Development and Validation of a Prognosis-Prediction Signature for Patients with Lung Adenocarcinoma Based on 11 Telomere-Related Genes.

BACKGROUND: The occurrence and progression of lung cancer are correlated with telomeres and telomerase. Telomere length is reduced in the majority of tumors, including lung cancers. Telomere length variations have been associated with lung cancer risk and may serve as therapeutic targets as well as predictive biomarkers for lung cancer. Nevertheless, the effects of telomere-associated genes on lung cancer prognosis have not been thoroughly studied. We aim to investigate the relationship between telomere-associated genes and lung cancer prognosis. METHODS: The Cancer Genome Atlas and Genotype-Tissue Expression databases were used as training sets to build a predictive model. Three integrated Gene Expression Omnibus datasets served as validation sets. Using cluster consistency analysis and regression with the least absolute shrinkage and selection operator, we developed a telomere-related gene risk signature (TMGsig) based on 11 overall survival-related genes (RBBP8, PLK1, DSG2, HOXA7, ANAPC4, CSNK1E, SYAP1, ALDOA, PHF1, MUTYH, and PGS1). RESULTS: The results indicated a negative outcome for the high-risk score group. Immunological microenvironment and somatic mutations differed between the high- and low-risk groups. A statistically significant difference existed between the low-risk and high-risk groups in terms of the expression levels of B cells and CD4 cells, and the risk score was essentially inversely linked with immune cell expression. CONCLUSIONS: TMGsig can predict outcomes in patients with lung adenocarcinoma.

MicroRNA­200a suppresses migration and invasion and enhances the radiosensitivity of NSCLC cells by inhibiting the HGF/c­Met signaling pathway.

Hepatocyte growth factor (HGF), an activator of the c­Met signaling pathway, is involved in tumor invasiveness, metastasis and radiotherapy resistance. In the present study, a novel HGF regulatory pathway in lung cancer involving micro-RNAs (miRNAs/miR) is described. Immunohistochemical staining and western blot analyses demonstrated that HGF was upregulated and associated with miR­200a downregulation in non­small cell lung cancer (NSCLC) samples compared with normal lung tissues. The association between HGF and miR­200a was associated with the degree of tumor malignancy and cell migration and invasion. miR­200a negatively regulated HGF expression by targeting the 3'­untranslated region of the HGF mRNA. miR­200a overexpression induced HGF downregulation, decreased NSCLC cell migration and invasion, promoted apoptosis, and decreased cell survival in A549 and H1299 cells in response to ionizing radiation. The present results revealed a previously uncharacterized role of miRNA­200a in regulating tumor malignancy and radiosensitivity by suppressing HGF expression, a key factor in the HGF/c­Met pathway.

MiRNA-200a expression is inverse correlation with hepatocyte growth factor expression in stromal fibroblasts and its high expression predicts a good prognosis in patients with non-small cell lung cancer.

Cancer-associated fibroblasts (CAFs) play an important role in favoring tumor progression. However, little is known concerning expression of miRNA-200a and its potential target gene hepatocyte growth factor (HGF) in CAFs. In the present study, we investigated expression levels and prognostic significance of miRNA-200a and HGF in stromal fibroblasts of non-small cell lung cancer (NSCLC), and evaluated the correlation between miRNA-200a and HGF. In situ hybridization and immunohistochemical staining were used to investigate expression levels of miRNA-200a and HGF in 134 formalin-fixed paraffin-embedded tumor specimens from clinical stage I -IIIA NSCLC, respectively. The results showed a significant inverse correlation existed between miRNA-200a and HGF expression level in stromal fibroblasts (χ2 = 21.778, p = 0.000). In vitro, the upregulation of miRNA-200a reduced expression of HGF protein in human CAFs. The 3-year overall survival (OS) rates with low and high miRNA-200a expression in stromal fibroblasts were 39.0% and 53.4%, respectively (χ2=4.25, p=0.039). The 3-year OS rates with low and high HGF expression in stromal fibroblasts were 60.3% and 31.8%, respectively (χ2=12.55, p=0.000). The multivariate analysis showed that clinical stage and HGF expression level in stromal fibroblasts were the independent predictive factors of OS. These results suggested that miRNA-200a expression was inverse correlation with HGF expression in stromal fibroblasts. High miRNA-200a and low HGF expression in stromal fibroblasts may predict a good prognosis in patients with NSCLC.