Yitong Pan1, Yeqin Sha2, Hongye Wang2, Hao Zhuang2, Xiaohan Ren3, Xianji Zhu4, Xiyi Wei3. 1. Department of Respiratory Medicine, Shanghai Pudong Hospital, Fudan University Pudong Medical Center, 2800 Gongwei Road, Huinan Town, Pudong, Shanghai 201399; Department of Bioinformatics, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, China. 2. Department of Bioinformatics, First Clinical Medical College of Nanjing Medical University, Nanjing, China. 3. Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China. 4. Department of Respiratory Medicine, Shanghai Pudong Hospital, Fudan University Pudong Medical Center, 2800 Gongwei Road, Huinan Town, Pudong, Shanghai 201399, China.
Abstract
CONTEXT: Increasing evidence has indicated an association between immune cell infiltration in lung adenocarcinoma (LUAD) and clinical outcomes. AIMS: This study aimed to investigate the effect of 22 tumor-infiltrating immune cells (TIICs) on the prognosis of patients with LUAD. SETTINGS AND DESIGN: This was a case-control study. MATERIALS AND METHODS: The CIBERSORT algorithm calculated the proportion of cases from the Cancer Genome Atlas (TCGA) cohort. Cox regression analysis evaluated the effect of TIICs on the prognosis of LUAD. The immune risk score model was constructed based on a statistical correlation. Multivariate cox regression analysis investigated independent factors. P < 0.05 was considered to be statistically significant. RESULTS: Certain immune cells had differential infiltration between normal tissues and LUAD. Univariate Cox regression analysis revealed that four immune cell types were statistically correlated with LUAD-related survival risk, and an immune risk scoring model was constructed. The results indicated that patients in the high-risk group were associated with poor outcomes. In addition, the multivariate cox analysis revealed that the immune risk scoring model was an independent factor for LUAD prognosis prediction. Ultimately, a nomogram was established to comprehensively predict the survival of LUAD patients. CONCLUSIONS: TIICs played an essential role in the prognosis of LUAD. Furthermore, the immune risk score was a poor predictive factor of LUAD, and the established model was reliable in predicting the prognosis of LUAD.
CONTEXT: Increasing evidence has indicated an association between immune cell infiltration in lung adenocarcinoma (LUAD) and clinical outcomes. AIMS: This study aimed to investigate the effect of 22 tumor-infiltrating immune cells (TIICs) on the prognosis of patients with LUAD. SETTINGS AND DESIGN: This was a case-control study. MATERIALS AND METHODS: The CIBERSORT algorithm calculated the proportion of cases from the Cancer Genome Atlas (TCGA) cohort. Cox regression analysis evaluated the effect of TIICs on the prognosis of LUAD. The immune risk score model was constructed based on a statistical correlation. Multivariate cox regression analysis investigated independent factors. P < 0.05 was considered to be statistically significant. RESULTS: Certain immune cells had differential infiltration between normal tissues and LUAD. Univariate Cox regression analysis revealed that four immune cell types were statistically correlated with LUAD-related survival risk, and an immune risk scoring model was constructed. The results indicated that patients in the high-risk group were associated with poor outcomes. In addition, the multivariate cox analysis revealed that the immune risk scoring model was an independent factor for LUAD prognosis prediction. Ultimately, a nomogram was established to comprehensively predict the survival of LUAD patients. CONCLUSIONS: TIICs played an essential role in the prognosis of LUAD. Furthermore, the immune risk score was a poor predictive factor of LUAD, and the established model was reliable in predicting the prognosis of LUAD.