Microarray profiling of differentially expressed lncRNAs and mRNAs in lung adenocarcinomas and bioinformatics analysis

A novel glycosyltransferase-related lncRNA signature correlates with lung adenocarcinoma prognosis

Background

Lung adenocarcinoma (LUAD) is one of the most fatal cancers in the world. Previous studies have shown the increase in glycosylation level, and abnormal expressions of related enzymes are closely related to various cancers. Long non-coding RNAs (lncRNAs) play an important role in the proliferation, metabolism, and migration of cancer cells, but the underlying role of glycosyltransferase (GT)-related lncRNAs in LUAD remains to be elucidated.

Methods

We abstracted 14,056 lncRNAs from The Cancer Genome Atlas (TCGA) dataset and 257 GT-related genes from the Gene Set Enrichment Analysis (GSEA) database. Univariate, LASSO-penalized, and multivariate Cox regression analyses were conducted to construct a GT-related lncRNA prognosis model.

Results

A total of 2,726 GT-related lncRNAs were identified through Pearson’s correlation analysis, and eight of them were utilized to construct a GT-related lncRNA model. The overall survival (OS) of the low-risk group continued to be superior to that of the high-risk group according to the subgroups classified by clinical features. The risk model was proved to have independent prognostic characteristics for LUAD by univariate and multivariate Cox regression analyses. The status of the tumor immune microenvironment and the relevant immunotherapy response was significantly different between the two risk groups. The candidate drugs aimed at LUAD subtype differentiation were identified.

Conclusion

We constructed a risk model comprising eight GT-related lncRNAs which was identified as an independent predictor of prognoses to predict patient survival and guide-related treatments for patients with LUAD.

MicroRNA miR-3646 promotes malignancy of lung adenocarcinoma cells by suppressing sorbin and SH3 domain-containing protein 1 via the c-Jun NH2-terminal kinase signaling pathway

Lung adenocarcinoma (LUAD) is a highly malignant tumor. In this study, we examined the role of miR-3646 and its underlying mechanism in the progression of LUAD. The expression of miR-3646 and sorbin and SH3 domain-containing protein 1 (SORBS1) in LUAD tissues and cells was evaluated by quantitative reverse transcription-polymerase chain reaction. LUAD cell adhesion, proliferation, apoptosis was determined. The targeting relationship between SORBS1 and miR-3646 was verified by dual luciferase and RNA pull-down assays. In vivo assays were performed to verify the in vitro results. The expression of miR-3646 was found to be upregulated in LUAD tissues and cells. MiR-3646 overexpression stimulated the proliferation and adhesion of LUAD cells but inhibite d apoptosis, whereas a miR-3646 inhibitor produced the opposite results. Furthermore, the inhibitory effect of miR-3646 inhibitor was verified in vivo. SORBS1, a target gene identified downstream of miR-3646, was downregulated in LUAD tissues and cells. Additionally, increased SORBS1 inhibited the malignant phenotypes of LUAD cells, which was restored by miR-3646 upregulation. Additionally, western blot analysis revealed that SORBS1 ectopic expression disrupted the JNK signaling pathway, and this effect was restored by miR-3646 overexpression. Thus, this study revealed that miR-3646 promotes LUAD cell proliferation and adhesion, and reduces apoptosis by directly downregulating SORBS1 via the JNK signaling pathway. Investigation of the molecular mechanism of LUAD carcinogenesis revealed that miR-3646 may serve as a biomarker for LUAD treatment.in vivo

Neurokinin-1 receptor promotes non-small cell lung cancer progression through transactivation of EGFR

Despite the great advances in target therapy, lung cancer remains the top cause of cancer-related death worldwide. G protein-coupled receptor neurokinin-1 (NK1R) is shown to play multiple roles in various cancers; however, the pathological roles and clinical implication in lung cancer are unclarified. Here we identified NK1R as a significantly upregulated GPCR in the transcriptome and tissue array of human lung cancer samples, associated with advanced clinical stages and poor prognosis. Notably, NK1R is co-expressed with epidermal growth factor receptor (EGFR) in NSCLC patients' tissues and co-localized in the tumor cells. NK1R can crosstalk with EGFR by interacting with EGFR, transactivating EGFR phosphorylation and regulating the intracellular signaling of ERK1/2 and Akt. Activation of NK1R promotes the proliferation, colony formation, EMT, MMP2/14 expression, and migration of lung cancer cells. The inhibition of NK1R by selective antagonist aprepitant repressed cell proliferation and migration in vitro. Knockdown of NK1R significantly slowed down the tumor growth in nude mice. The sensitivity of lung cancer cells to gefitinib/osimertinib is highly increased in the presence of the selective NK1R antagonist aprepitant. Our data suggest that NK1R plays an important role in lung cancer development through EGFR signaling and the crosstalk between NK1R and EGFR may provide a potential therapeutic target for lung cancer treatment.

