A new method for excavating feature lncRNA in lung adenocarcinoma based on pathway crosstalk analysis

LINC00319: Unraveling the spectrum from gene regulation to clinical applications in cancer progression

LncRNAs are RNA transcripts that exceed 200 nucleotides in length and do not encode proteins. LINC00319 is a type of lncRNA that is highly expressed in various cancers and is regulated by CCL18 and MYC. High levels of LINC00319 are associated with poorer prognosis and more malignant clinical features in cancer patients. LINC00319 can regulate the expression of downstream genes, including 2 protein-coding genes and 11 miRNAs. It participates in controlling three signaling pathways and various cellular behaviors. LINC00319 and its downstream genes are potential targets for cancer therapy and are associated with common cancer treatments. This article reviews the abnormal expression of LINC00319 in human cancers and related molecular mechanisms, providing clues for further diagnosis and treatment.

Screening of Immune-related lncRNAs in Lung Adenocarcinoma and Establishing a Survival Prognostic Risk Prediction Model

OBJECTIVE

This study aimed to improve lung adenocarcinoma (LUAD) prognosis prediction based on a signature of immune-related long non-coding RNAs (lncRNAs).

METHODS

LUAD samples from the TCGA database were divided into the immunity_H group and the immunity_L group. Differentially expressed RNAs (DERs) between the two groups were identified. Optimized immune-related lncRNAs combination was obtained using LASSO Cox regression. A prognostic risk prediction (RS) model was built and further validated in the training and validation datasets. A network among lncRNAs in the RS model, their co-expressed DERs, and the related KEGG pathways were established. Critical lncRNAs were validated in LUAD tissue samples.

RESULTS

In total, 255 DERs were obtained, and 11 immune-related lncRNAs were significantly related to prognosis. Six lncRNAs were demonstrated as an optimal combination for building the RS model, including LINC00944, LINC00930, LINC00607, LINC00582, LINC00543, and LINC00319. The KM curve and ROC curve revealed the RS model to be a reliable indicator for LUAD prognosis. LINC00944 and LINC00582 showed a co-expression relationship with the MS4A1. LINC00944, LINC00582, and MS4A1 were successfully validated in LUAD samples.

CONCLUSION

We have established a promising LUAD patient survival prediction model based on six immune-related lncRNAs. For LUAD patients, this prognostic model could guide personalized treatment.

A prospective prognostic signature for pancreatic adenocarcinoma based on ubiquitination-related mRNA-lncRNA with experimental validation in vitro and vivo

Ubiquitination-related genes (URGs) exerted a crucial part in a variety of human disease disorders; however, their association with pancreatic adenocarcinoma (PAAD) had yet to be clearly described. We aimed to comprehensively characterize the contributions of URGs in PAAD through in silico analysis and experimental validation, and then identified a robust mRNA-lncRNA-based molecular prognostic panel for patients with PAAD using bulk RNA-sequencing and single-cell RNA-sequencing data. Initially, we collected the multi-omics data from TCGA platform to depict a comprehensive landscape of URGs in pan-cancer. Furthermore, we were accurate to PAAD for in-depth analysis. Significant differences of the activation of ubiquitination pathways and the expression of URGs were detected between normal and malignant cells. Unsupervised hierarchical clustering determined two PAAD subtypes with distinct clinical outcomes, ubiquitination pathway activities, immune microenvironment, and functional annotation characteristics. The expression profiles of ubiquitination-associated mRNAs and lncRNAs in the training and validation datasets were utilized to develop and verify a novel ubiquitination-related mRNA-lncRNA prognostic panel, which had a satisfied prediction efficiency. Our ubiquitination-associated model could function as an effective prognostic index and outperformed four other recognized panels in evaluating PAAD patients' survival status. Tumor immune microenvironment, mutation burden, and chemotherapy response were intensively explored to demonstrate the underlying mechanism of prognostic difference according to our panel. Our findings also revealed that FTI-277, a farnesyltransferase inhibitor, had a better curative effect in high-risk patients, while MK-2206, an Akt allosteric inhibitor, had a superior therapeutic effect in low-risk patients. The real-time PCR results uncovered the RNA expression of AC005062.1 in all the three PAAD cell lines was elevated several thousandfold. In conclusion, our URGs-based classification panel could be triumphantly served as a prediction tool for survival evaluation in patients with PAAD, and the genes in this panel could be developed as a potential target in PAAD therapy.

Accurate prognostic prediction for patients with clear cell renal cell carcinoma using a ferroptosis-related long non-coding RNA risk model

INTRODUCTION

Ferroptosis is a recently discovered type of programmed cell death that plays a crucial role in tumor occurrence and progression. However, no prognostic model has been established yet for clear cell renal cell carcinoma (ccRCC) using ferroptosis-related long non-coding RNAs (lncRNAs).

