Name: Mass Cytometry Analysis of Systemic and Local Immune Responses in Hepatocellular Carcinoma (Video) | JoVE Journal
Uploaded: 2025-04-25T13:00:00.000+00:00
Duration: 8 min 25 s
Description: Learn mass cytometry analysis for profiling systemic and local immune responses in hepatocellular carcinoma using single-cell CyTOF. This method identifies 14 distinct immune cell types to advance understanding of tumor-immune interactions.

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5 minutes

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.).

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
<ol>
	<li>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.</li>
	<li>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.</li>
	<li>Tilt the centrifuge tube at 45&#176; 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.</li>
	<li>Place the centrifuge tube in the centrifuge and set the acceleration at 8 and deceleration at 3. Centrifuge at 450 x g, 4 &#176;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.</li>
	<li>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&#176;C for 5 min. After centrifugation, a pellet is formed at the bottom of the tube.</li>
	<li>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&#176;C for 5 min.</li>
	<li>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&#176;C for 2-3 months. 
	NOTE: As a general guideline, for resuspension, use 0.5 mL of 2% FBS-PBS per 1 x 106&#160;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.</li>
</ol>
2. Isolation of tumor tissue cells
NOTE: The method for the isolation of tumor tissue cells was adapted from Song et al.22.
<ol>
	<li>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.</li>
	<li>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&#160;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.</li>
	<li>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 &#176;C for 1 h. Filter the digestion solution through a 70 &#181;m filter.
	<ol>
		<li>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.</li>
	</ol>
	</li>
	<li>Centrifuge the filtrate at 500 x g for 5 min at 4&#160;&#176;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 &#176;C.</li>
	<li>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.</li>
	<li>Centrifuge the cell suspension at 500 x g for 5 min at 4 &#176;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&#160;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.</li>
</ol>
3. Cisplatin staining
<ol>
	<li>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+&#160;and Mg2+. Add cisplatin to a final concentration of 0.5 &#181;M, 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.</li>
	<li>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.</li>
</ol>
4. Fc receptor blocking
<ol>
	<li>Prepare a 50 &#181;L block mix in advance for each sample: Combine 48 &#181;L of cell staining buffer, then add 2 &#181;L of Fc blocking solution (cell staining buffer: Fc blocking solution=9:1).</li>
	<li>Suspend the cells from step 3.2 in the above mixture and let them sit at room temperature for 10 min.</li>
</ol>
5. Incubation of membrane protein antibodies
<ol>
	<li>For each cell sample obtained from step 4.2, prepare the membrane protein antibody mix by adding 1.1 &#181;L units of each antibody. Then, add cell staining buffer to reach a final volume of 55 &#181;L. At this point, the total volume is approximately 100 &#181;L. 
	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).</li>
	<li>Add 50 &#181;L of prepared antibody mix to each tube sample, bring the total volume to 100 &#181;L. Gently swirl the samples and incubate them at room temperature for 15 min.</li>
	<li>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.</li>
	<li>Discard the supernatant and briefly vortex the remaining liquid with the cell pellet to resuspend and thoroughly disperse the cell.</li>
</ol>
6. Nucleus protein staining
<ol>
	<li>Once the cells have been fully resuspended, add 500 &#181;L 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.</li>
	<li>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 &#181;L 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.</li>
	<li>Resuspend antibodies in 1x permeabilization buffer. Discard the supernatant, and add 50 &#181;L of the antibody mixture to each tube of cells. Gently pipette the cells to mix, then incubate at room temperature for 30-45 min.</li>
	<li>Add 1000 &#181;L of 1x permeabilization buffer to each tube, centrifuge at roomtemperature at 1,000 x g for 5 min, and discard the supernatant.</li>
	<li>Add 1000 &#181;L 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.</li>
</ol>
7. Cell fixation
<ol>
	<li>Prepare a 1.6% formaldehyde solution in PBS, with 1 mL needed per sample.</li>
	<li>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.</li>
	<li>Centrifuge at room temperature at 800 x g for 5 min and discard the supernatant.</li>
</ol>
8. Nuclear Intercalation Staining
<ol>
	<li>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.</li>
	<li>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.</li>
	<li>Incubate at room temperature for 1 h or at 4&#176;C overnight. Centrifuge at 500 g for 5 min at room temperature, and discard the supernatant.</li>
</ol>
9. Preparation of cell suspension
<ol>
	<li>Add 1000 &#181;L 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.</li>
	<li>Add 450 &#181;L to 900 &#181;L 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.</li>
</ol>
10. Mass cytometry and data analysis
<ol>
	<li>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&#39;s instructions.</li>
	<li>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.</li>
	<li>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.</li>
	<li>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.</li>
	<li>Apply Uniform Manifold Approximation and Projection (UMAP) for dimensionality reduction. Perform statistical analysis using the Wilcoxon test, considering a P-value &#60; 0.05 as statistically significant. Visualize the results using ggplot2.</li>
</ol>

