ● ● ● ● ● Regulatory LDT Menu Al Standardization UNNA 116#117Cytek Vision Comprehensive Solutions Company CYTEK TRANSCEND THE CONVENTIONAL Imaging Spatial Mass Spectral Microfluidics Autosampler Liquid biopsy Single cell analysis Genomics NGS Marine biology Environmental 117#118Cytek's Operational and Shareholder Goals Capital Efficiency Operational Excellence. CYTEK TRANSCEND THE CONVENTIONAL Maximize Free Cash Flow Commitment to Shareholder Value Creation Maintain Positive EBITDA Execution Speed Smart Acquisitions, Licenses and Joint Ventures 118#119Why Invest In Cytek - Investment Thesis Transformative Platform Technology Driving Growth & Expansion with strong global adoption rate CYTEK TRANSCEND THE CONVENTIONAL Strong Balance Sheet and Cash Flow Positive The most competitive innovator in Cell Analysis - fastest growth in the industry Attractive Valuation 119#120CYTEK TRANSCEND THE CONVENTIONAL (R) Investor and Analyst Day Thank you! June 22, 2022 120#121CYTEK TRANSCEND THE CONVENTIONAL Appendixes June 22, 2022#122Note: Fiscal Quarter Non-GAAP Adjusted GP Reconciliation ($ in thousands) Non-GAAP Adjusted Gross Profit Reconciliation ($ in thousands) GAAP Gross Profit Adjustments Amortization of Acquisition-Related Intangible Assets Stock-Based Compensation Expense Non-GAAP gross profit Revenue !Non-GAAP gross profit % FY20A 51,710 0 232 51,942 92,839 56% FY21A 79,144 237 1,508 80,888 127,950 63% 1 1Q2020 8,375 0 29 8,404 17,988 47% 2Q2020 8,270 0 40 8,310 19,137 43% 3Q2020 15,615 0 38 15,653 25,095 62% 4Q2020 19,450 0 125 19,574 30,619 64% 1Q2021 14,487 0 112 14,599 24,272 60% 2Q2021 19,745 0 120 19,864 30,408 65% 3Q2021 21,276 0 559 21,835 34,376 64% 4Q2021 23,636 237 717 24,589 38,893 63% CYTEK TRANSCEND THE CONVENTIONAL 4Q2022 20,177 337 708 21,221 35,064 61% 122#123Note: Fiscal Quarter Non-GAAP Adjusted EBITDA ($ in thousands) Non-GAAP Adjusted EBITDA Reconciliation ($ in thousands) Net Income Adjustments Depreciation and Amortization Provision for (Benefits from) Income Tax Interest Income Interest Expense Foreign currency exchange loss (gain), ne Litigation Settlement Loss on Lease Exit Cost Acqisition Related Expenses Stock-Based Compensation Expense Adjusted EBITDA Revenue Adjusted EBITDA % of Revenue FY19A (16,827) 309 534 (711) 1 (32) 20,019 269 3,561 57,883 6% FY20A 19,411 578 (4,982) (110) 333 (463) 611 15,379 92,839 17% FY21A 3,027 1,241 2,921 (49) 1,741 1,481 6,586 17,525 127,950 14% 1Q2020 (839) 105 198 (86) O 104 105 (411) 17,988 -2% 2Q2020 8,111 161 (7,914) (15) 1 (79) 109 373 19,137 2% 3Q2020 6,539 179 387 (3) 2 (137) 125 7,091 25,095 28% 4Q2020 5,600 133 2,348 (5) 330 (350) 347 229 271 8,327 30,619 27% 1 1Q2021 101 169 50 (10) 375 663 456 1,804 24,272 7% 2Q2021 2,671 194 597 (9) 433 135 667 4,688 30,408 15% 3Q2021 1,420 194 655 (12) 442 388 2,455 5,542 34,376 16% 4Q2021 (1,165) 685 1,619 (19) 492 295 347 229 3,008 5,491 38,893 14% 1Q2022 (2,158) 1,470 (1,144) (18) 590 422 3,837 2,998 35,064 7% CYTEK TRANSCEND THE CONVENTIONAL 123#124Overview of Our Key Business Components Revenue Components Instruments Reagents / Applications Software Services Background Our instrument revenue primarily consists of sales of our Aurora and Northern Lights and Cell Sorter systems, instrument accessories, such as loaders ● ● We offer multiple versions of our Aurora and Northern Lights and Cell Sorter systems with different price points based on the number of lasers integrated in the systems We also derive revenue from sales of our conventional flow cytometry system, which is available for sale in China We recognize product revenue when control of the instrument is transferred to the customer We currently offer and are developing an additional range of kits and single vial reagents for both the Clinical and RUO (human & mouse) markets. As a full flow cytometry solutions provider, we are aggressively expanding our reagent offering of kits, single vial reagents, and paid panel design, support, and validation services to meet our customers' needs and to drive the continued and expanded adoption of our superior technology into both the Clinical and RUO markets. Our software is integrated into our instruments free of charge Our service revenue primarily consists of post-warranty service contracts, installations and repairs which are recognized over time Post-warranty service contracts are recognized ratably over the term of the contract and installations and repair services are recognized as they are delivered to the customer CYTEK TRANSCEND THE CONVENTIONAL 124