Analysis Of lncRNA Expression Research Articles

Analysis of lncRNA Expression in Patients With Eosinophilic and Neutrophilic Asthma Focusing on LNC_000127.

Long non-coding RNA (lncRNA) is important in many diseases. Some studies have shown that lncRNA affects the pathogenesis of systemic inflammation of asthma. lncRNA regulates gene transcription, protein expression, and epigenetic regulation. However, lncRNAs associated with different airway phenotypes, such as eosinophilic (Eos) and neutrophilic (Neu) asthma have not been identified. The goal of this study was to determine the differences in circulating lncRNA signatures in Eos and Neu samples. Using RNA-sequencing (RNA-seq), lncRNA expression was evaluated in peripheral whole blood samples among Eos patients, Neu patients, and healthy individuals (Control). Bioinformatic analysis was used to predict relevant biological pathways. Quantitative PCR (qPCR) was used to measure gene expression in whole blood samples, Jurkat cells, and human CD4+ T cells. Finally, a novel lncRNA, LNC_000127, was inhibited by transfection of Jurkat cells with a lentiviral vector, and the effect was examined by Human Asthma RT2 Profiler™ PCR Array and western blotting. Compared to control samples, Eos samples contained 190 unique lncRNAs and Neu samples had 166 unique lncRNAs (difference ≥2-fold). KEGG pathway annotation data and GO terms revealed that different lncRNAs are involved in different mechanisms. LNC_000127, was highly expressed in Eos samples before treatment; its expression was increased in Jurkat cells and human CD4+ T cells following stimulation with PMA/CD28. Subsequent analyses revealed that LNC_000127 functions in the Th2 inflammation pathway. The results suggest that lncRNAs are involved in different phenotypes of asthma. Whether the different phenotypes of asthma can be recognized based on these lncRNAs (as biomarkers) requires further analysis. Targeting LNC_000127 may be effective for reducing Th2 inflammation in Eos asthma.

Tissue specific long non-coding RNAs are involved in aroma formation of black tea

With the progress of sequencing technology coupled with in silico approaches, disclosure of long non-coding RNA (lncRNAs) from RNAseq data has become easy and reliable. Till today, no methodical investigation of lncRNAs and their regulatory roles in tea have been studied. In this study, using 170 RNAseq data (˜7157 million reads) of 11 harvestable tissues, 33,400 putative high certainty lncRNAs were discovered, among which 99.76% were found to be putative novel lncRNAs. The expression analysis of lncRNAs from 53 RNAseq data of 7 tissues (axillary bud, a bud and a leaf, a bud and 2 leaves, apical bud and 2 leaves, 2nd leaf, 4th leaf, and 6th leaf) demonstrated their tissue-specific expression. Further, around 1,654 lncRNAs were found to be endogenous target mimics of miRNAs that interacted with 698 mRNAs of tea genome. Based on their target i.e. coding-gene partners by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) biological pathway showed that 378 lncRNAs are involved in major aroma formation pathway of tea. Present study also provides valuable information to uncover the various molecular functions of lncRNAs that regulate aroma formation of tea.

Microarray analysis of lncRNA expression in rabies virus infected human neuroblastoma cells

Rabies, caused by the rabies virus (RABV), is the oldest known zoonotic infectious disease. Although the molecular mechanisms of RABV pathogenesis have been investigated extensively, the interactions between host and RABV are not clearly understood. It is now known that long non-coding RNAs (lncRNAs) participate in various physiological and pathological processes, but their possible roles in the host response to RABV infection remain to be elucidated. To better understand the pathogenesis of RABV, RNAs from RABV-infected and uninfected human neuroblastoma cells (SK-N-SH) were analyzed using human lncRNA microarrays. We identified 896 lncRNAs and 579 mRNAs that were differentially expressed after infection, indicating a potential role for lncRNAs in the immune response to RABV. Differentially expressed RNAs were examined using Gene Ontology (GO) analysis and were tentatively assigned to biological pathways using the Kyoto Encyclopedia of Genes and Genomes (KEGG). A lncRNA-mRNA-transcription factor co-expression network was constructed to relate lncRNAs to regulatory factors and pathways that may be important in virus-host interactions. The network analysis suggests that E2F4, TAF7 and several lncRNAs function as transcriptional regulators in various signaling pathways. This study is the first global analysis of lncRNA and mRNA co-expression during RABV infection, provides deeper insight into the mechanism of RABV pathogenesis, and reveals promising candidate for future investigation.

