Effect of Aberrant Long Noncoding RNA on the Prognosis of Clear Cell Renal Cell Carcinoma
Ontology highlight
ABSTRACT:
SUBMITTER: Wu H
PROVIDER: S-EPMC8433025 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:BackgroundIncreasing evidence has indicated that long noncoding RNAs (lncRNAs) are crucial regulators affecting the progression of human cancers. Recently, lncRNA downregulated in liver cancer stem cells (lnc-DILC) was identified to function as a tumor suppressor inhibiting the tumorigenesis and metastasis in liver cancer and colorectal cancer. However, to date, little is known about the functional roles of lnc-DILC in modulating malignant phenotypes of clear cell renal cell carcinoma (ccRCC) cells.Methodslnc-DILC expression in human ccRCC tissues was detected by qRT-PCR. Overexpression and knockdown experiments were carried out to determine the effects of lnc-DILC on ccRCC cell proliferation, migration and invasion. To reveal the underlying mechanisms of lnc-DILC functions in ccRCC cells. RNA immunoprecipitation, RNA pull-down, in vivo ubiquitination, co-immunoprecipitation and western blot assays were performed.ResultsHere, we identified that lnc-DILC levels were dramatically downregulated in ccRCC tissues. Loss of lnc-DILC expression was correlated with larger tumor size, advanced tumor grade and lymph node metastasis, and also predicted worse prognosis in patients with ccRCC. Functionally, knockdown and overexpression experiments demonstrated that lnc-DILC inhibited cell proliferation, migration and invasion in ccRCC cells. Mechanistic investigation revealed that lnc-DILC bound to tumor suppressor PTEN and suppressed its degradation. lnc-DILC repressed the PTEN ubiquitination through blocking the interaction between PTEN and E3 ubiquitin ligase WWP2 and recruiting the deubiquitinase USP11 to PTEN. Moreover, we demonstrated that PTEN-AKT signaling was crucial for lnc-DILC-mediated suppressive effects.ConclusionsIn summary, our research revealed a novel mechanism by which lnc-DILC regulates PTEN stability via WWP2 and USP11, and shed light on potential therapeutic strategies by the restoration of lnc-DILC expression in patients with ccRCC.
| S-EPMC6775667 | biostudies-literature
Project description:Several studies have indicated that HOXA transcript at the distal tip (HOTTIP) play important roles in the tumorigenesis and development of various cancers. We aim to investigate the expression and prognostic value of HOTTIP in clear cell renal cell carcinoma (ccRCC). A systematic review of PubMed, Embase, Medline, and Web of Science databases was performed to select eligible literatures relevant to the correlation between HOTTIP expression and clinical outcome of different cancers. The association between the HOTTIP level and overall survival (OS), lymph node metastasis (LNM), or clinical stage was subsequently analyzed. Survival analyses were performed in a large cohort of more than 500 patients with ccRCC from The Cancer Genome Atlas (TCGA) using bioinformatic methods. Seventeen studies with a total of 1594 patients with thirteen kinds of carcinomas were included in this analysis. The result showed that high HOTTIP expression could predict worse outcome in cancer patients, with the pooled hazard ratio (HR) of 2.34 (95% confidence interval (CI) 1.96-2.79, p < 0.0001). The result also showed that elevated HOTTIP expression was correlated with more LNM (OR = 2.61, 95% CI 1.91-3.58, p < 0.0001) and advanced clinical stage (OR = 3.57, 95% CI 2.58-4.93, p < 0.0001). We further validated that ccRCC patients with higher HOTTIP expression tend to have unsatisfactory outcomes both in the entire TCGA dataset and different clinical stratums, like age, grade, and stage. The tumor of those patients was associated with a larger size, easier to metastasis, advanced clinical stage, and a higher pathological grade. These findings suggested that increased HOTTIP expression might act as a novel prognostic marker for ccRCC patients.
