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“ Measuring Antigen Specific T-cells using Surface and Intracellular Staining Polychromatic Flow Cytometry ” 3 rd Annual CFAR Flow Cytometry Workshop 6-10 May, 2013 Janet Staats Flow Cytometry Core Facility Center for AIDS Research Duke University Medical Center E-mail: jotti@duke.edu.

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  1. “Measuring Antigen Specific T-cells using Surface and Intracellular Staining Polychromatic Flow Cytometry”3rd Annual CFAR Flow Cytometry Workshop6-10 May, 2013Janet StaatsFlow Cytometry Core FacilityCenter for AIDS ResearchDuke University Medical CenterE-mail: jotti@duke.edu

  2. Part 1 of 3 Overview of PFC Assay Duke University Medical Center

  3. Memory CD4 T Cell Response to Ag IL-2 IL-4 Rantes Apoptosis IFNg TNFa Proliferation/ Death APC-T cell interactions Cytokine/Chemokine expression From H. Maecker Duke University Medical Center

  4. Ag APC CD4+ T cell Whole protein MHC II CD4 cytokines MHC I peptide T, B, or APC CD8+ CTL Optimal peptide CD8 cytokines MHC I From H. Maecker Duke University Medical Center

  5. Response to CMV pp65 Peptide Mix pp65 protein peptide mix A2 peptide CMV lysate 0.27% 0.27% 0.04% 7.41% CD4 0.19% 2.03% 1.14% 0.87% CD8 From H. Maecker Duke University Medical Center

  6. Peptide Mixes 15 a.a. 11 a.a. CMV pp65: pool of 138 peptides HIV p55: pool of 120 peptides Duke University Medical Center

  7. Basic Subset Markers: • CD3 (T-cells) • CD4 (T-Helper Subset) • CD8 (T-Suppressor Subset) • Exclusion Markers: • CD14 (Monocytes) • CD19 (B-cells) • vAmine (Dead cell marker) • Maturational Markers: • CD45RO • CD27 • CD57 • Functional Markers: • CD107 • IFN- • TNF • IL-2 Sampson Clinical Trial:11-Color Maturation/Function Panel Duke University Medical Center

  8. Overview of 11-Color Assay 6 h M+ 7+g+M+ g+M+ Thursday - Friday Monday Tuesday Wednesday 4. Lyse/Fix 8. Analysis 2. Stimulate 5. Permeabilize 1. Thaw 3. Surface Stain 6. IC Stain 7. Acquisition Brefeldin Monensin Rest 6 hrs Wash Wash Wash Wash CD107 cytokine lymphocyte erythrocyte CD8+ CM Response Costim SEB CMVpp65 Amine CD14 CD3 CD4 CD8 CD45RO CD27 CD57 IFN IL2 TNF CD107 PE-Cy5 Duke University Medical Center

  9. Gating Strategy for 11-Color Maturation/Function Panel: 1 of 3 57.8 88.3 <G710-A>: CD4 CY55PE 0.79 FSC-H SSC-A <Violet H-A>: vAmine CD14PB CD19 PB 99.3 41.4 36.3 FSC-W <V705-A>: CD8 Q705 FSC-A <Violet G-A>: CD3 Amcyan Basic Gates: - 3 total Ungated Singlets CD3+ Exclusion- SSC-A FSC-H Exclusion (Violet H) FSC-W CD3 AmCyan FSC-A Scatter CD4+CD8- CD4+CD8+ CD4 PerCP-Cy5.5 CD8+CD4- CD8 Alexa700 Duke University Medical Center

  10. Gating Strategy for Sampson 11-Color Maturation/Function Panel: 2 of 3 54.1 28.6 56.4 43 <G660-A>: CD27 CY5PE <G660-A>: CD27 CY5PE 2.58 8.46 0.33 6.55 62.5 22 22.9 3.98 <G660-A>: CD27 CY5PE <V545-A>: CD57 Q545 1.07 13.2 5.67 0.12 <V545-A>: CD57 Q545 <V545-A>: CD57 Q545 3.98 11.7 21.5 51.7 55.9 24.2 42.9 56.9 Maturational Gates: - 5 per basic subset CD4+CD8- CD4+CD8+ N CM TE E CD8+CD4- CD27 APC-Alexa750 N CM TE E CD57 FITC N CM TE E CD57 FITC CD27 APC-Alexa750 EM CD57 FITC CD27 APC-Alexa750 EM CD45RO ECD EM CD45RO ECD CD45RO ECD Central Memory EffectorMemory Terminal Effector Naive Effector Central Memory EffectorMemory Terminal Effector Naive Effector Central Memory EffectorMemory Terminal Effector Naive Effector Duke University Medical Center

  11. Gating Strategy for Sampson 11-Color Maturation/Function Panel: 3 of 3 4.19 1.14 2.59 <R710-A>: CD107a AX680 0.31 Functional & Boolean Gates: Polyfunctional (1: ++++) - 4 functional gates per maturational subset - 16 boolean gates per maturational subset Polyfunctional (4: +++) CM: CD8+CD4- CD107 Bifunctional (6: ++) IFN- Boolean Gates Key: 7 = CD107 g = IFN- 2 = IL-2 T = TNF- IL-2 Monofunctional (4: +) TNF- Nonfunctional (1: ----) Duke University Medical Center

