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Introduction

Cancer progression is determined not only by the malignant behavior of tumors but also by the immune microenvironment. The tumor immune microenvironment also plays a pivotal role in determining the clinical response of non-small-cell lung cancer (NSCLC) to immunotherapies. To understand the possible mechanisms and explore new targets in lung cancer immunotherapy, we characterized the immune profiles in NSCLC patients.

Methods

Seventy-one NSCLC patients who underwent radical resection were selected. The immune cell composition in paired tumor and adjacent normal lung tissues was tested by flow cytometry. The associations of tumor immune microenvironment characteristics with clinicopathological factors and overall survival were analyzed. Kaplan–Meier curves and Cox proportional hazards models were used to determine differences in survival.

Results

Compared with adjacent normal lung tissues, an increased proportion of CD45⁺ hematopoietic-derived cells, CD4⁺ T cell subtypes, Tregs and B cells was observed in tumor samples with a reduced frequency of myeloid cell populations. There was no significant increase in total CD8⁺ T cells, but both PD1⁺ and CD38⁺ CD8⁺ T cells were significantly enriched in tumor samples and statistically significantly associated with tumor size. In addition, positive CD38 expression was highly correlated with PD1 positivity. A high proportion of CD8⁺ T cells and a low percentage of PD1⁺ CD8⁺ T cells were statistically significantly associated with better survival in stage II and III patients, whereas a low frequency of CD38⁺ CD8⁺ T cells was statistically significantly associated with better survival in all patients and identified as an independent prognostic factor (p=0.049).

Conclusion

We profiled the immune cells in the tumor tissues of NSCLC patients using flow cytometry. The results revealed significant enrichment of infiltrating immune cells. A strong correlation was identified between CD38 and PD-1 expression on CD8⁺ T cells in tumors. CD8⁺ T cells and their subtypes play a critical role in the prediction of prognosis.