Investigating the significance of tumor-infiltrating immune cells for the prognosis of lung squamous cell carcinoma

OBJECTIVE: Increasing evidence has indicated an association between immune cells infiltration in LSCC and clinical outcome. The aim of this research was tantamount to comprehensively investigate the effect of 22 tumor infiltrating immune cells (TIICs) on the prognosis of LSCC patients. METHODS: In our research, the CIBERSORT algorithm was utilized to calculate the proportion of 22 TIICs in 502 cases from the TCGA cohort. Cases with a CIBERSORT P-value of <0.05 were kept for further study. Using the CIBERSORT algorithm, we first investigated the difference of immune infiltration between normal tissue and LSCC in 22 subpopulations of immune cells. Kaplan-Meier analysis was used to analyze the effect of 22 TIICs on the prognosis of LSCC. An immune risk score model was constructed based on TIICs correlated with LSCC-related recurrence. Multivariate cox regression analysis was used to investigate whether the immune risk score was an independent factor for prognosis prediction of LSCC. Nomogram was under construction to comprehensively predict the survival rate of LSCC. RESULTS: The results of the different analysis showed that except of memory B cells, naive CD4+T cells, T cells and activated NK cells, the remaining immune cells all had differential infiltration in normal tissues and LSCC (p < 0.05). Kaplan-Meier analysis revealed two immune cells statistically related to LSCC-related recurrence, including activated mast cells and follicular helper T cells. Immune risk score model was constructed based on three immune cells including resting memory CD4+T cells, activated mast cells and follicular helper T cells retained by forward stepwise regression analysis. The Kaplan-Meier curve indicated that patients in the high-risk group linked to poor outcome (P = 8.277e−03). ROC curve indicated that the immune risk score model was reliable in predicting recurrence risk (AUC = 0.614). Multivariate cox regression analysis showed that the immune risk score model was just an independent factor for prognosis prediction of LSCC (HR = 2.99, 95% CI [1.65–5.40]; P = 0.0002). The nomogram model combined immune risk score and clinicopathologic parameter score to predict 3-year survival in patients with LSCC. CONCLUSIONS: Collectively, tumor-infiltrating immune cells play a major role in the prognosis of LSCC.