METHODS

In the present study, lncRNA expression profiles, sex, age, TMN stage, and other clinical data of ccRCC samples were extracted from The Cancer Genome Atlas database. In addition, ferroptosis-related lncRNAs were identified using co-expression analysis, and the risk model was established using Cox regression and least absolute shrinkage and selection operator regression analyses. Log-rank test and Kaplan-Meier analysis were performed to evaluate the predictive accuracy of the risk model for the overall survival (OS) of patients with ccRCC. Moreover, the functional enrichment of ferroptosis-related lncRNAs was performed and visualized using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes.

RESULTS

Eight prognostic ferroptosis-related lncRNAs were identified, such as LINC01615, AC026401.3, LINC00944, AL590094.1, DLGAP1-AS2, AC016773.1, AC147651.1, and AP000439.2, making up the ferroptosis-related lncRNA risk model. The risk model effectively divided patients with ccRCC into high- and low-risk groups, and their survival time was calculated. The high-risk group showed significantly shorter OS compared to the low-risk group. The nomogram to predict the survival rate of the patients revealed that the risk score was the most critical factor affecting OS in patients with ccRCC. The ferroptosis-related lncRNA risk model was an independent predictor of prognostic risk assessment in patients with ccRCC.

CONCLUSION

The ferroptosis-related lncRNAs risk model and genomic clinicopathological nomogram have the potential to accurately predict the prognosis of patients with ccRCC and could serve as potential therapeutic targets in the future.

Computational prediction of disease related lncRNAs using machine learning

Long non-coding RNAs (lncRNAs), which were once considered as transcriptional noise, are now in the limelight of current research. LncRNAs play a major role in regulating various biological processes such as imprinting, cell differentiation, and splicing. The mutations of lncRNAs are involved in various complex diseases. Identifying lncRNA-disease associations has gained a lot of attention as predicting it efficiently will lead towards better disease treatment. In this study, we have developed a machine learning model that predicts disease-related lncRNAs by combining sequence and structure-based features. The features were trained on SVM and Random Forest classifiers. We have compared our method with the state-of-the-art and obtained the highest F1 score of 76% on SVM classifier. Moreover, this study has overcome two serious limitations of the reported method which are lack of redundancy checking and implementation of oversampling for balancing the positive and negative class. Our method has achieved improved performance among machine learning models reported for lncRNA-disease associations. Combining multiple features together specifically lncRNAs sequence mutation has a significant contribution to the disease related lncRNA prediction.

A Survey on Computational Methods for Investigation on ncRNA-Disease Association through the Mode of Action Perspective

Molecular and sequencing technologies have been successfully used in decoding biological mechanisms of various diseases. As revealed by many novel discoveries, the role of non-coding RNAs (ncRNAs) in understanding disease mechanisms is becoming increasingly important. Since ncRNAs primarily act as regulators of transcription, associating ncRNAs with diseases involves multiple inference steps. Leveraging the fast-accumulating high-throughput screening results, a number of computational models predicting ncRNA-disease associations have been developed. These tools suggest novel disease-related biomarkers or therapeutic targetable ncRNAs, contributing to the realization of precision medicine. In this survey, we first introduce the biological roles of different ncRNAs and summarize the databases containing ncRNA-disease associations. Then, we suggest a new trend in recent computational prediction of ncRNA-disease association, which is the mode of action (MoA) network perspective. This perspective includes integrating ncRNAs with mRNA, pathway and phenotype information. In the next section, we describe computational methodologies widely used in this research domain. Existing computational studies are then summarized in terms of their coverage of the MoA network. Lastly, we discuss the potential applications and future roles of the MoA network in terms of integrating biological mechanisms for ncRNA-disease associations.

Exosomal AP000439.2 from clear cell renal cell carcinoma induces M2 macrophage polarization to promote tumor progression through activation of STAT3

Background

Tumorigenic phenotype of M2 tumor-associated macrophages promote tumor progression in response to exosomes cues imposed by tumor cells. However, the effect and underlying mechanisms of clear cell renal cell carcinoma (ccRCC)-derived exosomes (ccRCC-exo) on instructing macrophages phenotype remains unclear.

Methods

Macrophages were cocultured with ccRCC-exo and then evaluate the polarization of macrophages and migration of ccRCC cells. The effect and mechanism of lncRNA AP000439.2 overexpressed or deleted exosomes on macrophages M2 polarization were examined. Xenograft tumor mice model was used for in vivo validation.