| S-EPMC7255047 | biostudies-literature
Project description:BackgroundNecroptosis has been found to be associated with tumorigenesis and tumor progression. However, the prognostic effect of long noncoding RNAs (lncRNAs) associated with necroptosis in clear cell renal cell carcinoma (ccRCC) is still unclear.MethodsPearson correlation analysis was used to identify necroptosis-related genes and lncRNAs obtained from The Cancer Genome Atlas Kidney Renal Clear Cell Carcinoma (TCGA-KIRC) dataset. Least absolute shrinkage and selection operator (LASSO) regression and Cox regression analyses were used to identify a novel necroptosis-associated lncRNAs signature that significantly correlated with survival of ccRCC. Next, single sample gene set enrichment analysis (ssGSEA) was employed to assess the extent of infiltration with immune cells. Analyses to predict the half-maximal inhibitory concentration (IC50) of patients in different risk groups were also conducted. Moreover, follow-up data of an immunotherapy cohort were used to test for differences in the immunotherapeutic efficiency between two risk groups. Finally, patients with ccRCC were divided into two groups based on 6 prognostic lncRNAs.ResultsWe developed a signature of necroptosis-related lncRNAs, which was verified as an independent prognostic factor that can predict prognosis up to 7 years. Patients with higher risk scores were shown to have higher immune suppressive cell infiltration levels and expression of immune checkpoint genes, which suggests that these patients were in a state of immunosuppression. Patients in the low-risk group were found to have an increased response to immunotherapy. A prognostic prediction nomogram was conducted to predict long-term survival of patients. Cluster A tumors were considered hot tumors, since they were correlated with higher levels of immune infiltration and were more sensitive to immunotherapy.ConclusionsA comprehensive bioinformatics analysis was conducted, which found that the necroptosis-associated lncRNA signature might be a potent prognostic factor for patients with ccRCC, which could contribute to improved prognosis of these patients.
| S-EPMC9834578 | biostudies-literature
Project description:Clear cell renal cell carcinoma (ccRCC) is a common aggressive malignant tumor of the urinary system. Given the heterogeneity of the tumor microenvironment, immunotherapy may not fully exert its role in the treatment of advanced patients. Long noncoding RNA (lncRNA) has been reported to be critically associated with the differentiation and maturation of tumor-infiltrating lymphocytes (TILs), which work against tumor cells. In this study, we identified 10 TIL-related lncRNAs (AL590094.1, LINC02027, LINC00460, AC147651.1, AC026401.3, LINC00944, LINC01615, AP000439.2, AL162586.1, and AC084876.1) by Pearson correlation, univariate Cox regression, Lasso regression, and multivariate Cox regression based on The Cancer Genome Atlas (TCGA) database. A risk score model was established based on these lncRNAs. Next, a nomogram was constructed to predict the overall survival. By employing differentially expressed genes (DEGs) between groups with high and low risk scores, gene ontology (GO) enrichment analysis was performed to identify the major biological processes (BP) related to immune DEGs. We analyzed the mutation data of the groups and demonstrated that SETD2 and BAP1 had the highest mutation frequency in the high-risk group. The "CIBERSORT" R package was used to detect the abundance of TILs in the groups. The expression of lymphocyte markers was compared. We also determined the expression of two lncRNAs (AC084876.1 and AC026401.3) and their relationship with lymphocyte markers in the kidney tissue of ccRCC patients and showed that there was a positive correlation between AC084876.1 and FoxP3. Proliferation, migration, and invasion of AC084876.1-downregulated ccRCC cell lines were inhibited, and the expression of PD-L1 and TGF-β secretion decreased. To our knowledge, this is the first bioinformatics study to establish a prognostic model for ccRCC using TIL-related lncRNAs. These lncRNAs were associated with T-cell activities and may serve as biomarkers of disease prognosis.
| S-EPMC9730408 | biostudies-literature
Project description:BackgroundLong noncoding RNAs (lncRNAs) have been identified as important factors in cancer biology and are deregulated in many cancers. The present study aimed to determine the expression and roles of lncRNA DHRS4-AS1 in the progression of clear cell renal cell carcinoma (ccRCC).Methods and resultsUsing high-throughput RNA-sequencing data of ccRCC tumors from the Cancer Genome Atlas project, we identified lncRNA DHRS4-AS1 as significantly associated with ccRCC patients' overall survival. We confirmed the downregulation of DHRS4-AS1 in ccRCC by assessing its expression levels in a cohort of 52 tumor and paired non-tumor samples. In addition, we found that low DHRS4-AS1 expression was significantly associated with a high tumor node metastasis stage, lymph node metastasis, advanced pathological grade and poor prognosis. Furthermore, DHRS4-AS1 overexpression inhibited the progression of cell cycles of ccRCC in vitro. These data indicate that DHRS4-AS1 functions by preventing the proliferation and invasion, inhibiting the cell cycle progression and promoting the apoptosis of ccRCC cells.ConclusionTaken together, our findings identify the role of DHRS4-AS1 as a tumor inhibitor in ccRCC for the first time, demonstrating that DHRS4-AS1 is a potential prognostic biomarker that could potentially be applied in ccRCC therapy.
