BackgroundForkhead box F2 (FOXF2) is relatively limited to the adult lung, but its contribution to non-small cell lung cancer (NSCLC) prognosis is unclear.ResultsFOXF2 mRNA levels in NSCLC were lower than that in paired normal lung tissues (P = 0.012). The FOXF2low patients had shorter survival time than the FOXF2high patients (P = 0.024) especially in stage I (P = 0.002), chemotherapy (P = 0.018) and < 60 age groups (P = 0.002). Lower FOXF2 mRNA levels could independently predict poorer survival for patients with NSCLC (HR = 2.384, 95% CI = 1.241–4.577; P = 0.009), especially in stage I (HR =4.367, 95% CI =1.599–11.925; P = 0.004). The two independent datasets confirmed our findings.MethodsWe examined FOXF2 mRNA levels in 84 primary NSCLC and 8 normal lung tissues using qRT-PCR. Rank-sum tests and chi-square tests were used to assess the differences among groups with various clinicopathological factors. Kaplan-Meier tests were used to compare survival status in patients with different FOXF2 mRNA levels. Cox proportional hazards regression model was used to evaluate the predictive value of FOXF2 mRNA level in NSCLC patients. Independent validation was performed using an independent dataset (98 samples) and an online survival analysis software Kaplan-Meier plotter (1928 samples).ConclusionsOur results demonstrated that decreased FOXF2 expression is an independent predictive factor for poor prognosis of patients with NSCLC, especially in stage I NSCLC.

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ObjectiveTo explore the regulatory mechanism of immune prognostic factors in thyroid cancer.MethodsBased on the TCGA database and GEO database, this study used bioinformatics methods to study the potential regulatory mechanism of thyroid cancer prognosis, analyzed the differentially expressed genes and differential miRNAs between thyroid cancer and normal paracancerous tissues by R software, and constructed lasso risk factors. The immune prognostic factors of thyroid cancer were obtained from the model, and the miRDB website was used to predict the possibility of differential miRNA target binding of the immune prognostic factors and correlation analysis was performed, and finally verified by cell experiments.ResultsThere were 1413 differentially expressed genes between thyroid cancer and normal paracancerous tissues, among which 21 immune-related genes were prognostic factors with significant differences in expression; lasso risk model obtained AKAP12, APOC1, TIMP3, ADAMTS9, ANK2, HTRA3, SYNDIG1 , ADAMTS5 and DACT1 were nine prognostic factors. A total of 58 differential miRNAs were found in thyroid cancer tissues and non-cancerous tissues. The possibility of differential miRNA targeting and binding of immune prognostic factors on the miRDB website and cell experiments was analyzed.ConclusionsThe potential miRNA regulatory mechanism of immune prognostic factors in thyroid cancer has been explored.