A high-parameter spectral cytometry protocol for immune subset and functional characterization of cryopreserved human blood with 49 biomarkers

Summary

Comprehensive immune profiling of human blood is a critical approach for evaluating immune responses following therapeutic intervention in clinical trials. Here, we present a protocol to assess leukocyte lineages, activation status, and selected immune checkpoint expression in cryopreserved buffy coat using a high-dimensional, 49-color spectral flow cytometry antibody panel. We provide instructions for thawing, washing, and staining circulating immune cells, followed by guidance on data acquisition. This protocol is suitable for studying cancer immunology and other indications requiring deep immunophenotyping.

Graphical abstract

Highlights

• •Multiparametric spectral flow cytometry panel for circulating human leukocyte
• •Protocol for 49-biomarker immunophenotyping
• •Identification of myeloid and lymphoid lineages with functional status
• •Antibody panel applicable to cryopreserved buffy coat samples

Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.

Comprehensive immune profiling of human blood is a critical approach for evaluating immune responses following therapeutic intervention in clinical trials. Here, we present a protocol to assess leukocyte lineages, activation status, and selected immune checkpoint expression in cryopreserved buffy coat using a high-dimensional, 49-color spectral flow cytometry antibody panel. We provide instructions for thawing, washing, and staining circulating immune cells, followed by guidance on data acquisition. This protocol is suitable for studying cancer immunology and other indications requiring deep immunophenotyping.

Before you begin

This protocol outlines the immunophenotyping of cryopreserved human buffy coat available for human clinical trial correlative studies using high-parameter spectral flow cytometry. The proposed panel is compatible to identify listed cell populations from freshly isolated PBMCs and other leukocyte-rich single cell suspensions, while being broadly applicable to tissue samples for immunophenotyping in healthy and pathophysiologic contexts.

Panel design rules were followed.¹ We used the Cytek Full Spectrum Viewer (Cytek Biosciences) (https://spectrum.cytekbio.com/) to select fluorochromes based on their emission spectra to minimize spectral overlap on co-expressed marker-conjugate pairs. Antigens were ranked by their expression levels and staining indices were generated via titrations acquired on a Cytek Aurora 5L. Generally, fluorochromes with higher stain indices were paired with infrequently expressed antigens, and highly expressed antigens were assigned to fluorochromes with low stain indices to reduce spreading error. Considerations related to conjugate availability and validated clones in the literature were made.

For optimal results based, titrating cell viability reagent and antibodies, especially for low-expression antigens with control specimens prior to protocol initiation improves outcomes and data interpretation. Optimization of all protocol steps is recommended on-site to obtain consistent results.

Preparation of all buffers and antibody cocktails prior to thawing cells, and same-day staining is preferable for this protocol due to the use of tandem dyes that can degrade over time without tandem stabilizer, especially in highly multiplexed staining. High-quality single-stained controls are essential for successful spectral unmixing. For dim fluorochromes or low-expression antigens, beads may outperform cells as single-color controls by providing higher signal resolution. In this protocol, a mix of cells and bead-based single stains were used to achieve optimal separation of key protein biomarkers.

Efficient workflow relies on pre-calculated volumes and freshly prepared buffers. The proposed staining process is divided into four sequential steps: Fc block/viability dye, surface staining cycle 1 (C1), surface staining cycle 2 (C2), and intracellular (IC) staining.

Antibodies binding surface proteins are split into two cycles to mitigate issues arising from low buffer volume in large, multiplexed cocktails. Separating cellular antigen-targeted antibodies into two groups ensures the buffer volume reaches approximately 50% of the total, preserving both cell viability and staining quality. To minimize steric interference from highly expressed antigens, antibodies targeting dim biomarkers are included in the C1 cycle.

Innovation

We generated an extended panel to identify leukocyte subsets and interrogate their activation status, as well as select immune checkpoint expression (Tables 1 and 2), by adapting the OMIP-69² and OMIP-102³ protocols. Herein, we include granulocyte markers and intracellular markers for major transcription factors, cytokine production, and cell proliferation assessment. The overall workflow is shown in Figure 1.

Table 1.

Summary of all lineage subsets assessed with the 49-color panel

Cell type	Lineage biomarkers	Major Role	Function in TME
Initial Gating	Exclusion/Inclusion: FSC/SSC, FSC-H/SSC-H single cells, Viability dye, CD45+ gate	Quality Control & Lineage Definition	Ensures analysis is performed only on viable, single hematopoietic cells.
T cells	CD3+	Pan-T Cell Lineage Biomarker	Defines the total pool of T cells present in the TME.
CD8+	CD3+, CD8+	Cytotoxicity/Anti-tumor Effector	Kills infected or malignant cells, primary anti-tumor effector.
CD4+	CD3+, CD4+	T-helper & Immune Coordination	Coordinates immune response (T-helper function), secretes cytokines.
CD4+ Th1	CD3+, CD4+, CCR4-, CXCR3+	Drive anti-tumor immunity	Produce interferon gamma and IL-12
CD4+ Th2	CD3+, CD4+. CCR4+, CXCR3-	Release Cytokines to Decrease Inflammation	Produce IL-4
Transitional CD4 Th	CD3+, CD4+, CCR4+, CXCR3+	Anti-Tumor Immune Response	Enhances cytotoxic T cell responses and aids in the activation of other immune cells
γδ T cells	CD3+, TCRγδ+	Innate-like T cell activity	Innate-like recognition; rapid, non-MHC-restricted immune response.
Tregs	CD3+, CD25+, FoxP3+	Immune Suppression & Tolerance	Suppresses effector T cells (CD8/CD4) and dampens anti-tumor immunity.
Monocytes/Dendritic Cells/B cells	HLA-DR+	Antigen Presentation	Essential for presenting tumor antigens to T cells (APC function).
Classical Monocytes	HLA-DR+, CD14+, CD16-	Phagocytosis/Precursor	Progenitor cells to macrophages and dendritic cells. Can be used as a biomarker.
Intermediate Monocytes	HLA-DR+, CD14+, CD16+	Inflammatory Monitoring	Transitionary state from classical monocytes and non-classical monocytes. Can be used as a biomarker.
Non-classical Monocytes	HLA-DR+, CD14-, CD16+	Vessel Surveillance	Patrolling monocytes that remain in the blood and remove damaged cells and debris from the vasculature.
Plasmatoid Dendritic Cells (pDCs)	HLA-DR+, CD123+	Anti-Viral Signaling	Specialized for mass production of Type I Interferons, a key anti-viral/anti-tumor signal.
Classical Dendritic Cells 1 (cDC1)	HLA-DR+, CD141+	Cross-Presentation	Cross-presentation of tumor antigens, critical for activating CD8+ T cells.
Classical Dendritic Cells 2 (cDC2)	HLA-DR+, CD1c+	T-Helper Activation	Specialized in Type 2 immunity and activating CD4+ T cells
B Cells	CD3-, CD19+, CD20+	Adaptive Immunity & TLS Formation	Antigen presentation and can form tertiary lymphoid structures (TLS) linked to better prognosis.
Plasmablasts	CD3-, CD19+, CD20-	Humoral Immunity Effector	Antibody secretion, a key mechanism of humoral immunity in the TME.
NK Cells	CD3-, CD56+, CD16−/+	Innate Cytotoxicity
CD56dim, CD16+ NK Cells	CD56dim, CD16+	Cytotoxicity/Anti-tumor	NKp46+ and - cells are cytotoxic killers responsible for direct tumor cell destruction
CD56bright, CD16+ NK Cells	CD56bright, CD16+	Cytokine Producers	Primarily immune-regulatory and cytokine-producing, orchestrating the adaptive immune response by recruiting other cells
Granulocytes	CD15+	Innate Immune Response
Basophils	CD123+	Inflammation Mediator	Release histamine and inflammatory mediators; involved in allergic and inflammatory responses.
Eosinophils	CD49d+, CD15+	Immune Modulation/Remodeling	Can contribute to both tumor promotion and inhibition, often involved in tissue remodeling.
Neutrophils	CD45+, CD15+	Innate Immunity	Major innate components, often associated with tumor-promoting inflammation (TANs).