Results

The ccRCC-exo significantly activated macrophages to M2 phenotype presented by increased expression of transforming growth factor-beta (TGF-β) and interleukin 10 (IL-10) at mRNA and protein levels, and these M2 macrophages in turn facilitating the migration of ccRCC cells. LncRNA AP000439.2 was highly enriched in the ccRCC-exo. Overexpression of exosomal AP000439.2 promoted M2 macrophage polarization whereas AP000439.2-deficient exosome had the opposite effects. Nuclear-localized AP000439.2 directly interacted with signal transducer and activator of transcription 3 (STAT3) proteins and phosphorylated STAT3 in macrophages. RNA-Seq results showed overexpression of AP000439.2 activated NF-κB signaling pathway. Silencing of STAT3 suppressed overexpression of AP000439.2-induced up-regulation of TGF-β and IL-10 expression, and p65 phosphorylation. AP000439.2-deleted exosome inhibited tumor growth in vivo.

Conclusion

Exosomes from ccRCC deliver AP000439.2 to promote M2 macrophage polarization via STAT3, thus enhancing ccRCC progression, indicating exosomal AP000439.2 might be a novel therapeutic target in ccRCC.

Identification of Key Modules and Genes Associated with Major Depressive Disorder in Adolescents

Major depressive disorder (MDD) is a leading cause of disability worldwide. Adolescence is a crucial period for the occurrence and development of depression. There are essential distinctions between adolescent and adult depression patients, and the etiology of depressive disorder is unclear. The interactions of multiple genes in a co-expression network are likely to be involved in the physiopathology of MDD. In the present study, RNA-Seq data of mRNA were acquired from the peripheral blood of MDD in adolescents and healthy control (HC) subjects. Co-expression modules were constructed via weighted gene co-expression network analysis (WGCNA) to investigate the relationships between the underlying modules and MDD in adolescents. In the combined MDD and HC groups, the dynamic tree cutting method was utilized to assign genes to modules through hierarchical clustering. Moreover, functional enrichment analysis was conducted on those co-expression genes from interested modules. The results showed that eight modules were constructed by WGCNA. The blue module was significantly associated with MDD after multiple comparison adjustment. Several Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways associated with stress and inflammation were identified in this module, including histone methylation, apoptosis, NF-kappa β signaling pathway, and TNF signaling pathway. Five genes related to inflammation, immunity, and the nervous system were identified as hub genes: CNTNAP3, IL1RAP, MEGF9, UBE2W, and UBE2D1. All of these findings supported that MDD was associated with stress, inflammation, and immune responses, helping us to obtain a better understanding of the internal molecular mechanism and to explore biomarkers for the diagnosis or treatment of depression in adolescents.

LncRNA LINC00460: Function and mechanism in human cancer

Long non-coding RNAs (LncRNAs), which are more than 200 nucleotides in length and with limited protein-coding potential, play vital roles in the pathogenesis, tumorigenesis, and angiogenesis of cancers. Aberrant expression of lncRNAs has been detected in various carcinomas and may be correlated with oncogenesis by affecting related genes expression. Recently, an increasing number of studies have reported on long intergenic non-protein coding RNA 460 (LINC00460) in human tumor fields. LINC00460 is upregulated in diverse cancer tissues and cells. The upregulated expression level of LINC00460 is correlated with larger tumor size, tumor node metastasis (TNM) stage, lymph node metastasis, and shorter overall survival. The regulatory mechanism of LINC00460 was complex and diverse. LINC00460 could act as a competitive endogenous RNA (ceRNA), directly bind with proteins or regulate multiple pathways, which affected tumor progression. Moreover, LINC00460 was also identified to increase drug resistance, and therefore, weaken the effectiveness of tumor treatment. It has become increasingly important to investigate the roles of LINC00460 in various cancers by different mechanisms. Therefore, a more comprehensive understanding of LINC00460 is crucial to expound on the cellular function and molecular mechanism of human cancers. In this review, we refer to studies concerning LINC00460 and provide the basis for the evaluation of LINC00460 as a predicted biomarker or potential therapeutic target in malignancies, and also provide ideas for the future research of lncRNAs similar to LINC00460.

Immune infiltration landscape and immune-marker molecular typing of pulmonary fibrosis with pulmonary hypertension

BACKGROUND

Pulmonary arterial hypertension (PH) secondary to pulmonary fibrosis (PF) is one of the most common complications in PF patients, it causes severe disease and usually have a poor prognosis. Whether the combination of PH and PF is a unique disease phenotype is unclear. We aimed to screen the key modules associated with PH-PF immune infiltration based on WGCNA and identify the hub genes for molecular typing.