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<li>Serban, G. M., Mănescu, I. B., Manu, D. R., Dobreanu, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Optimization+of+a+density+gradient+centrifugation+protocol+for+isolation+of+peripheral+blood+mononuclear+cells%5BTitle%5D)+AND+%22Acta+Marisiensis+-+Seria+Medica%22%5BJournal%5D)">Optimization of a density gradient centrifugation protocol for isolation of peripheral blood mononuclear cells.</a> Acta Marisiensis - Seria Medica. 64 (2), 83-90 (2018).</li>
<li>Shcherbakova, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Factors+affecting+cell+viability+during+the+enzymatic+dissociation+of+human+endocrine+tumor+tissues%5BTitle%5D)+AND+%22Biology+%28Basel%29%22%5BJournal%5D)">Factors affecting cell viability during the enzymatic dissociation of human endocrine tumor tissues.</a> Biology (Basel). 13 (9), 665(2024).</li>
<li>Devine, R. D., Alkhalaileh, H. S., Lyberger, J. M., Behbehani, G. K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Alternative+methods+of+viability+determination+in+single+cell+mass+cytometry%5BTitle%5D)+AND+%22Cytometry+A%22%5BJournal%5D)">Alternative methods of viability determination in single cell mass cytometry.</a> Cytometry A. 99 (10), 1042-1053 (2021).</li>
<li>Gonzalez, V. D., Huang, Y. W., Fantl, W. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Mass+cytometry+for+the+characterization+of+individual+cell+types+in+ovarian+solid+tumors%5BTitle%5D)+AND+%22Methods+Mol+Biol%22%5BJournal%5D)">Mass cytometry for the characterization of individual cell types in ovarian solid tumors.</a> Methods Mol Biol. 2424, 59-94 (2022).</li>
<li>Zabransky, D. J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Profiling+of+syngeneic+mouse+hcc+tumor+models+as+a+framework+to+understand+anti-pd-1+sensitive+tumor+microenvironments%5BTitle%5D)+AND+%22Hepatology%22%5BJournal%5D)">Profiling of syngeneic mouse hcc tumor models as a framework to understand anti-pd-1 sensitive tumor microenvironments.</a> Hepatology. 77 (5), 1566-1579 (2023).</li>
<li>Levine, L. S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Single-cell+analysis+by+mass+cytometry+reveals+metabolic+states+of+early-activated+cd8%28%2B%29+t+cells+during+the+primary+immune+response%5BTitle%5D)+AND+%22Immunity%22%5BJournal%5D)">Single-cell analysis by mass cytometry reveals metabolic states of early-activated cd8(+) t cells during the primary immune response.</a> Immunity. 54 (4), 829-844.e5 (2021).</li>
<li>Lv, B., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Immunotherapy%3A+Reshape+the+tumor+immune+microenvironment%5BTitle%5D)+AND+%22Front+Immunol%22%5BJournal%5D)">Immunotherapy: Reshape the tumor immune microenvironment.</a> Front Immunol. 13, 844142(2022).</li>
<li>Zhou, Z., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Deciphering+the+tumor+immune+microenvironment+from+a+multidimensional+omics+perspective%3A+Insight+into+next-generation+car-t+cell+immunotherapy+and+beyond%5BTitle%5D)+AND+%22Mol+Cancer%22%5BJournal%5D)">Deciphering the tumor immune microenvironment from a multidimensional omics perspective: Insight into next-generation car-t cell immunotherapy and beyond.</a> Mol Cancer. 23 (1), 131(2024).</li>
<li>Hsieh, W. C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Spatial+multi-omics+analyses+of+the+tumor+immune+microenvironment%5BTitle%5D)+AND+%22J+Biomed+Sci%22%5BJournal%5D)">Spatial multi-omics analyses of the tumor immune microenvironment.</a> J Biomed Sci. 29 (1), 96(2022).</li>
<li>Wang, Z., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Gdf15+induces+immunosuppression+via+cd48+on+regulatory+t+cells+in+hepatocellular+carcinoma%5BTitle%5D)+AND+%22J+Immunother+Cancer%22%5BJournal%5D)">Gdf15 induces immunosuppression via cd48 on regulatory t cells in hepatocellular carcinoma.</a> J Immunother Cancer. 9 (9), e002787(2021).</li>
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The authors declare that they have no conflicts of interest.

