Identification of novel differentially expressed lncRNA and mRNA transcripts in clear cell renal cell carcinoma by expression profiling.
ABSTRACT: Clear cell renal cell carcinoma (ccRCC) is a common human malignancy. Despite numerous efforts, there is still no reliable biomarker or combination of biomarkers available for daily practice. Our study was designed to explore the expression profile of messenger RNA (mRNA) and long non-coding RNA (lncRNA) transcripts in ccRCC in order to identify potential diagnostic biomarkers for patients with ccRCC. Total RNA from corresponding normal and malignant tissue of 15 patients with ccRCC was isolated. Expression profiling was performed using a custom Agilent gene expression microarray which allowed the analysis of 34,144 mRNA and 32,183 lncRNA transcripts. We observed that a subset of mRNA (n = 1064; 3.1%) and lncRNA (n = 1308; 4.1%) transcripts are dysregulated (fold change > 2) in ccRCC tissue. The relative higher number of differentially expressed lncRNAs indicates that lncRNA profiling may be better suited for diagnostic purposes; a number of so far unknown RNAs with potential diagnostic interest in ccRCC are identified by our gene expression profiling study. The data are deposited in the Gene Expression Omnibus (GSE61763).
Project description:Long non-coding RNAs (lncRNA) play an important role in carcinogenesis; knowledge on lncRNA expression in renal cell carcinoma is rudimental. As a basis for biomarker development, we aimed to explore the lncRNA expression profile in clear cell renal cell carcinoma (ccRCC) tissue.Microarray experiments were performed to determine the expression of 32,183 lncRNA transcripts belonging to 17,512 lncRNAs in 15 corresponding normal and malignant renal tissues. Validation was performed using quantitative real-time PCR in 55 ccRCC and 52 normal renal specimens. Computational analysis was performed to determine lncRNA-microRNA (MiRTarget2) and lncRNA-protein (catRAPID omics) interactions. We identified 1,308 dysregulated transcripts (expression change >2-fold; upregulated: 568, downregulated: 740) in ccRCC tissue. Among these, aberrant expression was validated using PCR: lnc-BMP2-2 (mean expression change: 37-fold), lnc-CPN2-1 (13-fold), lnc-FZD1-2 (9-fold), lnc-ITPR2-3 (15-fold), lnc-SLC30A4-1 (15-fold), and lnc-SPAM1-6 (10-fold) were highly overexpressed in ccRCC, whereas lnc-ACACA-1 (135-fold), lnc-FOXG1-2 (19-fold), lnc-LCP2-2 (2-fold), lnc-RP3-368B9 (19-fold), and lnc-TTC34-3 (314-fold) were downregulated. There was no correlation between lncRNA expression with clinical-pathological parameters. Computational analyses revealed that these lncRNAs are involved in RNA-protein networks related to splicing, binding, transport, localization, and processing of RNA. Small interfering RNA (siRNA)-mediated knockdown of lnc-BMP2-2 and lnc-CPN2-1 did not influence cell proliferation.We identified many novel lncRNA transcripts dysregulated in ccRCC which may be useful for novel diagnostic biomarkers.
Project description:PurposeEmerging evidence suggests that many differentially expressed long non-coding RNAs (lncRNAs) are involved in tumorigenesis. However, the functional roles of these transcripts and the mechanisms responsible for their deregulation in non-small-cell lung cancer (NSCLC) remain elusive. Here, we identified a novel lncRNA (lncRNA 1308), which was significantly upregulated in NSCLC tissues and investigated its biological function and potential molecular mechanism.MethodsDifferences in the lncRNA expression profiles between NSCLC and tumor-adjacent normal tissues were assessed by lncRNA expression microarray analysis. The microRNA in vivo precipitation (miRIP) method was used to identify the targeting microRNAs (miRNAs) on lncRNA 1308, and luciferase reporter assays were performed. Loss-of-function studies were used to explore the effect of lncRNA 1308 on lung carcinogenesis in NSCLC cells.ResultsThe novel lncRNA 1308 was upregulated in NSCLC tissues and cell lines. By using biotin-labeled lncRNA 1308 for miRIP in NSCLC cells and dual-luciferase reporter assays, the results suggested that miRNA-124 was associated with lncRNA 1308. Furthermore, the expression of a disintegrin and a metalloproteinase 15 (ADAM 15) was downregulated in NSCLC cells when silencing of lncRNA 1308, the target of oncogenic miR-124, inhibits NSCLC cell proliferation and invasion. Conversely, the expression of ADAM 15 was significantly increased, when inhibiting the expression of miR-124, and alleviated cell invasion inhibition.ConclusionThe results suggested that lncRNA 1308 may function as a competing endogenous RNA (ceRNA) for miR-124 to regulate cell invasion through the miR-124/ADAM 15 signaling pathway, indicating that lncRNA 1308 plays an important role in the disease progression of NSCLC.