Global long non-coding RNA expression in the rostral anterior cingulate cortex of depressed suicides

Long non-coding RNAs (lncRNAs) are an emerging class of regulatory RNA that may be implicated in psychiatric disorders. Here we performed RNA-sequencing in the rostral anterior cingulate cortex of 26 depressed suicides and 24 matched controls. We first performed differential lncRNA expression analysis, and then conducted Weighted Gene Co-expression Network Analysis (WGCNA) to identify co-expression modules associating with depression and suicide. We identified 23 differentially expressed lncRNAs (FDR < 0.1) as well as their differentially expressed overlapping and antisense protein-coding genes. Several of these overlapping or antisense genes were associated with interferon signaling, which is a component of the innate immune response. Using WGCNA, we identified modules of highly co-expressed genes associated with depression and suicide and found protein-coding genes highly connected to differentially expressed lncRNAs within these modules. These protein-coding genes were located distal to their associated lncRNAs and were found to be part of several GO terms enriched in the significant modules, which include: cytoskeleton organization, plasma membrane, cell adhesion, nucleus, DNA-binding, and regulation of dendrite development and morphology. Altogether, we report that lncRNAs are differentially expressed in the brains of depressed individuals who died by suicide and may represent regulators of important molecular functions and biological processes.

Genome-wide identification and differentially expression analysis of lncRNAs in tilapia

BackgroundLong noncoding RNAs (LncRNAs) play important roles in fundamental biological processes. However, knowledge about the genome-wide distribution and stress-related expression of lncRNAs in tilapia is still limited.ResultsGenome-wide identification of lncRNAs in the tilapia genome was carried out in this study using bioinformatics tools. 103 RNAseq datasets that generated in our laboratory or collected from NCBI database were analyzed. In total, 72,276 high-confidence lncRNAs were identified. The averaged positive correlation coefficient (r_mean = 0.286) between overlapped lncRNA and mRNA pairs showed significant differences with the values for all lncRNA-mRNA pairs (r_mean = 0.176, z statistics = − 2.45, p value = 0.00071) and mRNA-mRNA pairs (r_mean = 0.186, z statistics = − 2.23, p value = 0.0129). Weighted correlation network analysis of the lncRNA and mRNA datasets from 12 tissues identified 21 modules and many interesting mRNA genes that clustered with lncRNAs. Overrepresentation test indicated that these mRNAs enriched in many biological processes, such as meiosis (p = 0.00164), DNA replication (p = 0.00246), metabolic process (p = 0.000838) and in molecular function, e.g., helicase activity (p = 0.000102) and catalytic activity (p = 0.0000612). Differential expression (DE) analysis identified 99 stress-related lncRNA genes and 1955 tissue-specific DE lncRNA genes. MiRNA-lncRNA interaction analysis detected 72,267 lncRNAs containing motifs with sequence complementary to 458 miRNAs.ConclusionsThis study provides an invaluable resource for further studies on molecular bases of lncRNAs in tilapia genomes. Further function analysis of the lncRNAs will help to elucidate their roles in regulating stress-related adaptation in tilapia.

Differential long noncoding RNA expressions in peripheral blood mononuclear cells for detection of acute ischemic stroke.

