05 June 2020 : Clinical Research
Tumor-Derived Exosomal eIF4E as a Biomarker for Survival Prediction in Patients with Non-Small Cell Lung Cancer
Qian Dong1BCE, Liangliang Dong2DEF, Sheng Liu3BCD, Yan Kong1DEF, Mi Zhang1BCD, Xingwen Wang4AG*DOI: 10.12659/MSM.923210
Med Sci Monit 2020; 26:e923210
Abstract
BACKGROUND: The aim of this study was to investigate the expression of tumor-derived exosomal RNA eIF4E (exo-eIF4E) in non-small cell lung cancer (NSCLC) and its correlation with prognosis.
MATERIAL AND METHODS: The Cancer Genome Atlas (TCGA) data was exacted to investigate the role of tissue eIF4E in NSCLC. We enrolled 99 NSCLC patients and 40 healthy volunteers with corresponding serum samples in this study. The levels of exo-eIF4E in the peripheral blood of each group were tested by quantitative polymerase chain reaction (PCR). The chi-squared test and the log-rank test were applied to analyze the correlation between the expression levels of exo-eIF4E and the patients’ clinical-pathological data, including the overall survival.
RESULTS: TCGA data showed that increased eIF4E in NSCLC tissues was associated with late-stage disease (P=0.0497) and inferior overall survival (P=0.017). The expression of exo-eIF4E in the serum of the NSCLC group was significantly higher than that in healthy individuals (P<0.001). Furthermore, advanced TNM stage (P=0.003), distant metastasis (P=0.008), and serum positive cytokeratin fragment 19 (CYFRA21-1) (P=0.023) are more likely present in NSCLC patients with higher exo-eIF4E expression. Moreover, the multivariate combined with univariate analyses verified exo-eIF4E as an independent prognostic factor for shorter overall survival (P=0.01) and progression-free survival (P=0.005). Shorter overall survival (P=0.0005) and inferior progression-free survival (P=0.0017) are more likely present in NSCLC patients with higher exo-eIF4E.
CONCLUSIONS: Tumor-derived exo-eIF4E in serum can be a practical tool to predict the prognosis of NSCLC.
Keywords: Eukaryotic Initiation Factor-4E, Exosome Multienzyme Ribonuclease Complex, Aged, 80 and over, Biomarkers, Tumor, Databases, Genetic, exosomes
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