Long non-coding RNA AGER-1 functionally upregulates the innate immunity gene AGER and approximates its anti-tumor effect in lung cancer

RNA epigenetics in pulmonary diseases: Insights into methylation modification of lncRNAs in lung cancer

Long non-coding RNAs (lncRNAs) are pivotal controllers of gene expression through epigenetic mechanisms, Methylation, a prominent area of study in epigenetics, significantly impacts cellular processes. Various RNA base methylations, including m6A, m5C, m1A, and 2'-O-methylation, profoundly influence lncRNA folding, interactions, and stability, thereby shaping their functionality. LncRNAs and methylation significantly contribute to tumor development, especially in lung cancer. Their roles encompass cell differentiation, proliferation, the generation of cancer stem cells, and modulation of immune responses. Recent studies have suggested that dysregulation of lncRNA methylation can contribute to lung cancer development. Furthermore, methylation modifications of lncRNAs hold potential for clinical application in lung cancer. Dysregulated lncRNA methylation can promote lung cancer progression and may offer insights into potential biomarker or therapeutic target. This review summarizes the current knowledge of lncRNA methylation in lung cancer and its implications for RNA epigenetics and pulmonary diseases.

An extensive overview of the role of lncRNAs generated from immune cells in the etiology of cancer

Long non-coding RNAs (lncRNAs) are involved in the control of critical tumor-suppressor and oncogenic pathways in cancer. These types of non-coding RNAs could affect both immune and cancer cells. The thorough analysis of lncRNAs derived from immune cells and the incorporation of new findings significantly advance our understanding of the complex role of lncRNAs in the context of cancer. This work highlights the promise of lncRNAs for translational therapeutic approaches while also establishing a solid foundation for comprehending the complex link between lncRNAs and cancer through a coherent narrative. The main findings of this article are that types of lncRNAs derived from immune cells, such as MM2P and MALAT1, can affect the behaviors of cancer cells, like invasion, angiogenesis, and proliferation. As research in this area grows, the therapeutic potential of targeting these lncRNAs offers promising opportunities for expanding our understanding of cancer biology and developing cutting-edge, precision-based therapies for cancer therapy.

Autophagy-related lncRNAs in tumor progression and drug resistance: A double-edged sword

The incidence and mortality rates of cancer are increasing every year worldwide but the survival rate of cancer patients is still unsatisfactory. Therefore, it is necessary to further elucidate the molecular mechanisms involved in tumor development and drug resistance to improve cancer cure or survival rates. In recent years, autophagy has become a hot topic in the field of oncology research, which plays a double-edged role in tumorigenesis, progression, and drug resistance. Meanwhile, long non-coding RNA (lncRNA) has also been shown to regulate autophagy, and the two-sided nature of autophagy determines the dual regulatory role of autophagy-related lncRNAs (ARlncRNAs). Therefore, ARlncRNAs can be effective therapeutic targets for various cancers. Furthermore, the high abundance and stability of ARlncRNAs in tumor tissues make them promising biomarkers. In this review, we summarized the roles and mechanisms of ARlncRNAs in tumor cell proliferation, apoptosis, migration, invasion, drug resistance, angiogenesis, radiation resistance, and immune regulation. In addition, we described the clinical significance of these ARlncRNAs, including as biomarkers/therapeutic targets and their association with clinical drugs.

AGER-1 Long Non-Coding RNA Levels Correlate with the Expression of the Advanced Glycosylation End-Product Receptor, a Regulator of the Inflammatory Response in Visceral Adipose Tissue of Women with Obesity and Type 2 Diabetes Mellitus

The advanced glycosylation end-product receptor (AGER) is involved in the development of metabolic inflammation and related complications in type 2 diabetes mellitus (T2DM). Tissue expression of the AGER gene (AGER) is regulated by epigenetic mediators, including a long non-coding RNA AGER-1 (lncAGER-1). This study aimed to investigate whether human obesity and T2DM are associated with an altered expression of AGER and lncAGER-1 in adipose tissue and, if so, whether these changes affect the local inflammatory milieu. The expression of genes encoding AGER, selected adipokines, and lncAGER-1 was assessed using real-time PCR in visceral (VAT) and subcutaneous (SAT) adipose tissue. VAT and SAT samples were obtained from 62 obese (BMI > 40 kg/m2; N = 24 diabetic) and 20 normal weight (BMI = 20-24.9 kg/m2) women, while a further 15 SAT samples were obtained from patients who were 18 to 24 months post-bariatric surgery. Tissue concentrations of adipokines were measured at the protein level using an ELISA-based method. Obesity was associated with increased AGER mRNA levels in SAT compared to normal weight status (p = 0.04) and surgical weight loss led to their significant decrease compared to pre-surgery levels (p = 0.01). Stratification by diabetic status revealed that AGER mRNA levels in VAT were higher in diabetic compared to non-diabetic women (p = 0.018). Elevated AGER mRNA levels in VAT of obese diabetic patients correlated with lncAGER-1 (p = 0.04, rs = 0.487) and with interleukin 1β (p = 0.008, rs = 0.525) and resistin (p = 0.004, rs = 0.6) mRNA concentrations. In conclusion, obesity in women is associated with increased expression of AGER in SAT, while T2DM is associated with increased AGER mRNA levels and pro-inflammatory adipokines in VAT.