Long noncoding RNAs (lncRNAs) have been highlighted to be involved in the pathological process of ischemic stroke (IS). The purpose of the present study was to investigate the expression profile of lncRNAs in peripheral blood mononuclear cells (PBMCs) of acute IS patients and to explore their utility as biomarkers of IS. Distinctive expression patterns of PBMC lncRNAs were identified by an lncRNA microarray and individual quantitative real-time PCR (qRT-PCR) in four independent sets for 206 IS, 179 healthy controls (HCs), and 55 patients with transient ischemic attack (TIA). A biomarker panel (lncRNA-based combination index) was established using logistic regression. LncRNA microarray analysis showed 70 up-regulated and 128 down-regulated lncRNAs in IS patients. Individual qRT-PCR validation demonstrated that three lncRNAs (linc-DHFRL1-4, SNHG15, and linc-FAM98A-3) were significantly up-regulated in IS patients compared with HCs and TIA patients. Longitudinal analysis of lncRNA expression up to 90 days after IS showed that linc-FAM98A-3 normalized to control levels by day 7, while SNHG15 remained increased, indicating the ability of lncRNAs to monitor IS dynamics. Receiver-operating characteristic (ROC) curve analysis showed that the lncRNA-based combination index outperformed serum brain-derived neurotrophic factor (BDNF) and neurone-specific enolase (NSE) in distinguishing IS patients from TIA patients and HCs with areas under ROC curve of more than 0.84. Furthermore, the combination index increased significantly after treatment and was correlated with neurological deficit severity of IS. The panel of these altered lncRNAs was associated with acute IS and could serve as a novel diagnostic method.

Abstract 3732: Insights into the non-coding genome of parathyroid tumors

Abstract Background. Parathyroid tumors are characterized by genetic and epigenetic alterations resulting in aberrant expression of protein coding genes and non-coding RNAs. Although long non-coding RNAs (lncRNAs) play a regulatory role in endocrine cancer pathogenesis, a lncRNAs signature in human parathyroid tumors is still missing. Here we investigated the lncRNAs alterations, both at genomic and transcriptional level, in human non-familial parathyroid tumors. Methods. The expression of 90 lncRNAs was investigated in 4 parathyroid carcinomas (PCas), 12 adenomas (PAds) and 2 normal glands (PaNs) using a commercial array. Both unsupervised (hierarchical clustering-HCL and Principal Component Analysis-PCA) and supervised (Significance Analysis of Microarray, SAM) analyses were performed to identify differences in lncRNAs expression between the 3 tissue types. Significant lncRNAs were validated in a second set of parathyroid tissues including 7 PCas, 26 PAds, 6 atypical PAds (aPAds) and 4 PaNs. Genomic characterization of 21 PAds was performed by array Comparative Genomic Hybridization (aCGH). CDC73 and Multiple Endocrine Neoplasia 1 (MEN1) genes mutations were detected by Sanger sequencing. Results. HCL analysis of lncRNAs expression identified 2 major groups in which PaNs and PCas were distinguished. Nine lncRNAs were differentially expressed in parathyroid tissues. Specifically, KCNQ1OT1 and SNHG6 were enriched in PaNs, HAR1B, MEG3, HOXA3as and NEAT1 expression characterized PAds, whereas BC200, HOXA6as and WT1-AS were significantly upregulated in PCas. Besides confirming previous data, validation analysis highlighted a different lncRNAs expression pattern in PCas and aPAds according to CDC73 mutation status, with mutated tumors overexpressing the majority of the lncRNAs. Interestingly, BACE1-AS, KCNQ1OT1, NEAT1 and SNHG6 levels in PAds were significantly correlated with MEN1 levels while HAR1B upregulation was associated with chromosome 11 loss of heterozygosity (LOH). Conclusions. Overall these findings shed light on lncRNAs deregulation in parathyroid pathobiology. Parathyroid tumors histotypes are characterized by different lncRNAs signatures that are related to chromosome 11 derangements and to MEN1 inactivation. Finally, MEN1 may play an epigenetic role in lncRNAs regulation, supporting the important role of chromosome 11 in parathyroid tumorigenesis. Citation Format: Annamaria Morotti, Irene Forno, Valentina Andrè, Vito Guarnieri, Andrea Terrasi, Rosa Maria Silipigni, Silvana Guerneri, Chiara Verdelli, Alfredo Scillitani, Leonardo Vicentini, Filomena Cetani, Edoardo Beretta, Sabrina Corbetta, Valentina Vaira. Insights into the non-coding genome of parathyroid tumors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3732.

LINC00857 expression predicts and mediates the response to platinum-based chemotherapy in muscle-invasive bladder cancer.

