Analysis Of lncRNA Expression Profiles Research Articles

Integrated Analysis of Long Non-Coding RNA Expression Profiles in Glaesserella parasuis-Induced Meningitis: New Insight into Pathogenesis

Glaesserella parasuis (G. parasuis) can elicit meningitis in pigs; however, the pathogenic mechanisms of meningitis induced by G. parasuis remain unclear. Long non-coding RNAs (lncRNAs) have been proven to play key roles in a variety of physiological and pathological processes. However, whether lncRNAs are involved in meningitis triggered by G. parasuis has not been investigated. In this study, we performed an integrative analysis of lncRNAs expression profiles in the porcine brain infected with G. parasuis using RNA-seq. The results showed that lncRNA expressions in G. parasuis-induced meningitis were modified, and a total of 306 lncRNAs exhibited significant differential expression, in which 176 lncRNAs were up-regulated and 130 lncRNAs were down-regulated. KEGG enrichment analysis demonstrated that the differentially expressed target mRNAs of affected lncRNAs in G. parasuis-infected porcine brain were mainly involved in the cell adhesion molecules (CAMs), Jak-STAT signaling pathway, PI3k-Akt signaling pathway, and TNF signaling pathway. The expression relationship between the most affected differential lncRNAs and their differential target mRNAs was visualized by a co-expression network. A protein-protein interaction network consisting of 12 differential targets was constructed using STRING analysis. In addition, differential expressions of important lncRNAs were validated by qRT-PCR. lncRNA ALDBSSCT0000007362, ALDBSSCT0000001959, ALDBSSCT0000005529, MSTRG.2939.1, and MSTRG.32374.1 showed the same expression pattern with the lncRNA sequencing data. Our results demonstrated that G. parasuis could modify the lncRNA expression profiles in the porcine brain. To the best of our knowledge, this is the first report revealing the integrative analysis of lncRNA expression profiles in G. parasuis-induced meningitis, which could enhance important information to understand the inflammatory functions of lncRNAs involved in swine meningitis, and also provide a foundation for finding out novel strategies to prevent and treat meningitis in piglets triggered by G. parasuis.

A Comprehensive Genome-Wide Analysis of lncRNA Expression Profile during Hepatic Carcinoma Cell Proliferation Promoted by Phospholipase Cγ2

A Comprehensive Genome-Wide Analysis of lncRNA Expression Profile during Hepatic Carcinoma Cell Proliferation Promoted by Phospholipase Cγ2

Identification of genomic instability related lncRNA signature with prognostic value and its role in cancer immunotherapy in pancreatic cancer.

Background: Increasing evidence suggested the critical roles of lncRNAs in the maintenance of genomic stability. However, the identification of genomic instability-related lncRNA signature (GILncSig) and its role in pancreatic cancer (PC) remains largely unexplored. Methods: In the present study, a systematic analysis of lncRNA expression profiles and somatic mutation profiles was performed in PC patients from The Cancer Genome Atlas (TCGA). We then develop a risk score model to describe the characteristics of the model and verify its prediction accuracy. ESTIMATE algorithm, single-sample gene set enrichment analysis (ssGSEA), and CIBERSORT analysis were employed to reveal the correlation between tumor immune microenvironment, immune infiltration, immune checkpoint blockade (ICB) therapy, and GILncSig in PC. Results: We identified 206 GILnc, of which five were screened to develop a prognostic GInLncSig model. Multivariate Cox regression analysis and stratified analysis revealed that the prognostic value of the GILncSig was independent of other clinical variables. Receiver operating characteristic (ROC) analysis suggested that GILncSig is better than the existing lncRNA-related signatures in predicting survival. Additionally, the prognostic performance of the GILncSig was also found to be favorable in patients carrying wild-type KRAS, TP53, and SMAD4. Besides, a nomogram exhibited appreciable reliability for clinical application in predicting the prognosis of patients. Finally, the relationship between the GInLncSig model and the immune landscape in PC reflected its application value in clinical immunotherapy. Conclusion: In summary, the GILncSig identified by us may serve as novel prognostic biomarkers, and could have a crucial role in immunotherapy decisions for PC patients.