Table 2.

Summary of functional markers used to identify activation status and checkpoint molecule expression

Biomarker	Rationale in TME/Immune status
Proliferation & Cell Cycle
Ki-67	Nuclear proliferation biomarker used to identify cells actively engaged in the cell cycle
Early Activation & Residence
CD69	Early activation biomarker rapidly expressed on T cells and NK cells upon TCR or cytokine stimulation
Effector Function & Cytotoxicity
Granzyme B	Key effector molecule released by cytotoxic T lymphocytes, NK cells, and B cells; directly facilitates target cell killing by triggering apoptosis
KLRG1	Biomarker of terminal differentiation in T cells; its presence is associated with highly differentiated, short-lived effector T cells
T Cell Exhaustion & Inhibition
PD-1	Primary immune checkpoint receptor expressed on activated and exhausted T cells; binding to its ligand (PD-L1) delivers an inhibitory signal, leading to T cell dysfunction
CTLA-4	A high-affinity inhibitory receptor expressed on activated T cells and Tregs; provides a crucial brake on T cell activation and immune response
LAG-3	Inhibitory receptor expressed on exhausted T cells, Tregs, and NK cells; it binds to MHC Class II molecules, contributing to T cell dysfunction and dampening anti-tumor immunity
TIM-3	Exhaustion biomarker highly expressed on dysfunctional/exhausted T cells; it delivers an inhibitory signal, limiting T cell effector function
TIGIT	Inhibitory receptor on T cells and NK cells; suppresses T cell activation and promotes an exhausted phenotype
TOX	key transcription factor defining exhaustion in CD8+ T cells; its high expression is critical for establishing the state of exhausted T cells
CD39	Contributes to an inhibitory microenvironment
Co-stimulation & Regulation
ICOS	Provides a pro-survival and costimulatory signal to T cells, important for sustained T cell responses but also associated with the development of exhausted phenotypes
CD86	Co-stimulatory ligand expressed on antigen-presenting cells; binding to CD28 or CTLA-4 is essential for T cell priming and regulation.
Differentiation & Memory Subsets
CD45RA	Highly expressed on Naïve T cells that have not yet encountered antigen
CD45RO	Highly expressed on Memory T cells that have previously encountered antigen
CD197/CCR7	Chemokine receptor used, in combination with CD45RO, to distinguish central memory T cells from effector memory T cells
Plasma Cell and Activated Biomarker
CD38	Highly expressed on plasma cells and can also indicate recent or high activation levels on T cells

Figure 1.

Overall workflow of 49-color spectral flow cytometry panel from blood collection to data visualization

Blood collection using sodium-heparin tubes prevents blood coagulation prior to buffy coat isolation. Cryopreservation with 90% FBS/10% DMSO ensures short to long-term storage prior to cell staining. This protocol focuses on multiparametric cell staining. It provides general insights for data acquisition, analysis and visualization.

Institutional permissions

All human samples used in this protocol were obtained and utilized in accordance with institutional guidelines and approved by the appropriate ethics committee with informed consent from human subjects. All procedures involving human material were conducted in compliance with relevant institutional and national regulations. Researchers intending to use this protocol should ensure to obtain approval from relevant institutional review boards or ethics committees and comply with all applicable guidelines and regulations.

