<i>MAFG‐AS1</i> promotes tumor progression via regulation of the HuR/PTBP1 axis in bladder urothelial carcinoma

Xiao, Mengqing; Liu, Jianye; Xiang, Lei; Zhao, Kai; He, Dong; Zeng, Qinghai; Zhang, Qun; Xie, Dan; Deng, Minhua; Zhu, Yuxing; Zhang, Yeyu; Liu, Yan; Bo, Hao; Liu, Xiaoming; Chen, Xingyu; Gong, Lian; Bao, Ying; Hu, Yi; Cheng, Ying; Deng, Liping; Zhu, Rongrong; Xing, Xiaowei; Zhou, Ming; Xiong, Wei; Zhou, Yanhong; Zhou, Jianda; Li, Xiaohui; Cao, Ke

doi:10.1002/ctm2.241

Cited by 40 publications

(23 citation statements)

References 53 publications

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“…Besides, Xiao et al showed that MAFG-AS1 can promote BC proliferation, invasion, metastasis, and EMT in vitro and in vivo. Mechanistically, MAFG-AS1 directly binding to Hu antigen R (HuR) could recruit ubiquitin-specific proteinase 5 (USP5) to prevent HuR from degrading by ubiquitination [ 34 ]. For six remaining FRlncRNAs (AL136084.3, AC062017.1, AC008074.2, AC018653.3, LINC01767, and AC132807.2), there were no studies to report their prognostic roles in cancer.…”

Section: Discussionmentioning

confidence: 99%

Identification of a Nomogram from Ferroptosis-Related Long Noncoding RNAs Signature to Analyze Overall Survival in Patients with Bladder Cancer

Cui

Chai

Che

et al. 2021

Journal of Oncology

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Purpose. This study aimed to establish a nomogram to predict the overall survival (OS) of patients with bladder cancer (BC) by ferroptosis-related long noncoding RNAs (FRlncRNAs) signature. Methods. We obtained FRlncRNAs expression profiles and clinical data of patients with BC from the Cancer Genome Atlas database. The patients were divided into the training set, testing set, and overall set. Lasso regression and multivariate Cox regression were used to establish the FRlncRNAs signature, the prognosis of each group was compared by Kaplan–Meier (K-M) analysis, and the receiver operating characteristic (ROC) curve evaluated the accuracy of the model. The Gene Set Enrichment Analysis (GSEA) was used for the visualization of the functional enrichment for FRlncRNAs. The databases of GEPIA and K-M Plotter were used for subsequent functional analysis of major FRlncRNAs. Results. Thirteen prognostic FRlncRNAs (LINC00942, MAFG-DT, AL049840.3, AL136084.3, OCIAD1-AS1, AC062017.1, AC008074.2, AC018653.3, AL031775.1, USP30-AS1, LINC01767, AC132807.2, and AL354919.2) were identified to be significantly different, constituting an FRlncRNAs signature. Patients with BC were divided into low-risk group and high-risk group by this signature in the training, testing, and overall sets. K-M analysis showed that the prognosis of patients in the high-risk group was poor and the difference in the subgroup analyses was statistically significant. ROC analysis revealed that the predictive ability of the model was more accurate than traditional assessment methods. A risk score based on FRlncRNAs signature was an independent prognostic factor for the patients with BC (HR = 1.388, 95%CI = 1.228–1.568, P < 0.001 ). Combining the FRlncRNAs signature and clinicopathological factors, a predictive nomogram was constructed. The nomogram can accurately predict the overall survival of patients and had high clinical practicability. The GSEA analysis showed that the primary pathways were WNT, MAPK, and cell-matrix adhesion signaling pathways. The major FRlncRNAs (MAFG-DT) were associated with poor prognosis in the GEPIA and K-M Plotter database. Conclusion. Thirteen prognostic FRlncRNAs and their nomogram were accurate tools for predicting the OS of BC, which might be molecular biomarkers and therapeutic targets.

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Section: Discussionmentioning

confidence: 99%

Identification of a Nomogram from Ferroptosis-Related Long Noncoding RNAs Signature to Analyze Overall Survival in Patients with Bladder Cancer

Cui

Chai

Che

et al. 2021

Journal of Oncology

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“…Herrera-Solorio et al (2020) showed that lncRNA SOX2-OT modulates an orchestrated resistance mechanism, promoting poor prognosis and human lung malignancy through genetic, epigenetic, and posttranslational mechanisms. Xiao et al (2020) found that the lncRNA MAFG-AS1, which is highly expressed in bladder urothelial carcinoma, is correlated with aggressive characteristics and poor prognosis of bladder urothelial carcinoma. As for BRCA, IRNAS HOTAIR, SPRY4-IT1, GAS5, MATAR25, PANDAR, and MATAR25, new players in tumor development and prognosis, have shown owning potential clinical applications in BRCA (Soudyab et al, 2016;Nagini, 2017;Chang et al, 2020).…”

Section: Introductionmentioning

confidence: 92%

Construction and Analysis of the Dysregulated ceRNA Network and Identification of Risk Long Noncoding RNAs in Breast Cancer

Zhang

et al. 2021

Front. Genet.

