Flow cytometry quantification of tumor-infiltrating lymphocytes to predict the survival of patients with diffuse large B-cell lymphoma

Abstract

Introduction: Our previous studies have demonstrated that tumor-infiltrating lymphocytes (TILs), including normal B cells, T cells, and natural killer (NK) cells, in diffuse large B-cell lymphoma (DLBCL) have a significantly favorable impact on the clinical outcomes of patients treated with standard chemoimmunotherapy. In this study, to gain a full overview of the tumor immune microenvironment (TIME), we assembled a flow cytometry cohort of 102 patients diagnosed with DLBCL at the Duke University Medical Center.

Methods: We collected diagnostic flow cytometry data, including the proportion of T cells, abnormal B cells, normal B cells, plasma cells, NK cells, monocytes, and granulocytes in fresh biopsy tissues at clinical presentation, and analyzed the correlations with patient survival and between different cell populations.

Results: We found that low T cell percentages in all viable cells and low ratios of T cells to abnormal B cells correlated with significantly poorer survival, whereas higher percentages of normal B cells among total B cells (or high ratios of normal B cells to abnormal B cells) and high percentages of NK cells among all viable cells correlated with significantly better survival in patients with DLBCL. After excluding a small number of patients with low T cell percentages, the normal B cell percentage among all B cells, but not T cell percentage among all cells, continued to show a remarkable prognostic effect. Data showed significant positive correlations between T cells and normal B cells, and between granulocytes and monocytes. Furthermore, we constructed a prognostic model based on clinical and flow cytometry factors, which divided the DLBCL cohort into two equal groups with remarkable differences in patient survival and treatment response.

Summary: TILs, including normal B cells, T cells, and NK cells, are associated with favorable clinical outcomes in DLBCL, and flow cytometry capable of quantifying the TIME may have additional clinical utility for prognostication.

Keywords: DLBCL; TIL; flow cytometry; microenvironment; normal B cells; prognosis; single-cell; tumor-infiltrating lymphocytes.

Figure 1

Flow cytometry dot plots for a representative DLBCL case with high proportions of T cells and normal B cells and low proportions of NK cells, monocytes, and granulocytes. (A) All viable cells (as determined by FSC and SSC, not shown) were evaluated by CD45 positivity and SSC (lymphocyte gate). (B) Lymphocytes were then differentiated by CD5 and CD19 where T-cells (orange) and B-cells (olive green) were distinguished. (C) Lymphocytes were also differentiated by CD10 and CD19 expression in order to isolate the CD10+/CD19+ B-cells (dark green) from the CD10-negative/CD19+ B-cells (olive green). (D) B-cells were then evaluated for kappa and lambda immunoglobulin light chain expression. Overall the K/L ratio was 0.4:1, but distinction between CD10+ and CD10-negative B-cells showed that the CD10+ B-cells were lambda-restricted (dark green) while the CD10-negative B-cells were polytypic (olive green). (E, F) Lymphocytes were also evaluated for CD3 and CD7 expression to distinguish T-cells (orange), B-cells (olive green), and NK-cells (black) (panel E). T-cells showed a normal CD4:CD8 ratio (panel F).

Figure 2

Analysis for the TIME components in the study cohort. (A) Pie chart showing the mean proportion of cell clusters in the DLBCL cohort. (B) Pearson correlation analysis. T cells showed highly significant positive correlation with normal B cells and weak negative correlation with granulocytes. Granulocytes showed significant positive correlation with monocytes (by percentage in all viable cells). Each dot in the scatter plots shows the flow cytometry result for one patient. (C) Patients with high ratios of normal B cells to abnormal B cells (that is, patients with high percentage of normal B cells in all B cells) had significant better survival in the overall cohort and in patients with high percentages of T cells in all viable cells.

Figure 3

Kaplan–Meier survival analysis. (A) T cell abundance, either by percentage of CD5+ T cells in all cells or by ratio of CD5+ T cells to abnormal B cells, was associated with significantly better survival of DLBCL patients. (B) High percentages of NK cells in all cells were associated with significantly better survival of patients. (C) High percentages of CD3+, CD4+, and CD8+ T cells in all cells were associated with significantly better survival of DLBCL patients with data available. The effect by CD8+ T cells was most significant. (D) Three DLBCL cases with a high percentage of granulocytes in all cells (>50%) had significantly poorer survival. (E) Distribution plot illustrating patient groups stratified by immune cell proportions with significant prognostic differences in the study cohort. One column represents one patient.

Figure 4

Patient groups stratified by LASSO-Cox regression analysis. (A) Left: Distribution of the patients with high-risk score (red color) and low-risk score (green color). Right: Scatter plot showing distribution of OS duration (years) of dead/alive patients according to the last follow-up data. (B) DLBCL patients with low-risk score had a higher complete remission rate compared with the high-risk group. (C, D) Kaplan-Meier curves showing that patients with high-risk scores (yellow lines) had significantly poorer overall survival (OS) and progression-free survival (PFS) than patients with low-risk scores (blue lines).