A five-long non-coding RNA signature to improve prognosis prediction of clear cell renal cell carcinoma

Shi, Da; Qu, Qinghua; Chang, Qimeng; Wang, Yilin; Gui, Yan; Dong, Dong

doi:10.18632/oncotarget.17506

Cited by 33 publications

(38 citation statements)

References 44 publications

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“…For example, using lncRNA expression profiling of 440 clear cell renal cell carcinoma tumors from the TCGA database, a 5-lncRNA signature was identified to be significantly associated with patient OS. 18 In univariate Cox regression analysis, five lncRNAs correlated with the patient OS. Next, based on this lncRNA signature, significant differences were found in the survival rate between patients in the highand low-risk groups.…”

Section: Discussionmentioning

confidence: 99%

Identification of a six‐gene signature with prognostic value for patients with endometrial carcinoma

et al. 2018

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Uterine corpus endometrial carcinoma (UCEC) is frequently diagnosed among women worldwide. However, there are different prognostic outcomes because of heterogeneity. Thus, the aim of the current study was to identify a gene signature that can predict the prognosis of patients with UCEC. UCEC gene expression profiles were first downloaded from the The Cancer Genome Atlas (TCGA) database. After data processing and forward screening, 11 390 key genes were selected. The UCEC samples were randomly divided into training and testing sets. In total, 996 genes with prognostic value were then examined by univariate Cox survival analysis with a P‐value <0.01 in the training set. Next, using robust likelihood‐based survival modeling, we developed a six‐gene signature (CTSW, PCSK4, LRRC8D, TNFRSF18, IHH, and CDKN2A) with a prognostic function in UCEC. A prognostic risk score system was developed by multivariate Cox proportional hazard regression based on this six‐gene signature. According to the Kaplan‐Meier curve, patients in the high‐risk group had significantly poorer overall survival (OS) outcomes than those in the low‐risk group (log‐rank test P‐value <0.0001). This signature was further validated in the testing dataset and the entire TCGA dataset. In conclusion, we conducted an integrated study to develop a six‐gene signature for the prognostic prediction of patients with UCEC. Our findings may provide novel biomarkers for prognosis and have significant implications in the understanding of therapeutic targets for UCEC.

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Section: Discussionmentioning

confidence: 99%

Identification of a six‐gene signature with prognostic value for patients with endometrial carcinoma

et al. 2018

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“…Many researches have provided the valid evidence to demonstrate the great effects of lncRNAs on complex processes of human diseases . As diagnostic or prognostic markers, ceRNAs have been uncovered in many reports . In some cases, lncRNAs can participate in ceRNA pattern to modulate gene expression .…”

Section: Discussionmentioning

confidence: 99%

“…[22][23][24][25] As diagnostic or prognostic markers, ceRNAs have been uncovered in many reports. [26][27][28][29][30][31][32] In some cases, lncRNAs can participate in ceRNA pattern to modulate gene expression. 33,34 In this study, we supposed that SNHG16 might be a ceRNA in HemECs.…”

Section: Discussionmentioning

confidence: 99%

LncRNA SNHG16 drives proliferation, migration, and invasion of hemangioma endothelial cell through modulation of miR‐520d‐3p/STAT3 axis