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Breast cancer (BRCA) is the second leading cause of cancer-related mortality in women worldwide. However, the molecular mechanism involved in the development of BRCA is not fully understood. In this study, based on the miRNA-mediated long non-coding RNA (lncRNA)–protein coding gene (PCG) relationship and lncRNA–PCG co-expression information, we constructed and analyzed a specific dysregulated lncRNA–PCG co-expression network in BRCA. Then, we performed the random walk with restart (RWR) method to prioritize BRCA-related lncRNAs through comparing their RWR score and significance. As a result, we identified 30 risk lncRNAs for BRCA, which can distinguish normal and tumor samples. Moreover, through gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis, we found that these risk lncRNAs mainly synergistically exerted functions related to cell cycle and DNA separation and replication. At last, we developed a four-lncRNA prognostic signature (including AP000851.1, LINC01977, MAFG-DT, SIAH2-AS1) and assessed the survival accuracy of the signature by performing time-dependent receiver operating characteristic (ROC) analysis. The areas under the ROC curve for 1, 3, 5, and 10 years of survival prediction were 0.68, 0.61, 0.62, and 0.63, respectively. The multivariable Cox regression results verified that the four-lncRNA signature could be used as an independent prognostic biomarker in BRCA. In summary, these results have important reference value for the study of diagnosis, treatment, and prognosis evaluation of BRCA.

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“…Recent developments in next-generation sequencing technologies have greatly expanded our knowledge of non-coding RNAs, and these non-coding RNAs are considerably more abundant than mRNAs (26). Many studies have revealed the role of lncRNAs in cancer development, indicating their potential as novel biomarkers for cancer diagnosis and prognosis (27)(28)(29). To better understand the molecular markers of relapsed HCC, we comprehensively analyzed the database and identified lncRNAs that can be used to predict OS and RFS.…”

Section: Discussionmentioning

confidence: 99%

A Co-Expression Network Reveals the Potential Regulatory Mechanism of lncRNAs in Relapsed Hepatocellular Carcinoma

et al. 2021

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BackgroundThe mechanistic basis for relapsed hepatocellular carcinoma (HCC) remains poorly understood. Recent research has highlighted the important roles of long non-coding RNAs (lncRNAs) in HCC. However, there are only a few studies on the association between lncRNAs and HCC relapse.MethodsDifferentially expressed lncRNAs and mRNAs between a primary HCC group and relapsed HCC group were identified using the edge R package to analyze the GSE101432 dataset. The differentially expressed lncRNAs and mRNAs were used to construct a lncRNA–mRNA co-expression network. Weighted gene co-expression network analysis followed by Gene Ontology (GO) enrichment analyses were conducted on the database. Furthermore, correlation and survival analyses were performed using The Cancer Genome Atlas database, and expression in the clinical samples was verified by qRT-PCR. Thereafter, we inputted the genes from the two groups into the HCC TNM stage and tumor grade database from TCGA. Finally, we performed Kaplan–Meier survival analysis on the lncRNAs related to relapsed HCC.ResultsIn this study, lncRNAs and mRNAs associated with HCC relapse were identified. Two gene modules were found to be closely linked to this. The GO terms in the yellow and black modules were related to cell proliferation, differentiation, and survival, as well as some transcription-related biological processes. Through qRT-PCR, we found that the expression levels of LINC00941 and LINC00668 in relapsed HCC were higher than those in primary HCC. Further, mRNA levels of LOX, OTX1, MICB, NDUFA4L2, BAIAP2L2, and KCTD17 were changed in relapsed HCC compared to levels in primary HCC. In addition, we verified that these genes could predict the overall survival and recurrence-free survival of HCC. Moreover, we found that LINC00668 and LINC00941 could affect tumor grade and TNM stages. In total, we identified and validated two lncRNAs (LINC00941 and LINC00668) and six mRNAs (LOX, MICB, OTX1, BAIAP2L2, KCTD17, NDUFA4L2) associated with HCC relapse.ConclusionIn summary, we identified the key gene modules and central genes associated with relapsed HCC and constructed lncRNA–mRNA networks related to this. These genes are likely to have potential prognostic value for relapsed HCC and might shed new light on novel biomarkers or diagnostic targets for relapsed HCC.

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MAFG‐AS1 promotes tumor progression via regulation of the HuR/PTBP1 axis in bladder urothelial carcinoma

Abstract: Our findings indicate that MAFG-AS1 acts as an oncogene to promote the progression of BUC via regulation of the HUR/PTBP1 axis. Targeting MAFG-AS1 may provide a novel strategy for individualized therapy and a potential biomarker for prognosis of BUC

Cited by 40 publications

References 53 publications

Identification of a Nomogram from Ferroptosis-Related Long Noncoding RNAs Signature to Analyze Overall Survival in Patients with Bladder Cancer

Identification of a Nomogram from Ferroptosis-Related Long Noncoding RNAs Signature to Analyze Overall Survival in Patients with Bladder Cancer

Construction and Analysis of the Dysregulated ceRNA Network and Identification of Risk Long Noncoding RNAs in Breast Cancer

A Co-Expression Network Reveals the Potential Regulatory Mechanism of lncRNAs in Relapsed Hepatocellular Carcinoma

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