Approximately 20% of patients with bladder cancer are diagnosed with muscle‐invasive disease (MIBC). The treatment involves radical cystectomy, but almost 50% of patients with MIBC eventually relapse and develop metastasis. The use of platinum‐based chemotherapy in the neoadjuvant setting or for metastatic patients has been shown to improve the overall survival in a subset of patients. Unfortunately, no biomarkers are available to select patients with MIBC who will benefit from chemotherapy or to monitor the efficacy of the treatment. Recently, long noncoding RNAs (lncRNAs) were shown to regulate a variety of processes involved in the development and progression of cancer, including bladder cancer. Moreover, several lncRNAs have been shown to play a role in chemotherapy resistance. Here, we analyzed lncRNA expression associated with response to platinum‐based chemotherapy in metastatic MIBC using data from the MiTranscriptome lncRNA expression database. Expression of the lncRNA,LINC00857, was found to be upregulated in tumors from patients that did not respond to platinum‐based chemotherapy. Moreover, high expression of LINC00857 is correlated with shorter recurrence‐free and overall survival of patients with MIBC. Knockdown of LINC00857 significantly decreased cell viability of bladder cancer cell lines through the induction of apoptosis. Furthermore, LINC00857 knockdown sensitized UM‐UC‐3 and T24 bladder cancer cells to cisplatin, via the negative regulation of the LMAN1 gene. Our data indicate that LINC00857 plays an important role in the regulation of response to platinum‐based chemotherapy. LINC00857 potentially could serve as a novel prognostic and predictive biomarker and might be a therapeutic target to overcome cisplatin resistance in patients with MIBC.

LncRNA-based study of epigenetic regulations in diabetic peripheral neuropathy.

Diabetes remains one of the most prevalent non-communicable diseases in the world, affecting over 400 million of people worldwide, causing serious complications leading to amputations and even death. Over the years, researchers have found that, in addition to genomic mutations, epigenetic mechanisms also play a role in the development of diabetes-specifically type-2 diabetes. Long noncoding RNAs (lncRNAs) have been linked to mediate epigenetic mechanisms, including those in late-stage diabetes. This study attempts to assess the unexplored topic of how lncRNAs could be used to assess the epigenetic mechanisms present in diabetic peripheral neuropathy (DPN); a serious complication of the disease often leading to amputation. Differential lncRNA expression analysis was done with a dataset containing DPN and healthy patients. Standard and corrected t test, and also LIMMA was applied. Results of this study indicates the usefulness of lncRNAs as an exploratory tool to elucidate the complexity of the epigenetic mechanisms of human DPN.

In Inflamed Intestinal Tissues and Epithelial Cells, Interleukin 22 Signaling Increases Expression of H19 Long Noncoding RNA, Which Promotes Mucosal Regeneration

Inflammation affects regeneration of the intestinal epithelia; long noncoding RNAs (lncRNAs) regulate cell functions, such as proliferation, differentiation, and migration. We investigated the mechanisms by which the lncRNA H19, imprinted maternally expressed transcript (H19) regulates regeneration of intestinal epithelium using cell cultures and mouse models of inflammation. We performed RNA-sequencing transcriptome analyses of intestinal tissues from mice with lipopolysaccharide (LPS)-induced sepsis to identify lncRNAs associated with inflammation; findings were confirmed by quantitative real-time polymerase chain reaction and in situ hybridization analyses of intestinal tissues from mice with sepsis or dextran sulfate sodium (DSS)-induced mucosal wound healing and patients with ulcerative colitis compared to healthy individuals (controls). We screened cytokines for their ability to induce expression of H19 in HT-29 cells and intestinal epithelial cells (IECs), and confirmed findings in crypt epithelial organoids derived from mouse small intestine. IECs were incubated with different signal transduction inhibitors and effects on H19 lncRNA levels were measured. We assessed intestinal epithelial proliferation or regeneration in H19ΔEx1/+ mice given LPS or DSS vs wild-type littermates (control mice). H19 was overexpressed in IECs using lentiviral vectors and cell proliferation was measured. We performed RNA antisense purification, RNA immunoprecipitation, and luciferase reporter assays to study functions of H19 in IECs. In RNA-sequencing transcriptome analysis of lncRNA expression in intestinal tissues from mice, we found that levels of H19 lncRNA changed significantly with LPS exposure. Levels of H19 lncRNA increased in intestinal tissues of patients with ulcerative colitis, mice with LPS-induced and polymicrobial sepsis, or mice with DSS-induced colitis, compared with controls. Increased H19 lncRNA localized to epithelial cells in the intestine, regardless of Lgr5 messenger RNA expression. Exposure of IECs to interleukin 22 (IL22) increased levels of H19 lncRNA with time and dose, which required STAT3 and protein kinase A activity. IL22 induced expression of H19 in mouse intestinal epithelial organoids within 6 hours. Exposure to IL22 increased growth of intestinal epithelial organoids derived from control mice, but not H19ΔEx1/+ mice. Overexpression of H19 in HT-29 cells increased their proliferation. Intestinal mucosa healed more slowly after withdrawal of DSS from H19ΔEx1/+ mice vs control mice. Crypt epithelial cells from H19ΔEx1/+ mice proliferated more slowly than those from control mice after exposure to LPS. H19 lncRNA bound to p53 and microRNAs that inhibit cell proliferation, including microRNA 34a and let-7; H19 lncRNA binding blocked their function, leading to increased expression of genes that promote regeneration of the epithelium. The level of lncRNA H19 is increased in inflamed intestinal tissues from mice and patients. The inflammatory cytokine IL22 induces expression of H19 in IECs, which is required for intestinal epithelial proliferation and mucosal healing. H19 lncRNA appears to inhibit p53 protein and microRNA 34a and let-7 to promote proliferation of IECs and epithelial regeneration.

