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HIGH DIMENSIONAL FLOW CYTOMETRY FOR COMPREHENSIVE IMMUNE MONITORING IN CLINICAL TRIALS Dominic Gagnon, Yoav Peretz, Marylène For8n, Claire Landry, and David Favre ImmuneCarta Services, 2901 Rachel Est, Suite 22, Montréal, QC, Canada, H1W 4A4 Introduc8on Immune Monitoring Data Analysis Precision, Stability and Reproducibility Conclusions Study Cases of Immune Monitoring Frequency (%CD8) Frequency (%CD4) Figure 14: Study protocol and immune monitoring of the AGS004 pilot study to invesNgate the safety and immunologic acNvity of an autologous HIV immunotherapeuNc agent. (NCT00381212 ) ICS and CFSE prolifera8on assays were performed as indicated in the study protocol (leW). The frequencies of the HIV(GNRV)specific CD8 and CD4 T cell responses and their func8onal profiles (CD107a, IFNγ and IL2) (right) are compared between baseline and visit 8 aWer vaccine administra8on. Pie charts represent the rela8ve distribu8on of the func8onal subsets within the total CD8 and CD4 T cell pools. Sta8s8cal significant differences (P < 0.05) between pre (V2) and post (V8)vaccine 8me points are indicated by WilcoxonRank and a Student’s ttest (# and +, respec8vely). The 90 th and 75 th percen8le threshold applied to background subtracted CD8 and CD4 T cell responses were 0.01% and 0.005%, respec8vely. Pretreatment Phase Vaccine ART Vaccine ARTI Booster Phase Followup & Safety ART: an8retroviral treatment ARTI: ART interrup8on V6 V2 V9 90 mL 90 mL 90 mL 90 mL 90 mL 90 mL Client PRODUCT PRODUCTION ImmuneCarta DC TARGET PRODUCTION w0 w4 w8 w12 w16 w20 V8 V3 V13 Vaccine Treatment Visit/Week Samples wk0 wk8 wk16 wk20 wk24 BASELINE IM SAMPLES POSTTHERAPY IM SAMPLES Immune Monitoring ICS ICS and CFSE CFSE CFSE CFSE CFSE Exported as “Experiment” from Diva database to Raw Data Server .fcs files read from Raw Data Server on FlowJo template .jo, .csv, and .PDF from FlowJo saved in Derived Data Server Batch layout PDF, and data table saved in Derived Data Server QA if needed Assay Acquisi8on Sta8on Raw Data Server Analysis Sta8on Derived Data Server QC Sta8on Client Report • Another analyst on another iMac analysis sta8on • Verify ga8ng and documenta8on • Confirm data report across all files • Phenotyping • Func8onal profiling • Enumera8on • ICS • Prolifera8on • PhosFlow • Cyotkine bead arrays • BD Diva/ LSR II • Daily and monthly QC • Acquisi8on template applied • Applica8on sepngs used • Compensa8on and staining references • Delete/modify restricted • Regular backup • Presenta8ons • Data Table • PDF • iMac analysis sta8on • Import FlowJo assay template • Exploratory analysis can also be done with SPICE/PRISM • Users can only create or read files • Regular backup Figure 9: Flow of work for data analysis. Sample processing, assays and data acquisi8on are based on preapproved worksheets related to study requirements. Samples are acquired on BD LSR II cytometers based on predefined sepngs and templates. The raw FACS data are exported directly to the Raw Data server and used on FlowJo analysis template on the Derived Data server. Once analysis has been completed and documented, a full QC of data analysis is performed. Final client data and report are generated, while the whole process is audited by the Quality Assurance (GLP studies). Figure 2: Overview of immune monitoring services. ImmuneCarta Services include all steps from strategic planning to final reports