Detection of Specific Immune Cell Subpopulation Changes Associated with Systemic Immune Inflammation-Index Level in Germ Cell Tumors

Life (Basel). 2022 May 2;12(5):678. doi: 10.3390/life12050678.

Abstract

The tumor microenvironment (TME) and the host inflammatory response are closely interconnected. The interplay between systemic inflammation and the local immune response may influence tumor development and progression in various types of cancer. The systemic immune-inflammation index (SII) represents a prognostic marker for germ cell tumors (GCTs). The aim of the present study was to detect specific immune cell subpopulation changes which were associated with the SII level in chemotherapy-naïve GCT patients. In total, 51 GCT patients, prior to cisplatin-based chemotherapy, were included in the present study. Immunophenotyping of peripheral blood leukocyte subpopulations was performed using flow cytometry. The SII level was correlated with the percentage of various leukocyte subpopulations. The obtained results demonstrated that SII levels above the cut-off value of SII ≥ 1003 were associated with higher neutrophil percentages. An inverse correlation was found between the SII and the peripheral lymphocyte percentage that logically reflects the calculations of the SII index. Furthermore, the presented data also showed that in the lymphocyte subpopulation, the association with the SII was driven by T-cell subpopulations. In innate immunity-cell subpopulations, we observed a correlation between SII level and neutrophils as well as associations with eosinophil, basophil, natural killer cell and dendritic cell percentages. We suppose that the described interactions represent a manifestation of cancer-induced immune suppression. The results of the present study contribute to the elucidation of the interrelationship between tumor cells and the innate/adaptive immune system of the host.

Keywords: germ cell tumors; leukocyte subpopulations; lymphocytopenia; neutrophilia; systemic immune–inflammation index.

Grants and funding

This work was supported by the VEGA Grant Agency of the Slovak Republic under grant numbers 1/0043/18, 1/0327/19, 1/0349/21 and 2/0053/19; the Slovak Research and Development Agency under grant numbers APVV-15-0086, APVV-19-0411 and APVV-20-0158; the Ministry of Health of the Slovak Republic under grant number 2019/57-BMCSAV-1; and The Integrated Infrastructure Operational Program for the Project Systemic Public Research Infrastructure—Biobank for Cancer and Rare Diseases, ITMS: 313011AFG5; and was co-financed by the European Regional Development Fund.