Long Non-coding RNA Signature Research Articles

The Cuproptosis-Related Long Noncoding RNA Signature Predicts Prognosis and Immune Cell Infiltration in Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC), ranking as one of the most common malignant tumors, is one of the leading causes of cancer death, with a poor prognosis. Cuproptosis, a novel programmed cell death modality that has just been confirmed recently, may play an important role in HCC prognosis. Long noncoding RNA (LncRNA) is a key participant in tumorigenesis and immune responses. It may be of great significance to predict HCC based on cuproptosis genes and their related LncRNA. The sample data on HCC patients were obtained from The Cancer Genome Atlas (TCGA) database. Combined with cuproptosis-related genes collected from the literature search, expression analysis was carried out to find cuproptosis genes and their related LncRNAs significantly expressed in HCC. The prognostic model was constructed by least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox regression. The feasibility of these signature LncRNAs used for the evaluation of the overall survival rate in HCC patients as independent factors was investigated. The expression profile of cuproptosis, immune cell infiltration, and the status of somatic mutation were analyzed and compared. A prognostic model of HCC consisting of seven cuproptosis gene-related LncRNA signatures was constructed. Multiple verification methods have showed that this model can accurately predict the prognosis of HCC patients. It was showed that the classified high-risk group under the risk score of this model had worse survival status, more significant expression of the immune function, and higher mutation frequency. During the analysis, the cuproptosis gene CDKN2A was found to be most closely related to LncRNA DDX11-AS1 in the expression profile of HCC patients. The cuproptosis-related signature LncRNA in HCC was identified, on the basis of which a model was constructed, and it was verified that it can be used to predict the prognosis of HCC patients. The potential role of these cuproptosis-related signature LncRNAs as new targets for disease therapy in antagonizing HCC development was discussed.

LncRNA PCA3 Suppressed Carotid Artery Stenosis and Vascular Smooth Muscle Cell Function via Negatively Modulating the miR-124-3p/ITGB1 Axis.

Due to the hidden pathogen, carotid artery stenosis (CAS) always occurred at an advanced stage leading to serious sequelae and even deaths. The significance of long noncoding RNA (lncRNA) prostate cancer antigen 3 (PCA3) in CAS incidence and progression were evaluated aiming to explore a potential target for its therapy. Serum samples were collected from 83 asymptomatic CAS patients and 52 healthy individuals and PCA3 was compared using polymerase chain reaction (PCR). The PCA3 levels were compared between stable and unstable plaque in CAS patients. The effect of PCA3 on vascular smooth muscle cells (VSMCs) proliferation and motility was assessed by CCK8 and transwell assay. PCA3 was downregulated in CAS patients and their unstable plaque tissues compared with healthy individuals and stable plaque, respectively. Reduced PCA3 could discriminate CAS patients with relatively high sensitivity and specificity and were associated with higher total cholesterol level and stenosis degree, unstable plaque, and complications. PCA3 downregulation predicted the adverse outcomes of CAS patients. In VSMCs, overexpressing PCA3 significantly suppressed cell proliferation, migration, and invasion, which was alleviated by miR-124-3p/ITGB1 axis. PCA3 served as a biomarker of CAS and regulates the function of VSMCs through sponging miR-124-3p/ITGB1 and indirectly influence the stability of plaque.

Deregulated Long Non-Coding RNA HCG11 in Cerebral Atherosclerosis Serves as a Biomarker to Predict the Risk of Cerebrovascular Events.

Carotid artery stenosis (CAS) is one of the main risk factors of ischemic stroke (IS), which needs a screening and monitoring biomarker. The study focused on the clinical significance of long non-coding RNA (lncRNA) HCG11 in CAS patients aiming to identify a potential therapeutic target for CAS. Serum samples were collected from 70 CAS patients and 80 age- and gender-matched healthy people. HCG11 levels were measured via quantitative real-time PCR (qRT-PCR), and its significance in CAS identification and development prediction was also assessed. HCG11 was enriched in the serum of CAS patients, and serves as a possible biomarker for disease diagnosis with the area under the curve (AUC) of 0.930. Elevated expression of HCG11 was significantly correlated with hypertension, dyslipidemia, and degree of carotid stenosis. HCG11 was highly expressed in severe CAS cases compared to moderate ones, which was positively related to the disease severity. Cox regression analysis determined the close relationship of serum HCG11 with the occurrence of cerebral ischemia events. CAS patients with high HCG11 expression showed a high occurrence rate of cerebral ischemia events. The upregulation of HCG11 could serve as a potential diagnostic biomarker for CAS and is positively related to the disease severity. Serum HCG11 can independently predict the occurrence of following cerebral ischemia events.