Comprehensive analysis of lncRNA expression profiles in postmenopausal osteoporosis

To explore the key lncRNAs affecting postmenopausal osteoporosis (PMOP) progression, the transcriptome sequencing of peripheral blood mononuclear cells from fifteen early postmenopausal women, according to bone mineral density, were divided into groups of osteoporosis, osteopenia and normality, in each of which the expression profiles of lncRNAs was investigated. From the results we observed nine candidates of lncRNAs, which were to be compared with miRBase, and found that MIR22HG as one candidate of lncRNA was most likely to be directly used as miRNA precursor. Based on the KEGG annotation and lncRNA-miRNA-mRNA-KEGG network, we analyzed the potential role of candidate lncRNAs. The results showed that the expression profiles of lncRNAs could help identify the novel ones involved in the progression of PMOP, and that MIR22HG could serve as a miRNA precursor to regulate FoxO signaling pathway in bone metabolism. Our findings can be of great help in predicting and diagnosing early PMOP.

Comprehensive Analysis of lncRNA Expression Profile and the Potential Role of ENST00000604491 in Graves' Disease.

Background Graves' disease (GD) is one of the most common autoimmune diseases worldwide and develops in 20 to 50 cases per 100,000 persons annually. Long noncoding RNAs (lncRNAs) are widely expressed in multiple human diseases and have pivotal functions in gene regulation. This study is aimed at determining the lncRNA profile in peripheral blood mononuclear cells (PBMCs) from GD patients and investigating the role of ENST00000604491 in GD. Methods A total of 31 GD patients and 32 normal controls were enrolled in the study. Next-generation sequencing was performed to identify the dysregulated lncRNAs in the PBMCs from the 5 GD patients and 5 normal controls, and 26 GD patients and 27 controls were used to verify the selected lncRNAs. The relative expression of verified lncRNAs, forkhead box P1 (FOXP1), and IKAROS family zinc finger 3 (IKZF3) from these samples was detected by quantitative real-time PCR. The potential biomarker value was assessed by using receiver operating characteristic (ROC) curve analysis. Results A total of 37,683 dysregulated expressed lncRNAs were indicated, of which 5 lncRNAs were significantly upregulated and 83 lncRNAs were remarkably downregulated in the GD patients compared with healthy subjects. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses showed that abnormally expressed lncRNAs were mainly enriched in immune system-related signalling pathways. Among the selected lncRNAs, the relative expression of ENST00000604491 was significantly downregulated and negatively correlated with the serum levels of thyroid-stimulating hormone receptor antibodies (TRAb) in GD patients. Further studies confirmed that decreased FOXP1 expression was inversely correlated with serum TRAb levels in GD patients. Moreover, there was a notably positive correlation between ENST00000604491 expression and FOXP1 transcript levels in GD. The area under the ROC curve of ENST00000604491 was up to 0.74 (95% confidence interval: 0.60-0.87, p < 0.01), and the sensitivity and specificity were 53.85% and 88.89%, respectively. Conclusion The present study identifies ENST00000604491 as a significantly attenuated lncRNA in GD patients, which may contribute to the pathogenesis of GD by regulating FOXP1 and represent a potential biomarker for GD.

Comprehensive analysis of lncRNA expression profiles in rats with cerebral ischemia-reperfusion injury after treatment with 20(R)-ginsenoside Rg3.

