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Method Article

Mass Cytometry Analysis of Systemic and Local Immune Responses in Hepatocellular Carcinoma

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DOI:

10.3791/67425

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April 25th, 2025

 ,  ,  ,  ,  ,  ,  ,  ,  ,  , 
1Department of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital, Zhejiang University School of Medicine

* These authors contributed equally

In This Article

Summary

This protocol outlines a comprehensive mass cytometry (cytometry by time-of-flight [CyTOF]) analysis method for evaluating both systemic and local immune responses in hepatocellular carcinoma (HCC). The approach aims to provide insights into the immune landscape of HCC, offering a deeper understanding of the tumor microenvironment and the associated immune mechanisms.

Abstract

Hepatocellular carcinoma (HCC) is one of the most common and deadliest forms of liver cancer worldwide. Despite advances in treatment, the prognosis for HCC patients remains poor due to the complex interplay of genetic, environmental, and immunological factors driving its progression. Understanding the immune landscape of HCC is crucial for developing effective therapies, particularly in the field of immunotherapy, which holds great promises for improving patient outcomes. This study employs mass cytometry (cytometry by time-of-flight [CyTOF]) technology to investigate both systemic and local immune responses in patients with HCC. By analyzing peripheral blood and tumor samples, the research aims to identify unique immune cell populations, and their functional states associated with HCC progression. The findings provide a comprehensive overview of the immune landscape in HCC, highlighting potential biomarkers and therapeutic targets. This approach offers valuable insights into the immune mechanisms underlying HCC and paves the way for the development of more effective immunotherapies for this malignancy.

Introduction

Hepatocellular carcinoma (HCC) is the most common primary liver cancer and a significant global health issue due to its high incidence and mortality rates1. According to the World Health Organization, HCC ranks as the fifth most common cancer and the second leading cause of cancer-related deaths worldwide2. It is particularly prevalent in regions with high rates of chronic hepatitis B and C infections, such as East Asia and sub-Saharan Africa3. Major risk factors include viral hepatitis, cirrhosis, and metabolic syndrome4. HCC requires long-term treatment, imposing substantial physical and financial burdens, underscoring the need for effective prevention, early detection, and innovative treatment strategies5.

The immune system plays a crucial role in the development of HCC. The liver is an immunologically active organ with an abundance of immune cells, including liver-resident macrophages, natural killer (NK) cells, and T cells, which are essential for monitoring and eliminating abnormal cells6. However, HCC can evade immune surveillance by expressing immunosuppressive molecules, recruiting immunosuppressive cells, and altering the tumor microenvironment7,8. This immune escape not only promotes tumor growth and metastasis but also affects the response to immunotherapy9,10.

Systemic and local immune responses in the tumor microenvironment are key factors influencing cancer progression and therapeutic outcomes. Systemic immune responses involve circulating immune cells that can recognize and attack distant tumor cells, such as peripheral T cells, NK cells, and monocytes that can target tumor cells throughout the body. Local immune responses focus on immune cell activity within the tumor microenvironment, including tumor-infiltrating lymphocytes (TILs), tumor-associated macrophages (TAMs), and regulatory T cells (Tregs). While TILs often exert cytotoxic effects against tumor cells, TAMs and Tregs typically contribute to an immunosuppressive environment that supports tumor growth11,12. Tumor cells and stromal cells can reshape the tumor microenvironment to promote immunosuppression and evade immune surveillance. The interaction between systemic and local immune responses determines the overall effectiveness of anti-tumor immunity11. Understanding this interaction can aid in developing more effective immunotherapy strategies.

Traditional flow cytometry and immunohistochemistry, while widely used in immunological studies, exhibit significant limitations when it comes to analyzing complex immune landscapes due to their inability to perform comprehensive, high-dimensional analysis. Flow cytometry is highly effective for detecting surface and functional markers at the single-cell level; however, its capacity for simultaneous multi-marker analysis is restricted, often limited by spectral overlap and practical constraints on the number of fluorescent tags that can be used13,14. Immunohistochemistry, on the other hand, provides valuable insights into the tissue context of specific markers, but it is similarly hampered by the limited number of analyzable markers and the inherent difficulties of achieving robust, quantitative, high-dimensional assessments15.