Overexpression of lncRNA A2M-AS1 inhibits cell growth and aggressiveness via regulating the miR-587/bone morphogenetic protein 3 axis in lung adenocarcinoma

Lung adenocarcinoma (LUAD) is a malignant tumor that occurs in the lungs. Numerous reports have substantiated the participation of long non-coding RNAs (lncRNAs) in the tumorigenesis of LUAD. Previously, lncRNA alpha-2-macroglobulin antisense RNA 1 (A2M-AS1) was confirmed to be an important regulator in the biological processes of LUAD and dysregulation of A2M-AS1 was associated with non-small cell lung cancer (NSCLC) progression. However, the precise mechanism of A2M-AS1 in LUAD has not been elucidated. Therefore, our study was designed to investigate the detailed molecular mechanism of A2M-AS1 in LUAD. Herein, the expression of lncRNA A2M-AS1, microRNA (miRNA) miR-587, and bone morphogenetic protein 3 (BMP3) in LUAD cell lines and tissues were detected by real-time quantitative polymerase chain reaction (RT-qPCR) and western blotting. The viability, proliferation, migration and invasion of LUAD cells were tested by cell counting kit-8 (CCK-8), colony formation and Transwell assays. In vivo tumor growth was investigated by xenograft animal experiment. Interactions among A2M-AS1, miR-587 and BMP3 were measured by RNA pulldown and luciferase reporter assays. In this study, A2M-AS1 was downregulated in LUAD tissues and cells and related to poor prognosis in LUAD patients. A2M-AS1 overexpression suppressed LUAD cell proliferation, migration and invasion in vitro and inhibited tumor growth in vivo. Mechanistically, A2M-AS1 directly bound with miR-587 to promote BMP3 expression in LUAD cells. Low expression of BMP3 was found in LUAD tissues and cells and was closely correlated with poor prognosis in LUAD patients. BMP3 deficiency reserved the inhibitory influence of A2M-AS1 overexpression on LUAD cell behaviors. Overall, A2M-AS1 inhibits cell growth and aggressiveness via regulating the miR-587/BMP3 axis in LUAD.

The bioinformatics analysis of RIOX2 gene in lung adenocarcinoma and squamous cell carcinoma

Lung cancer is characterized by high morbidity and mortality rates, and it has become an important public health issue worldwide. The occurrence and development of tumors is a multi-gene and multi-stage complex process. As an oncogene, ribosomal oxygenase 2 (RIOX2) has been associated with a variety of cancers. In this article, we analyzed the correlation between RIOX2 expression and methylation in lung cancer based on the databases including the cancer genome atlas (TCGA) (https://portal.gdc.cancer.gov/) and the gene expression omnibus (GEO) (https://www.ncbi.nlm.nih.gov/geo/). It was found that RIOX2 is highly expressed in lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) tissues, whose expression is negatively correlated with its methylation level. In this regard, methylation at cg09716038, cg14773523, cg14941179, and cg22299097 had a significant negative correlation with RIOX2 expression in LUAD, whereas in LUSC, methylation at cg09716038, cg14773523, cg14941179, cg22299097, cg05451573, cg10779801, and cg23629183 is negatively correlated with RIOX2 expression. According to the analysis based on the databases, RIOX2 gene could not be considered as the independent prognostic biomarker in lung adenocarcinoma or squamous cell lung cancer. However, the molecular mechanism of RIOX2 gene in the development of lung cancer may be helpful in improving lung cancer therapy.

Long non-coding RNA GLIDR accelerates the tumorigenesis of lung adenocarcinoma by miR-1270/TCF12 axis

Lung adenocarcinoma (LUAD) is a deadly cancer with a high incidence worldwide. Long noncoding RNAs (lncRNAs) have been confirmed to have the regulatory effects on the occurrence and development of LUAD. But the specific functions of lncRNA GLIDR in LUAD are still not explicit and need to be investigated. On the basis of the outcomes of RT-qPCR experiments, the relative expression of GLIDR was evidently up-regulated in LUAD cells, while that of miR-1270 was down-regulated. The down-regulation of GLIDR inhibits cell proliferation in accordance with the results of CCK-8, EdU and colony formation assays, and accelerates cell apoptosis according to the results of flow cytometry and JC-1 analyses. Luciferase reporter, RNA pull down and RIP assays indicated that GLIDR could sponge miR-1270 in LUAD. Additionally, TCF12 was proved as the target gene of miR-1270. Furthermore, rescue experiments indicated that overexpression of TCF12 could offset the inhibitory functions of silencing GLIDR on cell behaviors. In brief, this study has demonstrated that GLIDR/miR-1270/TCF12 axis plays the crucial role in LUAD, which offers a new insight into researches on molecular mechanism concerning LUAD and provides with a new perspective for LUAD treatment.

Regulatory roles of osteopontin in human lung cancer cell epithelial-to-mesenchymal transitions and responses

BACKGROUND

Lung cancer is still the main cause of death in patients with cancer, due to poor understanding of intracellular regulations. Of those, osteopontin (OPN) may induce the epithelial-to-mesenchymal transition (EMT) to promote tumor cell metastasis. The present study aims to evaluate the regulatory mechanism of internal and external OPN in the development of lung cancer.

