Major and minor populations of lymphocytes: local features in different stages of colon cancer - A. B. Sagakyants; E. A. Dzhenkova; E. A. Mirzoyan; I. A. Novikova; E. Yu. Zlatnik; E. S. Bondarenko; A. V. Shaposhnikov; A. A. Maslov; O. Yu. Kaymakchi; Yu. V. Przhedetskiy; A. N Shevchenko (Южно-Российский онкологический журнал, 2023)
Purpose of the study. Was to reveal characteristics of the immunocompetent cells in colon cancer (CC) according to the disease stage, and to identify prognostic factors of cancer development.Materials and methods. The study included 50 patients with CC: stage I – 4 patients (8 %), II – 25 (50 %), III – 21 (42 %). All patients underwent standard surgical intervention at the initial stage, the obtained material was used for subsequent studies: a cell suspension was obtained from the tumor tissue, peritumoral zone (1–3 cm from the tumor), which was treated with an antibody panel (Becton Dickinson, USA) to identify the main subpopulations of leukocytes and lymphocytes.Results. The tumor tissues of patients with stages I + II showed a decrease in the relative number of DP, DN, NKT and CD19+, compared to peritumoral tissues, by 33 %, 42 %, 31 % and 82 % respectively. Tumor tissues of stage III patients demonstrated elevated relative numbers of CD3+, CD4+, NK by 57 %, 34 %, 48 %, and decreased DP, DN, NKT, CD19+ by 33 %, 74 %, 31 %, 59 %, compared to peritumoral tissues. DP, DN, NKT and CD19+ in the tumor decreased by 78 %, 74 %, 39 %, 60 %, respectively, and the relative number of lymphocytes increased by 138 %, compared to the tissues of the resection line. A comparative analysis of local immunological parameters in the tumor tissues of patients with СС revealed that the relative numbers of lymphocytes and CD19+ were 58 % and 87 % higher, and DP and DN were 33 % and 27 % lower in tumor tissues of stage III patients, compared to tumor tissues of stage I + II patients.Conclusion. Thus, the obtained features of the local population and subpopulation composition of immunocompetent cells in CC, depending on the stage of the tumor process, can be used to predict the clinical course of the disease.