Key resources table

REAGENT or RESOURCE	SOURCE	IDENTIFIER
Antibodies
Spark UV 387-CD45RA (clone HI100). Working dilution (1:80)	BioLegend	Cat#304180; RRID: AB_2922538
BUV395-CD40 (clone 5C3). Working dilution (1:40)	BD Biosciences	Cat#565202; RRID: AB_2739110
BUV496-CD3 (clone UCHT1). Working dilution (1:40)	BD Biosciences	Cat#612940; RRID: AB_2870222
BUV563-CD56 (clone NCAM16.2). Working dilution (1:320)	BD Biosciences	Cat#612929; RRID: AB_2916880
BUV615-CD141 (clone 1A4). Working dilution (1:640)	BD Biosciences	Cat#752356; RRID: AB_2875873
BUV661-CD303 (clone V24-785). Working dilution (1:80)	BD Biosciences	Cat#749920; RRID: AB_2874159
BUV737-CD86 (clone FUN-1). Working dilution (1:160)	BD Biosciences	Cat#612785
BUV805-CD45 (clone HI30). Working dilution (1:40)	BD Biosciences	Cat#612892; RRID: AB_2870179
BV421-IFN gamma (clone B27). Working dilution (1:10)	BioLegend	Cat#506538; RRID: AB_2801098
Super Bright 436-LAG-3 (clone 3DS223H). Working dilution (1:20)	eBioscience	Cat#62223942; RRID: AB_2637155
Pacific Blue-CD1c (clone L161). Working dilution (1:80)	BioLegend	Cat#331508; RRID: AB_1186048
BV480-CD49d (clone 9F10). Working dilution (1:80)	BD Biosciences	Cat#752960; RRID: AB_2917915
BV510-CD11c (clone S-HCL-3). Working dilution (1:320)	BioLegend	Cat#371514; RRID: AB_2650797
BV570-CD45RO (clone UCHL1). Working dilution (1:40)	BioLegend	Cat#304226; RRID: AB_2563818
Qdot 605-CD2 (clone S5.5). Working dilution (1:160)	eBioscience	Cat#Q10172; RRID: AB_10374574
BV605-CD197 (clone G043H7). Working dilution (1:10)	BioLegend	Cat#353224; RRID: AB_2561753
BV650-CD69 (clone FN50). Working dilution (1:40)	BD Biosciences	Cat#563835; RRID: AB_2738442
BV711-FcER1 (clone AER-37). Working dilution (1:80)	BioLegend	Cat#334638; RRID: AB_2687186
Super Bright 702-CD185 (clone MU5UBEE). Working dilution (1:40)	eBioscience	Cat#67918542; RRID: AB_2717183
BV750-CD103 (clone Ber-ACT8). Working dilution (1:320)	BD Biosciences	Cat#747099; RRID: AB_2871852
BV786-CTLA-4 (clone BNI3). Working dilution (1:20)	BD Biosciences	Cat#563931; RRID: AB_2738491
BB515-CD25 (clone BC96). Working dilution (1:20)	BD Biosciences	Cat#567318; RRID: AB_2916553
AF532-CD4 (clone SK3). Working dilution (1:20)	eBioscience	Cat#58004742; RRID: AB_11218872
RB545-CD14 (clone M5E2). Working dilution (1:40)	BD Biosciences	Cat#569259; RRID: AB_3684913
NovaFluor Blue 585-CD8 (clone OKT8). Working dilution (1:80)	eBioscience	Cat#H003T03B04-A; RRID: AB_3097951
RB613-Tbet (clone 4B10). Working dilution (1:40)	BD Biosciences	Cat#571286; RRID: AB_3686387
PerCP-CD11b (clone M1/70). Working dilution (1:80)	BioLegend	Cat#101230; RRID: AB_2129374
RB670-CD19 (clone SJ25C1). Working dilution (1:20)	BD Biosciences	Cat#571897; RRID: AB_3686717
BB700-TIM3 (clone 7D3). Working dilution (1:80)	BD Biosciences	Cat#746178; RRID: AB_2871643
RB705-TCRgd (clone B1). Working dilution (1:10)	BD Biosciences	Cat#758179; RRID: AB_3676399
RB744-Ki67 (clone B56). Working dilution (1:40)	BD Biosciences	Cat#570503; RRID: AB_3685795
PerCP-Fire 806-HLA-DR (clone L243). Working dilution (1:40)	BD Biosciences	Cat#307695
RB780-CD279 (clone EH12.1). Working dilution (1:40)	BD Biosciences	Cat#568703; RRID: AB_3684479
RY586-GZMB (clone GB11). Working dilution (1:133)	BD Biosciences	Cat#568134; RRID: AB_3684065
Spark YG 593-CD20 (clone 2H7). Working dilution (1:80)	BioLegend	Cat#302368; RRID: AB_2894449
PE-CF594-CD15 (clone 7C3.RMAB). Working dilution (1:80)	BD Biosciences	Cat#568932; RRID: AB_3684640
PE-Fire 640-CD183 (clone G025H7). Working dilution (1:20)	BioLegend	Cat#353764; RRID: AB_2922569
PE-Cy5-CD123 (clone 9F5). Working dilution (1:20)	BD Biosciences	Cat#561009; RRID: AB_394029
PE-AF700-CD16 (clone 3G8). Working dilution (1:320)	Invitrogen	Cat#MHCD1624; RRID: AB_1037353
RY703-CD278 (clone DX29). Working dilution (1:160)	BD Biosciences	Cat#770725; RRID: AB_3692594
PE-Fire 744-KLRG1 (clone SA231A2). Working dilution (1:80)	BioLegend	Cat#367752; RRID: AB_3097454
RY775-TIGIT (clone TgMab-2). Working dilution (1:320)	BD Biosciences	Cat#771419; RRID: AB_3693255
PE-Fire 810-NKp46 (clone 9E2). Working dilution (1:80)	BioLegend	Cat#331953; RRID: AB_2936531
APC-CD194 (clone L291H4). Working dilution (1:640)	BioLegend	Cat#359408; RRID: AB_2562429
AF647-TOX (clone NAN448B). Working dilution (1:80)	BD Biosciences	Cat#568356; RRID: AB_3684207
Spark NIR 685-FoxP3 (clone 150D). Working dilution (1:10)	BioLegend	Cat#320130; RRID: AB_2890753
R718-CD39 (clone A1). Working dilution (1:160)	BD Biosciences	Cat#567675; RRID: AB_2916696
APC-Fire 810-CD38 (clone HB-7). Working dilution (1:640)	BioLegend	Cat#356643; RRID: AB_2860936
Biological samples
Human Buffy Coat from healthy volunteers	OHSU
Chemicals, peptides, and recombinant proteins
Gibco™ DPBS, no calcium, no magnesium	Fisher Scientific	Cat#14-190-250
Zombie-NIR-Live/Dead (Amine Reactive). Working dilution (1:3200)	BioLegend	Cat#423105
CellBlox Blocking Buffer	Thermo Fisher Scientific	Cat#B001T03F01
BD Horizon Brilliant Stain Buffer	BD Biosciences	Cat#566349
Human TruStain FcX (Fc Receptor Blocking Solution)	BioLegend	Cat#422302
Invitrogen™ eBioscience™ Foxp3/Transcription Factor Staining Buffer Set	Fisher Scientific	Cat#50-112-8857
Fixation/Permeabilization Concentrate	Thermo Fisher Scientific	Cat#00-5123
Fixation/Permeabilization Diluent	Thermo Fisher Scientific	Cat#00-5223
Permeabilization Buffer (10x)	Thermo Fisher Scientific	Cat#00-8333
Invitrogen™ UltraComp eBeads™ Compensation Beads	Fisher Scientific	Cat#50-112-9040
Gibco™ DMEM, high glucose, pyruvate	Fisher Scientific	Cat#11-995-073
0.5 M EDTA PH 8.0	Fisher Scientific	Cat#AM9260G
Software and algorithms
SpectroFlo	Cytek	N/A
FlowJoTM v10.10.0	Becton Dickson & Co	N/A
Other
Cytek Aurora 5-Laser Spectral Cytometer- UV, Violet, Blue, Violet, and Red.	Cytek	N/A

Materials and equipment

Titration buffer (calculations for 1 set of titrations: 7 titers and an unstained control).

