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The long non-coding RNA lnc-ZNF180-2 is a prognostic biomarker in patients with clear cell renal cell carcinoma.

ABSTRACT: 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.

SUBMITTER: Ellinger J

PROVIDER: S-EPMC4633906 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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The long non-coding RNA lnc-ZNF180-2 is a prognostic biomarker in patients with clear cell renal cell carcinoma.

Ellinger Jörg J Alam Jahedul J Rothenburg Jannik J Deng Mario M Schmidt Doris D Syring Isabella I Miersch Herdis H Perner Sven S Müller Stefan C SC

American journal of cancer research 20150815 9

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 prof ...[more]

PMID: 26609485

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Project description:BackgroundThe immune microenvironment is a critical regulator of clear cell renal cell carcinoma (ccRCC) progression. However, the underlying mechanisms the regulatory role of immune-related long non-coding RNAs (irlncRNAs) in the ccRCC tumor microenvironment (TME) are still obscure. Herein, we investigated prognostics role of irlncRNAs for ccRCC.MethodsThe raw data of patients with ccRCC were downloaded from The Cancer Genome Atlas (TCGA) database, and immune-related genes were obtained from the ImmPort database. First, we investigated the correlation between the immune-related genes and irlncRNAs. Then, we identified the differentially expressed irlncRNA pairs (ILRPs) between normal and cancer tissue samples, and prognostic model was constructed with the differentially expressed ILRPs. We further explored whether the signature risk scores of ILRPs had a considerable impact on immune cell infiltration. Finally, we performed a drug sensitivity analysis based on risk score.ResultsThere were 13 upregulated and 40 downregulated irlncRNAs between the ccRCC and normal tissue samples. We further selected the irlncRNAs that significantly affect the prognosis of patients with ccRCC via univariate Cox, lasso regression, and multivariate regression analyses. Twelve ILRPs were used to construct a prognostic signature. The model showed the ILRPs model could be used to assess the prognosis of ccRCC patients. Study of the influence of risk score and clinical characteristics on the prognosis of patients with ccRCC showed risk score to be an independent factor affecting the outcome of ccRCC. We further performed the difference analysis of immune cell abundance between ccRCC and normal tissue samples. The results showed that patients with higher abundance of M0 macrophages, plasma cells, follicular helper T cells, and regulatory T cells (Tregs) had a poor outcome. Finally, we performed a drug sensitivity analysis based on risk score. The results showed that high-risk score patients are sensitive to orafenib, sunitinib, temsirolimus, cisplatin, and gemcitabine.ConclusionsOur study has developed a novel and reasonable ILPRs model for prognostic prediction, which does not require transcriptional levels to be detected.

Project description:BackgroundAs the main histological subtype of renal cell carcinoma, clear cell renal cell carcinoma (ccRCC) places a heavy burden on health worldwide. Autophagy-related long non-coding RNAs (ARlncRs) have shown tremendous potential as prognostic signatures in several studies, but the relationship between them and ccRCC still has to be demonstrated.MethodsThe RNA-sequencing and clinical characteristics of 483 ccRCC patients were downloaded download from the Cancer Genome Atlas and International Cancer Genome Consortium. ARlncRs were determined by Pearson correlation analysis. Univariate and multivariate Cox regression analyses were applied to establish a risk score model. A nomogram was constructed considering independent prognostic factors. The Harrell concordance index calibration curve and the receiver operating characteristic analysis were utilized to evaluate the nomogram. Furthermore, functional enrichment analysis was used for differentially expressed genes between the two groups of high- and low-risk scores.ResultsA total of 9 SARlncRs were established as a risk score model. The Kaplan-Meier survival curve, principal component analysis, and subgroup analysis showed that low overall survival of patients was associated with high-risk scores. Age, M stage, and risk score were identified as independent prognostic factors to establish a nomogram, whose concordance index in the training cohort, internal validation, and external ICGC cohort was 0.793, 0.671, and 0.668 respectively. The area under the curve for 5-year OS prediction in the training cohort, internal validation, and external ICGC cohort was 0.840, 0.706, and 0.708, respectively. GO analysis and KEGG analysis of DEGs demonstrated that immune- and inflammatory-related pathways are likely to be critically involved in the progress of ccRCC.ConclusionsWe established and validated a novel ARlncRs prognostic risk model which is valuable as a potential therapeutic target and prognosis indicator for ccRCC. A nomogram including the risk model is a promising clinical tool for outcomes prediction of ccRCC patients and further formulation of individualized strategy.

Project description:Background: The incidence of clear cell renal cell carcinoma (ccRCC) is high and has increased gradually in recent years. At present, due to the lack of effective prognostic indicators, the prognosis of ccRCC patients is greatly affected.Necroptosis is a type of cell death, and along with cell necrosis is considered a new cancer treatment strategy. The aim of this study was to construct a new marker for predicting the prognosis of ccRCC patients based on long non-coding RNA (nrlncRNAs) associated with necroptosis. Methods: RNA sequence data and clinical information of ccRCC patients from the Cancer Genome Atlas database (TCGA) were downloaded. NrlncRNA was identified by Pearson correlation study. The differentially expressed nrlncRNA and nrlncRNA pairs were identified by univariate Cox regression and Lasso-Cox regression. Finally, a Kaplan-Meier survival study, Cox regression, clinicopathological features correlation study, and receiver operating characteristic (ROC) spectrum were used to evaluate the prediction ability of 25-nrlncrnas for markers. In addition, correlations between the risk values and sensitivity to tumor-infiltrating immune cells, immune checkpoint inhibitors, and targeted drugs were also investigated. Results: In the current research, a novel marker of 25-nrlncRNAs pairs was developed to improve prognostic prediction in patients with ccRCC. Compared with clinicopathological features, nrlncRNAs had a higher diagnostic validity for markers, with the 1-year, 3-years, and 5-years operating characteristic regions being 0.902, 0.835, and 0.856, respectively, and compared with the stage of 0.868, an increase of 0.034. Cox regression and stratified survival studies showed that this marker could be an independent predictor of ccRCC patients. In addition, patients with different risk scores had significant differences in tumor-infiltrating immune cells, immune checkpoint, and semi-inhibitory concentration of targeted drugs. The feature could be used to evaluate the clinical efficacy of immunotherapy and targeted drug therapy. Conclusion: 25-nrlncRNAs pair markers may help to evaluate the prognosis and molecular characteristics of ccRCC patients, which improve treatment methods and can be more used in clinical practice.

Dataset Information

The long non-coding RNA lnc-ZNF180-2 is a prognostic biomarker in patients with clear cell renal cell carcinoma.

Publications

The long non-coding RNA lnc-ZNF180-2 is a prognostic biomarker in patients with clear cell renal cell carcinoma.

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