Analysis of LncRNA expression in cell differentiation

ABSTRACTLineage-specific cell differentiation is a precise and coordinated biological process. To explore the roles of long noncoding RNA (lncRNA) in this process, the expression of polyA-minus RNAs was comparatively studied during the course of myocyte and adipocyte differentiation. In addition to identifying thousands of novel lncRNAs, distinct lncRNA profiles were revealed during lineage-specific differentiation, showing their active involvement in this process. This study further found that lncRNAs were organized in clusters and are co-regulated, constituting transcription open domains (TODs). In myocyte differentiation of C2C12 cells, loss-of-function screening identified three myogenic lncRNAs. Knockdown of their expression compromised not only the differentiation process, but also the essential signaling pathway. In addition to showing that lncRNAs are actively involved in cell differentiation, our results start to reveal a comprehensive signaling pathway, involving both protein and lncRNA factors.

Identification of lncRNAs by microarray analysis reveals the potential role of lncRNAs in cervical cancer pathogenesis.

Long non-coding RNAs (lncRNAs) have been acknowledged to serve a significant role in cancer biology and abnormal expression in tumors is frequently observed. However, their mechanisms in cervical cancer remain unclear. With a genome-wide analysis of lncRNA expression in cervical cancer tissues, the present study aimed to identify lncRNA targets for the further study of cervical cancer. To elucidate the specific role of lncRNAs in the pathogenesis of this type of cancer, 6 cervical cancer samples paired with normal cervical tissues were obtained. Expression profiles of lncRNAs and mRNAs were constructed through microarray analysis and confirmed by reverse transcription-quantitative polymerase chain reaction (RT-qPCR) methods. Gene Ontology and pathway enrichment analyses were performed with computational methods. On the basis of correlations between the differential expression levels of lncRNAs and mRNAs, a coding-non-coding gene co-expression network (CNC network) was established. The differential expression of 5,844 lncRNAs and 4,436 mRNAs were discovered in cervical cancer samples compared with normal cervical tissues. Among the differentially expressed lncRNAs, 14 were chosen at random and validated by RT-qPCR; the majority of the results measured were consistent with the microarray results. Furthermore, the lncRNA ENST00000551152 was found to be upregulated and TCO. NS_00001368 lncRNA was downregulated in cervical cancer cell lines. The CNC network included 592 network nodes and 934 associations between 12 lncRNAs and 580 protein-coding genes, indicating that one lncRNA could act on a maximum of 141 coding genes, and that one coding gene may corresponded with a maximum of 5 lncRNAs. Overall, the present study has provided a complete expression profile of lncRNAs and mRNAs in cervical cancer, which may now be used to establish a solid foundation for cervical cancer research. These results may provide significant information for improving the understanding of the pathogenesis of cervical cancer and indicate potential therapeutic targets.

Peripheral whole blood lncRNA expression analysis in patients with eosinophilic asthma.