This study was aimed at investigating the differentially expressions of long noncoding RNAs (lncRNAs) and mRNAs in the brains of a middle cerebral artery occlusion/reperfusion (MCAO/R) group and a MCAO/R + 20(R)-Rg3 group. Biological enrichment analysis was performed, and a lncRNA-mRNA coexpression network was constructed, to reveal the targets and pathways of 20(R)-Rg3 involved in the regulation of cerebral ischemia-reperfusion injury (CIRI). The RNA-seq high-throughput sequencing method was employed to detect differentially-expressed genes between the groups, which were verified by RT-PCR. Functional enrichment analyses of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway were performed to explore the biological functions and relevant pathways. The coexpression network of the screened lncRNAs and mRNAs was built by using Cytoscape software. The results identified 77 upregulated lncRNAs, 162 downregulated lncRNAs, 66 upregulated mRNAs and 472 downregulated mRNAs in the MCAO/R + 20(R)-Rg3 group, compared with those in the MCAO/R group. GO enrichment analysis showed that the GO terms were mainly enriched in stimulation response, cellular response, and stress response. KEGG pathways were mainly related to the tumor necrosis factor (TNF), NF-κB, cytokine, and other receptor signaling pathways. In addition, the coexpression analysis between lncRNA and mRNA identified 314 nodes and 515 connections between 6 lncRNAs and 308 mRNAs, of which 511 were positive and 4 were negative. Among them, ENSRNOG-00000059555 was strongly correlated with AABR07001160.1. This study revealed multiple lncRNAs were involved in the neuroprotection of 20(R)-Rg3 against CIRI and thereby provided new insights into the use of 20(R)-Rg3 as a novel neuro protectant in ischemic stroke management.

SOX2-OT induced by PAI-1 promotes triple-negative breast cancer cells metastasis by sponging miR-942-5p and activating PI3K/Akt signaling.

Triple-negative breast cancer (TNBC) has an aggressive biological behavior and poor outcome. Our published study showed that PAI-1 could induce the migration and metastasis of TNBC cells. However, the underlying mechanism by which PAI-1 regulates TNBC metastasis has not been addressed. Here, we demonstrated that PAI-1 is high expressed in TNBC and promotes TNBC cells tumorigenesis. Using microarray analysis of lncRNA expression profiles, we identified a lncRNA SOX2-OT, which is induced by PAI-1 and could function as an oncogenic lncRNA in TNBC. Mechanistic analysis demonstrated that SOX2-OT acts as a molecular sponge for miR-942-5p to regulate the expression of PIK3CA, ultimately leading to activating PI3K/Akt signaling pathway and promoting TNBC metastasis. Taken together, our findings suggest that SOX2-OT regulates PAI-1-induced TNBC cell metastasis through miR-942-5p/PIK3CA signaling and illustrate the great potential of developing new SOX2-OT-targeting therapy for TNBC patients.

Identification and characterization of novel infection associated transcripts in macrophages

ABSTRACT By analysis of lncRNA expression profiles of macrophages in response to Mycobacterium tuberculosis (Mtb) infection, we identified novel highly expressed transcripts, unique in encompassing a protein coding transcript- Cytidine Monophosphate Kinase 2 (CMPK2) and a previously identified lncRNA- Negative Regulator of Interferon Response (NRIR). While these transcripts (TILT1, 2,3 – TLR4 and Infection induced Long Transcript) are induced by virulent Mtb as well as lipopolysaccharide (LPS) early, lack of/delayed expression in non-viable Mtb/BCG infected cells, respectively, suggest an important role in macrophage responses. The elevated expression by 3 hr in response to fast growing bacteria further emphasizes the importance of these RNAs in the macrophage infection response. Overall, we provide evidence for the presence of multiple transcripts that form a part of the early infection response programme of macrophages. Abbreviations: IFN: Interferon; NRIR: negative regulator of interferon response; CMPK2: cytidine/ uridine monophosphate kinase; LPS: lipopolysaccharide; LAM: Lipoarabinomannan; PIMs: Phosphatidylinositol Mannosides; TILT1, 2,3: TLR4 and Infection induced Long Transcript; TLR4: Toll-like receptor 4; Mtb: Mycobacterium tuberculosis; BCG: Mycobacterium bovis BCG; MDMs: human monocyte derived macrophages

Long non-coding RNA profile study identifies an immune-related lncRNA prognostic signature for prostate adenocarcinoma

