The expression profile and clinic significance of the SIX family in non-small cell lung cancer

Abstract

Background

The SIX family homeobox genes have been demonstrated to be involved in the tumor initiation and progression, but their clinicopathological features and prognostic values in non-small cell lung cancer (NSCLC) have not been well defined. We analyzed relevant datasets and performed a systemic review and a meta-analysis to assess the profile of SIX family members in NSCLC and evaluate their importance as biomarkers for diagnosis and prediction of NSCLC.

Methods

This meta-analysis included 17 studies with 2358 patients. Hazard ratio (HR) and 95 % confidence interval (CI) were calculated to represent the prognosis of NSCLC with expression of the SIX family genes. Heterogeneity of the ORs and HRs was assessed and quantified using the Cochrane Q and I 2 test. Begg's rank correlation method and Egger's weighted regression method were used to screen for potential publication bias. Bar graphs of representative datasets were plotted to show the correlation between the SIX expression and clinicopathological features of NSCLC. Kaplan-Meier survival curves were used to validate our prognostic analysis by pooled HR.

Results

The systematic meta-analysis unveiled that the higher expressions of SIX1-5 were associated with the greater possibility of the tumorigenesis. SIX4 and SIX6 were linked to the lymph node metastasis (LNM). SIX2, SIX3, and SIX4 were correlated with higher TNM stages. Furthermore, the elevated expressions of SIX2, SIX4, and SIX6 predicted poor overall survival (OS) in NSCLC (SIX2: HR = 1.14, 95 % CI, 1.00-1.31; SIX4: HR = 1.39, 95 % CI, 1.16-1.66; SIX6: HR = 1.18, 95 % CI, 1.00-1.38) and poor relapse-free survival (RFS) in lung adenocarcinoma (ADC) (SIX2: HR = 1.42, 95 % CI, 1.14-1.77; SIX4: HR = 1.52, 95 % CI, 1.09-2.11; SIX6: HR = 1.25, 95 % CI, 1.01-1.56).

Conclusions

Our report demonstrated that the SIX family members play distinct roles in the tumorigenesis of NSCLC and can be potential biomarkers in predicting prognosis of NSCLC patients.