METHOD

Using the gene expression profile GSE24988 of PF patients with or without PH from the Gene Expression Omnibus (GEO) database, we evaluated immune cell infiltration using Cibersortx and immune cell gene signature files. Different immune cell types were screened using the Wilcoxon test; differentially expressed genes were screened using samr. The molecular pathways implicated in these differential responses were identified using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes functional enrichment analyses. A weighted co-expression network of the differential genes was constructed, relevant co-expression modules were identified, and relationships between modules and differential immune cell infiltration were calculated. The modules most relevant to this disease were identified using weighted correlation network analysis. From these, we constructed a co-expression network; using the STRING database, we integrated the values into the human protein-protein interaction network before constructing a co-expression interaction subnet, screening genes associated with immunity and unsupervised molecular typing, and analyzing the immune cell infiltration and expression of key genes in each disease type.

RESULTS

Of the 22 immune cell types from the PF GEO data, 20 different immune cell types were identified. There were 1622 differentially expressed genes (295 upregulated and 1327 downregulated). The resulting weighted co-expression network identified six co-expression modules. These were screened to identify the modules most relevant to the disease phenotype (the green module). By calculating the correlations between modules and the differentially infiltrated immune cells, extracting the green module co-expression network (46 genes), extracting 25 key genes using gene significance and module-membership thresholds, and combining these with the 10 key genes in the human protein-protein interaction network, we identified five immune cell-related marker genes that might be applied as biomarkers. Using these marker genes, we evaluated these disease samples using unsupervised clustering molecular typing.

CONCLUSION

Our results demonstrated that all PF combined with PH samples belonged to four categories. Studies on the five key genes are required to validate their diagnostic and prognostic value.

Upregulated LINC00319 aggravates neuronal injury induced by oxygen-glucose deprivation via modulating miR-200a-3p

Ischemic stroke is one of the main causes of physical disability and mortality worldwide. Long non-coding RNAs (lncRNAs) are reported to be dysregulated in various biological progressions and serve important roles in pathological processes of cerebral ischemia. However, their biological actions and potential mechanisms in the progression of ischemic stroke remain unknown. The present study aimed to investigate the functions of LINC00319 on ischemic brain injury. It was identified that LINC00319 was significantly upregulated in the Gene Expression Omnibus profile of ischemic stroke. Furthermore, LINC00319 overexpression elevated caspase-3 activity and increased the apoptotic rate of neuronal cells, as well as decreased cell viability and glucose uptake. It was also demonstrated that LINC00319 participated in oxygen-glucose deprivation (OGD)-induced cerebral ischemic injury. LINC00319 could competitively bind with microRNA (miR)-200a-3p and decrease its expression. Moreover, miR-200a-3p could partly offset the negative effects of LINC00319 overexpression on neuronal injury caused by OGD. Collectively, the present results suggested that LINC00319 promoted apoptosis and aggravated neuronal injury induced by OGD by regulating miR-200a-3p, which may be important for ischemic stroke treatment.

The Role of lncRNA PCAT6 in Cancers

Long non-coding RNA (lncRNA) PCAT6 is a member of the Prostate Cancer Associated Transcripts family of molecules. In this review, we focus on the latest studies involving PCAT6 in the diagnosis, treatment, and prognosis of malignant tumors of the digestive, respiratory, urinary, reproductive, motion, and nervous systems. PCAT6 was found to be highly expressed in gastric cancer, colon cancer, hepatocellular carcinoma, lung cancer, bladder cancer, ovarian cancer, breast cancer, cervical cancer, osteosarcoma, glioblastoma, and other tumors. PCAT6 can promote the development and progression of different types of malignant tumors through various mechanisms. Overall, these findings suggest that PCAT6 may play an increasingly vital role in the clinical assessment of these malignant tumors. It can function as an oncogene and may be used as a potential new prognostic biomarker of these tumors.

Development and validation of a novel N6-methyladenosine (m6A)-related multi- long non-coding RNA (lncRNA) prognostic signature in pancreatic adenocarcinoma

