Identification of long non-coding RNAs that stimulate cell survival in bladder cancer.
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ABSTRACT:
SUBMITTER: Dudek AM
PROVIDER: S-EPMC5470981 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Bladder cancer (BC) is the most common malignant tumor in the urinary system, and its early diagnosis is conducive to improving clinical prognosis and prolonging overall survival time. However, few biomarkers with high sensitivity and specificity are used as diagnostic markers for BC. Multiple long non-coding RNAs (lncRNAs) are abnormally expressed in BC, and play key roles in tumorigenesis, progression and prognosis of BC. In this review, we summarize the expression, function, molecular mechanisms and the clinical significance of lncRNAs on bladder cancer. There are more than 100 dysregulated lncRNAs in BC, which are involved in the regulation of proliferation, cell cycle, apoptosis, migration, invasion, metabolism and drug resistance of BC. Meanwhile, the molecular mechanisms of lncRNAs in BC was explored, including lncRNAs interacting with DNA, RNA and proteins. Additionally, the abnormal expression of thirty-six lncRNAs is closely associated with multiple clinical characteristics of BC, including tumor size, metastasis, invasion, and drug sensitivity or resistance of BC. Furthermore, we summarize some potential diagnostic and prognostic biomarkers of lncRNA for BC. This review provides promising novel biomarkers in early diagnosis, prognosis and monitoring of BC based on lncRNAs.
| S-EPMC8371405 | biostudies-literature
Project description:BackgroundCumulative evidence from several tumor studies, including bladder cancer, emphasizes the importance of the tumor microenvironment (TME) in tumorigenesis, development, and metastasis, which can be regulated by long non-coding RNAs (lncRNAs). This study aims to identify bladder cancer (BC) microenvironment-associated lncRNAs for their prognostic value predicting the survival of BC patients.MethodsThe data of BC patients regarding lncRNA expression and corresponding clinical characteristics were obtained from The Cancer Genome Atlas (TCGA). The Cox regression analysis and the least absolute shrinkage and selection operator (LASSO) regression analysis were performed to screen lncRNAs following the calculation of the immune score for each sample. For the screened lncRNAs, a risk score model was constructed to predict the survival, and 3- and 5-year overall survival (OS) rates were assessed using a nomogram. The calibration curve and concordance index (C-index) validated the performance of the nomogram. Finally, to explore the potential function related to the screened lncRNAs, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were performed.ResultsThe multivariate Cox regression analysis screened five TME-associated lncRNAs regarded as independent factors influencing the tumor progression. The corresponding risk score model was established as follows: (-0.15816 AC064805.1) + (0.10015 AC084033.3) + (-0.17977 AC092112.1) + (-0.05673AC103691.1) + (0.17789 AL391704.1) + (-0.16258 LINC00892). The C-index for the nomogram was 0.63 (95% CI: 0.625-0.635). Also, the calibration curve verified the predictive effectiveness by showing a good concordance between the nomogram prediction and the actual observation. GO and KEGG analysis demonstrated that six TME-associated lncRNAs were most likely linked to tumor metastasis and progression.ConclusionThe present study determined six lncRNAs as independent immuno-biomarkers in the TME, constructed a nomogram to predict their prognostic value, and investigated the potential biological processes to understand their regulatory roles in the progression of BC.
| S-EPMC7689372 | biostudies-literature
Project description:As various data suggest that lncRNAs are important in human cancer, we hypothesized that they play a role in urothelial carcinogenesis. To test this hypothesis we analysed 83 normal and malignant urothelial samples using NCodeM-bM-^DM-" Human Non-coding RNA Microarrays for differentially expressed lncRNAs with potential regulatory functions in urothelial cell cancer (UCC). We identified global changes in lncRNA expression that reflect the disease phenotype. We then performed explorative analysis (siRNA gene knock-down and loss-of-function studies) of selected species and identified those with potential prognostic roles. Quantitative real-time PCR was used to validate the microarray findings. Total RNA was extracted from urothelial samples from 57 patients with UCC (23 low-grade NMI, 14 high-grade NMI and 20 invasive tumours) and from 26 disease free controls.
2014-02-28 | E-GEOD-55433 | biostudies-arrayexpress
Project description:As various data suggest that lncRNAs are important in human cancer, we hypothesized that they play a role in urothelial carcinogenesis. To test this hypothesis we analysed 83 normal and malignant urothelial samples using NCode™ Human Non-coding RNA Microarrays for differentially expressed lncRNAs with potential regulatory functions in urothelial cell cancer (UCC). We identified global changes in lncRNA expression that reflect the disease phenotype. We then performed explorative analysis (siRNA gene knock-down and loss-of-function studies) of selected species and identified those with potential prognostic roles. Quantitative real-time PCR was used to validate the microarray findings.