MRNA and long-noncoding RNA signatures for improving the prognosis prediction of cutaneous skin melanoma efficiently.

Non-coding RNAs occupy a significant fraction of the human genome, and their biological significance during the pathological process is proved. More and more lncRNAs are reported in cancer research. To investigate the non-coding RNA's biological relevance with cutaneous skin melanoma, we first compared the survival analysis by combining the most differentially expressed mRNA and non-coding RNA expression values. The result showed that the abundantly expressed mRNAs and lncRNAs have significant effects on the survival of patients. Compared to the mRNAs, these lncRNAs have more impact on the progress of cutaneous skin melanoma. Thus, we combined the two types of RNA factors having significant effects as risk factors to construct the diagnosis model, and the survival analysis confirmed the robustness of the diagnosis model. In summary, a list of eight lncRNA and five mRNA expression signatures can be used to improve the prognosis prediction of cutaneous skin melanoma, as well as help us to understand the pathogenic mechanism and provide a hint for targeting therapy.

Long Noncoding RNA MIR600HG Binds to MicroRNA-125a-5p to Prevent Pancreatic Cancer Progression Via Mitochondrial Tumor Suppressor 1-Dependent Suppression of Extracellular Regulated Protein Kinases Signaling Pathway.

Significance of long noncoding RNAs in pancreatic cancer (PC) progression has been documented. Here, we identified a novel long noncoding RNA MIR600HG in PC and its underlying mechanism during PC progression. Through bioinformatics analysis, we selected MIR600HG, microRNA-125a-5p (miR-125a-5p), and mitochondrial tumor suppressor 1 (MTUS1) as objects with their expression patterns assayed in the collected PC tissues and PC cells. Pancreatic cancer cells were manipulated with ectopic expression and deficiency of MIR600HG, miR-125a-5p, and/or MTUS1 for assaying cell biological processes in vitro and tumorigenesis in vivo. MIR600HG and MTUS1 levels were downregulated and miR-125a-5p was upregulated in PC tissues and cells. MIR600HG could bind to miR-125a-5p, while miR-125a-5p negatively targeted MTUS1. MIR600HG resulted in suppression in malignant properties of PCs. All these changes could be reversed by miR-125a-5p elevation. In addition, miR-125a-5p targeted MTUS1 to activate the extracellular regulated protein kinases signaling pathway. In vivo experiment also verified the inhibitory role of MIR600HG in PC. Taken together, MIR600HG acts as an inhibitor for PC progression by upregulating miR-125a-5p-mediated MTUS1 through extracellular regulated protein kinases pathway.

Role of Long Non-Coding RNAs in Human-Induced Pluripotent Stem Cells Derived Megakaryocytes: A p53, HOX Antisense Intergenic RNA Myeloid 1, and miR-125b Interaction Study.

Megakaryocytes (MKs) are rare polyploid cells found in the bone marrow and produce platelets. Platelets are small cell fragments that are essential during wound healing and vascular hemostasis. In vitro differentiation of MKs from human-induced pluripotent stem cell-derived CD34+ hematopoietic stem cells (hiPSC-HSCs) could provide an alternative treatment option for thrombocytopenic patients as a platelet source. In this approach, we developed a method to produce functional MKs from hiPSC-HSCs using a xeno-free and feeder-free condition and minimize the variation and risk from animal-derived products in cell culture. We have also investigated the genome-wide expression as well as functional significance of long noncoding RNAs (lncRNAs) in hiPSC-HSC-derived MKs to get insight into MK biology. We have performed lncRNAs expression profiling by using the Human LncProfilers qPCR Array Kit and identified 26 differentially regulated lncRNAs in hiPSC-HSC-derived MKs as compared with those in hiPSC-HSCs. HOX antisense intergenic RNA myeloid 1 (HOTAIRM1) was the most highly upregulated lncRNA in hiPSC-HSC-derived MKs and phorbol 12-myristate 13-acetate (PMA)-induced megakaryocytic-differentiating K562 cells. Furthermore, we have studied the potential mechanism of HOTAIRM1 based on the interactions between HOTAIRM1, p53, and miR-125b in PMA-induced K562 cells. Our results demonstrated that during MK maturation, HOTAIRM1 might be associated with the transcriptional regulation of p53 via acting as a decoy for miR-125b. Thus, the interaction between HOTAIRM1, p53, and miR-125b is likely involved in controlling cell cycling (cyclin D1), reactive oxygen species production, and apoptosis to support terminal maturation of MKs. SIGNIFICANCE STATEMENT: In vitro generation of megakaryocytes (MKs) from human-induced pluripotent stem cell-derived hematopoietic stem cells (hiPSC-HSCs) could provide an alternative source of platelets for treating thrombocytopenic patients. This study has investigated the functional significance of long non-coding RNAs in hiPSC-HSC-derived MKs, which remains unclear. This study's findings suggest that the regulatory role of HOX antisense intergenic RNA myeloid 1 (HOTAIRM1) in p53-mediated regulation of cyclin D1 during megakaryocytopoiesis is to promote MK maturation by decoying miR-125b.