Prostate adenocarcinoma (PRAD) is the highest incidence rate of male urogenital morbidity worldwide. Long non-coding RNAs (lncRNAs), as a significant class of gene expression regulators, play a critical role in immune regulation. The purpose of this study is to explore a new immune related lncRNA signature to exactly predict the prognosis of PRAD patients. In this study, we conducted a genome-wide comparative analysis of lncRNA expression profiles in 532 patients with PRAD from the Cancer Genome Atlas (TCGA) database. The immune-related lncRNAs were identified by Cox regression model, and then a new five immune-related lncRNAs signature (FRMD6-AS2, AC008770.3, AC109460.3, AC011899.2, and AC008063.1) were constructed, which could predict the prognosis of PRAD patients. Univariate and multivariate Cox regression analysis showed that the signature could be an independent prognostic indicator of overall survival (OS). Through further study of different clinic-pathological parameters, we found that PRAD samples can be divided into high-risk groups with shorter OS and low-risk groups with longer OS by the signature. Principal component analysis showed that five immune-related lncRNA signature could distinguish the high-risk group from low-risk group in view of the immune-related lncRNAs. The difference of immune status between the two groups was observed by gene set enrichment analysis and the ESTIMATE algorithm. Except FRMD6-AS2, the expression of the other 4 lncRNAs were remarkably up-regulated in tumor tissues. In conclusion, the identified five immune-related lncRNAs signature had important clinical significance in prognosis prediction, and can be used as potential immunotherapy targets for PRAD patients.

Early detection of hepatocellular carcinoma via liquid biopsy: panel of small extracellular vesicle-derived long noncoding RNAs identified as markers.

This study investigated the diagnostic potential of serum small extracellular vesicle‐derived long noncoding RNAs (EV‐lncRNAs) for hepatocellular carcinoma (HCC). Driver oncogenic lncRNA candidates were selected by a comparative analysis of lncRNA expression profiles from two whole transcriptome human HCC datasets (Catholic_LIHC and TCGA_LIHC). Expression of selected lncRNAs in serum and small EVs was evaluated using quantitative reverse transcription PCR. Diagnostic power of serum EV‐lncRNAs for HCC was determined in the test (n = 44) and validation (n = 139) cohorts. Of the six promising driver onco‐lncRNAs, DLEU2, HOTTIP, MALAT1, and SNHG1 exhibited favorable performance in the test cohort. In the validation cohort, serum EV‐MALAT1 displayed excellent discriminant ability, while EV‐DLEU2, EV‐HOTTIP, and EV‐SNHG1 showed good discriminant ability between HCC and non‐HCC. Furthermore, a panel combining EV‐MALAT1 and EV‐SNHG1 achieved the best area under the curve (AUC; 0.899, 95% CI = 0.816–0.982) for very early HCC, whereas a panel with EV‐DLEU2 and alpha‐fetoprotein exhibited the best positivity (96%) in very early HCC. Serum small EV‐MALAT1, EV‐DLEU2, EV‐HOTTIP, and EV‐SNHG1 may represent promising diagnostic markers for very early‐stage HCC.

Identification and Validation of a Four-Long Non-coding RNA Signature Associated With Immune Infiltration and Prognosis in Colon Cancer.

The emerging evidence has demonstrated the critical roles of long non-coding RNAs (lncRNAs) as regulators in the tumor immune microenvironment (TIME). However, the tumor immune infiltration-associated lncRNAs and their clinical significance in colon cancer have not yet been thoroughly investigated. This study performed an integrative analysis of lncRNA expression profiles and immune cell infiltration profiles and identified 258 immune infiltration-associated lncRNAs. Of them, four lncRNAs (AC008494.3, LINC00926, AC022034.1, and SNHG26) were significantly and independently associated with the patient’s overall survival. Finally, we developed a tumor immune infiltration-associated lncRNA signature (TIILncSig) comprising of these four lncRNAs, which can divide colon cancer patients of The Cancer Genome Atlas (TCGA) into high-risk and low-risk groups with a significantly different outcome [Hazard ratio (HR) = 2.718, 95% CI = 1.955–3.779, p < 0.001]. Prognostic performance of the TIILncSig was further validated in another independent colon cancer cohort (HR = 1.832, 95% CI = 1.045–3.21, p = 0.034). Results of multivariate Cox regression and stratification analysis demonstrated that the TIILncSig is an independent predictive factor from other clinical features (HR = 2.687, 95% CI = 1.912–3.776, p < 0.001 for TCGA cohort and HR = 1.837, 95% CI = 1.047–3.223, p = 0.034 for GSE17538 cohort). Literature analysis provided experimental evidence supporting roles of the TIILncSig in cancer carcinogenesis and progression and immune regulation. Summary, our study will help to understand the mechanisms of lncRNAs in immune regulation in the tumor microenvironment and provide novel biomarkers or targets for prognosis prediction and therapy decision-making for patients with colon cancer.