Long non-coding RNAs in non-small cell lung cancer: implications for preventing therapeutic resistance

Lung cancer has the highest mortality and morbidity rates among all cancers worldwide. Despite many complex treatment options, including radiotherapy, chemotherapy, targeted drugs, immunotherapy, and combinations of these treatments, efficacy is low in cases of resistance to therapy, metastasis, and advanced disease, contributing to low overall survival. There is a pressing need for the discovery of novel biomarkers and therapeutic targets for the early diagnosis of lung cancer and to determine the efficacy and outcomes of drug treatments. There is now substantial evidence for the diagnostic and prognostic value of long noncoding RNAs (lncRNAs). This review briefly discusses recent findings on the roles and mechanisms of action of lncRNAs in the responses to therapy in non-small cell lung cancer.

Advanced Glycation End Products' Receptor DNA Methylation Associated with Immune Infiltration and Prognosis of Lung Adenocarcinoma and Lung Squamous Cell Carcinoma

Background

Advanced glycation end products' receptor (AGER) is a multiligand receptor that interacts with a wide range of ligands. Previous studies have shown that abnormal AGER expression is closely related to immune infiltration and tumorigenesis. However, the AGER DNA methylation relationship between prognosis and infiltrating immune cells in LUAD and LUSC is still unclear.

Methods

AGER expression in pan-cancer was obtained by using the UALCAN databases. Kaplan-Meier plotter showed the correlation of AGER mRNA expression levels and clinicopathological parameters. The protein expression levels for AGER were derived from Human Protein Atlas Database Analysis. The copy number, somatic mutation, and DNA methylation of AGER were presented with UCSC Xena database. TIMER platform and TISIDB website were used to show the correlation between AGER expression and tumor immune cell infiltration level.

Results

The expression level of AGER was significantly reduced in lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC). Low expression of AGER was significantly correlated with histology, stage, lymph node metastasis, and tumor protein 53 (TP53) mutation and could be used as a potential indicator of poor prognosis of LUAD and LUSC. Moreover, AGER expression was positively correlated with the infiltrating immune cells. Further analysis showed that copy number variation (CNV), mutation, and DNA methylation were involved in AGER downregulation. In addition, we also found that hypermethylated AGER was significantly correlated with tumor-infiltrating lymphocytes.

Conclusion

AGER may be a candidate for the prognostic biomarker of LUAD and LUSC related to tumor immune microenvironment.

Glycation-Associated Diabetic Nephropathy and the Role of Long Noncoding RNAs

The glycation of various biomolecules is the root cause of many pathological conditions associated with diabetic nephropathy and end-stage kidney disease. Glycation imbalances metabolism and increases renal cell injury. Numerous therapeutic measures have narrowed down the adverse effects of endogenous glycation, but efficient and potent measures are miles away. Recent advances in the identification and characterization of noncoding RNAs, especially the long noncoding RNAs (lncRNAs), have opened a mammon of new biology to explore the mitigations for glycation-associated diabetic nephropathy. Furthermore, tissue-specific distribution and condition-specific expression make lncRNA a promising key for second-generation therapeutic interventions. Though the techniques to identify and exemplify noncoding RNAs are rapidly evolving, the lncRNA study encounters multiple methodological constraints. This review will discuss lncRNAs and their possible involvement in glycation and advanced glycation end products (AGEs) signaling pathways. We further highlight the possible approaches for lncRNA-based therapeutics and their working mechanism for perturbing glycation and conclude our review with lncRNAs biology-related future opportunities.

A feature selection-based framework to identify biomarkers for cancer diagnosis: A focus on lung adenocarcinoma

Lung cancer (LC) represents most of the cancer incidences in the world. There are many types of LC, but Lung Adenocarcinoma (LUAD) is the most common type. Although RNA-seq and microarray data provide a vast amount of gene expression data, most of the genes are insignificant to clinical diagnosis. Feature selection (FS) techniques overcome the high dimensionality and sparsity issues of the large-scale data. We propose a framework that applies an ensemble of feature selection techniques to identify genes highly correlated to LUAD. Utilizing LUAD RNA-seq data from the Cancer Genome Atlas (TCGA), we employed mutual information (MI) and recursive feature elimination (RFE) feature selection techniques along with support vector machine (SVM) classification model. We have also utilized Random Forest (RF) as an embedded FS technique. The results were integrated and candidate biomarker genes across all techniques were identified. The proposed framework has identified 12 potential biomarkers that are highly correlated with different LC types, especially LUAD. A predictive model has been trained utilizing the identified biomarker expression profiling and performance of 97.99% was achieved. In addition, upon performing differential gene expression analysis, we could find that all 12 genes were significantly differentially expressed between normal and LUAD tissues, and strongly correlated with LUAD according to previous reports. We here propose that using multiple feature selection methods effectively reduces the number of identified biomarkers and directly affects their biological relevance.