Accumulating evidence has unveiled the pivotal roles of N6-methyladenosine (m6A) in pancreatic adenocarcinoma (PAAD). However, there are not many researches to predict the prognosis of PAAD using m6A-related long non-coding RNAs (lncRNAs). Raw data from The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC), and the Genotype-Tissue Expression project (GTEx) were utilized to comprehensively analyze the expression and prognostic performances of 145 m6A-related lncRNAs in PAAD and to develop and validate a novel m6A-related multi-lncRNA prognostic signature (m6A-LPS) for PAAD patients. In total, 57 differentially expressed m6A-related lncRNAs with prognostic values were identified. Based on LASSO-Cox regression analysis, m6A-LPS was constructed and verified by using five-lncRNA expression profiles for TCGA and ICGC cohorts. PAAD patients were then divided into high- and low-risKBIE_A_1933868k subgroups with different clinical outcomes according to the median risk score; this was further verified by time-dependent receiver operating characteristic curves. Risk scores were significantly associated with clinical parameters such as histological grade and cancer status among PAAD patients. A nomogram consisting of risk score, grade, and cancer status was generated to predict the survival probability of PAAD patients, as also demonstrated by calibration curves. Discrepancies in cellular processes, signaling pathways, and immune status between the high- and low-risk subgroups were investigated by functional and single-sample gene set enrichment analyses. In conclusion, the novel m6A-LPS for PAAD patients was developed and validated, which might provide new insight into clinical decision-making and precision medicine.

A metabolism-related 4-lncRNA prognostic signature and corresponding mechanisms in intrahepatic cholangiocarcinoma

Background

Long non-coding RNA (lncRNA) plays a critical role in the malignant progression of intrahepatic cholangiocarcinoma (iCCA). This study aimed to establish a 4-lncRNA prognostic signature and explore corresponding potential mechanisms in patients with iCCA.

Methods

The original lncRNA-seq and clinical data were collected from the TCGA and GEO databases. Overlapping and differentially expressed lncRNAs (DE-lncRNAs) were further identified from transcriptome data. Univariate regression analysis was performed to screen survival-related DE-lncRNAs, which were further selected to develop an optimal signature to predict prognosis using multivariate regression analysis. The Kaplan-Meier survival curve visualized the discrimination of the signature on overall survival (OS). The area under the curve (AUC) and C-index were used to verify the predictive accuracy of the signature. Combined with clinical data, multivariate survival analysis was used to reveal the independent predictive capability of the signature. In addition, a prognostic nomogram was constructed. Finally, the common target genes of 4 lncRNAs were predicted by the co-expression method, and the corresponding functions were annotated by GO and KEGG enrichment analysis. Gene set enrichment analysis (GSEA) was also performed to explore the potential mechanism of the signature. Quantitative real-time PCR was used to evaluated the expression of 4 lncRNAs in an independent cohort.

Results

We identified and constructed a 4-lncRNA (AC138430.1, AGAP2-AS1, AP001783.1, and AP005233.2) prognostic signature using regression analysis, and it had the capability to independently predict prognosis. The AUCs were 0.952, 0.909, and 0.882 at 1, 2, and 3 years, respectively, and the C-index was 0.808, which showed good predictive capability. Subsequently, combined with clinical data, we constructed a nomogram with good clinical application. Finally, 252 target genes of all four lncRNAs were identified by the co-expression method, and functional enrichment analysis showed that the signature was strongly correlated with metabolism-related mechanisms in tumourigenesis. The same results were also validated via GSEA.

Conclusion

We demonstrated that a metabolism-related 4-lncRNA prognostic signature could be a novel biomarker and deeply explored the target genes and potential mechanism. This study will provide a promising therapeutic strategy for patients with intrahepatic cholangiocarcinoma.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08322-5.

LINC00941 Promotes Progression of Non-Small Cell Lung Cancer by Sponging miR-877-3p to Regulate VEGFA Expression

Long noncoding RNAs (lncRNAs) play critical roles in carcinoma occurrence and metastasis. LINC00941 has been found to mediate the development of gastric cancer, and LINC00941 was negatively associated with the longer overall survival of lung adenocarcinoma patients. Herein, our aim was to investigate the effects and mechanisms of LINC00941 in NSCLC progression. Microarray was used to identify the change lncRNAs in NSCLC, LINC00941 was found to increase in tumor tissues and patients' plasma. Knockdown of LINC00941 didn't modulate the proliferation of NSCLC cells, but inhibition of LINC00941 in NSCLC cells suppressed the angiogenesis ability of human umbilical vein endothelial cells (HUVECs). Moreover, LINC00941 promoted tumorigenesis in vivo, while si-LINC00941 inhibited tumor development of NSCLC. VEGFA was should to be significantly modulated by LINC00941 in NSCLC cells, then luciferase assay proved that LINC00941 regulated VEGFA expression via interacting with miR-877-3p. Followed functional experiments indicated that overexpression of LINC00941 accelerated angiogenesis and NSCLC tumor progression via miR-877-3p/VEGFA axis both in vitro and in vivo. In conclusion, our results clarified the LINC00941 function for the first time, and LINC00941 promoted the progression of NSCLC, which was mediated by miR-877-3p/VEGFA axis. This study might provide new understanding and targets for NSCLC diagnosis and treatment.