to clients. It oWen involves study setup, lab manual wri8ng and sample management which are cri8cal steps for cellbased analysis as flow cytometry assays. Customized assays as per client needs require assay development and valida8on prior to immune monitoring of clinical samples. All steps include an ac8ve followup with the sponsor, are performed using proprietary SOPs and worksheets and are documented as per applicable GLP regula8ons. Strategic Planning and Communica8on Proac8ve Rela8onship with Sponsors, CRO, and Clinical Sites Standard and Customized Immune Monitoring Assays Study Progress and Final Report to Sponsor •Innova8on and development program •Design of immune monitoring strategy and workplan •Ph.D.level Principal Scien8sts assigned to each study •Involved in study setup, lab manual wri8ng, and sample management •Onsite training of clinical sites for maximum sample viability and recovery •Assay development, qualifica8on, and valida8on; SOP & worksheets •Data integrity, high quality and high throughput processing and analysis •Documenta8on, sample tracking and control, GLP/GCLP training •Conference calls, interim and final scien8fic reports •Quality Assurance Statement •Ac8ve par8cipa8on in scien8fic posters and publica8ons Figure 8: Reproducibility and %CV from external QC samples: results obtained with BD MulNcheck CD4 low controls in 14 experiments with lot # 40L in April 2010 and 17 experiments with lot # 50L in May 2010. The first graph represents the enumera8on of lymphocytes (CD45), T cell popula8ons (CD3, CD4, and CD8), B cells, and NK cells. The second graph represents the enumera8on of the same popula8ons. Coefficient of varia8on are indicated in blue. CD4 Low control, lot # 40L CD45 CD3 CD4 CD8 B NK 0 250 500 750 1000 1250 1500 Populations Count/uL CD4 Low control, lot # 50L Populations Count/uL CD45 CD3 CD4 CD8 B NK 0 250 500 750 1000 1250 1500 2.5 3.1 3.7 4.1 3.1 3.2 5.0 4.9 5.6 4.7 5.6 5.2 Beads 0 10 2 10 3 10 4 10 5 FITC-A 0 20 40 60 80 100 % of Max Ungated 0 50K 100K 150K 200K 250K FSC-A 0 20 40 60 80 100 % of Max Beads 0 10 2 10 3 10 4 10 5 PE-A 0 20 40 60 80 100 % of Max Beads 0 10 2 10 3 10 4 10 5 PerCP-A 0 20 40 60 80 100 % of Max Beads 0 10 2 10 3 10 4 10 5 FITC-A 0 20 40 60 80 100 % of Max Beads 0 10 2 10 3 10 4 10 5 PE-A 0 20 40 60 80 100 % of Max Beads 0 10 2 10 3 10 4 10 5 PerCP-A 0 20 40 60 80 100 % of Max Ungated 0 50K 100K 150K 200K 250K SSC-A 0 20 40 60 80 100 % of Max Figure 4: Stability of the signal using applicaNon seangs coupled with CS&T. Compbeads were stained 45 8mes with either FITC, PE or PerCP (3 month survey) and were used to determine compensa8on for 81 experiments using cytometer # 1 and 31 experiments using cytometer # 2. Voltages were determined by the Applica8on Sepngs linked to the daily CS&T Performance check. First row: 11color cytometer, second row, 18color cytometer with yellowgreen laser (see increased posi8ve PE signal without increasing the background). FITC PE PerCP FSC/SSC LSR II # 1 LSR II # 2 Serum aliquoNng/ storage ELISA assays: Vaccine Nters Soluble markers Other soluble markers ImmuKnow Assay Performed at ImmuneCarta Services Performed at collaborator sites Flow cytometry T cell panel (12 colors) Innate panel (12 colors) Cell pellet cryopreservaNon DNA analysis (SNP/telomeres) Paxgene tube storage RNA/mRNA analysis Ficoll PhosFlow Flow cytometry B cell panel (11 colors) PBMC cryopreservaNon Figure 