Long noncoding RNA (lncRNA) plays roles in many diseases including asthma. Several lncRNAs function in the early differentiation of T-helper cells. lncRNA controls gene transcription, protein expression, and epigenetic regulation. Of the 4 asthma phenotypes, eosinophilic asthma (EA) is the most common. However, the lncRNAs associated with eosinophilic asthma have yet to be identified.We designed a study to identify the circulating lncRNA signature in EA samples. We tested whether significant differences in lncRNA expression were observed between blood samples from patients with EA and healthy individuals (control). Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed for the lncRNA-mRNA (messenger RNA) co-expression network. lncRNA expression was measured using quantitative real-time PCR (polymerase chain reaction).A total of 41 dysregulated lncRNAs and 762 dysregulated mRNAs (difference ≥ 2-fold) were found in EA compared to control samples. GO terms and KEGG pathway annotation data revealed that several lncRNAs are significantly associated with EA. KEGG pathway annotation indicated that the pathways most enriched in EA were measles, T cell receptor signaling pathway, peroxisome proliferator activated-receptors (PPAR) signaling pathway, Fc gamma R-mediated phagocytosis, NF (nuclear factor) kappa B signaling pathway, chemokine signaling pathway, and primary immunodeficiency. Using qRT-PCR, lncRNA was confirmed to differ significantly between EA and control samples.The results presented here show that several lncRNAs may take part in the immune regulation of EA. Whether these lncRNAs can be used as biomarkers needs further study.

Long noncoding RNAs involve in resistance to Verticillium dahliae, a fungal disease in cotton.

SummaryLong noncoding RNAs (lncRNAs) have several known functions in plant development, but their possible roles in responding to plant disease remain largely unresolved. In this study, we described a comprehensive disease‐responding lncRNA profiles in defence against a cotton fungal disease Verticillium dahliae. We further revealed the conserved and specific characters of disease‐responding process between two cotton species. Conservatively for two cotton species, we found the expression dominance of induced lncRNAs in the Dt subgenome, indicating a biased induction pattern in the co‐existing subgenomes of allotetraploid cotton. Comparative analysis of lncRNA expression and their proposed functions in resistant Gossypium barbadense cv. ‘7124’ versus susceptible Gossypium hirsutum cv. ‘YZ1’ revealed their distinct disease response mechanisms. Species‐specific (LS) lncRNAs containing more SNPs displayed a fiercer inducing level postinfection than the species‐conserved (core) lncRNAs. Gene Ontology enrichment of LS lncRNAs and core lncRNAs indicates distinct roles in the process of biotic stimulus. Further functional analysis showed that two core lncRNAs, GhlncNAT‐ANX2‐ and GhlncNAT‐RLP7‐silenced seedlings, displayed an enhanced resistance towards V. dahliae and Botrytis cinerea, possibly associated with the increased expression of LOX1 and LOX2. This study represents the first characterization of lncRNAs involved in resistance to fungal disease and provides new clues to elucidate cotton disease response mechanism.

PUB007 Screening and Validation of Lung Adenocarcinoma Related Long Non-Coding RNA Based on Profiling Microarray

A large number of long noncoding RNAs (lncRNAs) have been found to be implicated in varieties of tumors. However, the contributions of lncRNAs to tumorigenesis in lung adenocarcinoma (LAD) remain largely unknown. We performed a genome-wide analysis of lncRNA expression in LAD and matched nontumor (NT) tissues to identify new targets for further study of renal carcinoma. The genome-wide analysis of lncRNA expression in 3 LAD and matched NT tissues were conducted using 4×180K Agilent lncRNA Chips and 6 lncRNAs were selected and validated by qRT-PCR in 90 LAD patients. The differentially expressed lncRNAs and mRNAs were recognized through P value and fold-change (FC) filtering. Potential targets associated with LAD were identified by gene ontology and pathway analyses. Construction of the co-expression network was accomplished using Cytoscape. A total of 460 lncRNAs and 771 mRNAs were deregulated and 134 lncRNAs and 466 mRNAs were upregulated in LAD tissues, compared with paired NT tissues. PCR results showed the expressions of these 6 lncRNAs were consistent with the chips. Moreover, the co-expression network analysis portended 641 nodes and 571 connections between 109 lncRNAs and 532 coding genes. Lastly, LINC00578 could be involved in the pathogenesis of LAD and its expression level was closely related to disease-free survival (DFS) and overall survival (OS) in patients without distant metastasis. Our results indicated that these abnormal lncRNAs could respond to lung carcinoma progression and LINC00578 may act as a potential target for future treatment of LAD.