Buffer solutions

Reagent	Final concentration	Amount
PBS (phosphate-buffered saline)	1X	928 μL
EDTA (0.5 mM)	1.0 mM	2.0 μL
FBS (fetal bovine serum)	2%	20 μL
Human TruStain FcX	1:20	50 μL
Total	N/A	1.0 mL

Note: Make fresh.

Flow Cytometry Staining Buffer

Reagent	Final concentration	Amount
PBS	1X	489 mL
EDTA (0.5 mM)	1.0 mM	1.0 mL
FBS	2%	10 mL
Total	N/A	500 mL

Note: Store at 4C for up to 1 week.

Wash Buffer

Reagent	Final concentration	Amount
PBS	-	499 mL
EDTA (0.5 mM)	1.0 mM	1.0 mL
Total	N/A	500 mL

Note: Store at 4C for up to 1 month.

Fixation Buffer

Reagent	Final concentration	Amount
Fixation/Permeabilization Concentrate (4x)	1X	1.0 mL
Fixation/Permeabilization Diluent	N/A	3.0 mL
Total	N/A	4.0 mL

Note: Make fresh.

CRITICAL: Fixation/Permeabilization Concentrate contains formaldehyde, which is toxic and a suspected carcinogen.

Permeabilization Buffer

Reagent	Final concentration	Amount
Permeabilization Buffer (10x)	1X	1.0 mL
Distilled water	N/A	9.0 mL
Total	N/A	10 mL

Note: Make fresh.

Surface Stain Buffer

Reagent	Final concentration	Amount
BD Horizon Brilliant Stain Buffer (2X)	1X	0.259 mL
CellBlox Blocking Buffer (20X)	1X	0.026 mL
FACS buffer	N/A	0.233 mL
Total	N/A	0.5 mL

Note: Make fresh and keep on ice.

Intracellular Stain Buffer

Reagent	Final concentration	Amount
Permeabilization Buffer (1X)	(0.5X)	0.5 mL
Flow cytometry staining buffer (1x)	(0.5X)	0.5 ml
Total	N/A	1 mL

Note: Make fresh and keep on ice.

Cell Viability Stain with Fc Block

Reagent	Final concentration	Amount
Zombie-NIR viability dye	1:3200	0.313 mL
Human TruStain FcX	1:20	50 mL
PBS	N/A	949.7 mL
Total	N/A	1,000 mL

Note: Make fresh and store on ice until used.

CRITICAL: When pipetting small volumes make sure pipettes are properly calibrated.

Surface Antibody Mix 1

Reagent	Stock concentration (μg/ml)	Dilution	Amount per 1 × 106 cells (μL)
BUV 615-CD141	200	1:640	0.16
BUV 661-CD303	200	1:80	1.25
SUPER BRIGHT 436-LAG-3	250	1:20	5.0
PACIFIC BLUE-CD1c	500	1:80	1.25
BV 480-CD49d	200	1:80	1.25
BV 510-CD11c	100	1:320	0.31
QDOT 605-CD2	N/A	1:160	0.63
BV 650-CD69	200	1:40	2.5
BV711-FcER1	100	1:80	1.25
Super Bright 702-CD185	100	1:40	2.5
BV 750-CD103	200	1:320	0.31
BV 786-CTLA-4	200	1:20	5.0
BB 515-CD25	100	1:20	5.0
AF532-CD4	6	1:20	5.0
RB 545-CD14	400	1:40	2.5
NOVA FLUOR BLUE 585-CD8	160	1:80	1.25
PERCP-CD11b	200	1:80	1.25
BB 700-TIM3	200	1:80	1.25
RB 705-TCRgd	200	1:10	10.0
RB780-CD279	100	1:40	2.5
PE-CF594-CD15	100	1:80	1.25
PE-AF700-CD16	N/A	1:320	0.31
RY 703-CD278	200	1:160	0.63
PE FIRE 744-KLRG1	50	1:80	0.63
RY775-TIGIT	200	1:320	0.31
PE-FIRE 810-NKp46	25	1:80	1.25
Surface Stain Buffer	N/A	N/A	54.53
Total	N/A	N/A	100

Note: Make fresh and store on ice until use.

CRITICAL: Volumes and dilutions are empirically determined through titrations and optimized for 1 × 10⁶ cells stained in 100 μL volumes. When staining more than one sample, a larger volume of master mix can be made based on the number of samples.

Surface Antibody Mix 2

Reagent	Stock concentration (μg/ml)	Dilution	Amount per 1 × 106 cells (μL)
SPARK UV 387-CD45RA	200	1:80	1.25
BUV 395-CD40	25	1:40	2.5
BUV 496-CD3	200	1:40	2.5
BUV 563-CD56	50	1:320	0.31
BUV 737-CD86	100	1:160	0.63
BUV 805-CD45	100	1:40	2.5
BV 570-CD45RO	400	1:40	2.5
BV 605-CD197	100	1:10	10
RB 670-CD19	25	1:20	5.0
PERCP FIRE 806-HLA-DR	100	1:40	2.5
SPARK YG 593-CD20	200	1:80	1.25
PE-FIRE 640-CD183	100	1:20	5.0
PE CY5-CD123	13	1:20	5.0
APC-CD194	50	1:640	0.16
R718-CD39	N/A	1:160	0.63
APC-FIRE 810-CD38	200	1:640	0.16
Surface Stain Buffer	N/A	N/A	41.9
Total	N/A	N/A	100

Note: Make fresh and store on ice until use.

CRITICAL: Volumes and dilutions are empirically determined through titrations and optimized for 1 × 10⁶ cells stained in 100 μL volumes. When staining more than one sample, a larger volume of master mix can be made based on the number of samples.

Intracellular Antibody Mix

Reagent	Stock concentration (μg/ml)	Dilution	Amount per 1 × 106 cells (μL)
BV 421-IFN gamma	100	1:10	10.0
RB613-Tbet	200	1:40	2.5
RB744-Ki67	200	1:40	2.5
RY 586-GZMB	150	1:133	0.75
ALEXA FLUOR 647-TOX	200	1:80	1.25
SPARK NIR 685-FoxP3	200	1:10	10.0
Intracellular Stain Buffer	N/A	N/A	73.0
Total	N/A	N/A	100

Note: Make fresh and store on ice until use.