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...

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.

<table><tbody><tr><td>1&amp;times;PBS</td><td>HyClone</td><td>SH30256.01</td><td></td></tr><tr><td>10&amp;times;PBS</td><td>HyClone</td><td>SH30256.01</td><td></td></tr><tr><td>100 mm&amp;times;20 mm tissue-culture-treated culture dish</td><td>Corning</td><td>430167</td><td></td></tr><tr><td>1000 mL pipette tips</td><td>Rainin</td><td>30389218</td><td></td></tr><tr><td>15 mL centrifuge tube</td><td>NEST</td><td>601052</td><td></td></tr><tr><td>200 mL pipette tips</td><td>Rainin</td><td>30389241</td><td></td></tr><tr><td>40 mm nylon cell strainer/70-mm nylon cell strainer</td><td>Falcon</td><td>352340</td><td></td></tr><tr><td>50 mL centrifuge tube</td><td>NEST</td><td>602052</td><td></td></tr><tr><td>70 &amp;mu;m syringe fifilter</td><td>Sangon Biotech</td><td>F613462-9001</td><td></td></tr><tr><td>Anti-Human CCR2 Antibody (clone: K036C2)</td><td>BioLegend</td><td>357224</td><td></td></tr><tr><td>Anti-Human CCR3 Antibody (clone: 5E8)</td><td>BioLegend</td><td>310724</td><td></td></tr><tr><td>Anti-Human CCR7 Antibody (clone: G043H7)</td><td>BioLegend</td><td>353240</td><td></td></tr><tr><td>Anti-Human CD103 Antibody (clone: Ber-ACT8)</td><td>BioLegend</td><td>350202</td><td></td></tr><tr><td>Anti-Human CD115 Antibody (clone: 9-4D2-1E4)</td><td>BioLegend</td><td>347314</td><td></td></tr><tr><td>Anti-Human CD117 Antibody (clone: 104D2)</td><td>BioLegend</td><td>313201</td><td></td></tr><tr><td>Anti-human CD11b Antibody (clone: 1CRF44)&amp;nbsp;</td><td>BD</td><td>562721</td><td></td></tr><tr><td>Anti-human CD11c Antibody (clone: B-ly6)&amp;nbsp;</td><td>BD</td><td>563026</td><td></td></tr><tr><td>Anti-Human CD123 Antibody (clone: 6H6)</td><td>BioLegend</td><td>306002</td><td></td></tr><tr><td>Anti-Human CD127 Antibody (clone: A019D5)</td><td>BioLegend</td><td>351337</td><td></td></tr><tr><td>Anti-Human CD13 Antibody (clone: WM19)</td><td>BioLegend</td><td>301701</td><td></td></tr><tr><td>Anti-Human CD138 Antibody (clone: MI15)</td><td>BioLegend</td><td>356535</td><td></td></tr><tr><td>Anti-human CD14 Antibody (clone: HCD14)</td><td>BioLegend</td><td>325604</td><td></td></tr><tr><td>Anti-Human CD141 Antibody (clone: M80)</td><td>BioLegend</td><td>344102</td><td></td></tr><tr><td>Anti-Human CD15 Antibody (clone: QA19A61)</td><td>BioLegend</td><td>376302</td><td></td></tr><tr><td>Anti-human CD16 Antibody (clone: B7311)&amp;nbsp;</td><td>BD</td><td>561313</td><td></td></tr><tr><td>Anti-Human CD161 Antibody (clone: HP-3G10)</td><td>BioLegend</td><td>339902</td><td></td></tr><tr><td>Anti-Human CD163 Antibody (clone: GHI/61)</td><td>BioLegend</td><td>333603</td><td></td></tr><tr><td>Anti-Human CD169 Antibody (clone: 7-239)</td><td>BioLegend</td><td>346002</td><td></td></tr><tr><td>Anti-human CD19 Antibody (clone: HIB19)</td><td>BioLegend</td><td>302226</td><td></td></tr><tr><td>Anti-Human CD1c Antibody (clone: L161)</td><td>BioLegend</td><td>331501</td><td></td></tr><tr><td>Anti-Human CD20 Antibody (clone: 2H7)</td><td>BioLegend</td><td>302301</td><td></td></tr><tr><td>Anti-Human CD206 Antibody (clone: 15-2)</td><td>BioLegend</td><td>321151</td><td></td></tr><tr><td>Anti-Human CD24 Antibody (clone: ML5)</td><td>BioLegend</td><td>311129</td><td></td></tr><tr><td>Anti-Human CD25 Antibody (clone: BC96)</td><td>BioLegend</td><td>302624</td><td></td></tr><tr><td>Anti-human CD3 Antibody (clone: UCHT1)&amp;nbsp;</td><td>BD</td><td>555916</td><td></td></tr><tr><td>Anti-Human CD31 Antibody (clone: W18200D)</td><td>BioLegend</td><td>375902</td><td></td></tr><tr><td>Anti-Human CD32 Antibody (clone: FUN-2)</td><td>BioLegend</td><td>303232</td><td></td></tr><tr><td>Anti-Human CD326 Antibody (clone: CO17-1A)</td><td>BioLegend</td><td>369812</td><td></td></tr><tr><td>Anti-Human CD33 Antibody (clone: WM53)</td><td>BioLegend</td><td>303402</td><td></td></tr><tr><td>Anti-human CD4 Antibody (clone: L200)&amp;nbsp;</td><td>BD</td><td>563094</td><td></td></tr><tr><td>Anti-Human CD45 Antibody (clone: HI30)&amp;nbsp;</td><td>BD</td><td>563716</td><td></td></tr><tr><td>Anti-Human CD45RO Antibody (clone: UCHL1)</td><td>BioLegend</td><td>304220</td><td></td></tr><tr><td>Anti-human CD56 Antibody (clone: 5.1H11)</td><td>BioLegend</td><td>362510</td><td></td></tr><tr><td>Anti-Human CD64 Antibody (clone: S18012C)</td><td>BioLegend</td><td>399502</td><td></td></tr><tr><td>Anti-Human CD66b Antibody (clone: 6/40c)</td><td>BioLegend</td><td>392917</td><td></td></tr><tr><td>Anti-human CD68 Antibody (clone: Y1/82A)</td><td>BioLegend</td><td>333808</td><td></td></tr><tr><td>Anti-Human CD69 Antibody (clone: FN50)</td><td>BioLegend</td><td>310902</td><td></td></tr><tr><td>Anti-Human CD7 Antibody (clone: 4H9/CD7)</td><td>BioLegend</td><td>395602</td><td></td></tr><tr><td>Anti-human CD8 Antibody (clone: RPA-T8)&amp;nbsp;</td><td>BD</td><td>557750</td><td></td></tr><tr><td>Anti-Human CD80 Antibody (clone: W17149D)</td><td>BioLegend</td><td>375402</td><td></td></tr><tr><td>Anti-Human CD86 Antibody (clone: BU63)</td><td>BioLegend</td><td>374202</td><td></td></tr><tr><td>Anti-Human FOXP3 Antibody (clone: 206D)</td><td>BioLegend</td><td>320101</td><td></td></tr><tr><td>Anti-Human HLA_ABC Antibody (clone: W6/32)</td><td>BioLegend</td><td>311426</td><td></td></tr><tr><td>Anti-human HLA-DR Antibody (clone: L243)</td><td>BioLegend</td><td>307650</td><td></td></tr><tr><td>Anti-Human IgD Antibody (clone: IA6-2)</td><td>BioLegend</td><td>348211</td><td></td></tr><tr><td>Anti-Human Ki67 Antibody (clone: Ki-67)</td><td>BioLegend</td><td>350501</td><td></td></tr><tr><td>Anti-Human PD_L2 Antibody (clone: MH22B2)</td><td>BD</td><td>567783</td><td></td></tr><tr><td>Anti-Human PD1 Antibody (clone: EH12.2H7)</td><td>BioLegend</td><td>329951</td><td></td></tr><tr><td>Anti-Human PDL1 Antibody (clone: MIH2)</td><td>BioLegend</td><td>393602</td><td></td></tr><tr><td>Anti-human TCR-&amp;gamma;&amp;delta; Antibody (clone: B1)&amp;nbsp;</td><td>BD</td><td>740415</td><td></td></tr><tr><td>Cell cryopreservation solution</td><td>Thermo