Clinicopathologic and prognostic significance of long non-coding RNA myocardial infarction-associated transcript in multiple cancers.

The aim of the meta-analysis was to explore the clinicopathological and prognostic significance of long non-coding RNA (lncRNA) myocardial infarction-associated transcript (MIAT) in various cancers. We searched multiple databases, including PubMed, China National Knowledge 53 Infrastructure (CNKI), Springer, Web of Science, and Cochrane, for articles on the prognostic value of lncRNA MIAT in various cancers before 25 March 2021. The odds ratio (OR) and 95% confidence interval (CI) were adopted to evaluate the clinicopathological features and outcomes of cancers. The Cancer Genome Atlas dataset was used to identify the differential expression and prognostic significance of lncRNA MIAT. We enrolled 14 publications, including 1,573 cancer patients. Higher lncRNA MIAT expression was significantly related to worse overall survival (OR=3.13, 95% CI: 2.47-3.96, p<0.05), regardless of cancer types, sample size, and follow-up time of the included studies. Additionally, higher lncRNA MIAT expression was associated with larger tumour sizes (OR=1.67, 95% CI: 1.24-2.26, p<0.05), advanced clinical stage (OR=4.79, 95% CI: 3.38-6.79, p<0.05), lymph nodes metastasis (OR=7.33, 95% CI: 4.61-11.67, p<0.05), and distant metastasis (OR=2.62, 95% CI: 1.88-3.66, p<0.05), but not associated with age and gender. We found no publication bias, and sensitivity analysis indicated that the results were reliable. Higher lncRNA MIAT expression may predict larger tumour sizes, advanced clinical stage, metastasis of cancers, and lower overall survival rate. LncRNA MIAT may serve as a useful clinicopathological and prognostic biomarker for cancers.

Expression of lncRNA APF in Peripheral Blood of Patients with Acute Myocardial Infarction Caused by Coronary Heart Disease and its Clinical Significance.

Coronary heart disease (CHD) is the leading cause of death from cardiovascular disease. This study investigated the expression and clinical significance of long noncoding RNA (lncRNA) autophagy promoting factor (APF) in peripheral blood of patients with acute myocardial infarction (AMI) caused by CHD. Patients with angina pectoris (AP) (n = 80) and AMI (n = 96) and other patients (n = 60) with precordial discomfort but no CHD were included. The serum levels of lncRNA APF, MIAT, MALAT1, H19, CHAST, CDR1AS, miR-188-3p, and cardiac troponin I (cTnI) /creatine kinase (CK) /creatine kinase isozymes (CK-MB) were detected using reverse transcription-quantitative polymerase chain reaction or enzyme-linked immunosorbent assay. Patients with AMI were divided into high/low expression groups based on the median level of APF, and the clinical baseline indicators of patients with AMI were compared. The correlation between lncRNA APF and cTnI/CK/CK-MB/miR-188-3p was analyzed using Pearson analysis, and the clinical value of lncRNA APF was evaluated using the receiver operating characteristic curve. The levels of lncRNA APF, MIAT, MALAT1, H19, CHAST, and CDR1AS in patients with AMI were increased, whereas there were no differences in patients with AP. The APF levels in patients with AMI were higher than MIAT, MALAT1, and CHAST, whereas there were no differences between APF and H19 and CDR1AS. In patients with AMI, the high level of lncRNA APF was correlated with the history of smoking/drinking. Moreover, lncRNA APF was positively correlated with cTnI/CK/CK-MB levels and negatively correlated with miR-188-3p. LncRNA APF has high diagnostic efficacy for AMI. Overall, lncRNA APF is highly expressed in patients with AMI caused by CHD and has high diagnostic efficacy for AMI.