Comprehensive analysis of lncRNA expression profiles in cytopathic biotype BVDV-infected MDBK cells provides an insight into biological contexts of host–BVDV interactions

ABSTRACT Bovine viral diarrhea virus (BVDV) is the causative agent of bovine viral diarrhea-mucosal disease, which significantly affects the production performance of cattle, causing serious economic losses to the cattle industries worldwide. Up to now, some mechanisms involved in host–BVDV interaction are still not fully understood. The discovery of long non-coding RNAs (lncRNAs) has provided a new perspective on gene regulation in diverse biological contexts, particularly in viral infection and host immune responses. However, little is known about the profiles and functions of lncRNAs in host cells in response to BVDV infection. Here, we utilized Illumina sequencing to explore lncRNAs profiles in cytopathic (CP) biotype BVDV-infected MDBK cells to further reveal the potential roles of lncRNAs in BVDV infection and host–BVDV interaction with integrated analysis of lncRNAs and mRNA expression profiles. A total of 1747 significantly differentially expressed genes, DEGs (156 lncRNAs and 1591 mRNAs) were obtained via RNA-seq in BVDV-infected MDBK cells compared to mock-infected cells. Next, these DE lncRNAs and mRNAs were subjected to construct lncRNAs-mRNAs co-expression network followed by the prediction of potential functions of the DE lncRNAs. Co-expression network analysis elucidated that DE lncRNAs were significant enrichment in NOD-like receptor, TNF, NF-ĸB, ErbB, Ras, apoptosis, and fatty acid biosynthesis pathways, indicating that DE lncRNAs play important roles in host–BVDV interactions. Our data give an overview of changes in transcriptome and potential roles of lncRNAs, providing molecular biology basis for further exploring the mechanisms of host–BVDV interaction.

Analysis of lncRNA Expression Profile during the Formation of Male Germ Cells in Chickens.

Simple SummaryThe differentiation of germ cells plays an important role in sex differentiation in poultry. Therefore, it is necessary for us to explore the potential regulators in the process of germ cell development. In this study, RNA-seq was used to detect the expression profile of long non-coding RNAs (lncRNAs) in chicken embryonic stem cells (ESCs), primordial germ cells (PGCs) and spermatogonial stem cells (SSCs). The results showed that a total of 296, 280 and 357 differentially expressed lncRNAs (DELs) were screened in ESCs vs. PGCs, ESCs vs. SSCs and PGCs vs. SSCs, respectively. Functional analysis of the target genes of DELs showed that autophagy, Wnt/β-catenin, TGF-β, Notch and ErbB signaling pathways were involved in the differentiation process of male germ cells and, moreover, XLOC_612026, XLOC_612029, XLOC_240662, XLOC_362463, XLOC_023952, XLOC_674549, XLOC_160716, ALDBGALG0000001810, ALDBGALG0000002986, XLOC_657380674549, XLOC_022100 and XLOC_657380 were predicted to be the key lncRNAs in this process. Our findings could not only supply scientific data for constructing the gene regulatory network of germ cell development, but also provide new ideas for further optimizing the induction efficiency of germ cells in vitro.Germ cells have an irreplaceable role in transmitting genetic information from one generation to the next, and also play an important role in sex differentiation in poultry, while little is known about epigenetic factors that regulate germ cell differentiation. In this study, RNA-seq was used to detect the expression profiles of long non-coding RNAs (lncRNAs) during the differentiation of chicken embryonic stem cells (ESCs) into spermatogonial stem cells (SSCs). The results showed that a total of 296, 280 and 357 differentially expressed lncRNAs (DELs) were screened in ESCs vs. PGCs, ESCs vs. SSCs and PGCs vs. SSCs, respectively. Gene Ontology (GO) and KEGG enrichment analysis showed that DELs in the three cell groups were mainly enriched in autophagy, Wnt/β-catenin, TGF-β, Notch and ErbB and signaling pathways. The co-expression network of 37 candidate DELs and their target genes enriched in the biological function of germ cell development showed that XLOC_612026, XLOC_612029, XLOC_240662, XLOC_362463, XLOC_023952, XLOC_674549, XLOC_160716, ALDBGALG0000001810, ALDBGALG0000002986, XLOC_657380674549, XLOC_022100 and XLOC_657380 were the key lncRNAs in the process of male germ cell formation and, moreover, the function of these DELs may be related to the interaction of their target genes. Our findings preliminarily excavated the key lncRNAs and signaling pathways in the process of male chicken germ cell formation, which could be helpful to construct the gene regulatory network of germ cell development, and also provide new ideas for further optimizing the induction efficiency of germ cells in vitro.