CRITICAL: Volumes and dilutions are empirically determined through titrations and optimized for 1 × 10⁶ cells stained in 100 μL volumes. When staining more than one sample, a larger volume of master mix can be made based on the number of samples.

Step-by-step method details

Antibody titrations

Timing: ∼3 h

Here, we describe steps to perform antibody titrations using serial dilutions with a fixed number of cells to identify optimal concentrations with maximum signal and minimal background noise (Figure 2).

Note: Performing antibody titrations prior to staining is essential to determine optimal dilution factors. Proper titration ensures strong signal, low background, accurate unmixing, and consistent results, all of which are especially important in high-parameter spectral cytometry. We recommend using two U-bottom 96-well plates, one for serial antibody dilutions (Plate 1) and another for cells (Plate 2). This setup allows for easy and organized transfer of antibodies to cells for staining.

Note: We adapted the recommended Cytek protocol.

• 1.
  Prepare Antibody Dilution Plate (Plate 1).

  • a.
    Calculate highest concentration of antibodies for titrations.

    Note: Manufacturer details for antibodies often represent concentration in mg/mL or μL/test. For antibodies provided in mg/mL, the highest titration concentration is 1000 ng/test in a final volume of 200 μL. For antibodies listed in μL/test, the highest titration concentration is 2X the recommended volume, also in a final volume of 200 μL.

    Example: LAG-3 (recommended 5.0 μL/test = 125 ng/test).
    125 ng/test × 2 = 250 ng/test.
    LAG-3 antibody stock concentration: 125 ng/5.0 μL.
    10 μL LAG-3 antibody + 190 μL flow cytometry staining buffer = 200 μL total.
  • b.
    In only the top row of a U-bottom 96-well plate, distribute highest concentration of antibody dilutions in appropriate staining buffer (Figure 2). For surface markers dilute antibodies in titration buffer. For intracellular antibodies dilute them in intracellular stain buffer.

    CRITICAL: Follow manufacturer’s instructions for fixation, permeabilization, and staining for intracellular markers.

• 2.
  Prepare Dilution Series (Plate 1).

  • a.
    Add 100 μL of titration buffer or intracellular stain buffer to dilution wells i.e., NOT the top row.
  • b.
    Using a multichannel pipette, transfer 100 μL from each well in the top row to the corresponding wells in the second row.

    Note: Mix thoroughly. Resuspend at least five times.

  • c.
    Continue transferring 100 μL from row to row down the plate until all seven desired dilution rows are complete.

    Note: Include at least one well with no antibody as an unstained control.

    Note: For intracellular markers, if it is easier to keep track of which column are surface markers or intracellular markers a separate plate for intracellular markers can be used.

• 3.
  Prepare Cell Plate (Plate 2).

  CRITICAL: Choose control cells most comparable to your experimental samples as different cellular compositions and/or cell types will have varied staining properties. If you have samples with limited cell numbers, see troubleshooting section below.

  • a.
    Resuspend cells in titration buffer to a concentration of 1 × 10⁶ cells/100 μL.
  • b.
    Dispense 100 μL of cells to each well totaling 1 × 10⁶ cells/well.

    CRITICAL: Be sure to resuspend the cells thoroughly.

  • c.
    Transfer 100 μL of antibody dilutions of surface markers from each well in Plate 1 into the corresponding well in Plate 2, final volume: 200 μL per well.
  • d.
    For wells that will have intracellular markers add 100 μL of titration buffer.
  • e.
    Carefully mix the antibodies and cells by pipetting.
  • f.
    Incubate plate in the dark on ice for 30-min.
  • g.
    Fixation and permeabilization.

    • i.
      Add 100 μL of fixation buffer per well, incubate 30-min on ice.
    • ii.
      Centrifuge at 400 × g for 5-min at 4°C.
    • iii.
      Discard supernatant by flicking the plate.
  • h.
    Resuspend cell pellet in 100 μL of Permeabilization Buffer.
  • i.
    Add 100 μL of the intracellular antibody dilutions from Plate 1 to the appropriate wells.
  • j.
    Carefully mix the antibodies and cells by pipetting.
  • k.
    Incubate 30-min on ice and in the dark.
  • l.
    Centrifuge at 400 × g for 5-min at 4°C.
  • m.
    Discard supernatant by flicking the plate.
  • n.
    Wash with 100 μL of Permeabilization Buffer.
  • o.
    Centrifuge at 400 × g for 5-min at 4°C.
  • p.
    Discard supernatant by flicking the plate.

    • i.
      Resuspend in 200 μL Flow Cytometry Staining Buffer.
    • ii.
      Keep on ice until samples are run on the Cytek Aurora 5L instrument.

• 4.Acquire data on a Cytek Aurora 5L instrument.
• 5.Calculate the median fluorescence intensity (MFI) and the data concatenated in FlowJo to visualize the different titrations.

CRITICAL: We recommend using the MFI of the positive and negative populations.

• 6.Empirically determine the correct dilution for the antibodies using the Separation Index (SI).
• 7.
  Use the formula below to determine the SI.

  $$SeperationIndex=\frac{MedianPositive-MedianNegative}{\left(84\%Negative-MedianNegative\right)/0.995}$$

Note: The higher the SI, the greater the separation from the positive and negative populations. We suggest balancing a large SI value with the least amount of antibody to reduce costs.

Figure 2.

Antibody titrations layout

(A) Plate maps for organizing titration workflow with serial antibody dilutions and a separate recipient plate for cell loading. Each column has 7 antibody titers and a negative control.

(B) Cytograms represent concatenated data to visualize the spread across dilution series with lower positive signal as the antibody concentration decreases. Stain indexes were calculated using FlowJo 10.10.0. for each evaluated marker.

Thawing and counting cells

Timing: Variable, highly dependent on number of samples

This step describes the cell preparation processus, thawing and counting to obtain desired cell concentrations.

• 8.Prefill appropriately sized conical tubes with pre-warmed DMEM.

Note: Ensure that DMSO is diluted to at least 1:1000 – e.g., 1.0 mL of cryopreserved cells can be added to at least 9.0 mL of the DMEM.