METHODS

We evaluated genetic variations and different bioinformatics of genes in chromosome 4 among subtypes of lung cancer using global databases. We validated the expression of OPN and EMT-related proteins (e.g., E-cadherin, vimentin) in 208 non-small-cell lung cancer (NSCLC) tumors and the adjacent nontumorous tissues, further to explore the function of OPN in the progression of lung cancer, with a focus on a potential communication between OPN and EMT in the lung cancer.

RESULTS

We found that OPN might act as a target molecule in lung cancer, which is associated with lymph node metastasis, postresection recurrence/metastasis, and prognosis of patients with lung cancer. Biological behaviors and pathological responses of OPN varied among diseases, challenges, and severities. Overexpression of OPN was correlated with the existence of EMT in lung cancer tissues. Internal and external OPN plays the decisive roles in lung cancer cell movement, proliferation, and EMT formation, through the upregulation of OPN-PI3K and OPN-MEK pathways. PI3K and MEK inhibitors downregulated the process of EMT and biological behaviors of lung cancer cells, probably through altering vimentin-associated cytoskeletons.

CONCLUSION

OPN can be a metastasis-associated or specific biomarker for lung cancer and a potential target for antimetastatic treatment.

Construction of a Prognostic Immune-Related LncRNA Risk Model for Lung Adenocarcinoma

Background

Lung adenocarcinoma (LUAD) originates mainly from the mucous epithelium and glandular epithelium of the bronchi. It is the most common pathologic subtype of non-small cell lung cancer (NSCLC). At present, there is still a lack of clear criteria to predict the efficacy of immunotherapy. The 5-year survival rate for LUAD patients remains low.

Methods

All data were downloaded from The Cancer Genome Atlas (TCGA) database. We used Gene Set Enrichment Analysis (GSEA) database to obtain immune-related mRNAs. Immune-related lncRNAs were acquired by using the correlation test of the immune-related genes with R version 3.6.3 (Pearson correlation coefficient cor = 0.5, P < 0.05). The TCGA-LUAD dataset was divided into the testing set and the training set randomly. Based on the training set to perform univariate and multivariate Cox regression analyses, we screened prognostic immune-related lncRNAs and given a risk score to each sample. Samples were divided into the high-risk group and the low-risk group according to the median risk score. By the combination of Kaplan–Meier (KM) survival curve, the receiver operating characteristic (ROC) (AUC) curve, the independent risk factor analysis, and the clinical data of the samples, we assessed the accuracy of the risk model. Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were performed on the differentially expressed mRNAs between the high-risk group and the low-risk group. The differentially expressed genes related to immune response between two risk groups were analyzed to evaluate the role of the model in predicting the efficacy and effects of immunotherapy. In order to explain the internal mechanism of the risk model in predicting the efficacy of immunotherapy, we analyzed the differentially expressed genes related to epithelial-mesenchymal transition (EMT) between two risk groups. We extracted RNA from normal bronchial epithelial cell and LUAD cells and verified the expression level of lncRNAs in the risk model by a quantitative real-time polymerase chain reaction (qRT-PCR) test. We compared our risk model with other published prognostic signatures with data from an independent cohort. We transfected LUAD cell with siRNA-LINC0253. Western blot analysis was performed to observed change of EMT-related marker in protein level.

Results

Through univariate Cox regression analysis, 24 immune-related lncRNAs were found to be strongly associated with the survival of the TCGA-LUAD dataset. Utilizing multivariate Cox regression analysis, 10 lncRNAs were selected to establish the risk model. The K-M survival curves and the ROC (AUC) curves proved that the risk model has a fine predictive effect. The GO enrichment analysis indicated that the effect of the differentially expressed genes between high-risk and low-risk groups is mainly involved in immune response and intercellular interaction. The KEGG enrichment analysis indicated that the differentially expressed genes between high-risk and low-risk groups are mainly involved in endocytosis and the MAPK signaling pathway. The expression of genes related to the efficacy of immunotherapy was significantly different between the two groups. A qRT-PCR test verified the expression level of lncRNAs in LUAD cells in the risk model. The AUC of ROC of 5 years in the independent validation dataset showed that this model had superior accuracy. Western blot analysis verified the change of EMT-related marker in protein level.

Conclusion

The immune lncRNA risk model established by us could better predict the prognosis of patients with LUAD.

Microarray profiling of differentially expressed lncRNAs and mRNAs in lung adenocarcinomas and bioinformatics analysis

Long noncoding RNAs (lncRNAs) dysregulation leads to malignant progression of lung cancer. Our study profiled differentially expressed lncRNA and mRNA in tumor and normal tissues of lung adenocarcinoma (LUAD). Further, analysis of the gene expression profiles of LUAD tissues (n = 533) and normal tissues (n = 59) from The Cancer Genome Atlas (TCGA). A total of 138 lncRNAs were differentially expressed between LUAD tissues and normal tissues (false discovery rate [FDR] q < 0.05, fold change (FC) ≥ 2), a number of which are key regulators of multiple cancer and biological processes in humans. For example, lncRNA A2M‐AS1 displayed the highest correlation with the co‐expressed mRNAs, indicating that it might play a key role in regulating differential gene expression in LUAD. The data from the current study of the comprehensive lncRNA expression profile in LUAD tissues provided useful information to guide the identification of potential LUAD biomarkers.