Long non-coding RNAs and exosomal lncRNAs: Potential functions in lung cancer progression, drug resistance and tumor microenvironment remodeling

Among the different kinds of tumors threatening human life, lung cancer is one that is commonly observed in both males and females. The aggressive behavior of lung cancer and interactions occurring in tumor microenvironment enhances the malignancy of this tumor. The lung tumor cells have demonstrated capacity in developing chemo- and radio-resistance. LncRNAs are a category of non-coding RNAs that do not encode proteins, but their aberrant expression is responsible for tumor development, especially lung cancer. In the present review, we focus on both lncRNAs and exosomal lncRNAs in lung cancer, and their ability in regulating proliferation and metastasis. Cell cycle progression and molecular mechanisms related to lung cancer metastasis such as EMT and MMPs are regulated by lncRNAs. LncRNAs interact with miRNAs, STAT, Wnt, EZH2, PTEN and PI3K/Akt signaling pathways to affect progression of lung cancer cells. LncRNAs demonstrate both tumor-suppressor and tumor-promoting functions in lung cancer. They can be considered as biomarkers in lung cancer and especially exosomal lncRNAs present in body fluids are potential tools for minimally invasive diagnosis. Furthermore, we discuss regulation of lncRNAs by anti-cancer drugs and genetic tools as well as the role of these factors in therapy response of lung cancer cells.

RAGE is a potential biomarker implicated in immune infiltrates and cellular senescence in lung adenocarcinoma

Background

Receptor for Advanced Glycation End‐products (RAGE) is an oncogene abnormally expressed in various cancers. However, the clinical value of RAGE and the biological role of RAGE in lung cancer have not been fully investigated.

Methods

We compared the RAGE expression using several public databases. The relationship between RAGE expression and clinicopathological variables was assessed. The R software package was used to carry out enrichment analyses of RAGE co‐expression and gene set enrichment analysis (GSEA). Additionally, we used the TIMER database to assess the association between immune infiltration and RAGE expression. The correlation between RAGE expression and senescence biomarkers in lung adenocarcinoma was analyzed using the TCGA database.

Results

Our findings indicated that the expression of RAGE was downregulated in lung adenocarcinoma, and down‐regulation of RAGE was related to poor overall survival and disease‐free survival. Functional enrichment analysis indicated that RAGE co‐expression genes were mainly associated with neutrophil activation involved in immune response, neutrophil degranulation, and regulation of leukocyte‐mediated immunity. Correlation analysis revealed that RAGE expression was closely related to the purity of the tumor and immune infiltration. GSEA indicated that the RAGE‐related differential genes were mainly enriched in senescence‐related pathways. Besides, the RAGE expression was significantly associated with senescence‐related genes.

Conclusion

Down‐regulation of RAGE expression was associated with poor prognosis, as well as defective immune infiltration and cellular senescence in lung adenocarcinoma.

Development of a Machine Learning-Based Autophagy-Related lncRNA Signature to Improve Prognosis Prediction in Osteosarcoma Patients

Background

Osteosarcoma is a frequent bone malignancy in children and young adults. Despite the availability of some prognostic biomarkers, most of them fail to accurately predict prognosis in osteosarcoma patients. In this study, we used bioinformatics tools and machine learning algorithms to establish an autophagy-related long non-coding RNA (lncRNA) signature to predict the prognosis of osteosarcoma patients.

Methods

We obtained expression and clinical data from osteosarcoma patients in the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) and Gene Expression Omnibus (GEO) databases. We acquired an autophagy gene list from the Human Autophagy Database (HADb) and identified autophagy-related lncRNAs by co-expression analyses. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of the autophagy-related lncRNAs were conducted. Univariate and multivariate Cox regression analyses were performed to assess the prognostic value of the autophagy-related lncRNA signature and validate the relationship between the signature and osteosarcoma patient survival in an independent cohort. We also investigated the relationship between the signature and immune cell infiltration.