• 9.Thaw cells in water bath at 37° C until a small chunk of ice is left.
• 10.Pipette 1.0 mL of ice cold DMEM into the cryovial.
• 11.Transfer cryovial contents into the corresponding pre-filled conical tube.
• 12.Centrifuge at 400 g for 5-min.
• 13.Discard supernatant by inverting tubes.
• 14.Resuspend in 1.0 mL of flow cytometry staining buffer.
• 15.Count cells using a hemacytometer or automated counting system as per manufacturer’s instructions.
• 16.Using cell concentration calculations, resuspend cells to 1 × 10⁶ cells/100 μL volume.

Note: If cells are too diluted, spin down and resuspend in appropriate volume. See troubleshooting section.

• 17.Dispense cells at 1 × 10⁶ cells/well in 100 μL for staining.

Note: Full panel staining was done in a U-bottom 96-well plate to help with handling and efficiency for working with a larger number of samples.

Surface staining of single-color controls, FMOs, and samples

Timing: ∼2 h

Here, we describe steps allowing to assess cell viability and stains surface markers.

• 18.
  Dispense 1 × 10⁶ cells/well for staining into a round bottom 96-well plate.

  • a.
    Centrifuge at 400 × g for 5-min at 4°C.
  • b.
    Rinse with 200 μL of wash buffer.
  • c.
    Discard supernatant by flicking the plate i.e., inverting rapidly to empty the liquid entirely.

• 19.
  Fc Block and Cell Viability Stain.

  • a.
    Transfer 100 μL of Cell Viability Stain with Fc Block into each well and resuspend the cell pellet.

    CRITICAL: Do not add Cell Viability Stain to unstained, single stain controls, or the FMO that excludes the Cell Viability Stain.

  • b.
    Incubate for 30-min on ice or at 4°C in the dark.
  • c.
    Rinse with 100 μL of wash buffer.
  • d.
    Centrifuge at 400 × g for 5-min at 4°C.
  • e.
    Discard supernatant by flicking the plate.

• 20.
  Surface Staining of Surface Markers.

  • a.
    Add surface Ab cocktail C1 to samples (100 μL/well).
  • b.
    Incubate for 20-min on ice or at 4°C in the dark.
  • c.
    Rinse with 100 μL of Flow Cytometry Staining Buffer.
  • d.
    Centrifuge at 400 × g for 5-min at 4°C.
  • e.
    Discard supernatant by flicking the plate.
  • f.
    Add surface Ab cocktail C2 to samples (100 μL/well).
  • g.
    Incubate for 20-min for C2 on ice or at 4°C in the dark.
  • h.
    Rinse with 100 μL of Flow Cytometry Staining Buffer.
  • i.
    Centrifuge at 400 × g for 5-min at 4°C.
  • j.
    Discard supernatant by flicking the plate.

Intracellular staining of single-color controls, FMOs, and samples

Timing: ∼1 h

Here, we describe steps for intracellular staining of proteins assessed with the proposed panel.

• 21.
  Fixation and Permeabilization.

  Note: If intracellular staining is not required, samples can be fixed using Fixation Buffer, washed and resuspended in Flow Cytometry Staining Buffer.

  Note: It is important to conduct fixation and permeabilization steps on all samples regardless of whether that specific sample is being stained with intracellular markers. This ensures all cells are treated under the same conditions.

  • a.
    Add 100 μL of Permeabilization Buffer per well, incubate 30-min on ice.
  • b.
    Centrifuge at 400 × g for 5-min at 4°C.
  • c.
    Discard supernatant by flicking the plate.

• 22.
  Intracellular Staining.

  • a.
    Add intracellular Ab cocktail IC to the samples (100 μL/well).
  • b.
    Incubate 30-min on ice and in the dark.
  • c.
    Centrifuge at 400 × g for 5-min at 4°C.
  • d.
    Discard supernatant by flicking the plate.
  • e.
    Wash with 100 μL of Permeabilization Buffer.
  • f.
    Centrifuge at 400 × g for 5-min at 4°C.
  • g.
    Discard supernatant by flicking the plate.
  • h.
    Resuspend in 200 μL Flow Cytometry Staining Buffer.
  • i.
    Keep on ice until samples are run on the Cytek Aurora 5L instrument.

Fluorescence minus one

Timing: ∼4 h

Here, we include guidelines for fluorescence minus one (FMO) preparation prior to acquisition (Figure 3).

Figure 3.

Fluorescence Minus One (FMO) plate layout

Plate maps for organizing FMO workflow for the 49-marker pane, including viability dye, surface and intracellular staining.

FMOs are important for determining impact of single fluorophores on remaining positive and negative populations when all other fluorophores are present except for one.

• 23.Make single-sample antibody mixtures as detailed in the antibody cocktail recipes while replacing one antibody with buffer.

Note: Do this for the cell viability stain as well.

• 24.Generates 49 individual FMO samples as mix minus one.

Note: Be sure to include one unstained single cell control. For a 49-plex panel, this step is time-consuming and may benefit from multiple people supporting the experimental staining and control staining steps concurrently.

Should that not be possible, we recommend staining controls and samples on consecutive days. All staining and data acquisition must mirror experimental samples following the protocols below.

CRITICAL: If staining with intracellular markers, it is important to conduct fixation and permeabilization steps on all samples regardless of whether that specific sample is being stained with antibodies for intracellular biomarkers. This ensures all cells are treated under similar conditions.

Single-color stains—Cells and beads

Timing: ∼4 h

Here, we describe guidelines for single color control preparation for each antibody-fluorochrome conjugate used.

Single color stains are necessary for unmixing as they provide a spectral signature free of interference from other fluorophores. In the case of this protocol there will be 49 single color controls plus two unstained controls: one for cells and one for beads. This is required to account for signal strength and antigen availability. Whether a cell or bead single color stain is most appropriate for use during unmixing is determined empirically at analysis.

• 25.
  Single Color Staining with Cells.

  • a.
    Stain cells using the antibody concentrations and protocol listed in “Surface staining of single-color controls, FMOs, and samples”.
• 26.
  Single Color Staining with Beads.

  • a.
    Beads are calculated at a ratio of 1-drop per 2 wells.
  • b.
    Collect the appropriate number of drops for wells and add 1.5 mL of PBS per 25 drops to your beads.
  • c.
    Distribute beads at a volume of 100 μL per well and add 1.0 μL of antibody to each well.
  • d.
    Incubate for 20-min.
  • e.
    Be sure to include unstained beads as a control.
  • f.
    Rinse with 100 μL of wash buffer.
  • g.
    Centrifuge at 400 × g for 5-min at 4°C.
  • h.
    Discard supernatant by flicking the plate.
  • i.
    Resuspend each well in 100 μL of flow cytometry staining buffer.
  • j.
    Continue to acquisition.