Zhao

Fu²,

Zhang

et al. 2018

Cancer Medicine

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It has been verified that long noncoding RNAs (lncRNAs) have great effects on various biological behaviors of human diseases. Although more and more lncRNAs have been studied in human cancers, countless lncRNAs still need to be excavated. This study aims to investigate the impacts of lncRNA SNHG16 on proliferation and metastasis of human hemangioma endothelial cell (HemECs). qRT‐PCR analysis was carried out to explore the expression pattern of SNHG16, miR‐520d‐3p, and STAT3. The effect of SNHG16 on cell proliferation was detected by MTT and colony formation assay. Flow cytometry analysis was performed to test the apoptosis of HemECs cells. Migration and invasion of HemECs cells were determined and examined by transwell assays. Tube formation assay helped to observe the influence of SNHG16 expression on the vasoformation of HemECs cells. The correlations among SNHG16, miR‐520d‐3p, and STAT3 were certified by bioinformatics analysis, pull‐down assay, and dual‐luciferase reporter assay. Finally, rescue assays were conducted to demonstrate the effects of SNHG16‐miR‐520d‐3p‐STAT3 axis on biological behaviors of HemECs cell. SNHG16 was strongly expressed in proliferating phase hemangioma tissues and HemECs cells. Silenced SNHG16 negatively affected proliferation, migration, and invasion of HemECs cell. LncRNA SNHG16 acted as a ceRNA to upregulate STAT3 through binding with miR‐520d‐3p in HemECs cell. LncRNA SNHG16 acted as a ceRNA to drive proliferation, vasoformation, migration, and invasion of HemECs cells through modulating miR‐520d‐3p/STAT3 axis.

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“…He et al, Tang et al and Zang et al used TCGA lncRNA dataset to identify a lncRNA expression-based prognostic signature for assessing the survival of patients with soft-tissue sarcoma, lung cancer, and colorectal adenocarcinoma [36][37][38]. TCGA lncRNA datasets of cutaneous melanoma [39], bladder urothelial carcinoma [40], breast cancer [41], clear cell renal cell carcinoma [42], gastric cancer [43,44], head and neck squamous cell carcinoma [45], and HCC [46] have been used in lncRNA expressionbased prognostic signature investigations by other researchers. These studies used a genome-wide screening method to identify potential prognostic lncRNAs and calculated a risk score based on lncRNA expression.…”

Section: Discussionmentioning

confidence: 99%

Identification of Potential Prognostic Long Non-Coding RNA Biomarkers for Predicting Survival in Patients with Hepatocellular Carcinoma

Liao

Yang

Huang

et al. 2018

Cell Physiol Biochem

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Background/Aims: The aim of the current study was to identify potential prognostic long non-coding RNA (lncRNA) biomarkers for predicting survival in patients with hepatocellular carcinoma (HCC) using The Cancer Genome Atlas (TCGA) dataset and bioinformatics analysis. Methods: RNA sequencing and clinical data of HCC patients from TCGA were used for prognostic association assessment by univariate Cox analysis. A prognostic signature was built using stepwise multivariable Cox analysis, and a comprehensive analysis was performed to evaluate its prognostic value. The prognostic signature was further evaluated by functional assessment and bioinformatics analysis. Results: Thirteen differentially expressed lncRNAs (DELs) were identified and used to construct a single prognostic signature. Patients with high risk scores showed a significantly increased risk of death (adjusted P < 0.0001, adjusted hazard ratio = 3.522, 95% confidence interval = 2.307–5.376). In the time-dependent receiver operating characteristic analysis, the prognostic signature performed well for HCC survival prediction with an area under curve of 0.809, 0.782 and 0.79 for 1-, 3- and 5-year survival, respectively. Comprehensive survival analysis of the 13-DEL prognostic signature suggested that it serves as an independent factor in HCC, showing a better performance for prognosis prediction than traditional clinical indicators. Functional assessment and bioinformatics analysis suggested that the prognostic signature was associated with the cell cycle and peroxisome proliferator-activated receptor signaling pathway. Conclusions: The novel lncRNA expression signature identified in the present study may be a potential biomarker for predicting the prognosis of HCC patients.

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A five-long non-coding RNA signature to improve prognosis prediction of clear cell renal cell carcinoma

Cited by 33 publications

References 44 publications

Identification of a six‐gene signature with prognostic value for patients with endometrial carcinoma

Identification of a six‐gene signature with prognostic value for patients with endometrial carcinoma

LncRNA SNHG16 drives proliferation, migration, and invasion of hemangioma endothelial cell through modulation of miR‐520d‐3p/STAT3 axis

Identification of Potential Prognostic Long Non-Coding RNA Biomarkers for Predicting Survival in Patients with Hepatocellular Carcinoma

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