An optimized disaggregation method for human lung tumors that preserves the phenotype and function of the immune cells

Abstract

Careful preparation of human tissues is the cornerstone of obtaining accurate data in immunologic studies. Despite the essential importance of tissue processing in tumor immunology and clinical medicine, current methods of tissue disaggregation have not been rigorously tested for data fidelity. Thus, we critically evaluated the current techniques available in the literature that are used to prepare human lung tumors for immunologic studies. We discovered that these approaches are successful at digesting cellular attachments and ECMs; however, these methods frequently alter the immune cell composition and/or expression of surface molecules. We thus developed a novel approach to prepare human lung tumors for immunologic studies by combining gentle mechanical manipulation with an optimized cocktail of enzymes used at low doses. This enzymatic digestion cocktail optimized cell yield and cell viability, retrieved all major tumor-associated cell populations, and maintained the expression of cell-surface markers for lineage definition and in vivo effector functions. To our knowledge, we present the first rigorously tested disaggregation method designed for human lung tumors.

Keywords: collagenase; enzymatic digestion; tumor-infiltrating immune cells.

Scheme 1.. Combined M&E approach: a step-by-step description.

Figure 1.. Cell yields and viabilities associated with various disaggregation methods in the combined M&E approach.

For bar graphs, each bar represents mean ± sem. Statistical analyses were performed with one-way ANOVA (*P < 0.05). Each method was tested on at least 4 tumor samples. (A) Average cell yields after disaggregation with multiple methods (millions/g). Tumors were divided into pieces of equal mass, disaggregated with different enzymatic cocktails, and the resulting single-cell suspensions counted via trypan blue exclusion, Cktl, Cocktail; Mech. disagg., mechanical disaggregation; Prot, protease. (B) Average percentage dead cells among disaggregation samples by use of trypan blue exclusion. (C) Cell viability after tumor digestion with Cocktail #2. Representative dot plots of disaggregated cells stained with Fixable Viability Dye eFluor 450 to detect live/dead cells. SSC-H, Side-scatter-height.

Figure 2.. The effects of multiple disaggregation methods on general tumor-associated immune cell-surface markers>.

Tumor tissue samples of equal mass underwent disaggregation with different enzymatic cocktails or mechanical disaggregation. The expression of the indicated surface markers within the disaggregation samples was then analyzed with flow cytometry on gated live CD45 cells. For bar graphs, each bar represents mean ± sem. Statistical analyses were performed with one-way ANOVA (*P < 0.05). Each method was tested on at least 3 tumor samples. (A and B) Graphical summaries of the proportion of CD4 and CD8 in the disaggregated tumor. (C and D) Representative dot plots displaying CD4 and CD8 expressions, respectively. One experiment of 4 is shown. Expression levels are marked in each gate, and MFIs are provided where appropriate. (E–H) Summary of the markers differentially cleaved by various disaggregation methods: HLA-DR on CD11b⁺ cells (E and F) and CD163⁺ on CD11b⁺ cells (G and H). Left panels show representative dot plots, and right panels summarize the data for all experiments.

Figure 3.. The effect of multiple disaggregation methods on tumor-associated myeloid cell-surface markers.

Tumor tissue samples of equal mass underwent disaggregation with Cocktail #2 (LC-Coll I, II, IV), CAEC, or HC-Coll I, as described previously. The expression of indicated markers was investigated by use of flow cytometry. Each bar represents mean ± sem. Statistical analyses were performed with one-way ANOVA (*P < 0.05). (A) Allophycocyanin (APC in Fig. 3) gating strategy. Dot plots depict CD11b⁺CD15^– cells; the CD14⁺CD33⁺ population was gated for further analysis. (B–F) Representative dot plots displaying the expression levels of HLA-DR, CD86, CD40, CD206, and CD54, respectively. One experiment of 4 is shown. Expression levels are marked in each gate, and MFIs are provided where appropriate. (G–J) Graphical summaries of the markers found to be differentially affected by disaggregation methods: HLA-DR^-, CD40⁺, CD206⁺, and CD54⁺, respectively.

Figure 4.. The effect of enzymatic exposure on HD peripheral blood leukocyte surface markers.

PBMCs and PBNs were incubated with PBS [control (None)], Cocktail #2 (Coll I, II, IV), or CAEC for 30 min. Lymphocyte, myeloid, and NK cell-surface markers were then analyzed by use of flow cytometry. Statistical analysis was performed with one-way ANOVA. (A–D) Representative dot plots displaying the expression levels of CD4, CD62L on CD3⁺ cells, CD62L on CD15⁺ cells, and CD56, CD33 on CD45+ cells, respectively. One of 5 experiments is shown. Expression levels are marked in each gate, and MFIs are displayed where appropriate. Control marker expression was used as a baseline.

Figure 5.. The effect of enzymatic exposure on the functional activity of HD peripheral blood leukocytes.

HD PBMCs and PBNs were incubated with PBS (control) or Cocktail #2 (Coll I, II, IV) for 30 min and then added to multiple in vitro functional assays. For bar graphs, statistical analysis was performed by Student’s t-tests (*P < 0.05). Each bar represents mean ± sem. (A) The effect of enzymatic exposure on T cell proliferation. CFSE-labeled control or Cocktail #2-treated PBMCs were stimulated with plate-bound anti-CD3 antibodies for 4 days. The proliferation of T cells was analyzed by CFSE dilution in the gated CD3⁺ cells. The histograms, representing 1 experiment of 5, show the percentage of dividing cells. (B and C) The effect of enzymatic exposure on myeloid cell regulation of T cell proliferation. CFSE-labeled T cells were stimulated with plate-bound anti-CD3/CD28 antibodies for 4 days in the presence of control or Cocktail #2-treated CD11b⁺ or CD15⁺ cells. The histograms, representing 1 experiment of 5, show the percentage of dividing T cells in the presence of CD11b⁺ cells or CD15⁺ cells. (D) Phagocytosis assay. Neutrophils were cocultured for 45 min with E. coli-pHrodo conjugates and then analyzed by flow cytometry. Representative flow cytometry dot plots from 1 of 5 experiments are shown. Percentages of cells that phagocytosed E. coli-pHrodo conjugates are displayed in gates. (E) ROS production by PMA-stimulated neutrophils, which were cultured in the presence or absence of PMA for 1 h before ROS concentration was measured in the supernatant by use of Amplex Red reagent. Graphical summary of 5 experiments is displayed. (F) Anti-tumor cytotoxicity of PMA-stimulated neutrophils. Neutrophils were cocultured in a 1:1 ratio with GFP-expressing A549 human NSCLC cells without PMA, in the presence of PMA, or the presence of PMA/apocynin (Apo) for 16 h. Graphical summary of 5 experiments is displayed.