2014-02-28 | GSE55433 | GEO
Project description:Background: Increasing evidence shows that dysregulated expression of long non-coding RNAs (lncRNAs) can serve as diagnostic or prognostic markers in bladder cancer. The aim of this study was to evaluate the clinical values of dysregulated lncRNAs in bladder cancer. Methods: Eligible studies were systematically searched in PubMed, Embase, and Web of Science databases from inception to December 2017. Odds ratios (OR) were calculated to investigate the correlation between lncRNAs and clinicopathological parameters. Pooled hazard ratios (HR) and 95% confidence interval (CI) were calculated to explore the prognostic value of lncRNAs in bladder cancer. Pooled diagnostic parameters were also calculated to estimate the performance of lncRNAs in diagnosing bladder cancer. All statistical analyses were performed by using STATA 13.1 program. Results: A total of 37 relevant studies were included to the present systematic review according to the inclusion and exclusion criteria, including 26 on clinicopathological parameters, 19 on prognosis, and 7 on diagnosis. For clinicopathological parameters, MALAT1 expression was significantly associated with lymph node metastasis (OR = 2.731; 95% CI: 1.409-5.292; p = 0.003), and high-level expression of XIST was related to larger tumor size (OR = 2.473; 95% CI: 1.159-5.276; p = 0.019) and higher TNM stage (OR = 0.400; 95% CI, 0.184-0.868; p = 0.020). For the prognostic values, the most significant association was observed between increased expressions of SPRY4-IT1 and poor overall survival (OS) (HR = 3.716; 95% CI: 2.084-6.719; p < 0.001); high MALAT1 expression was significantly associated with poor OS (HR = 1.611; 95% CI: 1.076-2.412; p = 0.020). For the diagnostic values, UCA1 expression profile achieved a combined AUC of 0.92, with sensitivity of 0.84 and specificity of 0.89 in distinguishing patients with bladder cancer from non-cancerous controls. Conclusions: In summary, systematic review elaborated that abnormal lncRNAs expression can serve as potential markers for prognostic evaluation in bladder cancer patients. In addition, the diagnostic meta-analysis concluded that abnormally expressed UCA1 can function as potential diagnostic markers for bladder cancer.
| S-EPMC5988895 | biostudies-literature
Project description:BackgroundStarving intratumoral microenvironment prominently alters genic profiles including long non-coding RNAs (lncRNAs), which further regulate bladder cancer (BCa) malignant biological properties, such as invasion and migration.MethodsTranscriptome RNA-sequencing data of 414 BCa tumor tissues and 19 normal tissues were obtained from TCGA database and paired samples of 132 BCa patients. A chain of in vitro validations such as qPCR, migration and invasion assays were performed to reveal the clinical relevance of AC011472.4 and AL157895.1.ResultsA total of 11 lncRNAs were identified as starvation-related lncRNAs, of which AC011472.4 and AL157895.1 were relevant to overall survival of BCa patients. Besides, a starvation-related risk score model was established based on the levels of AC011472.4 and AL157895.1. BCa patients with higher levels of AL157895.1 were divided into the high-risk group and usually obtained higher mortality rate, but AC011472.4 was contrary. AL157895.1 expressed highly in BCa cell lines and tumour tissues, especially in patients with the advanced grade, stage and T-stage, while AC011472.4 showed the reversed result. Moreover, increased level of AL157895.1 was remarkably correlated to T-stage, muscle invasion status and distant metastasis. SiRNAs-mediated silence of AC011472.4 and AL157895.1 respectively increased and diminished invasion and migration properties of BCa cells.ConclusionsIn this study, we highlight the significant roles of AC011472.4 and AL157895.1 on evaluating prognoses of BCa patients and validate their correlation with various clinical parameters. These findings provide an appropriate risk score model for BCa clinical decision making.
| S-EPMC9831724 | biostudies-literature
Project description:Bladder cancer (BC) is the sixth most common malignancy in men and 17th in women. Exosomal long non-coding RNAs (lncRNAs) have been defined as a novel biomarker for BC. The aim of this study is to evaluate the clinical significance of urine exosomal PVT-1, ANRIL and PCAT-1 as a biomarker in BC patients with tumors classified as T1 or T2. Exosomes were isolated from urine of BC patients and healthy donors, then characterized according to their shape, size, and exosome markers by Electron Microscopy, Dynamic light scattering, and Western blotting. Exosomal lncRNAs extraction was done to determine the expression levels of PVT-1, ANRIL and PCAT-1 by qRT-PCR. ANRIL and PCAT-1 expression was significantly higher in BC patients compared to normal subjects. To evaluate the performance of the identified lncRNAs for BC detection, we performed ROC curves analysis. The diagnostic accuracy of ANRIL and PCAT-1, measured by AUC, was 0.7229 (sensitivity = 46.67 % and specificity = 87.5 %) and 0.7292 (sensitivity = 43.33 % and specificity = 87.5 %). Transcript levels of lncRNAs in urinary exosomes are potential diagnostic biomarkers in bladder cancer.