Promising role of long non-coding RNA PCAT6 in malignancies

Long non-coding RNAs (lncRNAs), a newly identified class of non-coding RNA (ncRNA), are defined as RNA molecules at least 200 nucleotides in length that are not translated into proteins. LncRNAs contribute to a wide range of biological processes and are master regulators of disease occurrence, development, and response to therapy in human malignancies. The lncRNA prostate cancer‑associated transcript 6 (PCAT6) is upregulated in various human malignancies, including lung cancer, hepatocellular carcinoma, cervical cancer, osteosarcoma, glioblastoma, colorectal cancer, breast cancer, gastric cancer, gastrointestinal stromal tumors, and pancreatic ductal adenocarcinoma. High expression of PCAT6 is closely correlated with aggressive clinicopathological characteristics and poor prognosis in cancer patients, suggesting it is an oncogenic lncRNA. PCAT6 overexpression also facilitates cell proliferation, invasion, and migration while attenuating apoptosis, indicating that it might serve as a new prognostic biomarker and therapeutic target for malignancies. Here, we discuss the molecular mechanisms, regulatory functions, and potential clinical applications of PCAT6 in cancer.

The Cancer-Testis Long Non-coding RNA PCAT6 Facilitates the Malignant Phenotype of Ovarian Cancer by Sponging miR-143-3p

Background: It has been reported that long non-coding RNAs (lncRNAs) play critical roles in tumorigenesis. However, their roles in ovarian cancer (OC) remain to be elucidated. The aim of this study was to uncover the function and underlying mechanisms of PCAT6 in OC.

Methods: The expression pattern of PCAT6 in OC was analyzed in the GSE137238, GSE143897 and Gene Expression Profile Interactive Analysis (GEPIA) datasets. Kaplan–Meier Plotter online software was used for survival analysis. Loss-of-function assays and gain-of-function assays were used to assess the function of PCAT6 in OC development. Moreover, small-RNA sequencing, bioinformatic analysis, luciferase assays and rescue experiments were carried out to clarify the potential mechanism of PCAT6 in OC.

Results: PCAT6 expression was significantly increased in OC tissues and positively correlated with advanced stages and with poor overall survival, progression-free survival and post-progression survival. Knockdown of PCAT6 in A2780 and SKOV3 cells inhibited OC cell proliferation, migration and invasion. In contrast, Overexpression of PCAT6 exerted the opposite effects on OC cells. Notably, PCAT6 bound to miR-143-3p and affected the expression of transforming growth factor (TGF)-β-activated kinase 1 (TAK1). Subsequent rescue assays confirmed that upregulation of miR-143-3p decreased the PCAT6 overexpression-induced promotion of proliferation, migration and invasion. Moreover, downregulation of miR-143-3p reversed the PCAT6 knockdown-induced inhibition of proliferation, migration, and invasion.

Conclusions: Our findings demonstrate that PCAT6 plays an oncogenic role in OC and may be useful as a therapeutic target for OC.

The lncRNA PVT1 promotes invasive growth of lung adenocarcinoma cells by targeting miR-378c to regulate SLC2A1 expression

As an oncogene, plasmacytoma variant translocation 1 (PVT1) has been found to be highly expressed in several cancers. However, its specific role in lung adenocarcinoma (ADC) has not been fully elucidated. In this study, the expression of PVT1, miR-378c, and solute carrier family 2 member 1 (SLC2A1) was determined by quantitative real-time PCR and western blot. Dual-luciferase reporter assay was used to explore the relationship between PVT1 and miR-378c, as well as miR-378c and SLC2A1. The effects of PVT1 on the lung ADC cells proliferation, invasion, and migration were detected using MTT, wound-healing, and transwell assays. The results revealed that PVT1 was highly expressed in lung ADC cells, and the overexpression of PVT1 promoted the proliferation, migration, and invasion of lung ADC cells. In lung ADC cells, PVT1 negatively regulated miR-378c expression, and miR-378c negatively regulated SLC2A1 expression through binding to its 3'-untranslated coding regions. Knocking down of PVT1 inhibited the abilities of cell proliferation, migration, and invasion, while miR-378c inhibitor or SLC2A1 Vector diminished the effect. Together, silencing PVT1 downregulated SLC2A1 expression via targeting miR-378c, and then repressed lung ADC cells growth, migration, and invasion.