| S-EPMC6141115 | biostudies-literature
Project description:BackgroundClear cell renal cell carcinoma (ccRCC) is characterized by the accumulation of lipid-reactive oxygen species. Ferroptosis, due to the lipid peroxidation, has been reported to be strongly correlated with tumorigenesis and progression. However, the functions of the ferroptosis process in ccRCC remain unclear.MethodsAfter sample cleaning, data integration, and batch effect removal, we used the Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases to screen out the expression and prognostic value of ferroptosis-related lncRNAs and then performed the molecular subtyping using the K-means method. Then, the functional pathway enrichment and immune microenvironment infiltration between the different clusters were carried out. The results showed a significant difference in immune cell infiltration between the two clusters and the associated marker responded to individualized differences in treatment. Then, least absolute shrinkage and selection operator (LASSO) Cox regression was used to establish a prognostic signature based on 5 lncRNAs. This signature could accurately predicted patient prognosis and served as an independent clinical risk factor. We then combined significant clinical parameters in multivariate Cox regression and the prognostic signature to construct a clinical predictive nomogram, which provides appropriate guidance for predicting the overall survival of ccRCC patients.ResultsThe prognostic differentially expressed ferroptosis-related LncRNAs (DEFRlncRNAs) were found, and 5 lncRNAs were finally used to establish the prognostic signature in the TCGA cohort, with subsequently validation in the internal and external cohorts. Moreover, we conducted the molecular subtyping and divided the patients in the TCGA cohort into two clusters showing differences in Hallmark pathways, immune infiltration, immune target expression, and drug therapies. Differences between clusters contributed to individualizing treatment. Furthermore, a nomogram was established to better predict the clinical outcomes of the ccRCC patients.ConclusionsOur study conducted molecular subtyping and established a novel predictive signature based on the ferroptosis-related lncRNAs, which contributed to the prognostic prediction and individualizing treatment of ccRCC patients.
| S-EPMC9476564 | biostudies-literature
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.
| S-EPMC6172067 | biostudies-literature
Project description:BackgroundThe long noncoding RNA (lncRNA) OTUD6B antisense RNA 1 (OTUD6B-AS1) is oriented in an antisense direction to the protein-coding gene OTUD6B on the opposite DNA strand. TCGA database data show that the expression of the lncRNA OTUD6B-AS1 is downregulated and that OTUD6B-AS1 acts as an antioncogene in a variety of tumors. However, the expression and biological functions of the lncRNA OTUD6B-AS1 are still unknown in tumors, including clear cell renal cell carcinoma (ccRCC).MethodsThe expression level of OTUD6B-AS1 was measured in 75 paired human ccRCC tissue and corresponding adjacent normal renal tissue samples. The correlations between the OTUD6B-AS1 expression level and clinicopathological features were evaluated using the chi-square test. The effects of OTUD6B-AS1 on ccRCC cells were determined via MTT assay, clone formation assay, transwell assay, and flow cytometry. Furthermore, the impact of OTUD6B-AS1 overexpression on the activation of the Wnt/β-catenin signaling pathway was investigated. Finally, ACHN cells with OTUD6B-AS1 overexpression were subcutaneously injected into nude mice to evaluate the influence of OTUD6B-AS1 on tumor growth in vivo.ResultsIn this study, we found that the expression of the lncRNA OTUD6B-AS1 was downregulated in ccRCC tissue samples and that patients with low OTUD6B-AS1 expression had shorter overall survival than patients with high OTUD6B-AS1 expression, which showed that the different expression level of OTUD6B-AS1 indirectly correlated with survival of patients. Lentivirus-mediated OTUD6B-AS1 overexpression significantly decreased the proliferation of ccRCC cells and promoted the apoptosis of the cells. Furthermore, OTUD6B-AS1 overexpression partly inhibited cell migration and invasion. The overexpression of OTUD6B-AS1 decreased the activity of the Wnt/β-catenin pathway and suppressed the expression of epithelial-to-mesenchymal transition (EMT)-related proteins (E-cadherin, N-cadherin and Snail) in ccRCC cells. In addition, compared with the parental ACHN cells, OTUD6B-AS1-overexpressing ACHN cells injected into nude mice exhibited decreased tumor growth in vivo.ConclusionsTaken together, our findings present a road map for targeting the newly identified lncRNA OTUD6B-AS1 to suppress ccRCC progression in cell lines, and these results elucidate a novel potential therapeutic target for ccRCC treatment.