Results

We initially identified 69 autophagy-related lncRNAs, 13 of which were significant predictors of overall survival in osteosarcoma patients. Kaplan-Meier analyses revealed that the 13 autophagy-related lncRNAs could stratify patients based on their outcomes. Receiver operating characteristic curve analyses confirmed the superior prognostic value of the lncRNA signature compared to clinically used prognostic biomarkers. Importantly, the autophagy-related lncRNA signature predicted patient prognosis independently of clinicopathological characteristics. Furthermore, we found that the expression levels of the autophagy-related lncRNA signature were significantly associated with the infiltration levels of different immune cell subsets, including T cells, NK cells, and dendritic cells.

Conclusion

The autophagy-related lncRNA signature established here is an independent and robust predictor of osteosarcoma patient survival. Our findings also suggest that the expression of these 13 autophagy-related lncRNAs may promote osteosarcoma progression by regulating immune cell infiltration in the tumor microenvironment.

Immune-Related Four-lncRNA Signature for Patients with Cervical Cancer

Cervical cancer (CC) is a common gynecological malignancy for which prognostic and therapeutic biomarkers are urgently needed. The signature based on immune-related lncRNAs (IRLs) of CC has never been reported. This study is aimed at establishing an IRL signature for patients with CC. A cohort of 326 CC and 21 normal tissue samples with corresponding clinical information was included in this study. Twenty-eight IRLs were collected according to the Pearson correlation analysis between the immune score and lncRNA expression (p < 0.01). Four IRLs (BZRAP1-AS1, EMX2OS, ZNF667-AS1, and CTC-429P9.1) with the most significant prognostic values (p < 0.05) were identified which demonstrated an ability to stratify patients into the low-risk and high-risk groups by developing a risk score model. It was observed that patients in the low-risk group showed longer overall survival (OS) than those in the high-risk group in the training set, valid set, and total set. The area under the curve (AUC) of the receiver operating characteristic curve (ROC curve) for the four-IRL signature in predicting the one-, two-, and three-year survival rates was larger than 0.65. In addition, the low-risk and high-risk groups displayed different immune statuses in GSEA. These IRLs were also significantly correlated with immune cell infiltration. Our results showed that the IRL signature had a prognostic value for CC. Meanwhile, the specific mechanisms of the four IRLs in the development of CC were ascertained preliminarily.

Long noncoding RNA PANDAR inhibits the development of lung cancer by regulating autophagy and apoptosis pathways

Background: LncRNAs has been shown to play important roles in the progression of lung cancer, but it remains poorly understood whether lncRNAs affect the occurrence and development of lung cancer by regulating autophagy and apoptosis levels. Here, we investigated the roles of PANDAR in NSCLC. Materials and Methods: The expression profile and clinical application of PANDAR and its possible target gene BECN1 were tested in 276 cases of lung cancer tissues. Through some actual experiments, we explored functions of PANDAR about proliferation, apoptosis and autophagy of NSCLC cells in vitro. Results: PANDAR was found to downregulate both in lung cancer tissues and cell lines compared with corresponding controls (P < 0.05 for all), which was related to tumor stage (P < 0.05). Moreover, autophagy related gene BECN1 was also downregulated in lung cancer tissues comparison with normal tissues (P < 0.01), and there was a significant positive correlation between PANDAR and BECN1 levels (r = 0.789, P < 0.001). So, the high expression of PANDAR increased BECN1 expression levels and impaired the proliferation of NSCLC cell lines in vitro. Furthermore study showed PANDAR could regulate cell autophagy and apoptosis levels. Conclusion: These results indicated lncRNA PANDAR was a tumor suppressor and can inhibit NSCLC cell proliferation by activating autophagy and apoptosis pathways via upregulation of BECN1 expression.

Effect of AGER on the biological behavior of non‑small cell lung cancer H1299 cells

Advanced glycosylation end-product specific receptor (AGER) is a multi-ligand cell surface receptor abnormally expressed in lung cancer, and is a member of the immunoglobulin superfamily. Therefore, this study aimed to explore the effect of AGER on the biological behavior of non-small cell lung cancer (NSCLC) H1299 cell line. A microarray-based gene expression profiling analysis of the GSE27262 dataset from the Gene Expression Omnibus (GEO) database was conducted to identify differentially expressed genes, which were verified using The Cancer Genome Atlas (TCGA) database. The expression of AGER in the normal human lung BEAS-2B cell line and NSCLC H1299 cell line was examined using reverse transcription-quantitative PCR. Lentiviral interference and overexpression vectors of AGER were constructed and transfected into H1299 cells using Lipofectamine^®. AGER expression and biological properties, including cell viability, apoptosis, migration and invasion abilities, in H1299 cells were investigated using MTT, flow cytometry, wound healing and Transwell assays. AGER was expressed at a low level in NSCLC tissues and H1299 cells (P<0.05). Compared with control cells, AGER overexpression cells displayed decreased cell viability, proliferation, migration and invasion abilities, and significantly increased levels of apoptosis. Furthermore, AGER overexpression increased the expression of Bax and decreased the expression of Bcl-2 in H1299 cells (P<0.05), and AGER knockdown displayed the opposite effects on H1299 cells. Therefore, AGER overexpression decreased the proliferation, invasion and migration abilities of H1299 cells, and increased apoptosis. The present study suggested that AGER might serve as a potential molecular marker for NSCLC.

miR-185 inhibits prostate cancer angiogenesis induced by the nodal/ALK4 pathway

Background

Inhibition of angiogenesis in prostatic cancer could be a brand-new method to suppress tumour progression. Nodal/ALK4 has been associated with vascularization in many cancers. However, the relationship between and role of Nodal/ALK4 and miR-185 in human prostatic cancer is still unknown.