Fisher</td><td>A2644601</td><td></td></tr><tr><td>Cell-lD Cisplatin</td><td>Standard BioTools</td><td>201064</td><td></td></tr><tr><td>Cell-lD Intercalator-lr</td><td>Standard BioTools</td><td>201192A</td><td></td></tr><tr><td>Collagenase, Type IV</td><td>Gibco</td><td>17104019</td><td></td></tr><tr><td>Constant-temperature shake</td><td>FAITHFUL</td><td>FS-50B</td><td></td></tr><tr><td>CyTOF System</td><td>Fluidigm Corporation</td><td>Helios</td><td></td></tr><tr><td>Cytosplore</td><td>Cytosplore Consortium</td><td>2.3.1</td><td></td></tr><tr><td>Dispase II</td><td>Gibco</td><td>17105041</td><td></td></tr><tr><td>DNase I</td><td>Merck</td><td>DN25</td><td></td></tr><tr><td>Eppendorf centrifuge</td><td>Eppendorf</td><td>5702</td><td></td></tr><tr><td>EQ Four Element Calibration Beads</td><td>Standard BioTools</td><td>201078</td><td></td></tr><tr><td>FBS</td><td>Gibco</td><td>16000-044</td><td></td></tr><tr><td>Ficoll-paque</td><td>Cytiva</td><td>17-1440-02</td><td></td></tr><tr><td>Finnpipette</td><td>Thermo Scientific</td><td>4700870</td><td></td></tr><tr><td>Fixation buffer</td><td>Thermo Scientific</td><td>FB001</td><td></td></tr><tr><td>FlowJo</td><td>BD Life Sciences</td><td>10.1</td><td></td></tr><tr><td>Formaldehyde solution</td><td>Thermo Scientific</td><td>28906</td><td></td></tr><tr><td>Granzyme B Antibody, anti-human/mouse (clone: QA16A02)</td><td>BioLegend</td><td>396413</td><td></td></tr><tr><td>Heparin Tubes</td><td>BD</td><td>367874</td><td></td></tr><tr><td>Human BD Fc Block 2.5 mg/mL</td><td>BD</td><td>564220</td><td></td></tr><tr><td>MACS Tissue Storage Solution</td><td>Miltenyi</td><td>130-100-008</td><td></td></tr><tr><td>Maxpar Fix and Perm Buffer</td><td>Standard BioTools</td><td>201067</td><td></td></tr><tr><td>Maxpar metal-coniugated antibodies</td><td>Standard BioTools</td><td>Various</td><td></td></tr><tr><td>Maxpar PBS</td><td>Standard BioTools</td><td>201058</td><td></td></tr><tr><td>Maxpar Water</td><td>Standard BioTools</td><td>201069</td><td></td></tr><tr><td>Maxpare Cell Staining Buffer</td><td>Standard BioTools</td><td>201068</td><td></td></tr><tr><td>Metal-conjugated Anti-Human &amp;alpha;-SMA Antibody (clone: 1A4)</td><td>Miltenyi Biotec</td><td>130-098-145</td><td></td></tr><tr><td>Percoll</td><td>Merck</td><td>P4937-500ML</td><td></td></tr><tr><td>Permeabilization buffer</td><td>Thermo Scientific</td><td>00833356</td><td></td></tr><tr><td>RBC lysis buffer</td><td>BD</td><td>555899</td><td></td></tr><tr><td>Refrigerated centrifuge</td><td>Eppendorf</td><td>5910ri</td><td></td></tr><tr><td>RPMI 1640 medium&amp;nbsp;</td><td>GE HealthCare</td><td>SH30027.0</td><td></td></tr><tr><td>Scalpel</td><td>APPLYGEN</td><td>TB6298-1</td><td></td></tr><tr><td>Sterile Pasteur pipette</td><td>ZDAN</td><td>ZD-H03</td><td></td></tr><tr><td>Tissue digestion solution</td><td>Yeasen Biotech</td><td>41423ES30</td><td></td></tr><tr><td>Tuning Solution</td><td>Standard BioTools</td><td>201072</td><td></td></tr><tr><td>Vortex Mixer</td><td>Thermo Scientific</td><td>88882012</td><td></td></tr></tbody></table>