Aberrant Circulating SNHG1 Serves as a Biomarker to Distinguish Acute Myocardial Infarction and Construction of a Risk Model for Secondary Heart Failure.

Abstract: Acute myocardial infarction (AMI) is a severe condition observed in patients with coronary heart disease, and heart failure (HF) often occurs after AMI. This study aimed to evaluate the clinical significance of long noncoding RNA (lncRNA) small nucleolar RNA host gene 1 (SNHG1) in the diagnosis and prognosis of AMI and to construct a logistic predict model to determine the risk of post-AMI HF. This study analyzed the data of 229 patients with AMI. Serum SNHG1 levels were examined using quantitative real-time PCR, and its diagnostic value was evaluated using receiver operating characteristic analysis. The predictive value of SNHG1 for HF onset was evaluated using the Kaplan–Meier method and Cox regression analysis. The risk factors and predictive parameters included in the predictive model of post-AMI HF were determined using multivariate logistic regression analysis. In this study, we found that reduced serum SNHG1 was negatively correlated with the Gensini score of patients with AMI. The diagnostic performance of combining cardiac troponin I (cTnI) and creatine kinase (CK)-MB and SNHG1 was the best. Lower SNHG1 expression served as an independent indicator for HF secondary to AMI. A logistic risk model was constructed with the following equation: , and the predictive accuracy of this model was relatively high with an area under the curve of 0.890. Taken together, our results revealed that reduced SNHG1 combining cTnI and CK-MB had the best diagnostic performance in patients with AMI. A logistic risk model based on SNHG1, age, cTnI, CK-MB, left ventricular ejection fraction, and Gensini score may help to determine the development of HF in patients with AMI.

Investigating the potential clinical significance of long non-coding RNA 00092 in patients with breast cancer.

BackgroundAberrant promoter methylation and its resultant aberrant gene expression are important epigenetic mechanisms that promote the development of breast cancer (BC). However, the prognostic value of this type of methylation-driven gene in BC is unknown.MethodsTo identify DNA methylation-driven long non-coding RNAs (lncRNAs), a comprehensive analysis of RNA-sequencing and DNA methylation data of 1,200 clinical samples was performed. Differentially expressed lncRNAs (DELs) and survival-related lncRNAs in BC were identified using the R package. The function of the lncRNA was evaluated using Kaplan-Meier and receiver operating characteristic (ROC) curve analyses. The expression of the key lncRNA in tissues and cells was detected by quantitative real-time polymerase chain reaction (qRT-PCR). Biological functions of the key lncRNA were analyzed using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses. The Connectivity Map (CMap) was used to search for small-molecule targeted drugs for the key lncRNA. The functions of the key lncRNA in BC progression were investigated using cell proliferation and cell cycle assays.ResultsA total of 14 methylation-driven lncRNAs, 526 DELs, and 93 survival-associated lncRNAs were identified. The above data were intersected, and a unique lncRNA, LINC00092, was obtained. LINC00092 was hypermethylated and hypoexpressed in both BC tissues and cell lines. LINC00092 was found to be a diagnostic marker for BC, with its low expression being associated with poor prognosis (P=0.013). LINC00092 overexpression inhibited the proliferation and cell cycle of BC cells in vitro. Nimesulide and sulpiride were screened out as potential targeted therapeutic drugs for LINC00092 in BC, and sulpiride was observed to partially reverse the proliferative effect of (small interfer) si-LINC00092 on BC cells.ConclusionsLINC00092 is a methylation-driven lncRNA in BC and could be a potential therapeutic target for this disease.

Evolving Insights Into the Biological Function and Clinical Significance of Long Noncoding RNA in Glioblastoma.