Methods

Prostatic cancer DU145 cells and LNCaP cells were used to investigate the angiogenic effect induced by Nodal and the anti-angiogenic roles of miR-185. Colony formation assay, MTT assay, transwell assay and tube formation assay were used to explore cell proliferation, migration and tube-forming ability, respectively. A luciferase reporter assay confirmed the binding relationship between miR-185 and ALK4. The expression levels of miR-185, ALK4 and VEGF were detected by qRT-PCR and Western blotting. The effects of miR-185 and Nodal in prostate cancer were also investigated in animal experiments.

Results

VEGF expression was increased in DU145 cells and LNCaP cells after Nodal incubation, and Nodal activated the proliferation ability of prostatic cancer cells and the migration and tube-forming ability of human umbilical vein endothelial cells (HUVECs), which were all inhibited by treatment with the Nodal inhibitor SB431524. Bioinformatics analysis and luciferase assay were used to verify miR-185 as a target of ALK4. Prostatic cancer cell proliferation was inhibited by overexpression of miR-185, which was shown to regulate the migration and angiogenesis of HUVECs by targeting ALK4 for suppression. miR-185 also showed a significant inverse correlation with Nodal treatment and reversed the angiogenic effects induced by Nodal. More importantly, for the first time, xenograft experiments indicated that overexpression of miR-185 suppressed tumour development.

Conclusion

The Nodal/ALK4 pathway is important in the angiogenesis of prostate cancer and can be inhibited by targeting miR-185 to downregulate ALK4. These findings provide a new perspective on the mechanism of prostate cancer formation.

Meta-Analysis Based on Nonconvex Regularization

The widespread applications of high-throughput sequencing technology have produced a large number of publicly available gene expression datasets. However, due to the gene expression datasets have the characteristics of small sample size, high dimensionality and high noise, the application of biostatistics and machine learning methods to analyze gene expression data is a challenging task, such as the low reproducibility of important biomarkers in different studies. Meta-analysis is an effective approach to deal with these problems, but the current methods have some limitations. In this paper, we propose the meta-analysis based on three nonconvex regularization methods, which are L1/2 regularization (meta-Half), Minimax Concave Penalty regularization (meta-MCP) and Smoothly Clipped Absolute Deviation regularization (meta-SCAD). The three nonconvex regularization methods are effective approaches for variable selection developed in recent years. Through the hierarchical decomposition of coefficients, our methods not only maintain the flexibility of variable selection and improve the efficiency of selecting important biomarkers, but also summarize and synthesize scientific evidence from multiple studies to consider the relationship between different datasets. We give the efficient algorithms and the theoretical property for our methods. Furthermore, we apply our methods to the simulation data and three publicly available lung cancer gene expression datasets, and compare the performance with state-of-the-art methods. Our methods have good performance in simulation studies, and the analysis results on the three publicly available lung cancer gene expression datasets are clinically meaningful. Our methods can also be extended to other areas where datasets are heterogeneous.

Identification and Validation of Immune-Related Gene Prognostic Signature for Hepatocellular Carcinoma

Immune-related genes (IRGs) have been identified as critical drivers of the initiation and progression of hepatocellular carcinoma (HCC). This study is aimed at constructing an IRG signature for HCC and validating its prognostic value in clinical application. The prognostic signature was developed by integrating multiple IRG expression data sets from TCGA and GEO databases. The IRGs were then combined with clinical features to validate the robustness of the prognostic signature through bioinformatics tools. A total of 1039 IRGs were identified in the 657 HCC samples. Subsequently, the IRGs were subjected to univariate Cox regression and LASSO Cox regression analyses in the training set to construct an IRG signature comprising nine immune-related gene pairs (IRGPs). Functional analyses revealed that the nine IRGPs were associated with tumor immune mechanisms, including cell proliferation, cell-mediated immunity, and tumorigenesis signal pathway. Concerning the overall survival rate, the IRGPs distinctly grouped the HCC samples into the high- and low-risk groups. Also, we found that the risk score based on nine IRGPs was related to clinical and pathologic factors and remained a valid independent prognostic signature after adjusting for tumor TNM, grade, and grade in multivariate Cox regression analyses. The prognostic value of the nine IRGPs was further validated by forest and nomogram plots, which revealed that it was superior to the tumor TNM, grade, and stage. Our findings suggest that the nine-IRGP signature can be effective in determining the disease outcomes of HCC patients.