Project description:Clear cell renal cell carcinoma (ccRCC) is among the most common human malignancies. Long non-coding RNAs (lncRNA) regulate various cellular functions and have been implicated in ccRCC pathogenesis. In order to decipher the molecular biology of this tumor and to identify potential prognostic biomarkers and therapeutic targets, we re-evaluated published lncRNA expression profiling data. An expression profile of 49 lncRNAs allowed discrimination of localized and advanced ccRCC. The expression profile of six lncRNAs transcripts (lnc-ACO1625, lnc-CYP4A22-2/3, lnc-PEAK1.1-1, lnc-PCYOX1L, lnc-VCAN-1, lnc-ZNF180-2) with potential prognostic interest were validated in a cohort of 50 normal renal, 57 localized ccRCC and 45 advanced ccRCC tissues. lnc-ZNF180-2 levels were similar in localized ccRCC and normal renal tissue, but we observed a significant increase of lnc-ZNF180-2 expression in advanced ccRCC tissue. Furthermore, lnc-ZNF180-2 expression levels were an independent predictor of progression-free survival, cancer-specific survival and overall survival in ccRCC patients. We also observed that lnc-CYP4A22-2/3 expression levels allowed discrimination of ccRCC and normal renal tissue. In conclusion, lncRNAs are involved in renal carcinogenesis, and quantification of lnc-ZNF180-2 may be useful for the prediction of ccRCC patients outcome following nephrectomy.
Project description:One-third of clear cell renal cell carcinoma (ccRCC) patients present with metastasis at the time of diagnosis. The prognosis of these patients is poor. To identify potential prognostic biomarkers and therapeutic targets for ccRCC, we re-evaluated published long non-coding RNA (lncRNA) expression profiling data from the Gene Expression Omnibus and ArrayExpress database. We found that five lncRNAs were differentially expressed in ccRCC and adjacent tissues. These lncRNAs were assessed in an independent cohort of 71 paired patient samples using real-time PCR. Differences in expression of three of the lncRNAs (ENSG00000177133, TCL6, and ENSG00000244020) were validated in this analysis. Kaplan-Meier analysis indicated that low expression of ENSG00000177133 and TCL6 was associated with a poor prognosis. Univariate and multivariate regression analyses demonstrated that TCL6 but not ENSG00000177133 expression was an independent predictor of ccRCC aggressiveness and had hazard ratios predictive of clinical outcome. TCL6 expression was negatively correlated with pTNM stage. Overexpression of TCL6 in 786-O and Caki-1 ccRCC cells decreased proliferation and increased apoptosis compared to controls. Our results indicate that lncRNA expression is altered in ccRCC and that decreased TCL6 expression may be an independent adverse prognostic factor in ccRCC patients.