Glioblastoma (GBM) is one of the most prevalent and aggressive cancers worldwide. The overall survival period of GBM patients is only 15 months even with standard combination therapy. The absence of validated biomarkers for early diagnosis mainly accounts for worse clinical outcomes of GBM patients. Thus, there is an urgent requirement to characterize more biomarkers for the early diagnosis of GBM patients. In addition, the detailed molecular basis during GBM pathogenesis and oncogenesis is not fully understood, highlighting that it is of great significance to elucidate the molecular mechanisms of GBM initiation and development. Recently, accumulated pieces of evidence have revealed the central roles of long noncoding RNAs (lncRNAs) in the tumorigenesis and progression of GBM by binding with DNA, RNA, or protein. Targeting those oncogenic lncRNAs in GBM may be promising to develop more effective therapeutics. Furthermore, a better understanding of the biological function and underlying molecular basis of dysregulated lncRNAs in GBM initiation and development will offer new insights into GBM early diagnosis and develop novel treatments for GBM patients. Herein, this review builds on previous studies to summarize the dysregulated lncRNAs in GBM and their unique biological functions during GBM tumorigenesis and progression. In addition, new insights and challenges of lncRNA-based diagnostic and therapeutic potentials for GBM patients were also introduced.

Comprehensive Analysis of Potential Biomarkers of Acute Lymphoblastic Leukemia in Children by Using a Competing Endogenous RNA Network.

Acute lymphoblastic leukemia (ALL) is the most serious hematological carcinoma in adolescents. The significance of long noncoding RNAs (lncRNAs) and their regulative role in the proliferation and differentiation of myeloid cells in cancer has been recently reported. Nevertheless, key RNAs and the regulatory mechanism of competitive endogenous RNA (ceRNA) network affected by pediatric ALL are not fully illustrated. In this study, phase 2 and 3 pediatric ALL RNA profiles were extracted from the TARGET database and used to identify lncRNAs, microRNAs, and messenger RNAs in high-risk ALL and reconstruct the sponge ceRNA regulatory network. Results indicated that 44 lncRNAs, 25 miRNAs, and 115 mRNA were up/downregulated. Functional analysis with differentially expressed RNAs (DERNAs) showed enriched significant signaling pathways, including PI3K-Akt and p53 signaling cascades and other pathways associated with the tumor. Seventeen differential hub RNAs, including LINC00909, BZRAP1-AS1, C17orf76-AS1, HCG11, MIAT, SNHG5, SNHG15, and TP73-AS1, were identified. The Cox model of correlation indicated that 14 of these RNAs were associated with the progression of pediatric ALL. These findings would help clarify the regulatory role of several lncRNAs as well as provide insights into the leukemogenesis of pediatric ALL to further explore novel prognostic markers/therapeutic targets for ALL.

SLCO4A1-AS1 mediates pancreatic cancer development via miR-4673/KIF21B axis.

In this study, we intended to figure out the biological significance of long non-coding RNAs (lncRNAs) solute carrier organic anion transporter family member 4A1 antisense RNA 1 (SLCO4A1-AS1) in pancreatic cancer (PC). Cell counting kit-8, colony formation, wound healing, transwell, and flow cytometry experiments were performed to reveal how SLCO4A1-AS1 influences PC cell proliferation, migration, invasion, and apoptosis. Thereafter, bioinformatics analysis, RNA immunoprecipitation assay, luciferase reporter assay, and RNA pull-down assay were applied for determining the binding sites and binding capacities between SLCO4A1-AS1 and miR-4673 or kinesin family member 21B (KIF21B) and miR-4673. The results depicted that SLCO4A1-AS1 was upregulated in PC, and SLCO4A1-AS1 knockdown suppressed PC cell growth, migration, invasion, and induced cell apoptosis. Furthermore, SLCO4A1-AS1 was verified to modulate the expression of KIF21B by binding with miR-4673. SLCO4A1-AS1 exerted an oncogenic function in PC. The overexpression of SLCO4A1-AS1 aggravated the malignant behaviors of PC via the upregulation of KIF21B by sponging miR-4673. Our findings revealed a novel molecular mechanism mediated by SLCO4A1-AS1, which might play a significant role in modulating the biological processes of PC.

High Expression of Long Non-Coding RNA TMCO1-AS1 is Associated With Poor Prognosis of Hepatocellular Carcinoma.