3: Example of sample management for assays performed at ImmuneCarta Services and at collaborator sites. In this vaccine clinical trial on 200 subjects, ImmuneCarta provided mul8ple services including study design, central lab ac8vi8es, assays and integrated analy8cal report. In this example, fresh blood samples from each subject and each 8me point were collected at a CRO site nearby and immediately processed for analysis at ImmuneCarta or stored at ImmuneCarta for analysis at collaborator sites, e.g. genomics, gene8c, other soluble markers or PhosFlow. Figure 5: Reproducibility of CD34+ absolute counts using reference QCs over Nme. Three levels of CD Chex CD34 reference controls were used (3, 35, and 124 CD34 cells/µL) and two BD Stem Cell Control Kit (12.1 and 35.9 CD34 cells/µL). Coefficient of varia8on for CDChex level 1, 2, and 3 are respec8vely 8.98%, 3.84%, and 1.98%. For BD Stem cell low and high reference controls, the CV are respec8vely 6.94% and 3.48%. 25-Feb-2011 28-Feb-2011 1-Mar-2011 2-Mar-2011 4-Mar-2011 8-Mar-2011 11-Mar-2011 28-Mar-2011 29-Mar-2011 31-Mar-2011 1-Apr-2011 6-Apr-2011 8-Apr-2011 0 5 10 15 20 25 30 35 40 45 50 12.1 BD Stem Cell Control LOW BD Stem Cell Control HIGH Target value + 20% - 20% Target value + 20% - 20% CD34 count (cells/μL) 25-Feb-2011 28-Feb-2011 1-Mar-2011 2-Mar-2011 4-Mar-2011 8-Mar-2011 11-Mar-2011 28-Mar-2011 29-Mar-2011 31-Mar-2011 1-Apr-2011 6-Apr-2011 8-Apr-2011 0 2 4 6 3 50 100 150 28 35 42 124 CD-CHEX CD34+ Level 3 CD-CHEX CD34+ Level 2 CD-CHEX CD34+ Level 1 Target value + 20% - 20% Target value + 30% - 30% Target value + 20% - 20% CD34 count (cells/μL) Discovery Pre clinical Phase I Phase II Phase III Phase IV / Market Figure 13: SchemaNc of the drug discovery process. Table I: Overview of ImmuneCarta assays in different fields of applicaNon and therapeuNc areas. ImmuneCarta Services is a leading provider of services for preclinical and clinical studies related to immunology. Over the past 7 years, we have developed a broad bayery of innova8ve assays to characterize cell popula8ons and immune responses in the sepng of infec8ous diseases, cancer, vaccine trials and immunebased therapies. Based in Montréal, ImmuneCarta Services is specialized in advanced mul8parametric flowbased assays performed according to GLP regula8ons, GCLP guidelines governed by Quality Management Systems and standard opera8ng procedures. ImmuneCarta exper8se includes the assessment of phenotypic and func8onal markers, the characteriza8on of cell subset lineages, ac8va8on states, and signaling molecules, as well as the quan8ta8ve analysis of vaccine, pathogen or drugspecific responses based on an8body signatures, cytokine/ chemokine profiles, and signaling pathways. We describe here our experience as a contract research organiza8on providing services to the biopharmaceu8cal industry, in the execu8on of high dimensional flow cytometry analysis of subjects enrolled in Phase I/II clinical trials. Flow cytometry is a unique way to address complex cellular immunological profiling for drug development and Phase IIII clinical trials in infec8ous diseases, cancer, vaccine, transplanta8on, autoimmune disorders and related immunomodula8onbased therapies. High dimensional mul8parametric singlecell analysis is not only aimed to define mul8ple markers of different cell popula8ons simultaneously though helpful when clinical sample availability is limited, it is also