To effectively characterize complex immune environments, high-dimensional techniques like mass cytometry (cytometry by time-of-flight [CyTOF]) are essential. Mass cytometry is an advanced technology that employs mass spectrometry to analyze multiple protein markers in single cells. It enables multiparametric analysis of individual cells without the spectral overlap issues seen in traditional flow cytometry16. By using metal-tagged antibodies, it can measure dozens of markers simultaneously, offering a comprehensive and unbiased view of cellular phenotypes and functions17. For example, Gadalla et al. developed a CyTOF panel with more than 40 parameters for the analysis of peripheral blood mononuclear cells (PBMC) and tumor tissue, demonstrating its advantage in high-dimensional immunophenotyping18. Traditional flow cytometry, with its limited number of detectable parameters, was unable to identify these rare cell populations exhibiting unique phenotypes. In contrast, mass cytometry enabled a comprehensive evaluation of the functional states of these cells, providing a more detailed and robust characterization. Behbehani et al. utilized mass cytometry to analyze bone marrow samples from patients with myelodysplastic syndromes (MDS), successfully identifying and characterizing rare aberrant hematopoietic progenitor cells18. The ability of mass cytometry to simultaneously detect over 40 surface and intracellular markers significantly enhanced the detection of these low-frequency cell subsets19. These capabilities overcome traditional limitations and provide deeper insights into immune landscapes, driving progress in immunology and therapeutic development. The ability to comprehensively profile cellular phenotypes and functions at the single-cell level greatly advances the understanding of immunological processes and aids in the development of targeted therapies.

Mass cytometry provides comprehensive insights into the systemic and local immune cell populations in HCC by simultaneously detecting multiple protein markers. This technology can distinguish between various types of T cells within the tumor microenvironment, such as effector T cells, regulatory T cells (Tregs), and exhausted T cells, elucidating their specific roles in tumor progression. By utilizing mass cytometry, researchers can identify immune markers associated with HCC prognosis20. For instance, T cell subsets with high Programmed Cell Death Protein 1 (PD-1) expression can serve as predictors of a patient's response to immune checkpoint inhibitors21. Additionally, it facilitates the discovery of new therapeutic targets by identifying specific immunosuppressive molecules, thereby providing a foundation for personalized treatment strategies. Technology's ability to detect multiple markers and its single-cell resolution make it particularly advantageous for uncovering novel therapeutic targets and designing combination immunotherapies. This advanced approach holds significant potential for improving treatment outcomes in HCC patients by offering a detailed understanding of the immune landscape and enabling the development of tailored therapeutic interventions.

This study aims to utilize mass cytometry to analyze the systemic and local immune cell profiles of patients with HCC. The objectives are to characterize the immune cell populations, correlate these characteristics with clinical outcomes and therapeutic responses, and identify specific immune markers and cell subsets associated with HCC prognosis. By elucidating the roles of various immune cells in treatment responses, this study seeks to provide a foundation for personalized treatment strategies. The findings are expected to optimize existing immunotherapies and offer valuable insights for developing new treatments, ultimately aiming to improve overall survival and quality of life for HCC patients.

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Protocol

The steps for blood and HCC sample collection, peripheral blood mononuclear cells (PBMCs) isolation, single-cell dissociation, and staining are outlined in the following plan. The experimental reagents and materials are all listed in the Table of Materials. All experiments were carried out with the approval of the Ethics Committee of the First Affiliated Hospital, School of Medicine, Zhejiang University, ensuring that the collection of tumor samples did not interfere with pathological diagnosis. Written informed consent was obtained from all human subjects.