Note: Make sure to heavily vortex the beads for 30 s and gently vortex or pipette-mix each time you transfer this mixture to your wells to ensure homogeneity before use.

Data acquisition

Timing: Variable with number of samples

Here, we provide an outline for acquiring data from stained samples.

• 27.
  Run the unstained and single-color controls.

  • a.
    Run the unstained cells first and adjust the forward scatter and side scatter.
  • b.
    Run the single-color controls.
  • c.
    Check the single-color controls are giving the correct spectral reading as they are being acquired.

Note: Live unmixing can be done at this time but with the complexity of this panel unmixing appropriately can be time consuming. Unmixing after data acquisition allows for determining if beads or cells are the best to use as the single-color control.

• 28.Run the FMO and full panel samples.
• 29.Unmix data using SpectroFlo Software.
• 30.If necessary, move unmixed samples to FlowJo Software for subsequent gating and statistical output.
• 31.Gate on cell population as outlined in expected outcomes.

Expected outcomes

This protocol provides a robust method for characterizing circulating human immune cells through high-parameter spectral flow cytometry with qualitative and quantitative insights on activation and proliferation status of these populations as well as exhaustion profiles. We provide succinct downstream analysis guidance for data visualization.

Subset identification

This curated panel allows for identification of: B cell subsets (CD19⁺ CD20⁺ B cells and CD19⁺ CD20^- plasmablasts); T cells – general (CD3⁺ putative αβ T cells, CD3⁺ γδ T cells); NK cells including CD56^bright CD16^- NK cells and CD56^dim CD16⁺ NK cells, monocytes including classical monocytes, intermediate monocytes and non-classical monocytes, Dendritic cells including conventional dendritic cells 1 (cDC1), conventional dendritic cells 2 (cDC2) and plasmacytoid DCs (pDCs), granulocytes including eosinophils, basophils and neutrophils in Figure 4. T cell subsets/function from CD3⁺ αβ gate identification are displayed in Figure 5. CD4⁺ T cells including CD4⁺ central memory cells (T_CM), CD4⁺ memory stem cells (T_SCM), CD4⁺ effector T cells (T_EFF), CD4⁺ effector memory T cells (T_EM), CD4⁺ CD45RA⁺ effector memory T cells (T_EMRA), naïve CD4⁺ T cells, T_regs, CD8⁺ T cells including CD8⁺ T_SCM, CD8⁺ T_CM, CD8⁺ T_EFF, CD8⁺ T_EM, naïve CD8⁺ T cells, CD8⁺ T_EMRA. Immune complexity profiles can be visualized as a representation of all major lineages assessed, as shown in Figure 6. Functional status can be assessed following the gating strategy in Figure 7.

Figure 4.

Gating strategy for lineage delineation and functional assessment

(A) Initial gating strategy excluding debris, doublets and dead cells.

(B) Lineage gating for CD45+ immune cell and representative plots for major populations of B, T cell lineages and TCR γδ cells.

(C) Representative plots for the main phenotyping markers used for B cells and plasmablasts/plasma cells (CD19, CD20) and NK (CD56, CD16) cells.

(D) Myeloid subsets gating strategy to delineate antigen-presenting cells (HLA-DR), with monocyte subsets (CD14, CD16), dendritic cells (CD11c, CD141, CD1c), and granulocyte populations (all CD15; eosinophils, CD49d; basophils, CD123; and neutrophils).

Figure 5.

Gating strategy allowing for identification of CD3⁺T cell populations

(A) T regulatory cells (CD25, FoxP3) and major T cell lineages: CD4⁺ T, CD8⁺ T, double positive CD4⁺ CD8⁺ double negative CD4^- CD8^-).

(B and C) Activation and differentiation status (CD45RO, CD45RA, CD197/CCR7) with T effectors (T_EFF), T effector memory (T_EM), T central memory (T_CM), T stem-like cell memory (T_SCM), naïve and T effector memory expressing CD45RA (T_EMRA) of CD4⁺ T cells (B) and of CD8⁺ T cells (C). KLRG1 and CD69 activation status is also indicated.

Figure 6.

Overall immune complexity of 2 distinct samples assessed with the 49-color panel

Each column represents one sample evaluated by flow cytometry with the proposed panel. Color-coded immune subsets were gated as percentage of CD45.

Figure 7.

Functional assessment of proliferation, cytotoxicity and exhaustion parameters

(A) t-distributed stochastic neighbor embedding (tSNE) landscape of a sample including all clusters and colored by the intensity of expression of indicated markers of interest.

(B) Overlay of histograms showing mean fluorescence intensity of indicated markers for Sample #1. Color-coded histograms represent the individual subset annotated.

(C) Overlay of histograms showing mean fluorescence intensity of indicated markers for Sample #2. Color-coded histograms represent the individual subset annotated.

Quantification and statistical analysis

In this section, we detail instructions for t-SNE dimensional reduction and data visualization. Parameters selected in Figure 8 are sample-dependent and considerations listed below must be adjusted accordingly.

• 1.General considerations:

Figure 8.

FlowJo tab for parameters selection to generate t-SNE plots

The optimal tSNE parameters are often dataset dependent. It is common practice to run tSNE with different parameter combinations and evaluate the resulting plots to find the most informative visualization of your data.

tSNE is computationally intensive, especially with large datasets and high iteration counts.

• 2.
  Data Scaling:

  • Ensure your data is properly scaled (e.g., using log or biexponential transformations for fluorescence data) before running tSNE, as this can significantly impact the results.
• 3.Input parameters by selecting relevant markers:

Choose only the compensated parameters (denoted by “Comp-” prefix) that are relevant to the biological question being investigated. Exclude parameters like scatter (FSC, SSC) or viability stains unless they are critical for defining specific populations in your analysis.