one of very few analy8cal plazorms that can address complex proteinbased signatures (biomarkers, disease stage, etc.) and func8onal networks (mechanisms) from relevant and wellcharacterized primary human or animal cells at the single cell level. The immune monitoring of Phase I to Phase III clinical trials aims to design, perform and interpret immunological data that enable industry to move vaccines, immunotherapeu8cs and drug candidates through the regulatory process (FDA, EMEA, others). High dimensionality flow cytometric analysis also allows for the defini8on of immunological profiles that are disease and stage specific, enabling elimina8on of many unsuitable drug, vaccine or therapy candidates prior or at the 8me of “inman” studies. This requires both a scien8fic exper8se in immunology, physiology and pathology as well as a clear understanding of technicali8es related to instruments, reagents and high dimensional data mining. As a service company for the pharmaceu8cal industry, ImmuneCarta regulatory process and standardized procedures are cri8cal to ensure data integrity and quality, especially when interpre8ng complex data sets to define disease stage, drug efficacy or toxicity. Overall, immune assays for diagnos8c, research or biomarker discovery may impact on all aspects and stages of immune system tes8ng, vaccine and immunotherapeu8c design and development as well as drug screening. They are enablers, permipng GO/ NOGO decisionmaking, thus saving both 8me and money, enhancing safety and providing surrogate markers of clinical efficacy and/or mechanis8c insights. Flow cytometry is based on fluorescence, fluidic and op8cal tools with the help of signal and image computer treatment. ImmuneCarta Services uses 3 and 4laser LSR II Becton Dickinson instruments. These instruments are high performance systems allowing simultaneous analysis of up to 18 colors using automated sampler in 96well plate format. High dimensional flow cytometry requires sensi8ve and precise methods with op8mal stability and reproducibility of the signal. For customized an8body panels, qualifica8on or valida8on steps are necessary to address specificity, precision, accuracy, lower and upper limits and range of detec8on, stability and reproducibility of the analysis. The precision and accuracy of flow cytometry experiments also depends on stable applica8on sepngs (CS&T beads) as well as internal and/or external quality control (QC) samples. Since 2004, ImmuneCarta has applied a broad array of innova8ve assays for the biopharmaceu8cal industry and government ins8tu8ons to characterize the immune profiling of adap8ve and innate immunity and the potency of immunerelated drugs or vaccines in exploratory and Phase I and Phase II clinical trials. ImmuneCarta Services recently formed a strategic alliance with Caprion Proteome Inc., the leading company in proteomics and biomarker discovery (www.caprion.com ) in order to integrate single cell mul8parametric flow cytometry analysis with soluble markers, serological measurements and other large datasets including genomics and proteomics. High throughput analysis of high dimensional flow cytometry data requires advanced soWware and methods. Data analysis performed at ImmuneCarta Services relies on flow data acquisi8on using DiVa soWware (BD Biosciences), and data analysis with FlowJo (Treestar Inc.), Excel (Windows), PESTLE/SPICE (NIH), Cluster (Open