mass cytometry analysis of systemic and local immune responses in hepatocellular carcinoma

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

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.

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...

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.

Hepatocellular carcinoma (HCC) is one of the most common and deadliest forms of liver cancer worldwide. Despite advances in treatment, the prognosis for ...

Mass cytometry allows us to analyze both systematic and local immune responses in hepatocellular carcinoma. By profiling immune cells at the single-cell level, we identify unique subsets and the functional states linked to tumor progression, offering insights into immune evasion mechanisms and the potential therapeutic targets for personalized treatments. Our protocol uses mass cytometry to analyze over 14 markers simultaneously at the single-cell level, avoiding spectral overlap seen in traditional flow cytometry. This involves precise identification of real cell populations, and provides high dimensional data for detailed immune profiling and the biomarker discovery.[Narrator] To begin, thaw the frozen peripheral blood mononuclear cell and the hepatocarcinoma cell suspensions. After cell recovery, resuspend the cells in one milliliter of PBS without calcium and magnesium. Add cisplatin to a final concentration of 0.5 micromolar, mix well, and incubate at room temperature for two minutes. To stop the reaction, centrifuge the tubes at 500 G for five minutes at room temperature. Discard the supernatant, then add one milliliter of cell staining buffer to each tube. After centrifuging again, carefully discard the supernatant. To perform FC receptor blocking, first, prepare a 50 microliter block mix for each sample, combine 48 microliters of cell staining buffer with two microliters of FC blocking solution. Resuspend the cell pellet in the block mix and incubate. Next, add 1.1 microliters of each antibody per sample into a labeled tube to prepare the membrane protein antibody mix. Make up the volume to 55 microliters with cell staining buffer. Transfer 50 microliters of the prepared antibody mix into each sample tube, bringing the total volume to 100 microliters. Then gently swirl the samples to mix before incubating at room temperature for 15 minutes. Add one milliliters of cell staining buffer to each sample tube. Centrifuge at 500 G for five minutes at room temperature and discard the supernatant. After the final wash, briefly vortex the remaining liquid with the cell pellet to thoroughly resuspend the cells. For nucleus protein staining, add 500 microliters of the mixed fixation solution to the resuspended cells. Gently mix the samples before incubating at room temperature for 30 minutes. After incubation, centrifuge at 500 G for five minutes at room temperature and discard the supernatant. Next, pipette 1000 microliters of permeabilization buffer to each tube to wash the cells. Then centrifuge the tubes at 1000 G for five minutes at room temperature. Add 50 microliters of the antibody mixture into each tube after discarding the supernatant. Gently pipette the cells to mix thoroughly before incubating. Next, pipette 1000 microliters of permeabilization buffer to each tube, centrifuge again, then discard the supernatant. To fix the cells, add one milliliter of 1.6% formaldehyde prepared in PBS into each sample tube and vortex to mix the contents thoroughly. After incubating at room temperature for 10 minutes, centrifuge the samples and discard the supernatant. For nuclear intercalation staining, first dilute Cell-ID Intercalator Iridium with fix and permeabilization buffer. Pipette one milliliter of the intercalation solution into each sample. Gently mix and vortex. Place the samples at four degrees Celsius overnight, then centrifuge as before. When incubation is complete, pipette 1000 microliters of cell staining buffer into the tube. Centrifuge the tubes at 800 G for five minutes and discard the supernatant. Finally, resuspend the cells in 450 to 900 microliters of deionized water. Stain the cells with trypan blue for cell counting before further analysis. To begin, switch on the mass cytometer and launch the program. Analyze the samples in the CyTOF system and acquire the mass cytometric data of the peripheral blood mononuclear cells and the hepatocarcinoma cell samples. Launch the data processing software on the instrument and pre-process the CD45+ cell population in the FCS file. Then, 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. Transform the data with a co-factor of five. Next, launch the clustering software and identify the main clusters based on the SPADE algorithm, grouping cells with similar marker expression profiles into clusters. Apply hierarchical stochastic neighbor embedding, or HSNE, for dimensionality reduction and identification of distinct clusters. Then use the CyTOF kit package in our software to perform re-clustering of the major clusters. Use the PhenoGraph program to identify sub-clusters with default parameters. A total of 14 distinct cell types were identified in the peripheral blood mononuclear cell samples. Marker expression patterns for each of the 14 cell types were detailed in the heat map, showing unique expression profiles for distinct cell populations. The distribution of these cell types varied across samples with sample D having a higher proportion of CD4 T cells, samples A and B showing significant enrichment of B cells, and CD141+, conventional dendritic cells, predominantly present in sample C. Eight cell types were identified in the tissue samples including monocytes, T cells, neutrophils, natural killer cells, B cells, plasmacytoid dendritic cells, eosinophils, and myeloid dendritic cells. Marker expression profiles for the tissue cell types indicate distinct patterns for each cell population. Tissue samples showed a consistent proportion of cell types across all patients, reflecting shared immunological characteristics with hepatocellular carcinoma.

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Research

JoVE Journal

Biology

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