Systematic analysis of mRNA expression profiles in NSCLC cell lines to screen metastasis-related genes

A Novel Hypoxia-Related Gene Signature with Strong Predicting Ability in Non-Small-Cell Lung Cancer Identified by Comprehensive Profiling

Background

Non-small-cell lung cancer (NSCLC) is the most common malignant tumor among males and females worldwide. Hypoxia is a typical feature of the tumor microenvironment, and it affects cancer development. Circular RNAs (circRNAs) have been reported to sponge miRNAs to regulate target gene expression and play an essential role in tumorigenesis and progression. This study is aimed at identifying whether circRNAs could be used as the diagnostic biomarkers for NSCLC.

Methods

The heterogeneity of samples in this study was assessed by principal component analysis (PCA). Furthermore, the Gene Expression Omnibus (GEO) database was normalized by the affy R package. We further screened the differentially expressed genes (DEGs) and differentially expressed circular RNAs (DEcircRNAs) using the DEseq2 R package. Moreover, we analyzed the Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment of DEGs using the cluster profile R package. Besides, the Gene Set Enrichment Analysis (GSEA) was used to identify the biological function of DEGs. The interaction between DEGs and the competing endogenous RNAs (ceRNA) network was detected using STRING and visualized using Cytoscape. Starbase predicted the miRNAs of target hub genes, and miRanda predicted the target miRNAs of circRNAs. The RNA-seq profiler and clinical information were downloaded from The Cancer Genome Atlas (TCGA) database. Then, the variables were assessed by the univariate and multivariate Cox proportional hazard regression models. Significant variables in the univariate Cox proportional hazard regression model were included in the multivariate Cox proportional hazard regression model to analyze the association between the variables of clinical features. Furthermore, the overall survival of variables was determined by the Kaplan-Meier survival curve, and the time-dependent receiver operating characteristic (ROC) curve analysis was used to calculate and validate the risk score in NSCLC patients. Moreover, predictive nomograms were constructed and used to predict the prognostic features between the high-risk and low-risk score groups.

Results

We screened a total of 2039 DEGs, including 1293 upregulated DEGs and 746 downregulated DEGs in hypoxia-treated A549 cells. A549 cells treated with hypoxia had a total of 70 DEcircRNAs, including 21 upregulated and 49 downregulated DEcircRNAs, compared to A549 cells treated with normoxia. The upregulated genes were significantly enriched in 284 GO terms and 42 KEGG pathways, while the downregulated genes were significantly enriched in 184 GO terms and 25 KEGG pathways. Moreover, the function analysis by GSEA showed enrichment in the enzyme-linked receptor protein signaling pathway, hypoxia-inducible factor- (HIF-) 1 signaling pathway, and G protein-coupled receptor (GPCR) downstream signaling. Furthermore, six hub modules and 10 hub genes, CDC45, EXO1, PLK1, RFC4, CCNB1, CDC6, MCM10, DLGAP5, AURKA, and POLE2, were identified. The ceRNA network was constructed, and it consisted of 4 circRNAs, 14 miRNAs, and 38 mRNAs. The ROC curve was constructed and calculated. The area under the curve (AUC) value was 0.62, and the optimal threshold was 0.28. Based on the optimal threshold, the patients were divided into the high-risk score and low-risk score groups. The survival rate in the high-risk score group was lower than that in the low-risk score group. The expression of SERPINE1, STC2, and LPCAT1; clinical stage; and age of the patient were significantly correlated with the high-risk score. Moreover, nomograms were established based on the risk factors in multivariate analysis, and the median survival time, 3-year survival probability, and 5-year survival were possibly predicted according to nomograms.

Conclusion

The ceRNA network associated with NSCLC was identified, and the hub genes, circRNAs, might act as the potential biomarkers for NSCLC.