1. Isolation of PBMCs

  1. Draw a blood sample from the vein of HCC patients and use a tube filled with an anticoagulant to prevent the blood from clotting. Blood samples were obtained from 4 patients (2 males and 2 females) aged 50-60 years, with an average age of 55 years. For each patient, collect 10-20 mL of peripheral blood to ensure sufficient volume for subsequent PBMCs isolation while minimizing patient discomfort.
  2. Draw a specific volume of blood (e.g., 6 mL) and add an equal volume of peripheral blood lymphocyte separation liquid (Ficol-paque or Lymphoprep) to a 15 mL centrifuge tube.
    NOTE: The total volume should ideally not exceed 12 mL to allow space for proper mixing and to prevent overflow; the maximum recommended volume for a 15 mL centrifuge tube is 14 mL.
  3. Tilt the centrifuge tube at 45° and slowly add the blood along the wall of the tube, carefully laying the blood slowly on top of peripheral blood lymphocyte separation liquid to avoid mixing the two layers.
    NOTE: A pipet can be used to slowly add blood along the wall of the tube.
  4. Place the centrifuge tube in the centrifuge and set the acceleration at 8 and deceleration at 3. Centrifuge at 450 x g, 4 °C, for 30 min. After centrifugation, 4 layers are formed in the test tube, from top to bottom: plasma layer, PBMCs layer (white membrane layer), Ficol-Paque layer, and red blood cell and granulocyte layer.
  5. Using a pipette, carefully collect the PBMCs layer into a new sterile centrifuge tube. Add 3 times the volume of PBS and centrifuge at 500 x g at 4°C for 5 min. After centrifugation, a pellet is formed at the bottom of the tube.
  6. Discard the supernatant using a pipette, add 1 mL of 2% Fetal Bovine Serum-Phosphate Buffered Saline (FBS-PBS) to resuspend the cells, and then add 3 mL of Red Blood Cell (RBC) lysis buffer. Centrifuge at 500 x g at 4°C for 5 min.
  7. Ensure there are no red blood cells at the bottom of the tube, indicating that the red blood cells have been completely lysed. Resuspend the cells in 2% FBS-PBS and proceed directly with the subsequent experiments, or add cell cryopreservation solution and store at -80°C for 2-3 months.
    NOTE: As a general guideline, for resuspension, use 0.5 mL of 2% FBS-PBS per 1 x 106 cells. The cell count is determined using a hemocytometer or an automated cell counter after trypan blue staining to distinguish live cells from dead cells. This ratio helps ensure optimal cell recovery and viability during subsequent procedures.

2. Isolation of tumor tissue cells

NOTE: The method for the isolation of tumor tissue cells was adapted from Song et al.22.

  1. After resecting the HCC, guided by a pathologist, use a sterile scalpel to excise a portion of the tumor tissue. The tissue block should be approximately 1 cm3 in size. Rinse off any surface stains with pre-chilled 1x PBS. Immerse the tissue in a 15 mL centrifuge tube containing about 5 mL of RPMI 1640 medium containing 10% FBS. Place the tube on ice and transport it back to the laboratory for further processing.
  2. Thoroughly rinse off blood stains and manually remove fatty connective tissue using forceps to ensure complete tissue cleaning with pre-cooled 2% FBS-PBS. Transfer the tissue to a tissue-culture-treated dish containing a digestion solution. Secure the tumor tissue with forceps and cut it into pieces smaller than 1 mm3 with a scalpel. Transfer the tissue digestion solution to a 50 mL centrifuge tube, adding more tissue digestion solution until the total volume is approximately 15 mL.
  3. Place the centrifuge tube containing the tissue digestion mixture in a shaker. Tilt or flatten it and secure it for digestion at 150 rpm and 37 °C for 1 h. Filter the digestion solution through a 70 µm filter.
    1. During this procedure, use a 1 mL syringe plunger to grind the tissue fragments. Rinse the filter with a 2% FBS-1640 solution. Take the filtrate and transfer it to a 15 mL centrifuge tube.
  4. Centrifuge the filtrate at 500 x g for 5 min at 4 °C. After centrifugation, discard the supernatant. Cautiously re-suspend the pellet in approximately 10 mL of 36% Percoll solution. Then, centrifuge it again at 500 x g for 5 min at 4 °C.
  5. Gently aspirate 1 mL of RBC lysis buffer with a pipette to resuspend the cell suspension. Transfer the suspension to a new 15 mL centrifuge tube and add the RBC lysis buffer to reach a total volume of 10 mL. Let the mixture sit at room temperature for 10 min.
    NOTE: A new centrifuge tube is used to prevent any impurities on the tube wall from re-entering the cell suspension, thereby reducing the risk of decreased cell yield.
  6. Centrifuge the cell suspension at 500 x g for 5 min at 4 °C, then resuspend the cells in an appropriate volume of 2% FBS-PBS. As a general guideline, use 0.5 mL of 2% FBS-PBS per 1 x 106 cells for resuspension.
    NOTE: The cell count is determined by using a hemocytometer or an automated cell counter after trypan blue staining to distinguish live cells from dead cells. The resuspension volume depends on the required cell quantity for subsequent experiments. This ratio helps ensure optimal cell recovery and viability during subsequent procedures.