Project description:Long noncoding RNAs (lncRNAs) play a crucial role in tumorigenesis. The aim of this study is to identify lncRNA signature that can predict breast cancer patient survival. RNA expression data from 1064 patients were downloaded from The Cancer Genome Atlas project. Cox regression, Kaplan-Meier, and receiver operating characteristic (ROC) analyses were performed to construct a model for predicting the overall survival (OS) of patients and evaluate it. A model consisting of three lncRNA genes (CAT104, LINC01234, and STXBP5-AS1) was identified. The Kaplan-Meier analysis and ROC curves proved that the model could predict the prognostic survival with good sensitivity and specificity in both the validation set (AUC?=?0.752, 95% confidence intervals (CI): 0.651-0.854) and the microarray dataset (AUC?=?0.714, 95%CI: 0.615-0.814). Further study showed the three-lncRNA signature was not only pervasive in different breast cancer stages, subtypes and age groups, but also provides more accurate prognostic information than some widely known biomarkers. The results suggested that RNA-seq transcriptome profiling provides that the three-lncRNA signature is an independent prognostic biomarker, and have clinical significance. In addition, lncRNA, miRNA, and mRNA interaction network indicated lncRNAs may intervene in breast cancer pathogenesis by binding to miR-190b, acting as competing endogenous RNAs.
Project description:Clear cell renal cell carcinoma (ccRCC) is one of the most common malignant carcinomas and its molecular mechanisms remain unclear. Long noncoding RNA (lncRNA) could bind sites of miRNA which affect the expression of mRNA according to the competing endogenous (ceRNA) theory. The aim of the present study was to construct a ceRNA network and to identify key lncRNA to predict survival prognosis. We identified differentially expressed mRNA, lncRNA and miRNA between tumor tissues and normal tissues from The Cancer Genome Atlas database. Then, using bioinformatics tools, we explored the connection of 89 lncRNA, 10 miRNA and 22 mRNA, and we constructed the ceRNA network. Furthermore, we analyzed the functions and pathways of 22 differentially expressed mRNA. Then, univariate and multivariate Cox regression analyses of these 89 lncRNA and overall survival were explored. Nine lncRNA were finally screened out in the training group. The patients were divided into high-risk and low-risk groups according to the 9 lncRNA and low-risk scores having better clinical overall survival (P < .01). Furthermore, the receiver operating characteristic curve demonstrates the predicted role of the 9 lncRNA. The 9-lncRNA signature was successfully proved in the testing group and the entire group. Finally, multivariate Cox regression analysis and stratification analysis further proved that the 9-lncRNA signature was an independent factor to predict survival. In summary, the present study provides a deeper understanding of the lncRNA-related ceRNA network in ccRCC and suggests that the 9-lncRNA signature could serve as an independent biomarker to predict survival in ccRCC patients.
Project description:Long noncoding RNA (lncRNA) has been recognized as a regulator of gene expression, and the dysregulation of lncRNAs is involved in the progression of many types of cancer, including epithelial ovarian cancer (EOC). To explore the potential roles of lncRNAs in EOC, we performed lncRNA and mRNA microarray profiling in malignant EOC, benign ovarian cyst and healthy control tissues. In this study, 663 transcripts of lncRNAs were found to be differentially expressed in malignant EOC compared with benign and normal control tissues. We also selected 18 altered lncRNAs to confirm the validity of the microarray analysis using quantitative real-time PCR (qPCR). Pathway and Gene Ontology (GO) analyses demonstrated that these altered transcripts were involved in multiple biological processes, especially the cell cycle. Furthermore, Series Test of Cluster (STC) and lncRNA-mRNA co-expression network analyses were conducted to predict lncRNA expression trends and the potential target genes of lncRNAs. We also determined that two antisense lncRNAs (RP11-597D13.9 and ADAMTS9-AS1) were associated with their nearby coding genes (FAM198B, ADAMTS9), which participated in cancer progression. This study offers helpful information to understand the initiation and development mechanisms of EOC.
