Dataset Information

Analysis of the Polycomb-related lncRNAs HOTAIR and ANRIL in bladder cancer.

ABSTRACT: BACKGROUND: Long non-coding RNAs (lncRNAs) have been claimed as key molecular players in gene expression regulation, being involved in diverse epigenetic processes. They are aberrantly expressed in various tumors, but their exact role in bladder cancer is still obscure. We have recently found a major role of the Polycomb repression complex in recurrence of non-muscle-invasive bladder cancer. Here, we report the xpression of Polycomb-related lncRNAs:antisense noncoding RNA in the INK4 locus (ANRIL) and HOX antisense intergenic RNA (HOTAIR) in these tumors. FINDINGS: We studied a dataset of non-invasive bladder cancer samples by quantitative reverse transcription PCR (RT-qPCR) and analyzed also invasive bladder cancer samples using TCGA data. Our results showed that, while ANRIL seemed not to have a determining role, an increased HOTAIR expression appeared in recurrent and high-graded tumors associated with poor prognosis. In addition, through genome-wide transcriptome analyses, we observed that HOTAIR-EZH2-complex-regulated genes can efficiently discriminate between non-tumoral, recurrent, and non-recurrent bladder cancer samples. We also observed a significant correlation between EZH2 and HOTAIR expression levels. Using overexpression, knockdown, and pharmacological approaches in bladder cancer cell lines, we also observed that EZH2 regulates HOTAIR expression. CONCLUSIONS: Our findings indicate that HOTAIR expression has prognostic value for bladder cancer progression, recurrence, and survival and suggest that HOTAIR plays active roles in modulating the cancer epigenome, becoming an interesting candidate as a target for cancer diagnosis and therapy. The observed HOTAIR regulation by EZH2 and the possibility of modulating EZH2 activity with specific inhibitors open new possible paths to be explored in bladder cancer therapy.

SUBMITTER: Martinez-Fernandez M

PROVIDER: S-EPMC4599691 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Analysis of the Polycomb-related lncRNAs HOTAIR and ANRIL in bladder cancer.

Martínez-Fernández Mónica M Feber Andrew A Dueñas Marta M Segovia Cristina C Rubio Carolina C Fernandez Maria M Villacampa Felipe F Duarte José J López-Calderón Fernando F FF Gómez-Rodriguez Ma José MJ Castellano Daniel D Rodriguez-Peralto Jose L JL de la Rosa Federico F Beck Stephan S Paramio Jesús M JM

Clinical epigenetics 20151008

<h4>Background</h4>Long non-coding RNAs (lncRNAs) have been claimed as key molecular players in gene expression regulation, being involved in diverse epigenetic processes. They are aberrantly expressed in various tumors, but their exact role in bladder cancer is still obscure. We have recently found a major role of the Polycomb repression complex in recurrence of non-muscle-invasive bladder cancer. Here, we report the xpression of Polycomb-related lncRNAs:antisense noncoding RNA in the INK4 locu ...[more]

PMID: 26457124

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Project description:Both lncRNAs and the N6-methyladenosine (m6A) modification are key regulators of tumorigenesis and innate immunity. However, little is known about the m6A modification of lncRNAs and their clinical and immune relevance in bladder cancer. In this study, we identified m6A-related lncRNAs using Pearson correlation analysis in The Cancer Genome Atlas (TCGA) and the IMvigor210 datasets. Next, univariate Cox regression was performed using the TCGA dataset to filter prognostic m6A-related lncRNAs, which were further subjected to the least absolute shrinkage and selection operator (LASSO) Cox regression to establish a 12 m6A-related lncRNA prognostic score (m6A-LRS). The m6A-LRS was validated in the IMvigor210 dataset. In addition, high m6A-LRS tumors, characterized by decreased tumor mutation load and neoantigen load, showed poorer response to immunotherapy than those with low m6A-LRS in the IMvigor210 dataset. Further, we constructed an m6A-LRS-based nomogram that demonstrated a strong ability to predict overall survival in patients with bladder cancer. Moreover, enrichment analysis revealed that tumor-associated biological processes, oncogenic signaling, and tumor hallmarks were commonly associated with a high m6A-LRS. Gene set variation analysis also indicated that high m6A-LRS was associated with activation of canonical oncogenic signatures, such as the epithelial-to-mesenchymal transition, cell cycle regulators, and DNA replication, as well as activation of immunosuppressive signatures, such as the T-cell exhaustion and pan-fibroblast-TGF-β response signatures. Furthermore, we observed distinct tumor microenvironment cell infiltration characteristics between high- and low-risk tumors. High m6A-LRS tumors showed reduced infiltration of CD8+ T-cells and enhanced infiltration of macrophages and fibroblasts. Additionally, we established a competing endogenous RNA network based on the12 m6A-related lncRNAs. Finally, three lncRNAs (SNHG16, SBF2-AS1, and BDNF-AS) were selected for further validation. The qualitative PCR assay on 10 pairs of bladder cancer and adjacent normal control samples validated the differential expression, and methylated RNA immunoprecipitation (MeRIP) analysis demonstrated a robust m6A enrichment in T24 bladder cancer cells compared with normal uroepithelial cells (SVHUC-1). In conclusion, this study introduced an m6A-related lncRNA signature that identified a subgroup of patients with poor prognoses and suboptimal immune responses, thus providing novel approaches for treatment response prediction and patient stratification in bladder cancer.

Project description:Telomerase allows eukaryotic cells to proliferate indefinitely, an important characteristic of tumor cells. Telomerase-related long no coding RNAs (TERLs) are involved in prognosis and drug sensitivity prediction; however, their association with bladder cancer (BLCA) is still unreported. The objective of this research is to determine a predictive prognostic TERL signature for OS and to provide an efficient treatment option for BLCA. The RNA sequence, clinical information, and mutational data of BLCA patients were acquired from The Cancer Genome Atlas (TCGA) database. With the help of the data from least absolute shrinkage and selection operator (LASSO) regression and Cox regression, a prognostic signature was established including 14 TERLs, which could divide BLCA patients into low-risk (L-R) and high-risk (H-R) cohorts. The time-dependent receiver operating characteristic (ROC) curve demonstrated the greater predictive power of the model. By combing the TERLs-based signature and clinical risk factors (age, sex, grade, and stage), a prognostic nomogram was constructed to forecast the survival rates of patients with BLCA at 1-, 3-, and 5-years, which was well matched by calibration plots C-index and Decision curve analysis (DCA). Furthermore, the L-R cohort showed higher tumor mutation burden (TMB) and lower tumor immune dysfunction and exclusion (TIDE) than the H-R cohort, as well as substantial variability in immune cell infiltration and immune function between the two cohorts was elucidated. As for external validation, LINC01711 and RAP2C-AS1 were identified as poor prognostic factors by survival analysis from the Kaplan-Meier Plotter database, which were validated in BLCA cell lines (EJ, 253J, T24, and 5637) and SV-HUC-1 cells as the control group using qRT-PCR. In addition, interference with the expression of RAP2C-AS1 suppresses the proliferation and migration of BLCA cells, and RAP2C-AS1 could affect the expression of CD274 and CTLA4, which could serve as prognostic markers and characterize the tumor microenvironment in BLCA. Overall, the model based on the 14-TERLs signature can efficiently predict the prognosis and drug treatment response in individuals with bladder cancer.

Dataset Information

Analysis of the Polycomb-related lncRNAs HOTAIR and ANRIL in bladder cancer.

Publications

Analysis of the Polycomb-related lncRNAs HOTAIR and ANRIL in bladder cancer.

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