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

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.