Sevoflurane Inhibits Proliferation, Invasion, but Enhances Apoptosis of Lung Cancer Cells by Wnt/β-catenin Signaling via Regulating lncRNA PCAT6/miR-326 Axis

Sevoflurane was frequently used as a volatile anesthetic in cancer surgery. However, the potential mechanism of sevoflurane on lung cancer remains largely unclear. In this study, lung cancer cell lines (H446 and H1975) were treated by various concentrations of sevoflurane. 3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2-H-tetrazolium bromide (MTT) assessment and colony formation assay were performed to detect the cell viability and proliferation, separately. Also, transwell assay or flow cytometry assay was applied as well to evaluate the invasive ability or apoptosis in lung cancer cells, respectively. Western blot assay was employed to detect the protein levels of β-catenin and Wnt5a. Moreover, quantitative real-time polymerase chain reaction (qRT-PCR) was used to examine the expression level of prostate cancer-associated transcript 6 (PCAT6) and miR-326 in lung cancer tissues and cells. The target interaction between miR-326 and PCAT6 or Wnt5a was predicted by bioinformatics analysis and verified by the dual-luciferase reporter gene assay. Sevoflurane inhibited the abilities on viability, proliferation, invasion, and activation of Wnt/β-catenin signaling, but promoted apoptosis of H446 and H1975 cells in a dose-dependent manner. The expression of PCAT6 was increased in lung cancer tissues and cells, except for that of miR-326. Besides, sevoflurane could lead to expressed limitation of PCAT6 or improvement of miR-326. This process presented a stepwise manner. Up-regulation of PCAT6 restored the suppression of sevoflurane on abilities of proliferation, invasion, rather than apoptosis, and re-activated the Wnt5a/β-catenin signaling in cells. Moreover, the putative binding sites between miR-326 and PCTA6 or Wnt5a were predicted by starBase v2.0 software online. PCAT6 suppressing effects on cells could be reversed by pre-treatment with miR-326 vector. The promotion of Wnt5a inverted effects led from miR-326 or sevoflurane. Our study indicated that sevoflurane inhibited the proliferation, and invasion, but enhanced the apoptosis in lung cancer cells by regulating the lncRNA PCAT6/miR-326/Wnt5a/β-catenin axis.

Long Noncoding RNA RAET1K Enhances CCNE1 Expression and Cell Cycle Arrest of Lung Adenocarcinoma Cell by Sponging miRNA-135a-5p

Molecular dysregulation is believed to participate in the onset and progression of lung adenocarcinoma (LUAD). This study aimed to identify and evaluate the potential key long noncoding RNAs (lncRNAs) involved in the significant dysfunctional process of LUAD. We found that lncRNA retinoic acid early transcript 1K (RAET1K) was upregulated in tumor tissues and were correlated with a poor prognosis of patients with LUAD; further, for the first time, we detected the biological roles of RAET1K. Weighted gene correlation network and gene set enrichment analysis revealed that high RAET1K expression is related to cell cycle dysfunction through upregulated cyclin E1 (CCNE1) by targeting miR-135. The dual-luciferase reporter gene assay was performed to clarify the binding relationship between RAET1K and miR-135a-5p in transgenic A549 and H1299 cells. Real-time PCR and Western blot analyses showed that RAET1K overexpression and miR-135a-5p inhibition exerted a strong synergistic effect on CCNE1 expression, and cell cycle flow cytometry analysis was used to confirm the arrest of A549 and H1299 cells at the G1/S phase. The lncRNA RAET1K/miR-135a-5p axis might participate in the regulation of LUAD progression by influencing CCNE1 expression and the accumulation of cells arrested at the G1/S phase boundary.

A cluster of long non-coding RNAs exhibit diagnostic and prognostic values in renal cell carcinoma

Kidney cancer ranked in the top 10 for both men and women in the estimated numbers of new cancer cases in the United States in 2018. Targeted therapies have recently been administered to patients with clear cell renal cell carcinoma (ccRCC), but the overall survival of patients at the terminal stage of the disease has not been as good as expected. It is therefore necessary to uncover efficient biomarkers for early diagnosis, and to clarify the molecular mechanisms underlying ccRCC progression and metastasis. Increased evidence has shown that long non-coding RNAs (lncRNAs) play important roles during tumor progression. In this study, 10 candidate lncRNAs with diagnostic and prognostic values in ccRCC were identified: IGFL2-AS1, AC023043.1, AP000439.2, AC124854.1, AL355102.4, TMEM246-AS1, AL133467.3, ZNF582-AS1, LINC01510 and PSMG3-AS1. Enrichment analysis revealed metabolic and functional pathways, which may be closely associated with kidney cancer tumorigenesis. Six representative processes were summarized, namely glycolysis, amino acid metabolism, lipid synthesis, reductive carboxylation, nucleotide metabolism, transmembrane transport and signal transduction. In combination, the present results provided prognostic and diagnostic biomarkers for ccRCC and might pave the way for targeted intervention and molecular therapies in the future.