Background: The molecular pathways along with the clinical significance of long non-coding RNAs (lncRNAs) in hepatocellular carcinoma (HCC) remain uncertain. Our study sought to identify and characterize lncRNAs associated with HCC. Methods: LncRNA TMCO1-AS1 was identified by differential expression analysis, receiver operating characteristic (ROC) analysis, and univariate analysis using RNA sequencing and clinical information of HCC from the public database. Then clinical correlations and survival analysis were conducted to further appraise the prognostic significance of lncRNA TMCO1-AS1 in HCC. Hepatoma and adjoining normal tissues from 66 patients who received surgical operation at our center were used to verify the results of the bioinformatics analysis. A survival prognostic model was established combining TMCO1-AS1 expression and other clinical characteristics. Results: Bioinformatics analysis showed the aberrant high expression of TMCO1-AS1 in HCC tissue. TMCO1-AS1 expression was positively correlated with alpha-fetoprotein (AFP) level, vascular invasion, tumor stage, as well as tumor differentiation. Moreover, survival analysis found a significant inverse association between the expression of TMCO1-AS1 and the survival of patients with HCC. Cox analysis indicated that TMCO1-AS1 was an independent factor for HCC prognosis. Analysis of the HCC tissues from patients at our center provided results similar to those of the bioinformatics analysis. Risk models for overall survival (OS) and recurrence-free survival (RFS) incorporating TMCO1-AS1 exhibited better sensitivity and specificity than using clinical characteristics alone. Conclusion: High TMCO1-AS1 expression is significantly correlated with the unfavorable poor prognosis of HCC, indicating its potential of being a novel prognostic marker for HCC.

Prognostic significance of long non-coding RNA five prime to XIST in various cancers

BackgroundTo observe the clinicopathological and prognostic value of long non-coding RNA five prime to X inactive specific transcript (lncFTX) in multiple tumors.MethodsEligible studies for lncFTX were identified by searching PubMed, Embase, Web of Science and Cochrane Library databases from inception to December 01, 2020. Stata 12.0 software was used to calculate the odds ratio (OR)/hazard ratio (HR) and 95% confidence interval (95% CI). We used The Cancer Genome Atlas (TCGA) dataset to further investigate the differential expression and prognostic value of lncFTX.ResultsWe included 11 studies involving a total of 1633 patients. The results showed that the expression of lncFTX was positively associated with advanced TNM stage (III-IV versus I-II) (OR = 2.30, 95% CI: 1.74–3.03, P < 0.05), lymph nodes metastasis (OR = 3.01, 95% CI: 2.00–4.52, P < 0.05), distant metastasis (OR = 3.68, 95% CI: 2.13–6.34, P < 0.05), and cancer mortality (HR = 1.83, 95% CI: 1.20–2.81, P < 0.05). However, the expression of lncFTX was not associated with tumor differentiation (poor differentiation versus well or moderate differentiation) and vessel invasion of cancer. Subgroup analysis showed that the higher lncFTX expression was associated with shorter overall survival in cancer patients, regardless of the sample size and cancer type. No publication bias was found, and the sensitivity analysis results suggested that the main findings were robust. Elevated expression and prognostic significance of FTX were confirmed using TCGA dataset.ConclusionsThis study found that the expression of lncFTX was positively associated with advanced tumor node metastasis (TNM) stage, lymph nodes, distant metastasis and, cancer mortality, suggesting that lncFTX might be a potential prognostic biomarker for tumors.

Model Construction and Identification of Genome Instability-Associated LncRNA Signature Markers in Bladder Cancer

Background: Studies have shown that long non-coding RNA (LncRNA) plays a critical role in maintaining genomic instability. The correlation between lncRNA and genomic instability is still worth exploring in bladder cancer as a new tumour marker. Methods: Therefore, combined with the lncRNA expression profile and somatic mutation profile of bladder cancer, we established a computing framework of lncRNA related to genomic instability and identified 58 new lncRNA related to genomic instability. Next, we identified a lncRNA signature (GILncSig), based on these 58 new genes, which divided patients into high-risk and low-risk groups. The clinical prognosis was significantly different and was further verified in an independent cohort of patients. Results: We confirmed that GILncSig is related to the genomic mutation rate of bladder cancer, suggesting that GILncSig can be used as an indicator of genomic instability. The results show that GILncSig has prognostic value independent of age, sex, grade, and stage and is vital in evaluating clinical prognosis. To sum up, this study provides a vital research basis and methods for further exploring the role of lncRNA in the genomic instability of bladder cancer and provides a theoretical basis for the identification of bladder cancer biomarkers related to genomic instability.