source, Stanford), Java TreeView (Open source), Prism (GraphPad SoWware) and/or other specialized soWware for sta8s8cal analysis and systems biology. All data are acquired and analyzed in compliance with 21 CFR Part11 to ensure quality and integrity of the raw data and its analysis. Predefined FlowJo templates are qualified or validated (GLP study) prior to being used throughout studies and require minimal ga8ng adjustments that are documented accordingly. Over the past 7 years, we have implemented assays using high throughput analy8cal methods with 10 to 18flow cytometry parameters on fresh and cryopreserved human peripheral blood samples. Overall, immune monitoring of clinical trials involve study planning, assay valida8on, specimen handling, assay execu8on, monitoring, repor8ng, and quality review performed as per applicable GLP regula8ons and GCLP guidelines governed by quality systems and standard opera8ng procedures. 0 10 20 30 40 50 60 0 10 20 30 40 50 60 V2 V2-redo Switched IgG Switched IgA Unswitched IgM MZ-like Immature B cell Naive IgM-IgD+ Naive IgM+IgD+ Naive IgM+IgD- Memory IgA+ Memory IgG+ Memory IgM+IgD+ Memory IgM+IgD- Memory IgM-IgD+ Plasma B cells Plasma IgA+ Plasma IgD+ Plasma IgG+ Plasma IgM+ % Parent Figure 6: Reproducibility of high dimensional flow cytometry. Phenotyping of T, B, and innate cells using 1112 color an8body panels was assessed independently on two blood samples from 20 subjects at Visit 2 (V2 and V2redo). Distribu8on of popula8ons and cell counts are highly correlated with R 2 > 0.99. Innate cell Counts 0 20 40 60 80 100 0 20 40 60 80 100 CD28- (CD8) CD4 (CD3) CD8 (CD3) PD-1 (CD4) PD-1 (CD8) CD57 (CD4) CD57 (CD8) Naive (CD8) CM (CD8) EM (CD8) TEM1 (CD8) TEM2 (CD8) ILD (CD8) LD (CD8) Naive (CD4) CM (CD4) EM (CD4) TEM1 (CD4) TEM2 (CD4) ILD (CD4) LD (CD4) Mem CD45RA- (CD8) Mem CD45RA- (CD4) V2 V2-Redo % Parent T cell Subsets B cell Subsets 0 400 800 1200 1600 2000 0 400 800 1200 1600 2000 V2 V2-Redo CD3 CD4 CD8 DP DN B cells HLA-DR+ B cells HLA-DR- Monocytes pDC mDC1 mDC2 All NK NK 56-16+ NK 56bright16- NK 56low16- NK 56low16+ NK 56bright16low Cell counts (cells/µL) R 2 = 0.9956 R 2 = 0.9955 R 2 = 0.9954 Figure 7: Reproducibility and %CV from internal QC samples (frozen PBMC, L747) on 11color T, B, and Innate cell phenotype panels. Results from 32 experiments are shown over one year (July 2010 to September 2011). The first graph represents the enumera8on of T cell popula8ons (CD3, CD4, and CD8). The second graph represents the enumera8on of B cells, the monocytes, and subpopula8ons of dendri8c cells. The third graph represents the enumera8on of natural killer (NK) subpopula8ons. Coefficient of varia8on are indicated in blue. B, mono, and DC L747 B cells HLA-DR+ B cells HLA-DR- Mono PDC mDC1 mDC2 0 10 20 30 40 50 500 1000 1500 B, Mono, and DC Populations Count / uL T Cells L747 CD3 CD4 CD8 DP DN 0 100 200 300 2000 4000 6000 8000 10000 T Cells Populations Count / uL NK L747 ALL NK NK 56-16+ NK 56bright16- NK 56low16- NK 56low16+ NK 56bright16low 0 50 100 150 200 300 400 500 600 700 800 NK Populations Count / uL 18 18 19 39 38 36 66 44 29 24 31 18 36 23 38 19 23 Subj1 Subj1 Subj2 Flow Cytometry Singlecell analysis (% funcNonal response) StaNsNcal analysis and idenNficaNon of group differences in funcNonal responses Sample Figure 1: Overview of ImmuneCarta flow cytometry and analyNcal processes (example of immune profiling of mucosal CD4 + T cells by