3. Cisplatin staining

  1. Take 3 x 106 cells from the PBMCs obtained in step 1.7 and the tumor cells isolated in step 2.6, respectively. After cell recovery, resuspend them in 1 mL of PBS without Ca2+ and Mg2+. Add cisplatin to a final concentration of 0.5 µM, mix well, and incubate at room temperature for 2 min.
    NOTE: Cisplatin staining is performed to distinguish dead cells from live cells based on membrane integrity. Dead cells with compromised membranes will uptake cisplatin and show a positive signal, while live cells remain unstained23. The number of cells must be at least 1 x 106.
  2. Centrifuge the tubes at 500 x g for 5 min at room temperature, discard the supernatant, then add 1 mL of cell staining buffer to each tube containing the cell suspensions prepared in step 3.1 to stop the reaction. Centrifuge at 500 x g for 5 min at room temperature, discard the supernatant, and ensure that the cell pellet is not distributed linearly along the wall of the tube after centrifugation.

4. Fc receptor blocking

  1. Prepare a 50 µL block mix in advance for each sample: Combine 48 µL of cell staining buffer, then add 2 µL of Fc blocking solution (cell staining buffer: Fc blocking solution=9:1).
  2. Suspend the cells from step 3.2 in the above mixture and let them sit at room temperature for 10 min.

5. Incubation of membrane protein antibodies

  1. For each cell sample obtained from step 4.2, prepare the membrane protein antibody mix by adding 1.1 µL units of each antibody. Then, add cell staining buffer to reach a final volume of 55 µL. At this point, the total volume is approximately 100 µL.
    NOTE: The mix includes antibodies targeting key membrane proteins, such as CD163, CCR3, CD141, CD117, and CD4524,25. These antibodies were selected for their specificity in identifying membrane protein markers and were obtained from commercially available sources (see Table of Materials for details, including clone numbers, manufacturers, and catalog numbers).
  2. Add 50 µL of prepared antibody mix to each tube sample, bring the total volume to 100 µL. Gently swirl the samples and incubate them at room temperature for 15 min.
  3. Add 2 mL of cell staining buffer to each sample, centrifuge at 500 x g for 5 min at room temperature, and discard the supernatant. Repeat this step 2x.
  4. Discard the supernatant and briefly vortex the remaining liquid with the cell pellet to resuspend and thoroughly disperse the cell.