Long non-coding RNA AGER-1 inhibits colorectal cancer progression through sponging miR-182

OBJECTIVE

Abundant evidence has illustrated that long non-coding RNA (lncRNA) plays a vital role in the regulation of tumor development and progression. Ectopic expression of a novel lncRNA, termed lnc-AGER-1, has been discovered in cancers, and this lncRNA was reported to exert an anti-tumor effect. However, its biological mechanism remains unelucidated in colorectal cancer.

METHODS

A total of 159 paired colorectal cancer specimens and adjacent tissues was applied to detect the expression of lnc-AGER-1 by the quantitative Real-time PCR (qRT-PCR), and a series of functional assays was executed to uncover the role of this lncRNA on colorectal cancer.

RESULTS

We found that the expression of lnc-AGER-1 in the tumor tissues was significantly down-regulated, while compared with adjacent normal tissues (0.0115 ± 0.0718 vs. 0.0347 ± 0.157; P < 0.0001). Also, lnc-AGER-1 was observably associated with clinical T status (r = -0.184, P = 0.024). Patients with advanced T status exerted a significantly lower level of lnc-AGER-1 than those with early T status (20.0% vs. 40.7%, P = 0.021). Over-expression of lnc-AGER-1 inhibited cell proliferation and migration efficiency, and induced cell cycle arrest at the G0/G1 phase, and promoted cell apoptosis. Further research proved that lnc-AGER-1 altered the expression of its neighbor gene, AGER, through acting as a competing endogenous RNA for miR-182 in colorectal cancer.

CONCLUSION

lnc-AGER-1 has a suppressive role in colorectal cancer development via modulating AGER, which may serve as a target for colorectal cancer diagnosis and treatment.

Effects of hub genes on the clinicopathological and prognostic features of lung adenocarcinoma

Lung adenocarcinoma (LUAD) is a common malignancy; however, the majority of its underlying molecular mechanisms remain unknown. In the present study, weighted gene co-expression network analysis was applied to construct gene co-expression networks for the GSE19804 dataset, in order to screen hub genes associated with the pathogenesis of LUAD. In addition, with the aid of the Database for Annotation, Visualization and Integrated Discovery, Gene Ontology, and Kyoto Encyclopedia of Genes and Genomes, pathway enrichment analyses were performed on the genes in the selected module. Using the GSE40791 dataset and The Cancer Genome Atlas database, the hub genes were identified. It was discovered that the turquoise module was the most significant module associated with the tumor stage of LUAD. After performing functional enrichment analyses, it was indicated that the turquoise module was mainly enriched in signal transduction. Additionally, at the transcriptional and translational level, nine hub genes were identified and validated: Carbonic anhydrase 4 (CA4), platelet and endothelial cell adhesion molecule 1 (PECAM1), DnaJ member B4 (DNAJB4), advanced glycosylation end-product specific receptor (AGER), GTPase, IMAP family member 6 (GIMAP6), chromosome 10 open reading frame 54 (C10orf54), dedicator of cytokinesis 4 (DOCK4), Golgi membrane protein 1 (GOLM1) and platelet activating factor acetylhydrolase 1b catalytic subunit 3 (PAFAH1B3). CA4, PECAM1, DNAJB4, AGER, GIMAP6, C10orf54 and DOCK4 were expressed at lower levels in the tumor samples, whereas GOLM1 and PAFAH1B3 were highly expressed in tumor samples. In addition, all hub genes were associated with prognosis. In conclusion, one module and nine genes were recognized to be associated with the tumor stage of LUAD. These findings may enhance the understanding of the progression and prognosis of LUAD.

Down expression of lnc-BMP1-1 decreases that of Caveolin-1 is associated with the lung cancer susceptibility and cigarette smoking history

Lnc-BMP1-1 is a lncRNA transcribed from SFTPC (surfactant associated protein C), a lung tissue specific gene encoding pulmonary-associated surfactant protein C (SPC) that is solely secreted by alveolar typeⅡ epithelial cells, among which the ones with SFTPC+ might be transformed into lung adenocarcinoma cells. Caveolin-1 (Cav-1) is a candidate tumor suppressor gene and is vital for coping with oxidative stress induced by cigarette smoke. When comparing lung cancer tissues with their adjacent normal tissues, the expression of lnc-BMP1-1 were decreased, especially in patients with cigarette smoking history (P=0.027), and positively associated with the expression of Cav-1 (P<0.001). When comparing to A549 cells transfected with empty vector (A549-NC cells), the expression level of Cav-1 in A549 cells with over-expressed lnc-BMP1-1 (A549-BMP cells) was increased along with the decreased level of HDAC2 protein. The drug sensitivity of A549-BMP cells to Doxorubicin hydrochloride (DOX) was increased; the growth and migration capability of A549-BMP cells were inhibited along with the decreased protein level of Bcl-2 and DNMT3a; the growth of tumor in nude mice injected with A549-BMP cells were inhibited, too. Furthermore, the lnc-BMP1-1 and Cav-1 expression was also down-regulated in the human bronchial epithelial (16HBE) cells treated with cigarette smoke extract (CSE).