Long Non-Coding RNA Profile Study Identifies an Immune-Related lncRNA Prognostic Signature for Kidney Renal Clear Cell Carcinoma.

Kidney renal clear cell carcinoma (KIRC) is the predominant pathological subtype of renal cell carcinoma (RCC) in adults. Long non-coding RNAs (lncRNAs) are an important class of gene expression regulators and serve fundamental roles in immune regulation. The intent of this study is to develop a novel immune-related lncRNA signature to accurately predict the prognosis for KIRC patients. Here, we performed genome-wide comparative analysis of lncRNA expression profiles in 537 KIRC patients from The Cancer Genome Atlas (TCGA) database. Cox regression model–identified immune-related lncRNAs were extracted for constructing a novel five immune-related lncRNA signature (AC008105.3, LINC02084, AC243960.1, AC093278.2, and AC108449.2) with the ability to predict the prognosis of KIRC patients. Univariate and multivariate Cox regression analyses demonstrated that the signature could act as an independent prognostic predictor for overall survival (OS). With the further investigation on different clinicopathological parameters, we found that the signature could divide KIRC samples into high-risk groups with shorter OS and low-risk groups with longer OS in different subgroups. Principal component analysis suggested that the five immune-related lncRNA signature drew a clear distinction between high- and low-risk groups based on the immune-related lncRNAs. The different immune status between the two groups was observed in gene set enrichment analysis and the ESTIMATE algorithm. Except for AC093278.2, the expressions of the other four lncRNAs expression were significantly upregulated in tumor tissues. In summary, the identified immune-lncRNA signature had important clinical implications in prognosis prediction and could be exploited as underlying immune therapeutic targets for KIRC patients.

Analysis of lncRNA expression profiles by sequencing reveals that lnc-AL928768.3 and lnc-AC091493.1 are novel biomarkers for disease risk and activity of rheumatoid arthritis.

This study aimed to analyze long non-coding RNA (lncRNA) expression profiles in synovium tissue of patients with RA using RNA sequencing, and to further assess the clinical values of dysregulated lncRNAs in RA diagnosis and monitoring. Thirty patients with RA who underwent knee arthroscopy and 30 controls with knee trauma who underwent surgery were consecutively enrolled and synovium tissue samples of both groups were obtained during surgery. In the exploration stage, lncRNA and mRNA expression profiles in three RA samples and three control samples were detected by RNA sequencing and bioinformatic analyses were then performed. In the validation stage, quantitative polymerase chain reaction (qPCR) was subsequently used to detect expression of five candidate lncRNAs in 30 patients with RA and 30 control patients. A total of 349 lncRNAs and 1582 mRNAs were upregulated and 806 lncRNAs and 1295 mRNAs were downregulated in patients with RA compared with controls. Enrichment analyses revealed that these dysregulated lncRNAs and mRNAs were mainly involved in regulating immune response, leukocyte migration, complement activation, and Bcell receptor signaling pathway. Subsequent qPCR validation discovered that lnc-AL928768.3 (P < 0.001) and lnc-AC091493.1 (P < 0.001) were elevated in patients with RA compared with controls and afford good predictive values for RA risk by receiver operating characteristic (ROC) curve analysis. Additionally, the two lncRNAs were positively associated with C-reactive protein level and disease activity score in 28 joints (ESR) (all P < 0.05). Analysis of lncRNA expression profiles by sequencing reveals that lnc-AL928768.3 and lnc-AC091493.1 are novel biomarkers for RA risk and activity.