| S-EPMC7104196 | biostudies-literature
Project description:BackgroundFerroptosis is a distinct form of cell death that has the potential to supersede the drug resistance that is commonly observed with current chemotherapeutic agents. As a result, ferroptosis presents a new and innovative therapeutic pathway for cancer treatment. The current understanding regarding the expression of genes associated with ferroptosis in bladder cancer (BLCA) and their prognostic implications remains unclear. Consequently, this study aimed to examine the potential prognostic value of ferroptosis-associated long non-coding RNAs (lncRNAs) in BLCA.MethodsThe Cancer Genome Atlas (TCGA) was accessed to download RNA sequencing data and clinicopathological features of BLCA while accessing the FerrDb database to download ferroptosis-associated genes. The study calculated risk scores for ferroptosis-associated lncRNAs, and subsequently divided patients with BLCA into two groups, namely high- and low-risk, on the basis of the median risk score. Moreover, Kaplan-Meier (K-M) curves, Cox regression analysis, and column plots were utilized for evaluating the risk score prognostic value. Subsequently, the involvement of ferroptosis-associated mRNA, N6-methyladenosine (m6A) mRNA status, and immune responses was investigated for BLCA prognosis.ResultsThirty-six lncRNAs were identified to be differently expressed and linked to the prognosis of BLCA. The findings from the K-M curve analysis indicated a significant association between a high-risk lncRNA profile and poor BLCA prognosis. The area under curve (AUC) value of the receiver operating characteristic (ROC) curve was 0.810. The risk assessment model exhibited superior performance in predicting prognosis for BLCA compared to conventional clinicopathological features.ConclusionsThirty-six lncRNAs were found to be linked to ferroptosis for the prognosis of patients with BLCA, and these results may provide new insights for treating BLCA.
| S-EPMC10493782 | biostudies-literature
Project description:BackgroundSome studies have revealed a close relationship between metabolism-related genes and the prognosis of bladder cancer. However, the relationship between metabolism-related long non-coding RNAs (lncRNA) regulating the expression of genetic material and bladder cancer is still blank. From this, we developed and validated a prognostic model based on metabolism-associated lncRNA to analyze the prognosis of bladder cancer.MethodsGene expression, lncRNA sequencing data, and related clinical information were extracted from The Cancer Genome Atlas (TCGA). And we downloaded metabolism-related gene sets from the human metabolism database. Differential expression analysis is used to screen differentially expressed metabolism-related genes and lncRNAs between tumors and paracancer tissues. We then obtained metabolism-related lncRNAs associated with prognosis by correlational analyses, univariate Cox analysis, and logistic least absolute shrinkage and selection operator (LASSO) regression. A risk scoring model is constructed based on the regression coefficient corresponding to lncRNA calculated by multivariate Cox analysis. According to the median risk score, patients were divided into a high-risk group and a low-risk group. Then, we developed and evaluated a nomogram including risk scores and Clinical baseline data to predict the prognosis. Furthermore, we performed gene-set enrichment analysis (GSEA) to explore the role of these metabolism-related lncRNAs in the prognosis of bladder cancer.ResultsBy analyzing the extracted data, our research screened out 12 metabolism-related lncRNAs. There are significant differences in survival between high and low-risk groups divided by the median risk scoring model, and the low-risk group has a more favorable prognosis than the high-risk group. Univariate and multivariate Cox regression analysis showed that the risk score was closely related to the prognosis of bladder cancer. Then we established a nomogram based on multivariate analysis. After evaluation, the modified model has good predictive efficiency and clinical application value. Furthermore, the GSEA showed that these lncRNAs affected bladder cancer prognosis through multiple links.ConclusionsA predictive model was established and validated based on 12 metabolism-related lncRNAs and clinical information, and we found these lncRNA affected bladder cancer prognosis through multiple links.
| S-EPMC8913725 | biostudies-literature
Project description:BackgroundLong 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.ResultsMicroarray 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.ConclusionsWe identified many novel lncRNA transcripts dysregulated in ccRCC which may be useful for novel diagnostic biomarkers.
| S-EPMC4326488 | biostudies-literature