Identification and Function Analysis of a Five-Long Noncoding RNA Prognostic Signature for Endometrial Cancer Patients

Tang, Hong; Wu, Zhixi; Zhang, Yuan; Xia, Tingting; Liu, Dong; Cai, Jiarong; Ye, Qingjian

doi:10.1089/dna.2019.4944

Cited by 26 publications

(18 citation statements)

References 39 publications

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“…KCNMB2-AS1expression is correlated with the overall survival of patients with endometrial cancer. 28 However, the expression profile and precise functions of KCNMB2-AS1 in NSCLC remain unknown. In this study, GEPIA of the TCGA and GTEx databases was performed to analyze the expression of KCNMB2-AS1 in NSCLC.…”

Section: Dovepressmentioning

confidence: 99%

<p>Long Noncoding RNA KCNMB2-AS1 Increases ROCK1 Expression by Sponging microRNA-374a-3p to Facilitate the Progression of Non–Small-Cell Lung Cancer</p>

Huang

Wang

2020

CMAR

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Purpose The expression and roles of most long noncoding RNAs (lncRNAs) in non–small-cell lung cancer (NSCLC) remain poorly understood. Thus, this study investigated KCNMB2 antisense RNA 1 (KCNMB2-AS1) expression in NSCLC and determined the roles and mechanisms of KCNMB2-AS1 in regulating NSCLC progression. Methods KCNMB2-AS1 expression in NSCLC tissues and cells was detected using reverse transcription-quantitative polymerase chain reaction. Cell proliferation, apoptosis, migration, and invasion were evaluated using Cell Counting Kit-8, flow cytometry, Transwell migration, and Transwell invasion assays, respectively. In vivo tumor xenograft models were constructed to assess tumorigenicity. Bioinformatics predictions were performed to identify microRNAs targeting KCNMB2-AS1 . Interactions between KCNMB2-AS1 and miR-374a-3p were analyzed using RNA immunoprecipitation, luciferase reporter, and rescue experiments. Results KCNMB2-AS1 levels were increased in NSCLC tissues and cells. KCNMB2-AS1 silencing hindered NSCLC cell proliferation, migration, and invasion and promoted apoptosis in vitro. Additionally, KCNMB2-AS1 knockdown decreased tumor growth in vivo. Mechanistically, KCNMB2-AS1 functioned as an endogenous miR-374a-3p sponge and increased ρ-associated coiled-coil–containing protein kinase 1 (ROCK1) expression. Furthermore, increased miR-374a-3p/ROCK1 output attenuated KCNMB2-AS1 silencing-induced inhibition of NSCLC progression. Conclusion The KCNMB2-AS1/miR-374a-3p/ROCK1 pathway drives NSCLC progression, suggesting that this pathway can be targeted to reduce NSCLC progression.

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Section: Dovepressmentioning

confidence: 99%

<p>Long Noncoding RNA KCNMB2-AS1 Increases ROCK1 Expression by Sponging microRNA-374a-3p to Facilitate the Progression of Non–Small-Cell Lung Cancer</p>

Huang

Wang

2020

CMAR

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“…MSKCC nomogram consisted of five clinicopathological factors including age, lymph node status, FIGO stage, tumor grade, and histological subtype, which showed better discrimination and calibration values than the FIGO staging system 41 and could better stratified patients in other external validation 42 . There were also molecule‐based nomograms predicting OS of EC 43,44 . However, these studies only concentrated on either clinical indexes or gene expression, and the AUCs of these nomograms of 5‐year survival were lower than ours (AUC = 0.866).…”

Section: Discussionmentioning

confidence: 68%

Establishment and validation of a prognostic nomogram based on a novel five‐DNA methylation signature for survival in endometrial cancer patients