• 4.
  tSNE Algorithm Settings (within the tSNE platform in FlowJo):

  • a.
    Iterations: This determines the number of steps the algorithm takes to optimize the embedding. While FlowJo’s default Opt-SNE algorithm will stop when improvement plateaus, setting a higher maximum iteration count (e.g., 1000 or more) can lead to more robust clustering, especially for complex datasets.
  • b.
    Perplexity: This parameter relates to the number of nearest neighbors considered by the algorithm. A lower perplexity value emphasizes local structure, suitable for datasets with distinct, small clusters. A higher perplexity value considers a broader neighborhood, useful for datasets with more diffuse clusters or when trying to identify global structures. Experimentation with different perplexity values (e.g., 5, 30, 50) is often necessary to find the optimal setting for your specific data.
  • c.
    Learning rate: This controls the approximation thoroughness of the Barnes-Hut algorithm (used for calculating repulsive forces).A lower theta value increases accuracy but also computation time. A higher theta value reduces computation time but might decrease accuracy. This factor influences the step size of the gradient descent optimization. Adjusting it can impact the speed of convergence and the quality of the final embedding.
  • d.
    Gradient algorithm: FlowJo offers Barnes-Hut and FFT (Fitz Sne FFT). FFT: is generally recommended for datasets with up to 5 million events due to its speed. Barnes-Hut: is suggested for larger datasets.

Limitations

The protocol was optimized for frozen buffy coat samples.

The quality of the results is dependent on the number and viability of cells recovered in each sample. This is greatly affected by sample collection and subsequent handling, including the cryopreservation and thawing procedure. It is important to move quickly through this protocol once the cells have thawed. Buffy coat of PBMC isolation, freezing and storage are not included in this protocol.

Immune components across samples can vary greatly and some cell populations may be absent entirely. Without specific controls and normalization analyzing certain biomarkers may be difficult, thus requiring adjustments for targets.

Troubleshooting

Problem 1

Low number of cells (related to step 15 in “thawing and counting cells” section).

Potential solution

Use the same number of cells and staining volume across all samples, when possible, to ensure consistent antibody-to-cell ratios during staining. Variability in cell number can affect the optimal antibody concentration due to differences in antigen availability and surface area. In cases of limited cell number, you can reduce the total staining volume proportionally to maintain the same cell concentration and ratio (cells/μL). This preserves antibody binding kinetics and minimizes nonspecific binding or signal loss due to excess unbound antibody in dilute conditions as antigen expression and cellular context may differ significantly.

Problem 2

Low viability – analysis (related to step 15 in “thawing and counting cells” section).

Infrequent cell populations require a minimum number of events to be accurately analyzed. The low range of acceptable is 100-500 events.⁴ Back calculating from the rarest cell population determines the most optimal number of cells to acquire.

Potential solution

If possible, acquire more cells. If no additional cells are available, exclude cell populations with fewer than 100 events.

Problem 3

Unmixing errors (related to step 29 in “data acquisition” section).

Spectral flow cytometry utilizes the entire spectrum of a fluorophore allowing for larger antibody panels than traditional flow cytometry. Unmixing errors should be limited to fluorochrome pairs with a high similarity index. When these pairs were used herein, they were applied to mutually exclusive marker expression such that they could still resolve well with relatively low spreading errors.

Potential solution

Visual inspection of individual spectral profiles is critical for resolving unmixing issues. If the single-color control does not show a unique profile, use a fully stained sample to gate on the expected cell subset expressing the marker of interest to aid in refining the spectral profile.

If there is over-correction due to unmixing, make sure the single-color control is brighter than the sample. Compare unmixing between beads and cells and if the unmixing error remains you may need to rerun that specific control.

If you are new to spectral flow cytometry and need more information, resources on this topic are available on cytometer and antibody manufacturer websites.

Problem 4

Unexpectedly low expression and fluorescence intensity for high antigen expression (related to step 27c in “data acquisition” section).

Presented herein reflects a large antibody panel utilizing biomarkers that may not be present under all conditions, depending on your samples of interest and biological assessment. Human samples are variable, and it is important to include positive controls to be confident on interpretation when a signal is absent.

Potential solution

Review the staining process to ensure that a master mix containing relevant antibodies is used for all samples. Reassess single color controls and use a sample that will be comparable to the sample of interest.

Problem 5

Positive populations are not clearly separated (related to step 27c in “data acquisition” section).

Potential solution

Low brightness index on fluorochrome pairs for two lineage markers can result in an unclear separation. In addition, some biomarkers such as CD45RO, CD45RA, CCR7 with tertiary expression, will not show clear positive/negative separation. The use of FMOs is essential for accurate gating of these populations.

Problem 6

Inconsistent results (related to step 31 in “data acquisition” section).

Potential solution

If you are having inconsistent results between experimental replicates, you may be experiencing batch effects. Flow cytometer parameters can fluctuate in high use centers. It is important to have positive controls to assess parameters and instrument voltages before running samples. Whenever possible, run all experimental samples and controls using the same master mix and reagents. Reagent expiration and storage are critical to ensure reproducibility.

Resource availability

Lead contact

Requests for further information and resources should be directed to and will be fulfilled by the lead contact, Amanda Poissonnier (poissonn@ohsu.edu).

Technical contact

Questions about the technical specifics of performing the protocol should be directed to the technical contact, Amanda Poissonnier (poissonn@ohsu.edu).

Materials availability

This study did not generate new unique reagents.

Data and code availability

FCS files from healthy donors used herein are available upon request.

Acknowledgments

We thank the Coussens Lab members, OHSU Flow Cytometry Core, and Dr. Nathan Pennock for their expertise, assistance, and insightful discussions. This research was supported by the Susan G. Komen Leadership Grant (SAC240100), the National Foundation for Cancer Research, the Hildegard Lamfrom Endowed Chair in Basic Research, and the Knight Cancer Institute (P30 CA069533).

Author contributions

Conceptualization, A.P. and L.M.C.; experiment design and execution, A.P.W., M.L., E.H., and A.P.; data analysis, A.P.W., M.L., and A.P.; writing – original draft, A.P.W., M.L., E.H., and A.P.; writing – review and editing, A.P.W., M.L., E.H., A.P., and L.M.C.; supervision, A.P.; funding acquisition, L.M.C.

Declaration of interests

L.M.C. has received reagent support from Cell Signaling Technologies, Plexxikon, Inc., and Syndax Pharmaceuticals, Inc. and is on advisory board for Carisma Therapeutics, Inc., CytomX Therapeutics, Inc., Kineta, Inc., Cell Signaling Technologies, Inc., Alkermes, Inc., NextCure, Guardian Bio, Dispatch Biotherapeutics, AstraZeneca Partner of Choice Network (OHSU Site Leader), Genenta Sciences, and Lustgarten Foundation for Pancreatic Cancer Research Therapeutics Working Group, Inc.