6. Nucleus protein staining

  1. Once the cells have been fully resuspended, add 500 µL of the mixed solution (fixation: fixation/permeabilization = 3:1) to each sample from step 5.4. Gently mix the samples and incubate at room temperature for 30 min.
  2. Dilute the permeabilization buffer (10x) with deionized water. After incubation, centrifuge at 500 g for 5 min at room temperature and discard the supernatant. Add 1000 µL of 1x permeabilization buffer to each tube to wash the cells. Centrifuge at room temperature at 1,000 x g for 5 min, then discard the supernatant.
  3. Resuspend antibodies in 1x permeabilization buffer. Discard the supernatant, and add 50 µL of the antibody mixture to each tube of cells. Gently pipette the cells to mix, then incubate at room temperature for 30-45 min.
  4. Add 1000 µL of 1x permeabilization buffer to each tube, centrifuge at roomtemperature at 1,000 x g for 5 min, and discard the supernatant.
  5. Add 1000 µL of cell staining buffer to each tube to resuspend the cells again, centrifuge at room temperature at 1,000 x g for 5 min, and discard the supernatant.

7. Cell fixation

  1. Prepare a 1.6% formaldehyde solution in PBS, with 1 mL needed per sample.
  2. Add 1 mL of 1.6% formaldehyde solution to each sample from step 6.5, vortex to mix thoroughly, and incubate at room temperature for 10 min.
    NOTE: While formaldehyde is commonly used for cell fixation, alternative reagents such as 4% paraformaldehyde (PFA) or methanol can also be used. The choice of fixative should be based on the specific requirements of the experiment and the cellular features to be observed.
  3. Centrifuge at room temperature at 800 x g for 5 min and discard the supernatant.

8. Nuclear Intercalation Staining

  1. Prepare cell intercalation solution: Dilute Cell-ID Intercalator-Iridium (Ir) with Fix and permeabilization buffer to a final concentration of 125 nM. Prepare 1 mL of the solution per sample.
  2. Add 1 mL of the prepared cell intercalation solution to each fixed sample from step 7.3. Mix gently and vortex immediately. This helps to minimize the formation of cell aggregates.
  3. Incubate at room temperature for 1 h or at 4°C overnight. Centrifuge at 500 g for 5 min at room temperature, and discard the supernatant.

9. Preparation of cell suspension

  1. Add 1000 µL of cell staining buffer to the tube from step 8.3 and centrifuge at 800 x g for 5 min. Discard the supernatant. Repeat this step 2x.
  2. Add 450 µL to 900 µL of deionized water to resuspend the cells. Count the cells using a hemocytometer or an automated cell counter after trypan blue staining. After counting, proceed with data collection and analysis using mass cytometry.

10. Mass cytometry and data analysis

  1. Acquire mass cytometry data using a CyTOF system and save it as Flow Cytometry Standard (FCS) files. Ensure proper instrument calibration and quality control to reduce background noise and batch effects as per the manufacturer's instructions.
  2. Preprocess the CD45+ cell population in the FCS file using the associated software. Remove debris based on cell size (forward scatter, FSC) and granularity (side scatter, SSC). Exclude doublets by sequential gating of FSC-A/FSC-H or SSC-A/SSC-H plots. Eliminate dead cells using viability staining, such as cisplatin exclusion. Gate the CD45+ population to focus on immune cells and export the gated population for further analysis.
  3. Transform the data with a cofactor of 5 and identify the main clusters using clustering software. Perform clustering based on the Spanning-tree Progression Analysis of Density-normalized Events (SPADE) algorithm, which groups cells with similar marker expression profiles into clusters26. Use Hierarchical Stochastic Neighbor Embedding (HSNE) for dimensionality reduction and identification of distinct clusters26.
  4. Perform re-clustering of the major clusters using the cytofkit package in R software for unsupervised clustering. Identify sub-clusters with PhenoGraph using default parameters.
  5. Apply Uniform Manifold Approximation and Projection (UMAP) for dimensionality reduction. Perform statistical analysis using the Wilcoxon test, considering a P-value < 0.05 as statistically significant. Visualize the results using ggplot2.