Development and validation of a five-lncRNA signature with prognostic value in colon cancer.

Dysregulation of long noncoding RNAs (lncRNAs) has been found in a large number of human cancers, including colon cancer. Therefore, the implementation of potential lncRNAs biomarkers with prognostic prediction value are very much essential. GSE39582 data set was downloaded from database of Gene Expression Omnibus. Re-annotation analysis of lncRNA expression profiles was performed by NetAffx annotation files. Univariate and multivariate Cox proportional analyses helped select prognostic lncRNAs. Algorithm of random survival forest-variable hunting (RSF-VH) together with stepwise multivariate Cox proportional analysis were performed to establish lncRNA signature. The log-rank test was carried out to analyze and compare the Kaplan-Meier survival curves of patients' overall survival (OS). Receiver operating characteristic (ROC) analysis was used for comparing the survival prediction regarding its specificity and sensitivity based on lncRNA risk score, followed by calculating the values of area under the curve (AUC). The single-sample GSEA (ssGSEA) analysis was used to describe biological functions associated with this signature. Finally, to determine the robustness of this model, we used the validation sets including GSE17536 and The Cancer Genome Atlas data set.After re-annotation analysis of lncRNAs, a total of 14 lncRNA probes were obtained by univariate and multivariate Cox proportional analysis. Then, the RSF-VH algorithm and stepwise multivariate Cox analysis helped to build a five-lncRNA prognostic signature for colon cancer. The patients in group with high risk showed an obviously shorter survival time compared with patients in group with low risk with AUC of 0.75. In addition, the five-lncRNA signature can be used to independently predict the survival of patients with colon cancer. The ssGSEA analysis revealed that pathways such as extracellular matrix-receptor interaction was activated with an increase in risk score. These findings determined the strong power of prognostic prediction value of this five-lncRNA signature for colon cancer.

Systematic analysis of lncRNA expression profiles and atherosclerosis-associated lncRNA-mRNA network revealing functional lncRNAs in carotid atherosclerotic rabbit models.

Atherosclerosis, a multifactorial and chronic immune inflammatory disorder, is the main cause of multiple cardiovascular diseases. Researchers recently reported that lncRNAs may exert important functions in the progression of atherosclerosis (AS). Some studies found that lncRNAs can act as ceRNAs to communicate with each other by the competition of common miRNA response elements. However, lncRNA-associated ceRNA network in terms of atherosclerosis is limited. In present study, we pioneered to construct and systematically analyze the lncRNA-mRNA network and reveal its potential roles in carotid atherosclerotic rabbit models. Atherosclerosis was induced in rabbits (n = 3) carotid arteries via a high-fat diet and balloon injury, while age-matched rabbits (n = 3) were treated with normal chow as controls. RNA-seq analysis was conducted on rabbits carotid arteries (n = 6) with or without plaque formation. Based on the ceRNA mechanism, a ternary interaction network including lncRNA, mRNA, and miRNA was generated and an AS-related lncRNA-mRNA network (ASLMN) was extracted. Furthermore, we analyzed the properties of ASLMN and discovered that six lncRNAs (MSTRG.10603.16, 5258.4, 12799.3, 5352.1, 12022.1, and 12250.4) were highly related to AS through topological analysis. GO and KEGG enrichment analysis indicated that lncRNA MSTRG.5258.4 may downregulate inducible co-stimulator to perform a downregulated role in AS through T cell receptor signaling pathway and downregulate THBS1 to conduct a upregulated function in AS through ECM-receptor interaction pathway. Finally, our results elucidated the important function of lncRNAs in the origination and progression of AS. We provided an ASLMN of atherosclerosis development in carotid arteries of rabbits and probable targets which may lay the foundation for future research of clinical applications.

Comprehensive analysis of novel three-long noncoding RNA signatures as a diagnostic and prognostic biomarkers of human triple-negative breast cancer.