The characteristics of lung cancer in Xuanwei County: A review of differentially expressed genes and noncoding RNAs on cell proliferation and migration

The occurrence of lung cancers is the highest in Xuanwei County, Yunnan province, China, especially among nonsmoking women. Domestic combustion of smoky coal induces serious indoor air pollution and is considered to be the main cause of human lung cancers. The occurrence of lung cancer in Xuanwei County has unique characteristics, such as the high morbidity in nonsmoking women or people with no family history. In the present review, we summarize advances in identification of differentially expressed genes, regulatory lncRNAs and miRNAs in cell proliferation and migration of lung cancers in Xuanwei County. Moreover, several regulatory differentially expressed genes (DEGs) or noncoding RNAs have diagnostic and prognostic significance for lung cancers in Xuanwei County and have the potential to serve as biomarkers.

Analysis of Survival-Related lncRNA Landscape Identifies A Role for LINC01537 in Energy Metabolism and Lung Cancer Progression

Many long non-coding RNAs (lncRNAs) have emerged as good biomarkers and potential therapeutic targets for various cancers. We aimed to get a detailed understanding of the lncRNA landscape that is associated with lung cancer survival. A comparative analysis between our RNA sequencing (RNA-seq) data and TCGA datasets was conducted to reveal lncRNAs with significant correlations with lung cancer survival and then the association of the most promising lncRNA was validated in a cohort of 243 lung cancer patients. Comparing RNA-seq data with TCGA ones, 84 dysregulated lncRNAs were identified in lung cancer tissues, among which 10 lncRNAs were significantly associated with lung cancer survival. LINC01537 was the most significant one (p = 2.95 × 10⁻⁶). Validation analysis confirmed the downregulation of LINC01537 in lung cancer. LINC01537 was observed to inhibit tumor growth and metastasis. It also increased cellular sensitivity to nilotinib. PDE2A (phosphodiesterase 2A) was further identified to be a target of LINC01537 and it was seen that LINC01537 promoted PDE2A expression via RNA–RNA interaction to stabilize PDE2A mRNA and thus echoed effects of PDE2A on energy metabolism including both Warburg effect and mitochondrial respiration. Other regulators of tumor energy metabolism were also affected by LINC01537. These results elucidate a suppressed role of LINC01537 in lung cancer development involving tumor metabolic reprogramming, and we believe that it might be a biomarker for cancer survival prediction and therapy.

Potential of Zerumbone as an Anti-Cancer Agent

Cancer is still a major risk factor to public health globally, causing approximately 9.8 million deaths worldwide in 2018. Despite advances in conventional treatment modalities for cancer treatment, there are still few effective therapies available due to the lack of selectivity, adverse side effects, non-specific toxicities, and tumour recurrence. Therefore, there is an immediate need for essential alternative therapeutics, which can prove to be beneficial and safe against cancer. Various phytochemicals from natural sources have been found to exhibit beneficial medicinal properties against various human diseases. Zerumbone is one such compound isolated from Zingiber zerumbet Smith that possesses diverse pharmacological properties including those of antioxidant, antibacterial, antipyretic, anti-inflammatory, immunomodulatory, as well as anti-neoplastic. Zerumbone has shown its anti-cancer effects by causing significant suppression of proliferation, survival, angiogenesis, invasion, and metastasis through the molecular modulation of different pathways such as NF-κB, Akt, and IL-6/JAK2/STAT3 (interleukin-6/janus kinase-2/signal transducer and activator of transcription 3) and their downstream target proteins. The current review briefly summarizes the modes of action and therapeutic potential of zerumbone against various cancers.