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Results

To elucidate the immunological characteristics associated with HCC, a comprehensive analysis of immune cell populations was conducted. Paired PBMCs and HCC tissue samples were collected from 4 patients with HCC. Mass cytometry profiling was performed to examine immune cell populations at the single-cell proteomic level, using two antibody panels for both PBMCs and HCC tissue samples.

After quality control, 45,326 cells were incl...

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Discussion

This study leverages mass cytometry technology to provide an in-depth analysis of both systemic and local immune responses in HCC. The application of mass cytometry in this context enables the simultaneous detection of multiple markers at a single-cell level, offering a detailed immunophenotypic characterization that is crucial for understanding the complex immune landscape of HCC. Mass cytometry has revolutionized immunological studies by facilitating high-dimensional single-cell analysis. This technique employs rare me...

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Disclosures

The authors declare that they have no conflicts of interest.

Acknowledgements

This work was supported by the National Key Research and Development Program of China (grant 2019YFA0803000 to J.S.), the Excellent Youth Foundation of Zhejiang Scientific (grant R22H1610037 to J.S.), the National Natural Science Foundation of China (grant 82173078 to J.S.), the Natural Science Foundation of Zhejiang Province (grant 2022C03037 to J.S.).

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Materials

List of materials used in this article
NameCompanyCatalog NumberComments
1×PBSHyCloneSH30256.01
10×PBSHyCloneSH30256.01
100 mm×20 mm tissue-culture-treated culture dishCorning430167
1000 mL pipette tipsRainin30389218
15 mL centrifuge tubeNEST601052
200 mL pipette tipsRainin30389241
40 mm nylon cell strainer/70-mm nylon cell strainerFalcon352340
50 mL centrifuge tubeNEST602052
70 μm syringe fifilterSangon BiotechF613462-9001
Anti-Human CCR2 Antibody (clone: K036C2)BioLegend357224
Anti-Human CCR3 Antibody (clone: 5E8)BioLegend310724
Anti-Human CCR7 Antibody (clone: G043H7)BioLegend353240
Anti-Human CD103 Antibody (clone: Ber-ACT8)BioLegend350202
Anti-Human CD115 Antibody (clone: 9-4D2-1E4)BioLegend347314
Anti-Human CD117 Antibody (clone: 104D2)BioLegend313201
Anti-human CD11b Antibody (clone: 1CRF44) BD562721
Anti-human CD11c Antibody (clone: B-ly6) BD563026
Anti-Human CD123 Antibody (clone: 6H6)BioLegend306002
Anti-Human CD127 Antibody (clone: A019D5)BioLegend351337
Anti-Human CD13 Antibody (clone: WM19)BioLegend301701
Anti-Human CD138 Antibody (clone: MI15)BioLegend356535
Anti-human CD14 Antibody (clone: HCD14)BioLegend325604
Anti-Human CD141 Antibody (clone: M80)BioLegend344102
Anti-Human CD15 Antibody (clone: QA19A61)BioLegend376302
Anti-human CD16 Antibody (clone: B7311) BD561313
Anti-Human CD161 Antibody (clone: HP-3G10)BioLegend339902
Anti-Human CD163 Antibody (clone: GHI/61)BioLegend333603
Anti-Human CD169 Antibody (clone: 7-239)BioLegend346002
Anti-human CD19 Antibody (clone: HIB19)BioLegend302226
Anti-Human CD1c Antibody (clone: L161)BioLegend331501
Anti-Human CD20 Antibody (clone: 2H7)BioLegend302301
Anti-Human CD206 Antibody (clone: 15-2)BioLegend321151