A Competitive Endogenous RNA Network Based on Differentially Expressed lncRNA in Lipopolysaccharide-Induced Acute Lung Injury in Mice.

Non-coding RNAs have remarkable roles in acute lung injury (ALI) initiation. Nevertheless, the significance of long non-coding RNAs (lncRNAs) in ALI is still unknown. Herein, we purposed to identify potential key genes in ALI and create a competitive endogenous RNA (ceRNA) modulatory network to uncover possible molecular mechanisms that affect lung injury. We generated a lipopolysaccharide-triggered ALI mouse model, whose lung tissue was subjected to RNA sequencing, and then we conducted bioinformatics analysis to select genes showing differential expression (DE) and to build a lncRNA-miRNA (microRNA)- mRNA (messenger RNA) modulatory network. Besides, GO along with KEGG assessments were conducted to identify major biological processes and pathways, respectively, involved in ALI. Then, RT-qPCR assay was employed to verify levels of major RNAs. A protein-protein interaction (PPI) network was created using the Search Tool for the Retrieval of Interacting Genes (STRING) database, and the hub genes were obtained with the Molecular Complex Detection plugin. Finally, a key ceRNA subnetwork was built from major genes and their docking sites. Overall, a total of 8,610 lncRNAs were identified in the normal and LPS groups. Based on the 308 DE lncRNAs [p-value < 0.05, |log2 (fold change) | > 1] and 3,357 DE mRNAs [p-value < 0.05, |log2 (fold change) | > 1], lncRNA-miRNA and miRNA-mRNA pairs were predicted using miRanda. The lncRNA-miRNA-mRNA network was created from 175 lncRNAs, 22 miRNAs, and 209 mRNAs in ALI. The RT-qPCR data keep in step with the RNA sequencing data. GO along with KEGG analyses illustrated that DE mRNAs in this network were mainly bound up with the inflammatory response, developmental process, cell differentiation, cell proliferation, apoptosis, and the NF-kappa B, PI3K-Akt, HIF-1, MAPK, Jak-STAT, and Notch signaling pathways. A PPI network on the basis of the 209 genes was established, and three hub genes (Nkx2-1, Tbx2, and Atf5) were obtained from the network. Additionally, a lncRNA-miRNA-hub gene subnetwork was built from 15 lncRNAs, 3 miRNAs, and 3 mRNAs. Herein, novel ideas are presented to expand our knowledge on the regulation mechanisms of lncRNA-related ceRNAs in the pathogenesis of ALI.

Long noncoding RNAs to predict postoperative recurrence in bladder cancer and to develop a new molecular classification system.

BackgroundReliable molecular markers are much needed for early prediction of recurrence in muscle‐invasive bladder cancer (MIBC) patients. We aimed to build a long‐noncoding RNA (lncRNA) signature to improve recurrence prediction and lncRNA‐based molecular classification of MIBC.MethodsLncRNAs of 320 MIBC patients from the Cancer Genome Atlas (TCGA) database were analyzed, and a nomogram was established. A molecular classification system was created, and immunotherapy and chemotherapy response predictions, immune score analysis, immune infiltration analysis, and mutational data analysis were conducted. Survival analysis validation was also performed.ResultsAn eight‐lncRNA signature classifed the patients into high‐ and low‐risk subgroups, and these groups had significantly different (disease‐free survival) DFS. The ability of the eight‐lncRNA signature to make an accurate prognosis was tested using a validation dataset from our samples. The nomogram achieved a C‐index of 0.719 (95% CI, 0.674–0.764). Time‐dependent receiver operating characteristic curve (ROC) analysis indicated the superior prognostic accuracy of nomograms for DFS prediction (0.76, 95% CI, 0.697–0.807). Further, the four clusters (median DFS = 11.8, 15.3, 17.9, and 18.9 months, respectively) showed a high frequency of TTN (cluster 1), fibroblast growth factor receptor‐3 (cluster 2), TP53 (cluster 3), and TP53 mutations (cluster 4), respectively. They were enriched with M2 macrophages (cluster 1), CD8+ T cells (cluster 2), M0 macrophages (cluster 3), and M0 macrophages (cluster 4), respectively. Clusters 2 and 3 demonstrated potential sensitivity to immunotherapy and insensitivity to chemotherapy, whereas cluster 4 showed potential insensitivity to immunotherapy and sensitivity to chemotherapy.ConclusionsThe eight‐lncRNA signature risk model may be a reliable prognostic signature for MIBC, which provides new insights into prediction of recurrence of MIBC. The model may help clinical decision and eventually benefit patients.