Identification of differentially expressed genes and enriched pathways in lung cancer using bioinformatics analysis

Lung cancer is the leading cause of cancer‑associated mortality worldwide. The aim of the present study was to identify the differentially expressed genes (DEGs) and enriched pathways in lung cancer by bioinformatics analysis, and to provide potential targets for diagnosis and treatment. Valid microarray data of 31 pairs of lung cancer tissues and matched normal samples (GSE19804) were obtained from the Gene Expression Omnibus database. Significance analysis of the gene expression profile was used to identify DEGs between cancer tissues and normal tissues, and a total of 1,970 DEGs, which were significantly enriched in biological processes, were screened. Through the Gene Ontology function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, 77 KEGG pathways associated with lung cancer were identified, among which the Toll‑like receptor pathway was observed to be important. Protein‑protein interaction network analysis extracted 1,770 nodes and 10,667 edges, and identified 10 genes with key roles in lung cancer with highest degrees, hub centrality and betweenness. Additionally, the module analysis of protein‑protein interactions revealed that 'chemokine signaling pathway', 'cell cycle' and 'pathways in cancer' had a close association with lung cancer. In conclusion, the identified DEGs, particularly the hub genes, strengthen the understanding of the development and progression of lung cancer, and certain genes (including advanced glycosylation end‑product specific receptor and epidermal growth factor receptor) may be used as candidate target molecules to diagnose, monitor and treat lung cancer.

LncRNA HOXA-AS2 positively regulates osteogenesis of mesenchymal stem cells through inactivating NF-κB signalling

As is previously reported, mesenchymal stem cells have potential ability to differentiate into osteocytes. However, the underlying mechanism during this biological process is poorly understood. In the present study, we identify a novel long non-coding RNA named HOXA-AS2 as a critical regulator during the formation of osteogenesis. Attenuation of HOXA-AS2 can reduce the calcium deposition and repress the alkaline phosphatase activity. Moreover, the expressions of osteogenic marker genes are markedly downregulated after HOXA-AS2 depletion. Mechanistically, we found HOXA-AS2 can regulate the transcriptional activity of NF-κB, a critical inhibitor of osteogenesis. More importantly, HOXA-AS2 knockdown could result in the transcriptional repression of the osteogenic master transcription factor SP7 by a NF-κB/HDAC2-coordinated H3K27 deacetylation mechanism. Based on these studies, we conclude that HOXA-AS2 may serve as a promising therapeutic target for bone tissue repair and regeneration in the near future.

Long Noncoding RNA PRRG4-4 Promotes Viability, Cell Cycle, Migration, and Invasion in Lung Cancer Cells

There is a perception that long noncoding RNA (lncRNA) has relationship with carcinogenesis. Many studies have previously identified and validated that the section of chromosome 11p13 is associated with high incidence of tumor. In this study, we investigated a new lncRNA, named lncPRRG4-4, mapped to 11p13 and suspected that lncPRRG4-4 was a potential lung cancer-related gene. To explore its role in carcinogenesis, we first demonstrated that lncPRRG4-4 was upregulated in lung cancer tissues compared with adjacent nontumor tissues and functioned as an oncogene in lung cancer cells. The lncPRRG4-4 was significantly upregulated in lung cancer tissues compared with adjacent normal counterparts (mean ± standard deviation: 0.12 ± 0.84 vs. 0.05 ± 0.22; p < 0.001). Patients with metastasis exhibited high levels of lncPRRG4-4 expression than those without metastasis in both the southern samples (p = 0.045) and eastern samples (p = 0.030), total samples (p = 0.004). In addition, downregulation of lncPRRG4-4 expression inhibited lung cancer proliferation, viability, migration, and invasion ability, arrested cell cycle, facilitated apoptosis, and vice versa. Taken together, these observations suggested that the lncPRRG4-4 functions as an oncogene in lung cancer cells.

Long non-coding RNA implicated in the invasion and metastasis of head and neck cancer: possible function and mechanisms

Head and neck cancer (HNC) ranks as the 6th most common malignancy across the world. Metastasis is a hallmark of cancer, primarily contributing to the relapse and poor prognosis of HNC. Recently, long noncoding RNAs (lncRNAs), previously considered as non-functional, are increasingly appreciated by scholars to play crucial roles in mediating HNC metastasis. LncRNAs, which are located in the nucleus and cytoplasm, mainly exert their function via epigenetic modification, transcriptional control and translational regulation. As several lncRNAs are presently demonstrated to participate in HNC metastasis, we make a summary of the functions and mechanisms regarding these lncRNAs. As shown in the literature, most lncRNAs appear to promote the metastasis of HNC. Hence, we primarily discuss the lncRNAs involved in enhancing metastasis. Additionally, more studies are needed to understand those lncRNAs without clear mechanisms. Furthermore, we introduced the upstream regulator for the aberrant expression of lncRNAs in HNC. Finally, we concisely addressed future research prospects of lncRNAs, particularly the interplay between lncRNAs and tumor immunity as well as lncRNA-targeted therapeutic techniques, and we introduced clustered regularly interspaced short palindromic repeats (CRISPR)-Display as a possibly transformative tool to study lncRNAs. Although lncRNA research is still in the initial stage, it holds great promise to be applied as a prognosticator of HNC and a therapeutic target to inhibit HNC metastasis, which could significantly enhance the outcome of HNC patients.