Anti-Human CD24 Antibody (clone: ML5)BioLegend311129
Anti-Human CD25 Antibody (clone: BC96)BioLegend302624
Anti-human CD3 Antibody (clone: UCHT1) BD555916
Anti-Human CD31 Antibody (clone: W18200D)BioLegend375902
Anti-Human CD32 Antibody (clone: FUN-2)BioLegend303232
Anti-Human CD326 Antibody (clone: CO17-1A)BioLegend369812
Anti-Human CD33 Antibody (clone: WM53)BioLegend303402
Anti-human CD4 Antibody (clone: L200) BD563094
Anti-Human CD45 Antibody (clone: HI30) BD563716
Anti-Human CD45RO Antibody (clone: UCHL1)BioLegend304220
Anti-human CD56 Antibody (clone: 5.1H11)BioLegend362510
Anti-Human CD64 Antibody (clone: S18012C)BioLegend399502
Anti-Human CD66b Antibody (clone: 6/40c)BioLegend392917
Anti-human CD68 Antibody (clone: Y1/82A)BioLegend333808
Anti-Human CD69 Antibody (clone: FN50)BioLegend310902
Anti-Human CD7 Antibody (clone: 4H9/CD7)BioLegend395602
Anti-human CD8 Antibody (clone: RPA-T8) BD557750
Anti-Human CD80 Antibody (clone: W17149D)BioLegend375402
Anti-Human CD86 Antibody (clone: BU63)BioLegend374202
Anti-Human FOXP3 Antibody (clone: 206D)BioLegend320101
Anti-Human HLA_ABC Antibody (clone: W6/32)BioLegend311426
Anti-human HLA-DR Antibody (clone: L243)BioLegend307650
Anti-Human IgD Antibody (clone: IA6-2)BioLegend348211
Anti-Human Ki67 Antibody (clone: Ki-67)BioLegend350501
Anti-Human PD_L2 Antibody (clone: MH22B2)BD567783
Anti-Human PD1 Antibody (clone: EH12.2H7)BioLegend329951
Anti-Human PDL1 Antibody (clone: MIH2)BioLegend393602
Anti-human TCR-γδ Antibody (clone: B1) BD740415
Cell cryopreservation solutionThermo FisherA2644601
Cell-lD CisplatinStandard BioTools201064
Cell-lD Intercalator-lrStandard BioTools201192A
Collagenase, Type IVGibco17104019
Constant-temperature shakeFAITHFULFS-50B
CyTOF SystemFluidigm CorporationHelios
CytosploreCytosplore Consortium2.3.1
Dispase IIGibco17105041
DNase IMerckDN25
Eppendorf centrifugeEppendorf5702
EQ Four Element Calibration BeadsStandard BioTools201078
FBSGibco16000-044
Ficoll-paqueCytiva17-1440-02
FinnpipetteThermo Scientific4700870
Fixation bufferThermo ScientificFB001
FlowJoBD Life Sciences10.1
Formaldehyde solutionThermo Scientific28906
Granzyme B Antibody, anti-human/mouse (clone: QA16A02)BioLegend396413
Heparin TubesBD367874
Human BD Fc Block 2.5 mg/mLBD564220
MACS Tissue Storage SolutionMiltenyi130-100-008
Maxpar Fix and Perm BufferStandard BioTools201067
Maxpar metal-coniugated antibodiesStandard BioToolsVarious
Maxpar PBSStandard BioTools201058
Maxpar WaterStandard BioTools201069
Maxpare Cell Staining BufferStandard BioTools201068
Metal-conjugated Anti-Human α-SMA Antibody (clone: 1A4)Miltenyi Biotec130-098-145
PercollMerckP4937-500ML
Permeabilization bufferThermo Scientific00833356
RBC lysis bufferBD555899
Refrigerated centrifugeEppendorf5910ri
RPMI 1640 medium GE HealthCareSH30027.0
ScalpelAPPLYGENTB6298-1
Sterile Pasteur pipetteZDANZD-H03
Tissue digestion solutionYeasen Biotech41423ES30
Tuning SolutionStandard BioTools201072
Vortex MixerThermo Scientific88882012

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Immune ProfilingCyTOF AnalysisPeripheral BloodTumor Immune ResponseSingle Cell AnalysisImmune Cell SubsetsBiomarker DiscoverySPADE Clustering
Mass Cytometry Analysis of Systemic and Local Immune Responses in Hepatocellular Carcinoma
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