Biomarker discovery in highly invasive lung cancer cell through proteomics approaches

Lung cancer is one of the leading causes of cancer-related death worldwide. The most common type of lung cancer is non-small cell lung cancer (NSCLC). When NSCLC is detected, patients are typically already in a metastatic stage. Metastasized cancer is a major obstacle of effective treatment and understanding the mechanisms underlying metastasis is critical to treat cancer. Herein, we selected an invasive subpopulation from the human lung cancer cell line A549 using the transwell system and named it as A549-I5. Invasive and migratory activities of this cell line were analysed using wound healing, invasion, and migration assays. In addition, epithelial-mesenchymal transition (EMT) markers, such as Snail 1, Twist, Vimentin, N-cadherin and E-cadherin, were assessed through immunoblotting. In comparison to A549 cells, the invasive A549-I5 lung cancer cells had enhanced invasiveness, motility and EMT marker expression. Proteomic analysis identified 83 significantly differentially expressed proteins in A549-I5 cells. These identified proteins were classified according to their cellular functions and most were involved in cytoskeleton, redox regulation, protein degradation and protein folding. In summary, our results provide potential diagnostic markers and therapeutic candidates for the treatment of NSCLC metastasis. SIGNIFICANCE OF THE STUDY: When NSCLC is detected, most patients are already in a metastatic stage. Herein, we selected an invasive subpopulation from a human lung cancer cell line which had increased EMT markers as well as high wound healing, invasion and migration abilities. Proteomic analysis identified numerous proteins associated with functions in cytoskeleton, redox regulation, protein degradation and protein folding that were differentially expressed in these cells. These results may provide potential diagnostic markers and therapeutic candidates for the treatment of NSCLC metastasis.

NUSAP1 knockdown inhibits cell growth and metastasis of non-small-cell lung cancer through regulating BTG2/PI3K/Akt signaling

Non-small-cell lung cancer (NSCLC) is the most common malignancy along with high mortality rate worldwide. Recently, nucleolar and spindle-associated protein 1 (NUSAP1) has been reported to be involved in the malignant progression of several cancers. However, in NSCLC, the biological function of NUSAP1 and its molecular mechanism have not been reported. Here, our findings indicated that the NUSAP1 messenger RNA expression level was remarkably upregulated in NSCLC tissues compared with that of adjacent normal tissues. We also found that NUSAP1 gene expression was notably upregulated in NSCLC cell lines (A549, 95-D, H358, and H1299) compared with that of normal human bronchial epithelial cell line (16HBE). Subsequently, the biological function of NUSAP1 was investigated in A549 and H358 cells transfected with NUSAP1 small interfering RNA (siRNA), respectively. Results showed that NUSAP1 knockdown inhibited NSCLC cell proliferation, and promoted cell apoptosis. Furthermore, the number of cell migration and invasion was significantly suppressed by NUSAP1 knockdown. In addition, our results indicated that NUSAP1 knockdown increased the gene expression of B-cell translocation gene 2 (BTG2), but decreased the expression levels of phosphoinositide 3-kinase (PI3K) and phosphorylated serine/threonine kinase (p-AKT). BTG2 siRNA partly abrogates the effect of NUSAP1 knockdown on BTG2 gene expression. Fumonisin B1 (FB1), a AKT activator, reversed the effect of NUSAP1 knockdown on the biological function in NSCLC. Taken together, NUSAP1 knockdown promotes NSCLC cell apoptosis, and inhibits cell proliferation, cell migration, and invasion, which is associated with regulating BTG2/PI3K/Akt signal pathway. Our findings suggest that NUSAP1 is a promising molecular target for NSCLC treatment.

An insight into the complex roles of metallothioneins in malignant diseases with emphasis on (sub)isoforms/isoforms and epigenetics phenomena

Metallothioneins (MTs) belong to a group of small cysteine-rich proteins that are ubiquitous throughout all kingdoms. The main function of MTs is scavenging of free radicals and detoxification and homeostating of heavy metals. In humans, 16 genes localized on chromosome 16 have been identified to encode four MT isoforms labelled by numbers (MT-1-MT-4). MT-2, MT-3 and MT-4 proteins are encoded by a single gene. MT-1 comprises many (sub)isoforms. The known active MT-1 genes are MT-1A, -1B, -1E, -1F, -1G, -1H, -1M and -1X. The rest of the MT-1 genes (MT-1C, -1D, -1I, -1J and -1L) are pseudogenes. The expression and localization of individual MT (sub)isoforms and pseudogenes vary at intra-cellular level and in individual tissues. Changes in MT expression are associated with the process of carcinogenesis of various types of human malignancies, or with a more aggressive phenotype and therapeutic resistance. Hence, MT (sub)isoform profiling status could be utilized for diagnostics and therapy of tumour diseases. This review aims on a comprehensive summary of methods for analysis of MTs at (sub)isoforms levels, their expression in single tumour diseases and strategies how this knowledge can be utilized in anticancer therapy.