Project description:We previously reported dysregulated expression of liver-derived messenger RNA (mRNA) and long noncoding RNA (lncRNA) in patients with advanced fibrosis resulting from nonalcoholic fatty liver disease (NAFLD). Here we sought to identify changes in mRNA and lncRNA levels associated with activation of hepatic stellate cells (HSCs), the predominant source of extracellular matrix production in the liver and key to NAFLD-related fibrogenesis. We performed expression profiling of mRNA and lncRNA from LX-2 cells, an immortalized human HSC cell line, treated to induce phenotypes resembling quiescent and myofibroblastic states. We identified 1964 mRNAs (1377 upregulated and 587 downregulated) and 1460 lncRNAs (665 upregulated and 795 downregulated) showing statistically significant evidence (FDR ?0.05) for differential expression (fold change ?|2|) between quiescent and activated states. Pathway analysis of differentially expressed genes showed enrichment for hepatic fibrosis (FDR = 1.35E-16), osteoarthritis (FDR = 1.47E-14), and axonal guidance signaling (FDR = 1.09E-09). We observed 127 lncRNAs/nearby mRNA pairs showing differential expression, the majority of which were dysregulated in the same direction. A comparison of differentially expressed transcripts in LX-2 cells with RNA-sequencing results from NAFLD patients with or without liver fibrosis revealed 1047 mRNAs and 91 lncRNAs shared between the two datasets, suggesting that some of the expression changes occurring during HSC activation can be observed in biopsied human tissue. These results identify lncRNA and mRNA expression patterns associated with activated human HSCs that appear to recapitulate human NAFLD fibrosis.
Project description:The pioneering work from Lieping Chen's laboratory identified Siglec-15 as a novel tumor immune suppressor, while the regulatory mechanisms underlying the broad upregulation of Siglec-15 in human cancers remain obscure. Here we found that long non-coding RNA (lncRNA) LINC00973 was higher in Siglec-15-positive clear-cell renal cell carcinoma (ccRCC), and LINC00973 positively regulated Siglec-15 expression at transcriptional level. This effect was evidently dependent on miR-7109-3p (designated as miR-7109 hereafter), and we provided evidence that Siglec-15 is a direct target of miR-7109. Through sponging miR-7109, LINC00973 functioned as competing endogenous RNA (ceRNA) to control cell surface abundance of Siglec-15, and, consequently, was involved in cancer immune suppression. We further demonstrated that LINC00973 and miR-7109 expression in ccRCC antagonistically influenced immune activation of co-cultured Jurkat cells. Our study highlighted the importance of LINC00973-miR-7109-Siglec-15 in immune evasion in ccRCC, which offers significant opportunity for both therapeutic intervention and diagnostic/prognostic exploitations.
Project description:OBJECTIVES:The role of long non-coding RNA (lncRNA) expression in human head and neck squamous cell carcinoma (HNSCC) is still poorly understood. In this study, we aimed at establishing the onco-lncRNAome profiling of HNSCC and to identify lncRNAs correlating with prognosis and patient survival. MATERIALS AND METHODS:The Atlas of Noncoding RNAs in Cancer (TANRIC) database was employed to retrieve the lncRNA expression information generated from The Cancer Genome Atlas (TCGA) HNSCC RNA-sequencing data. RNA-sequencing data from HNSCC cell lines were also considered for this study. Bioinformatics approaches, such as differential gene expression analysis, survival analysis, principal component analysis, and Co-LncRNA enrichment analysis were performed. RESULTS:Using TCGA HNSCC RNA-sequencing data from 426 HNSCC and 42 adjacent normal tissues, we found 728 lncRNA transcripts significantly and differentially expressed in HNSCC. Among the 728 lncRNAs, 55 lncRNAs were significantly associated with poor prognosis, such as overall survival and/or disease-free survival. Next, we found 140 lncRNA transcripts significantly and differentially expressed between Human Papilloma Virus (HPV) positive tumors and HPV negative tumors. Thirty lncRNA transcripts were differentially expressed between TP53 mutated and TP53 wild type tumors. Co-LncRNA analysis suggested that protein-coding genes that are co-expressed with these deregulated lncRNAs might be involved in cancer associated molecular events. With consideration of differential expression of lncRNAs in a HNSCC cell lines panel (n=22), we found several lncRNAs that may represent potential targets for diagnosis, therapy and prevention of HNSCC. CONCLUSION:LncRNAs profiling could provide novel insights into the potential mechanisms of HNSCC oncogenesis.