intracellular cytokine detecNon) Plamorm Field of applicaNon Main therapeuNc area Assays Targeted Sample or Cell PopulaNon Markers Customizable Flow Cytometry Cytokine bead array ELISA/ELISPOT Chemiluminescence Molecular biology Drug development Biomarkers Biologics/Biosimilars Immune Monitoring Vaccine Epitope Mapping Immunotoxicology Infec8ous diseases Allergy Oncology Cardiology Autoimmunity Transplanta8on Immune Senescence Chronic Inflamma8on Cell EnumeraNon HematopoieNc stem cells Circula8ng CD34+ CD34, CD45, others ✓ • • • • • • Immune Cells T, B and Innate cells CD3, CD4, CD8, CD16/56, CD19, CD14, CD11c, CD45, CD123, others ✓ • • • • • • • • • • • • • • Tumor Cells Circula8ng Tumor Cells DNA, Cytokera8n, CD45 • • • • Immune Phenotyping Cell Lineage T, B, NK and NKT cells, Dendri8c cells, Basophils, Monocytes CD3, CD4, CD8/CD19, HLADR/CD16, CD56, Lin/Vα24, αGalCerCD1d tetramer, CD3/CD11c, CD123, Lin/CD123, Lin/CD14 ✓ • • • • • • • • • • • • • • • Cell Subsets DifferenNaNon T, B, NK and NKT cells, Dendri8c cells, Basophils, Monocytes CD45RA/RO, CD27, CCR7, CD28, CD62L/CD27, IgD/M, CD20, CD38,CD10,IgA/G/E/CD94/NKG2A, CD7, KIR2DL/DS/CD11c,/CD123, BDCA2/3/4, /FcγRs, IgE, CCR3/CD16, CD64, FcγRs ✓ • • • • • • • • • • • • • • • AnNgenic specificity Tetramerposi8ve an8genspecific CD8+/CD4+ T cells An8genspecific, HLArestricted TCR (using Tetramer/Pentamer/Dexamer) ✓ • • • • • • • • • • AcNvaNon/InhibiNon/ExhausNon/ Immune Senescence T, B and Innate cells HLADR, CD38, ICOS, OX40, 41BB, Ki67, CD40, CD95, PD1, CD57, CD83, CD80, CD86, CD160, Lag3, 2B4, CTLA4, Tim3 ✓ • • • • • • • • • • • • • • • Homing Receptors/Coreceptors T cells, B and Innate cells CCR4, CCR5, CCR6, CCR7, CCR9, CXCR3, α4β7 integrins, others ✓ • • • • • • • • • • • • • TranscripNonal Factors Treg, Th1, Th2, Th17, T~ FoxP3, Tbet, GATA3, RORγt, BCL6 ✓ • • • • • • • • • • • • FuncNonal Profiling Intracellular Cytokine/Chemokine Staining T, B, NK, NKT, Dendri8c cells, Monocytes IL2, TNFα, IFNγ, IL4, IL17, IL22, IL10, TGFβ, IL9, IL21, Mip1β, others ✓ • • • • • • • • • • • • • • • • Apoptosis/Necrosis T, B and Innate cells Annexin, caspase 3, CD95, PARP, TUNEL, Live/Dead, 7AAD ✓ • • • • • • • • • • • • • • • PhosphorylaNon (PhosFlow) T, B and Innate Cells, Tumor cells Akt, Btk, Elk, EGFR, Lck, LAT, Zap70, Syk, MEK1, NFκB, PKC, PLCγ1, PLC γ2, p38MAPK, ERKk1/2 Src, STAT1 to STAT6 ✓ • • • • • • • • • • • • • • • • Lymphocyte acNvity (ImmuKnow®) Total CD4 cells ATP • • • • • • • • • • ProliferaNve response/cell cycling T cells and subsets CFSE, Ki67, BrDU ✓ • • • • • • • • • • • • • • • • ELISPOT CD8+/CD4+ T cells, B cells IFNγ and/or IL2, TNFα, IgG, IgM ✓ • • • • • • • • • Cytotoxicity/DegranulaNon T, NK, NKT cells and subsets, Basophils CD107a, Granzyme, Perforin, CD63, others ✓ • • • • • • • • • • • • • • • Serology & Soluble Markers AnNbody Titers Serum, plasma Tetanus, Diphtheria, Hepa88s B, Cholera toxin B, CMV, others • • • • • • • • • • • • Cytokines/Chemokines/Adhesion Molecules/Growth Factors Serum, plasma, cell culture supernatant Interleukins, sICAM1, sICAM3, sVCAM1, sPECAM1, sESelec8n, sP Selec8n, GCSF, IL8, MCP1, MIG, MIP1α, MIP1β, others ✓ • • • • • • • • • • • • • • • • • Gene Expression & DNA Analysis mRNA expression (realNme PCR) Cells, 8ssue Specific mRNA quan8fica8on ✓ • • • • • • • • • • • • • T cell receptor excision circles (TREC) Cells, 8ssue sjTREC • • • • • • • • Final data and report exported in