LncRNA CCDC144NL-AS1 Serves as a Prognosis Biomarker for Non-small Cell Lung Cancer and Promotes Cellular Function by Targeting miR-490-3p.

This study revealed the prognostic significance of long non-coding RNA (lncRNA) CCDC144NL-AS1 in NSCLC patients and discussed the effect and mechanism of proliferation, migration, and invasion of non-small cell lung cancer (NSCLC) cells. 128 pairs of NSCLC tissues and paracancerous tissues were collected, and qRT-PCR was used to detect the differential expression of lncRNA CCDC144NL-AS1 in all tissues and cells lines. Kaplan-Meier analysis and Cox proportional hazards model analysis were used to estimate the prognostic value of lncRNA CCDC144NL-AS1. CCK-8 and Transwell assays confirmed the effect of lncRNA CCDC144NL-AS1 on the proliferation, migration, and invasion of NSCLC. Bioinformatics was used to predict the microRNAs that lncRNA CCDC144NL-AS1 might bind to miR-490-3p. The regulation of lncRNA CCDC144NL-AS1 on miR-490-3p was verified by luciferase activity assay with wide type or mutation. The expression of lncRNA CCDC144NL-AS1 was enhanced in both NSCLC tissues and cell lines. Patients with overexpression of lncRNA CCDC144NL-AS1 have a poor prognosis, and lncRNA CCDC144NL-AS1 is an independent prognostic factor for NSCLC. Increased the relative expression level of lncRNA CCDC144NL-AS1 can promote the proliferation, migration, and invasion of NSCLC cells. LncRNA CCDC144NL-AS1 might target miR-490-3p. LncRNA CCDC144NL-AS1 can be used as an oncogene of NSCLC to predict patient prognosis and promote tumor proliferation, migration, and invasion by targeting miR-490-3p.

Expression and Clinical Significance of Long Non-Coding RNA RP4-669H2.1 in Glioblastoma

Neuroglioma is the most common malignant tumor in the central nervous system and still has a poor prognosis. Here, we investigated the prognostic value of long non-coding RNAs(lncRNAs) in glioblastoma. We first analyzed the lncRNA expression profiles of glioblastoma (GBM) in The Cancer Genome Atlas database and selected the most differential survival genes (lncRNA RP4-669H2.1) for further validation. We then performed qRT-PCR using samples of 88 glioblastoma patients treated in our department between January 2011 and December 2017 that were retrospectively selected to validate the prognostic value of RP4-669H2.1expression in glioblastoma. Using a Cox multivariate analysis, we explored the prognostic value of RP4-669H2.1 and analyzed whether it was an independent prognostic factor. This analysis confirmed that the RP4-669H2.1 expression was significantly associated with glioblastoma-associated mortality in this patient cohort (P =1.80E–05) in TCGA database. In fact, the overall survival (OS) of the RP4-669H2.1 high-expression group (78 cases) was lower than that of the low-expression group (49 cases) (P = 4.6E–06) in TCGA database. Moreover, the TNM stage of the RP4-669H2.1 high-expression group was higher than that of the RP4-669H2.1 low-expression group (P = 0.001). A multivariate analysis further showed that a higher TNM stage (OR = 2.167, 95% CI: 1.349–3.479) and a higher RP4-669H2.1 expression (OR = 2.933, 95% CI: 1.122–7.663) were independent risk factors for the OS of glioblastoma patients. Finally, we predicted the target genes of RP4-669H2.1 using a Multi Experiment Matrix and annotated their biological functions. We observed that the target genes of RP4-669H2.1 were mainly enriched in biological functions related to DNA-binding transcription factor activity. Among these, we selected SMAD6 because the expression of RP4-669H2.1 was positively correlated with that of SMAD6 in glioblastoma. Overall, we conclude that the upregulation of RP4-669H2.1 is an independent poor prognosis factor for glioblastoma and that it can regulate the DNA-binding activity of transcription factors.