Currently, traditional predictors of prognosis (tumor size, nodal status, progesterone receptor [PR], estrogen receptor [ER], or human epidermal growth factor receptor-2 [HER2]) are insufficient for precise survival prediction for triple-negative breast cancer (TNBC). Long noncoding RNAs (lncRNAs) have been observed to exert critical functions in cancer, including in TNBC. Nevertheless, systematically tracking expression-based lncRNA biomarkers based on the sequence data for the prediction of prognosis in TNBC has not yet been investigated. To ascertain whether biomarkers exist that can distinguish TNBC from adjacent normal tissue or nTNBC, we implemented a comprehensive analysis of lncRNA expression profiles and clinical data of 1097 BC samples from The Cancer Genome Atlas database. A total of 1510 differentially expressed lncRNAs in normal and TNBC samples were extracted. Similarly, 672 differentially expressed lncRNAs between nTNBC and TNBC samples were detected. The receiver operating characteristic curve analysis indicated that three upregulated lncRNAs (AC091043.1, AP000924.1, and FOXCUT) may be of strong diagnostic value for predicting the existence of TNBC in the training and validation sets (area under the curve (AUC > 0.85). Kaplan-Meier analysis demonstrated that the other three lncRNAs (AC010343.3, AL354793.1, and FGF10-AS1) were associated with the prognosis of TNBC patients (P < 0.05). We used the three overall survival (OS)-related lncRNAs to establish a three-lncRNA signature. Multivariate Cox regression analysis suggested that the three-lncRNA signature was a prognostic factor independent of other clinical variables ( P < 0.01) for predicting OS in TNBC patients that could be utilized to classify patients into high- or low-risk subgroups. Our results might provide efficient signatures for clinical diagnosis and prognostic evaluation of TNBC.

Silencing of Long Noncoding RNA MIR22HG Triggers Cell Survival/Death Signaling via Oncogenes YBX1, MET, and p21 in Lung Cancer.

The long noncoding RNA (lncRNA) MIR22HG has previously been identified as a prognostic marker in hepatocellular carcinoma. Here, we performed a comprehensive analysis of lncRNA expression profiles from RNA-Seq data and report that MIR22HG plays a similar role in lung cancer. Analysis of 918 lung cancer and normal lung tissues and lung cancer cell lines revealed that MIR22HG was significantly downregulated in lung cancer; this decreased expression was associated with poor patient survival. MIR22HG bound and stabilized the YBX1 protein. Silencing of MIR22HG triggered both cell survival and cell death signaling through dysregulation of the oncogenes YBX1, MET, and p21. In this MIR22HG network, p21 played an oncogenic role by promoting cell proliferation and antiapoptosis in lung cancers. MIR22HG played a tumor-suppressive role as indicated by inhibition of multiple cell cycle-related genes in human primary lung tumors. These data show that MIR22HG has potential as a new diagnostic and prognostic marker and as a therapeutic target for lung cancer.Significance: The lncRNA MIR22HG functions as a tumor suppressor, with potential use a diagnostic/prognostic marker and therapeutic target in lung cancer. Cancer Res; 78(12); 3207-19. ©2018 AACR.

Screening and characterisation of sex differentiation-related long non-coding RNAs in Chinese soft-shell turtle (Pelodiscus sinensis)

Long non-coding RNAs (lncRNAs) perform distinct functions in various biological processes in mammals, including sex differentiation. However, the roles of lncRNAs in other vertebrates, especially in the Chinese soft-shell turtle (Pelodiscus sinensis), remain to be clarified. In this study, we performed genome-wide analysis of the lncRNA expression profiles in gonad tissues and screened numerous sex-specific lncRNAs in the Chinese soft-shell turtle. Of the 363,310,650 clean reads obtained, 5,994 sequences were typed as lncRNAs, of which 4,463 were novel. A selection of sex-specific lncRNAs (♀ 932, ♂ 449) from female ovaries and male testis were shown to act on target genes in cis and in trans, and most were involved in gonad differentiation based on Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. Furthermore, interactions among the differentially expressed lncRNA-mRNAs and protein coding genes were identified by construction of correlation networks. Overall, our systematic analysis of lncRNA expression profiles in gonad tissues revealed numerous sex-specific lncRNAs in P. sinensis. Thereby, these findings provide new insights into the function of lncRNAs in sex differentiation and highlight a group of candidate lncRNAs for future studies.