A five-long non-coding RNA signature with the ability to predict overall survival of patients with lung adenocarcinoma

An increasing number of studies have indicated that the abnormal expression of certain long non-coding RNAs (lncRNAs) is linked to the overall survival (OS) of patients with lung adenocarcinoma (LUAD). The aim of the present study was to establish an lncRNA signature to predict the survival of patients with LUAD. The gene expression profiles and associated clinical information of patients with LUAD were downloaded from The Cancer Genome Atlas database. The cohort was randomly sub-divided into training and verification cohorts. Univariate Cox regression analysis was performed on differentially expressed lncRNAs in the training cohort to select candidate lncRNAs closely associated with survival. Next, a risk score (RS) model consisting of 5 lncRNAs was established by multivariate Cox regression analysis on candidate lncRNAs. Using the median RS obtained from the training cohort as a cut-off point, patients were classified into high- and low-risk groups. Kaplan-Meier survival analysis revealed a significant difference in OS between high- and low-risk groups. The survival prediction ability of the 5-lncRNA signature was further tested in the verification and total cohorts. The results proved that the 5-lncRNA signature had good reliability and stability in survival prediction for patients with LUAD. The univariate Cox regression analysis for the 5-lncRNA signature in each cohort indicated that the 5-lncRNA signature was closely associated with survival. Multivariate Cox regression analysis and stratification analysis proved that the prognostic signature was an independent predictor of survival for patients with LUAD. In addition, functional enrichment analysis indicated that the 5 prognostic lncRNAs may be involved in the tumorigenesis of LUAD through cancer-associated pathways and biological processes. Taken together, the present study provided a 5-lncRNA signature that may serve as an independent survival predictor for patients with LUAD.

High throughput circRNA sequencing analysis reveals novel insights into the mechanism of nitidine chloride against hepatocellular carcinoma

Nitidine chloride (NC) has been demonstrated to have an anticancer effect in hepatocellular carcinoma (HCC). However, the mechanism of action of NC against HCC remains largely unclear. In this study, three pairs of NC-treated and NC-untreated HCC xenograft tumour tissues were collected for circRNA sequencing analysis. In total, 297 circRNAs were differently expressed between the two groups, with 188 upregulated and 109 downregulated, among which hsa_circ_0088364 and hsa_circ_0090049 were validated by real-time quantitative polymerase chain reaction. The in vitro experiments showed that the two circRNAs inhibited the malignant biological behaviour of HCC, suggesting that they may play important roles in the development of HCC. To elucidate whether the two circRNAs function as "miRNA sponges" in HCC, we identified circRNA-miRNA and miRNA-mRNA interactions by using the CircInteractome and miRwalk, respectively. Subsequently, 857 miRNA-associated differently expressed genes in HCC were selected for weighted gene co-expression network analysis. Module Eigengene turquoise with 423 genes was found to be significantly related to the survival time, pathology grade and TNM stage of HCC patients. Gene functional enrichment analysis showed that the 423 genes mainly functioned in DNA replication- and cell cycle-related biological processes and signalling cascades. Eighteen hubgenes (SMARCD1, CBX1, HCFC1, RBM12B, RCC2, NUP205, ECT2, PRIM2, RBM28, COPS7B, PRRC2A, GPR107, ANKRD52, TUBA1B, ATXN7L3, FUS, MCM8 and RACGAP1) associated with clinical outcomes of HCC patients were then identified. These findings showed that the crosstalk between hsa_circ_0088364 and hsa_circ_0090049 and their competing mRNAs may play important roles in HCC, providing interesting clues into the potential of circRNAs as therapeutic targets of NC in HCC.

PVT1 Promotes Cancer Progression via MicroRNAs

Non-coding RNA (ncRNA) plays a regulatory role in a variety of cellular activities. And long non-coding RNA (lncRNA) is one of the important kinds of ncRNA. Previous studies have shown that various lncRNAs are involved in the progression of cancer. LncRNA plasmacytoma variant translocation 1 (PVT1) is a newly discovered oncogenic factor that has been confirmed to be overexpressed in many cancer cells. Moreover, the role of PVT1 in cancer development is closely linked to microRNAs (miRNAs). PVT1 can act as a "sponge" for miRNAs to inhibit their activities, thereby affecting proliferation, invasion, and angiogenesis of cancer. In addition, PVT1 itself can be spliced and processed into several miRNAs such as miR-1204 and miR-1207, which can also regulate the development of cancer. This review summarizes various pathways through which PVT1 regulates the progression of cancer via miRNAs. We also propose additional regulatory mechanisms of PVT1 and their potential clinical applications.