Yin

Yuan

et al. 2020

Cancer Medicine

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Background This study aimed to explore the prognostic role of DNA methylation pattern in endometrial cancer (EC) patients. Methods Differentially methylated genes (DMGs) of EC patients with distinct survival from The Cancer Genome Atlas (TCGA) database were analyzed to identify methylated genes as biomarkers for EC prognosis. The Least Absolute Shrinkage and Selection Operator (LASSO) analysis was used to construct a risk score model. A nomogram was built based on analysis combining the risk score model with clinicopathological signatures together, and then verified in the validation cohort and patients in our own center. Results In total, 157 DMGs were identified between different prognostic groups. Based on the LASSO analysis, five genes (GBP4, OR8K3, GABRA2, RIPPLY2, and TRBV5‐7) were screened for the establishment of risk score model. The model outperformed in prognostic accuracy at varying follow‐up times (AUC for 3 years: 0.824, 5 years: 0.926, and 7 years: 0.853). Multivariate analysis identified four independent risk factors including menopausal status (HR = 3.006, 95%CI: 1.062–8.511, p = 0.038), recurrence (HR = 2.116, 95%CI: 1.061–4.379, p = 0.046), lymph node metastasis (LNM, HR = 3.465, 95%CI: 1.225–9.807, p = 0.019), and five‐DNA methylation risk model (HR = 3.654, 95%CI: 1.458–9.161, p = 0.006) in training cohort. The performance of the nomogram was good in the training (AUC = 0.828), validation (AUC = 0.866) and the whole cohorts (AUC = 0.843). Furthermore, we verified the nomogram with 24 patients in our center and the Kaplan–Meier survival curve also proved to be significantly different ( p < 0.01). The subgroup analysis in different stratifications indicated that the accuracy was high in different subgroups for age, histological type, tumor grade, and clinical stage (all p < 0.01). Conclusions Briefly, our work established and verified a five‐DNA methylation risk model, and a nomogram merging the model with clinicopathological characteristics to facilitate individual prediction of EC patients for clinicians.

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“…The six hublncRNAs are also proved to have significant predictive power of lung SCC patients' OS. Among the six hublncRNAs discussed in our study, previous work only suggested the LINC01352 was proved to be a potential biomarker in endometrial cancer (25). The other five lncRNAs are not covered by any existing literature regarding their connection with any types of cancer yet.…”

Section: Discussionmentioning

confidence: 70%

Novel long noncoding RNA (lncRNA) panel as biomarkers for prognosis in lung squamous cell carcinoma via competitive endogenous RNA (ceRNA) network analysis

Zhang¹,

Deng²,

Ji³

et al. 2021

Transl Cancer Res TCR

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Background:The recently discovered competitive endogenous RNA (ceRNA) mechanism is considered to be actively involved in the regulation of gene expression. Such process may play a significant role in the development and evolvement of cancer. This study further explores the connection between the ceRNA mechanism and the lung squamous cell carcinoma prognosis.Methods: We started with obtaining the RNA-seq [including long noncoding RNA (lncRNA), mRNA and microRNA (miRNA)] data of lung squamous cell carcinoma from The Cancer Genome Atlas (TCGA), and then analyzed the regulation of ceRNA network in lung squamous cell carcinoma. Bioinformatics tools based on R script were deployed.Results: Firstly, we found that three miRNAs, including hsa-miR-2278, hsa-miR-3176 and hsa-miR-3654 formed the core of ceRNA network of lung squamous cell carcinoma. Moreover, after unsupervised training of the ceRNA network, three miRNAs were closely correlated in the network. In detail, AL590226, AL090044 and LINC01352 could interact with miR-2278; AL360219 and AC092071 could interact with miR-3654; AC010976 could interact with miR-3176. The above six lncRNAs altogether, could be used as a biomarker panel to predict the prognosis of lung squamous cell carcinoma.Conclusions: Our study suggests that these six lncRNAs may be potential diagnostic and prognostic biomarkers of lung squamous cell carcinoma, which could potentially benefit the patients in the future.

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Identification and Function Analysis of a Five-Long Noncoding RNA Prognostic Signature for Endometrial Cancer Patients

Cited by 26 publications

References 39 publications

<p>Long Noncoding RNA KCNMB2-AS1 Increases ROCK1 Expression by Sponging microRNA-374a-3p to Facilitate the Progression of Non–Small-Cell Lung Cancer</p>

<p>Long Noncoding RNA KCNMB2-AS1 Increases ROCK1 Expression by Sponging microRNA-374a-3p to Facilitate the Progression of Non–Small-Cell Lung Cancer</p>

Establishment and validation of a prognostic nomogram based on a novel five‐DNA methylation signature for survival in endometrial cancer patients

Novel long noncoding RNA (lncRNA) panel as biomarkers for prognosis in lung squamous cell carcinoma via competitive endogenous RNA (ceRNA) network analysis

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