  12. Visualizing PFC Data:CMVpp65-specific Polyfunctional Response in CD8+ Central Memory Subset Increases Post-Vaccination Simplified Presentation of Incredibly Complex Evaluations Dr. Mario Roederer Immunotechnology Section VRC / NIAID / NIH Betts, (2006) Blood 107, 4781-4789. Makedonas, (2006) Springer Semin. Immunopathol. 28, 209-219. Duke University Medical Center

  13. Part 2 of 3 PFC Challenges Duke University Medical Center

  14. Challenges… Instrument - optical configuration, optimization, standardization, and calibration Reagent - optimization and standardization Sample processing Staining protocols Data Analysis - compensation & gating Operators Volume of data (death-by-excel!) Duke University Medical Center

  15. Consistency across batchesCD38 vs HLA-DR Staining on Ctrl 5L 28Feb08 5L CD8+ 04Marb08 5L CD8+ 06Mar08 5L CD8+ 11Mar08 5L CD8+ Duke University Medical Center

  16. uncompensated Difficulties in doing Automated Analysis related to Instrument Settings PMT settings compensation FSC/SSC settings optimal optimal low high CD3 CD69 SSC SSC CD4 IFNg CD4 FSC Duke University Medical Center

  17. Challenges… Instrument - optical configuration, optimization, standardization, and calibration Reagent - optimization and standardization Sample processing Staining protocols Data Analysis - compensation & gating Operators Volume of data (death-by-excel!) Duke University Medical Center

  18. <Blue A-A> <Blue B-A> <Violet H-A> Red A-A <Red C-A> <Red B-A> <Green E-A> <Green C-A> <Green B-A> <Green D-A> <Green A-A> Optimization using Spillover Assessments: Using Titration Files to Assess Spreading Error Blue Laser • CD3AC (5ug/ml) Spillover assessment: • After compensation CD3AC showed spilllover into Blue-B detector (FITC channel) Violet Laser Red Laser Green Laser Violet G- CD3 AmCyan • Ottinger, et. al., Poster #28, 23rd Annual Clinical Cytometry Meeting (2008) • Mahnke, et. al. Clin Lab Med. 2007 September; 27(3): 469-v. • Lamoreaux, et. al., Nature Protocols 1, 1507-1516 (2006) on line 9 November 2006 Duke University Medical Center

  19. 0.13 9.8e-4 20.5 66.3 4.58 0.047 Spillover Assessments:CD3 AmCyan (5µg/mL) Spillover into CD27 (0.32µg/mL) & CD57 FITC (1.8µg/mL) • Spillover from CD3AC interferes with detection of dim CD27 pos cells • Spillover from CD3AC does not interfere with detection of CD57 • Spillover is acceptable if it does not interfere with proper classification of events • mAb concentration may be varied to reduce spillover as long as frequency is unaffected Unstained Unstained SSC SSC CD27 FITC CD57 FITC CD3 AmCyan CD3 AmCyan Blue B Blue B Duke University Medical Center

  20. Is this positive??? CMV pp65 stimulated sample Maecker, et. al. Duke University Medical Center

  21. Tandems Degrade! • Ice • Dark • Fix • Controls • 6 hours Maecker, et. al. Duke University Medical Center

  22. Challenges… Instrument - optical configuration, optimization, standardization, and calibration Reagent - optimization and standardization Sample processing Staining protocols Data Analysis - compensation & gating Volume of data (death-by-excel!) Duke University Medical Center

  23. 9-Color Activation/Maturation Using Cryo-preserved PBMC Duke University Medical Center

  24. 26Feb08 5L CD8+ Lot 05262 28Feb08 5L CD8+ Lot 05262 04Marb08 5L CD8+ Lot 05262 06Mar08 5L CD8+ Lot 05262 11Mar08 5L CD8+ Lot 05262 Batch Processing ErrorCD38 vs HLA-DR Staining on Ctrl 5L Duke University Medical Center

  25. Challenges… Instrument - optical configuration, optimization, standardization, and calibration Reagent - optimization and standardization Sample processing Staining protocols Data Analysis - compensation & gating Operator Volume of data (death-by-excel!) Duke University Medical Center

  26. How would you gate? Markers: CD3 CD4 CD8 IL-2+IFNg (FSC) (SSC) Duke University Medical Center

  27. Reproducible analysis allows us to measure an expansion of CD4+ CM cells post vaccination with some degree of confidence Pre-Vaccination Post-Vaccination 8% 17% 17% 33% 2% 2% 25% 48% 27% 21% N CM EM TE E Duke University Medical Center

  28. ICS Standardization Conclusions • ICS assays can be performed by multiple laboratories using a common protocol with good inter-laboratory precision (<20% C.V.), that improves as the frequency of responding cells increases. • Gating is a significant source of variability, and can be reduced by centralized analysis and/or use of standardized gating. • Cryopreserved PBMC may yield slightly more consistent results than shipped whole blood. • Use of pre-aliquoted lyophilized reagents for stimulation and staining can reduce variability. BMC Immunology 2005, 6:13 http://www.biomedcentral.com/1471-2172/6/13 Duke University Medical Center

