Clinical value of CTLA4-associated microRNAs combined with inflammatory factors in the diagnosis of non-small cell lung cancer. (March 2020) - Liu, Xiaohong; Tang, Chunlian; Song, Xianda; Cheng, Lanfang; Liu, Ying; Ding, Fan; Xia, Chun; Xue, Lian; Xiao, Jun; Huang, Baorong
Background: The current study aimed to explore the value of cytotoxic T-lymphocyte-associated protein 4 (CTLA4)-associated microRNAs combined with inflammatory factors in the differential diagnosis of non-small cell lung cancer (NSCLC). Methods: A retrospective study including 245 NSCLC patients and 245 healthy controls was conducted on a testing group. A regression formula for NSCLC prediction was established based on the testing group. Two validation groups from two centres were used to assess the novel logistic regression model including 144 NSCLC patients and 144 healthy controls recruited from the Wuchang Hospital Affiliated to Wuhan University of Science and Technology, and 128 NSCLC patients and 128 healthy controls recruited from the Zhongnan Hospital of Wuhan University. Results: Predictive software and dual-luciferase reporter assays showed that miR-155-5p and miR-630 could target CTLA4 expression. The miR-155-5p and miR-630 concentrations in the NSCLC patients were significantly lower, and the neutrophil to lymphocyte ratio, hypersensitive C-reactive protein (hs-CRP), interleukin 6, cytokeratin-19-fragment (CYFRA21-1), squamous cell carcinoma antigen (SCCA) concentrations and the smoking rate were significantly higher than that in healthy controls ( P  <   0.05). A logistic regression model that included smoking, neutrophil to lymphocyte ratio, hs-CRP, interleukin 6, CYFRA21-1, SCCA, miR-155-5p and miR-630 was performed. This model presented a high discriminating value (AUC: 0.830, sensitivity/specificity: 74.6%/89.7%) than any single indicator. In the validation groups, this model still showed a high discriminating value (AUC = 0.838 with the internal validation group; AUC = 0.851 with the external validation group). Conclusion: The current model has potential significance for the non-invasive diagnosis for NSCLC.