Study Server Figure 12: Boolean gaNng analysis of 5 markers in mucosal CD4+ T cells using SPICE analysis. CorrelaNon of specific funcNonal signatures with immune acNvaNon (Ki67+). Combina8on of 3 among 5 markers (IFNγ, IL2, IL17, MIP1β, and TNFα) are displayed as dots and their means, as grey histograms. Sta8s8cally significant differences between HIV viral controllers and noncontrollers are shown by # (WilcoxonRank) and + (Student’s ttest). Figure 10: Example of a simple hierarchical gaNng for T, B and NK cell enumeraNon. Lymphocytes and BD TruCount Beads are gated based on SSC/CD45 expression. CD3posi8ve and CD3nega8ve popula8ons are defined. From CD3 gate, natural killer (NK) and B cells are discriminated based on CD16/CD56+ (NK) and CD19+ (B cells). From CD3+ gate, CD4+ and CD8+ T cells are defined as well as double nega8ve and double posi8ve T cells. <FITC-A>: CD3 70.8 29.2 <APC-Cy7-A>: CD8 <PE-Cy7-A>: CD4 <APC-A>: CD19 SSC-A <APC-A>: CD19 <PE-A>: CD16/CD56 <PerCP-Cy5-5-A>: CD45 SSC-A Beads Lymph CD3+ NK B Cells CD4 DP CD8 DN CD3- Figure 11: Example of Boolean gaNng of 6 funcNonal markers expressed in CD4+, CD8+ or memory subsets and effector T cells by ICS aoer anNgen sNmulaNon of cryopreserved PBMCs. Posi8ve responses for each of the markers are defined from the template analysis (IFNγ, CD107a, TNFα, IL2, IL4, and IL17). Boolean ga8ng is generated by FlowJo for all possible combina8ons (IFNγ+/ and CD107a +/ and TNFα+/, and IL2+/ and IL4+/ and IL17+/ ), e.g. leading to 2 n different gates. In this example, n = 6, genera8ng 64 gates for 8 popula8ons of interest per sample. CD107a TNFa IL-2 IFNg IL-17 IL-4 CD8+ T cells CD4+ T cells 0.13 0.354 0.157 0.0554 0.0294 1.68e-3 0.672 0.734 0.623 0.0614 0.0154 3.07e-3 Titer DistribuNons of Vaccinated Subjects Cytometric Vaccine Response Examples Plasmacyte Counts before (V2) and after (V3) immunization (left) All Plasmacytes (right) IgG+ Plasmacytes High Dimensionality Analysis of Hyporesponsiveness to Protein Subunit Vaccines in the Elderly -- Introduction to Study MK0000-131 Carayannopoulos LN 1, , Railkar RA 1 , Favre D 2 , Landry C 2 , Schaeffer AK 1 , Wiener MC 1 , Chastain M 1 , Loboda A 1 , Lukac S 1 , Duguay D 3 , Audet D 3 , St-Maurice F 3 , Kaslow DC 1 , Beals CR 1 , Sekaly RP 2,4 1 Merck Research Laboratories, USA | 2 National Immune Monitoring Laboratory – Genome Quebec, Canada | 3 Anapharm-Pharmanet Quebec, Canada | 4 VGTI-Florida 6 wk24 wk28 Figure 15: High dimensionality analysis of vaccine hyporesponse in healthy elderly subjects (NCT01119703 ) Titer distribu8on of vaccine responses to Tetanus, Diphtheria and Hepa88s B vaccines in elderly subjects (leW) and example of increase frequency of highly characterized B cell popula8ons one week (V3) aWer vaccine administra8on (V2) (middle). “Plasma B cells” are characterized as singlet/lymphocyte/CD19+/HLADR+/CD3/CD27+/CD10/CD20 cells. “Plasma IgG+ B cells” are plasma B cells expressing IgG on the cell surface. An example of heatmap represen8ng unsupervised clustering of high dimensional flow cytometric Boolean datasets of T, B and innate immune phenotyping (yaxis) is shown on the same cohort (N=120 subjects, xaxis) (right). Such unsupervised clustering of large flow cytometric datasets allows further analysis of genomic datasets or other large datasets by quan8ta8ve regression analysis related to individual immune profiling, as described in Loke, Favre et al., Blood 2010.