  29. CIC ICS Gating Panel 110 labs participated and there were 110 different approaches to gating

  30. A Before Backgate IFNg Backgate After Backgate Exclusion CD3 AmCyan B CD4 Gated CD8 Gated 5.23 0.27 Before Backgate CD8 APC-Cy7 0.38 5.74 CD4 PerCP-Cy5.5 After Backgate IFNg PE-Cy7 BACKGATING: purity & recovery Duke University Medical Center

  31. Unstim CEF CMV pp65 0.02% 0.01% 0.16% 0.03% 0.02% 0.17% IL2+IFN PE 0.02% 0.03% 0.21% Gating bias in proficiency panel results CD4 FITC Duke University Medical Center

  32. We NEED better analysis tools!!!Manual (Expert) vs. Automated Analysis of 4-Color ICS Data File (CMVpp65) Expert Gating Manual Cluster Gating Automated 0.18% 0.21% CD4 FITC IFN- + IL-2 PE 1.65% 1.9% CD8 PerCP-Cy5.5 Duke University Medical Center

  33. Would you know a positive if you saw one? Roederer. Cytometry Part A, 73A:384-385 (2008) Horton et. al. J Immuno Methods, 323:39-54 (2007) Maecker et. al. Cytometry Part A, 69A:1037-1042 (2006) Comin-Anduix et. al. Clin Cancer Res, 12(1):107-116 (2006) 2xSD? RCV? Outside Normal Range >0.05%? Duke University Medical Center

  34. Challenges… Instrument - optical configuration, optimization, standardization, and calibration Reagent - optimization and standardization Sample processing Staining protocols Data Analysis - compensation & gating Operator Volume of data (death-by-excel!) Duke University Medical Center

  35. Assay Complexity Duke University Medical Center

  36. Endpoints for 11-Color Maturation/Function PanelDEATH BY EXCEL …….. Basic (3) Maturation (5) Function Boolean (16) CD4+ CD8- CD4+ CD8+ CD4- CD8+ Naïve Central Memory Effector Memory Effector Terminal Effector CD107 IFN- IL-2 TNF- 240/stim Basic (3) Maturation (5) Boolean (16) X X = X 3 Stimulations/Sample (CoStim, SEB, CMVpp65) = 720 Endpoints/Sample 720 Endpoints/Sample x 200 Samples (192 Participants + 8 Controls) = 144,000 Endpoints/Trial Note 1: Frequency of parent only, reporting units of #cells/µL doubles the total EP/trial Duke University Medical Center

  37. Study ID Method Assay Name Batch # Operator Sample ID Visit ID Accession # % Viable (Flow) % Viable (Guava) Recovery CD4 count CD8 count Gate Name (Parameter Names) Tube Name File Name Error Code (1-11) • Checking: • X1 - for electronic data • X3 - for manual entry • Requires STRONG statistical support: • Quickly exceeds limits of excel • Format data for statistical analysis • FJ: column (gates) vs row (file) • CSV: column (identifiers) vs row (single value) • Check data • Manual check: 8sec/value x 143280 = 49 days!!! Data Annotation - for all 143,280 data points! Duke University Medical Center

  38. Part 3 of 3 Why does this matter?? Why are you here??? Duke University Medical Center

  39. Why is Reproducibility Important? CFSE Standardization Results (13 EXPERT IM Labs): • Very high inter-laboratory variability. • High background in some laboratories. • Responses to Gag and Nef peptide pools were detected in HIV negative (control) donors! Example Gag stimulation HIV negative donor Example CMVpp65 stimulation CMV positive donor % CD8+ CFSE low Laboratory Duke University Medical Center

  40. History of Flow-based Proficiency/Standardization Efforts Duke University Medical Center

  41. ICS Proficiency Testing Results: March 2007 The number of measurements outside the optimal range established by the GS was determined for each laboratory. Each laboratory performed a total of 54 measurements (27 for CD4+ cells and 27 for CD8+ cells). The red line represents 50% (=27) of the total measurements. Laboratories above this line had over 50% of their measurements outside the optimal range. The green line represents 20% of total measurements. The laboratories below this line had over 80% of their measurements within the optimal range. Duke University Medical Center

  42. CD4-CD8+ CD4+CD8- DAIDS ICS Proficiency:Round 6, 26Jun09 (CMVpp65) Rep #1 Rep #2 IFNg + IL-2 PE Rep #3 CD3 APC-Cy7 Duke University Medical Center

  43. Acknowledgements Patricia D’Souza (DAIDS) CFSE Standardization: Claire Laundry (NIML) Duke CFAR Kent Weinhold Jennifer Enzor Twan Weaver Jianling Shi Cliburn Chan CHAVI Duke DTRI Scottie Sparks (Roche) Duke Tisch Brain Tumor Center Gary Archer Duane Mitchell John Sampson EQAPOL VRC Steve Perfetto Laurie Lamoureaux Mario Roederer CVC Sylvia Janetski Duke University Medical Center

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