A long non-coding RNA expression signature to predict survival of patients with colon adenocarcinoma.

Colon cancer is the most common type of gastrointestinal cancer and is still the leading cause of cancer-related mortality worldwide. Long non-coding RNAs (lncRNAs) have been proved to be superior biomarkers in cancer diagnosis and prognosis than miRNAs and protein-coding genes. In the current study, our objective was to detect novel lncRNA biomarkers by analyzing lncRNA expression profiles and clinical data in a large cohort of patients with colon patients from The Cancer Genome Atlas (TCGA). By using Cox regression analysis, we identified two lncRNAs (SNHG6 and CTD-2354A18.1) which could be independent prognostic factors for predicting clinical outcome in colon adenocarcinoma. Then a linear combination of these two lncRNA biomarkers (SNHG6 and CTD-2354A18.1), termed two-lncRNA signature, was developed in the training set as a predictor for OS in patients with colon adenocarcinoma, and validated in the testing set and the entire patient set. This two-lncRNA signature demonstrated significant prognostic performance in both the testing set and the entire patient set which classified the patients into two groups with significantly different OS. The multivariate and stratified analysis suggested that the prognostic value of the two-lncRNA signature was independent of other traditional clinical variables. Functional analysis suggested that these two lncRNA biomarkers might be mainly involved in transcription/translation-related or DNA repair-related biological processes. In summary, our results warrant further studies on these lncRNAs that will improve our understanding of the mechanisms associated with pathogenesis and progression of colon adenocarcinoma.

Differential expression profiles of long non-coding RNAs as potential biomarkers for the early diagnosis of acute myocardial infarction.

Acute myocardial infarction (AMI) is a major cause of morbidity and mortality worldwide. The early diagnosis of AMI is crucial for deciding the course of treatment and saving lives. Long non-coding RNAs (lncRNAs) are recently discovered ncRNA class and their dysregulated expression has been implicated in cardiovascular diseases. In this study, we analyzed lncRNA expression pattern by using two microarray datasets of AMI and healthy samples from the Gene Expression Omnibus (GEO) database and tried to identify novel AMI-related lncRNAs and investigate the predictive roles of lncRNAs in the early diagnosis of AMI. From the discovery cohort, 11 differentially expressed lncRNAs were identified as candidate biomarkers that were validated in the discovery cohort, internal cohort and an independent cohort, respectively. Hierarchical clustering analysis suggested that the expression pattern of these 11 candidate lncRNA biomarkers was closely associated with disease status of samples. Then a lncRNA risk classifier was developed by integrating expression value of 11 differentially expressed lncRNAs using support vector machine (SVM) algorithm. The results of leaving one out cross-validation (LOOCV) suggested that the lncRNA risk classifier has a good discrimination between AMI patients and healthy samples with the area under ROC curve (AUC) of 0.955, 0.92 and 0.701 in three cohorts, respectively. Functional enrichment analysis suggested that these 11 candidate lncRNA biomarkers might be involved in inflammation- and immune-related biological processes. Our study indicates the potential roles in the early diagnosis of AMI and will improve our understanding of the molecular mechanism of the occurrence and recurrence of AMI.

Abstract 3501: Prognostic value of a 4 lncRNA signature in patients with non-small cell lung cancer: a lncRNA expression analysis