| S-EPMC6341572 | biostudies-literature
Project description:BackgroundLong noncoding RNA (lncRNA) is generally identified as competing endogenous RNA (ceRNA) that plays a vital role in the pathogenesis of kidney renal clear cell carcinoma (KIRC), the most common subtype of renal cell carcinoma with poor prognosis and unclear pathogenesis. This study established a novel ceRNA network and thus identified a three-lncRNA prognostic model in KIRC patients.MethodsDifferentially expressed genes (DEGs) were screened out from The Cancer Genome Atlas (TCGA) database. The lncATLAS was applied to determine the differentially expressed lncRNAs (DElncRNAs) of the cytoplasm. The miRcode, miRDB, miRTarBase, and TargetScan databases were utilized to predict the interactions of DElncRNAs, DEmiRNAs, and DEmRNAs. Cytoscape was used to construct the ceRNA network. Then, a lncRNA prognostic model (LPM) was constructed based on ceRNA-related lncRNA that was significantly related to overall survival (OS), and its predictive ability was evaluated. Moreover, an LPM-based nomogram model was constructed. The significantly different expression of genes in the LPM was validated in an independent clinical cohort (N?=?21) by quantitative RT-PCR.ResultsA novel ceRNA regulatory network, including 73 lncRNAs, 8 miRNAs, and 21 mRNAs was constructed. Functional enrichment analysis indicated that integral components of membrane and PI3K-Akt signaling pathway represented the most significant GO terms and pathway, respectively. The LPM established based on three lncRNAs (MIAT, LINC00460, and LINC00443) of great prognostic value from the ceRNA network was proven to be independent of conventional clinical parameters to differentiate patients with low or high risk of poor survival, with the AUC of 1-, 5- and 10-year OS were 0.723, 0.714 and 0.826 respectively. Furthermore, the nomogram showed a better predictive value in KIRC patients than individual prognostic parameters. The expression of MIAT and LINC00460 was significantly upregulated in the KIRC samples, while the expression of LINC00443 was significantly downregulated compared with the adjacent normal samples in the clinical cohort, TCGA, and GTEx.ConclusionThis LPM based on three-lncRNA could serve as an independent prognostic factor with a tremendous predictive ability for KIRC patients, and the identified novel ceRNA network may provide insight into the prognostic biomarkers and therapeutic targets of KIRC.
| S-EPMC7367230 | biostudies-literature
Project description:BackgroundRedox plays an essential role in the pathogeneses and progression of tumors, which could be regulated by long noncoding RNA (lncRNA). We aimed to develop and verify a novel redox-related lncRNA-based prognostic signature for clear cell renal cell carcinoma (ccRCC).Materials and methodsA total of 530 ccRCC patients from The Cancer Genome Atlas (TCGA) were included in this study. All the samples were randomly split into training and test group at a 1 : 1 ratio. Then, we screened differentially expressed redox-related lncRNAs and constructed a novel prognostic signature from the training group using the least absolute shrinkage and selection operation (LASSO) and COX regression. Next, to verify the accuracy of the signature, we conducted risk and survival analysis, as well as the construction of ROC curve, nomogram, and calibration curves in the training group, test group, and all samples. Finally, the redox gene-redox-related lncRNA interaction network was constructed, and gene set enrichment analysis (GSEA) was performed to investigate the status of redox-related functions between high/low-risk groups.ResultsA nine-redox-related lncRNA signature consisted of AC025580.3, COLCA1, AC027601.2, DLEU2, AC004918.3, AP006621.2, AL031670.1, SPINT1-AS1, and LAMA5-AS1 was significantly associated with overall survival in ccRCC patients. The signature proved efficient, and thus, a nomogram was successfully assembled. In addition, the GSEA results demonstrated that two major redox-related functions were enhanced in the high-risk group ccRCC patients.ConclusionsOur findings robustly demonstrate that the nine-redox-related lncRNA signature could serve as an efficient prognostic indicator for ccRCC.
| S-EPMC7781722 | biostudies-literature