Abstract Recently, increasing evidence indicates that lncRNA plays an important role in the cancer development and progression. In this study, we are aimed to identify lncRNA signature for predicting survival of non-small cell lung cancer (NSCLC) patients. A total of 366 NSCLC cases, which were divided into a training and validation set, were detected by lncRNA microarray (containing 2412 lncRNA probes), and another 73 cases as an independent set were analyzed by qRT-PCR. LncRNA microarray analysis identified a total of 305 differentially expressed lncRNAs (138 up-regulated and 167 down-regulated) between NSCLC and normal tissues in the training set. We then validated the microarray data by qRT-PCR analysis of 5 lncRNAs (2 up-regulated and 3 down-regulated) in 30 paired NSCLC and adjacent lung tissues randomly selected from the training set. We then used a stepwise forward process to select the best combination of lncRNAs with the most significance in prediction of NSCLC prognosis and a 4-lncRNA prognostic signature was established, which was significantly associated with overall survival (hazard ratio [HR]: 3.563, 95% confidence interval [CI]: 2.118-5.995, P &amp;lt;0.001) and disease-free survival (HR: 3.236, 95% CI: 2.116-4.940, P &amp;lt;0.001) in the training set. This prognostic signature was validated in the validation (OS, HR: 3.186, 95% CI: 1.849-5.488, P &amp;lt;0.001; DFS, HR: 2.967, 95% CI: 1.949-4.517, P &amp;lt;0.001) and independent sets (OS, HR: 4.703, 95% CI: 1.923-11.50, P &amp;lt;0.001; DFS, HR: 4.549, 95% CI: 2.139-9.674, P &amp;lt;0.001). This 4-lncRNA signature has been demonstrated as an independent prognostic factor, which significantly improves the prognostic accuracy of TNM staging system in a combined model as assessed by ROC curve analyses in the three sets, respectively. Therefore, the 4-lncRNA signature has potential prognostic role in NSCLC patients. Citation Format: XiaoRan Long, HuiYun Wang, ChunLei Ge, Xin Song, MeiYin Zhang, XiaoFeng Zhen. Prognostic value of a 4 lncRNA signature in patients with non-small cell lung cancer: a lncRNA expression analysis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 3501. doi:10.1158/1538-7445.AM2017-3501

A six-long non-coding RNAs signature as a potential prognostic marker for survival prediction of ER-positive breast cancer patients.

Dysregulated expression of lncRNAs has been observed in various human complex diseases (including cancers) by recent transcriptional profiling studies, highlighting potentials of lncRNAs as biomarkers for cancer diagnosis and prognosis. Despite some efforts have been made to search for novel lncRNA signature in breast cancer, the prognostic value of lncRNAs for ER-positive breast cancer patients still needs to be systematically investigated. In this study, we analyzed lncRNA expression profiles in a large of more than 600 breast cancer patients with ER-positive status from The Cancer Genome Atlas (TCGA) and identified six lncRNAs that are significantly associated with survival. Then a linear risk score model comprising six prognostic lncRNAs, termed six-lncRNA signature, was developed to identify high-risk patients from low-risk cases. The results of Kaplan-Meier analysis and ROC curves demonstrated the good sensitivity and specificity in survival prediction both in the training and testing datasets. Multivariate Cox regression analysis and stratified analysis showed that the six-lncRNA signature is an independent prognostic marker in survival prediction for ER-positive breast cancer patients. The GO enrichment analysis suggested that the six-lncRNA might involve with known breast cancer-related biological processes. With further experimental validation, these identified prognostic lncRNAs might have clinical implications for more personalized risk assessment for ER-positive breast cancer patients.

Panel of seven long noncoding RNA as a candidate prognostic biomarker for ovarian cancer.

Ovarian cancer is one of the most common and lethal gynecological malignancies. The diagnosis of ovarian cancer is often at an advanced stage. Accumulated evidence suggests that long noncoding RNAs (lncRNAs) play important roles during ovarian tumorigenesis. In this study, using the lncRNA-mining approach, we analyzed lncRNA expression profiles of 493 ovarian cancer patients from Gene Expression Omnibus datasets, and identified a signature group of seven lncRNAs (BC037530, AK021924, AK094536, AK094536, BC062365, BC004123 and BC007937) associated with patient survival in the training dataset GSE9891. We also formulated a risk score model to divide patients into low-risk and high-risk groups based on the expression of these seven lncRNAs. We further validated the predictive power of our risk score model in two other datasets, GSE26193 and GSE63885. Our analysis showed that the seven-lncRNA signature can serve as an independent predictor apart from Federation of Gynecology and Obstetrics (FIGO) stage and patient age. Further investigation revealed the seven-lncRNA signature correlated with few critical signaling pathways involved in cancer. Combined, all these findings strongly support that the seven-lncRNA signature can serve as a strong prognosis biomarker.