Long Non-coding RNA Double Homeobox A Pseudogene 8: A Novel Oncogenic Propellant in Human Cancer

Xue, Chen; Cai, Xiaona; Jia, Junjun

doi:10.3389/fcell.2021.709069

Cited by 4 publications

(4 citation statements)

References 54 publications

(102 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…DUXAP8 is a biomarker and therapeutic target of various cancers that is upregulated in GC, promotes cell proliferation and migration, and then accelerates the development of GC 32 , and this study verified the upregulation of DUXAP8 in GC. Previous studies have shown that lncRNA TP53TG1 can not only inhibit the development of GC by regulating the stability of CIP2A34 30 , but also play a promoting role in cancer development.…”

Section: Discussionsupporting

confidence: 69%

Construction of an oxidative stress-related lncRNAs signature to predict prognosis and the immune response in gastric cancer

Zhang

Feng

et al. 2023

Sci Rep

View full text Add to dashboard Cite

Oxidative stress, as a characteristic of cellular aerobic metabolism, plays a crucial regulatory role in the development and metastasis of gastric cancer (GC). Long noncoding RNAs (lncRNAs) are important regulators in GC development. However, research on the prognostic patterns of oxidative stress-related lncRNAs (OSRLs) and their functions in the immune microenvironment is currently insufficient. We identified the OSRLs signature (DIP2A-IT1, DUXAP8, TP53TG1, SNHG5, AC091057.1, AL355001.1, ARRDC1-AS1, and COLCA1) from 185 oxidative stress-related genes in The Cancer Genome Atlas (TCGA) cohort via random survival forest and Cox analyses, and the results were subsequently validated in the Gene Expression Omnibus (GEO) dataset. The patients were divided into high- and low-risk groups by the risk score of the OSRLs signature. Longer overall survival was detected in the low-risk group than in the high-risk group in both the TCGA cohort (P < 0. 001, HR = 0.43, 95% CI 0.31–0.62) and the GEO cohort (P = 0.014, HR = 0.67, 95% CI 0.48–0.93). Next, multivariate Cox analysis identified that the risk model was an independent prognostic characteristic (HR > 1, P = 0.005), and time-dependent receiver operating characteristic (ROC) curve analysis and nomogram analysis were utilized to evaluate the predictive ability of the risk model. Next, gene set enrichment analysis revealed that the immune-related pathway, Wnt/$$\upbeta$$ β -catenin signature, mammalian target of rapamycin complex 1 signature, and cytokine‒cytokine receptor interaction was enriched. High-risk patients were more responsive to CD200, TNFSF4, TNFSF9, and BTNL2 immune checkpoint blockade. The results of qRT‒PCR further proved the accuracy of our bioinformatic analysis. Overall, our study identified a novel OSRLs signature that can serve as a promising biomarker and prognostic indicator, which provides a personalized predictive approach for patient prognosis evaluation and treatment.

show abstract

Section: Discussionsupporting

confidence: 69%

Construction of an oxidative stress-related lncRNAs signature to predict prognosis and the immune response in gastric cancer

Zhang

Feng

et al. 2023

Sci Rep

View full text Add to dashboard Cite

show abstract

“…Recent studies have found that silencing DUXAP8 expression can inhibit cell proliferation and promote apoptosis by targeting miR-26b-5P (32). DUXAP8 is involved in the initiation of many tumors and has the potential as a therapeutic target (33). LncRNA PWAR6 regulates proliferation and migration by epigenetically silencing YAP1 in tumorigenesis of pancreatic ductal adenocarcinoma (34).…”

Section: Discussionmentioning

confidence: 99%

A Prognostic Model of Bladder Cancer Based on Metabolism-Related Long Non-Coding RNAs

Lai

Shen

et al. 2022

Front. Oncol.

View full text Add to dashboard Cite

BackgroundSome studies have revealed a close relationship between metabolism-related genes and the prognosis of bladder cancer. However, the relationship between metabolism-related long non-coding RNAs (lncRNA) regulating the expression of genetic material and bladder cancer is still blank. From this, we developed and validated a prognostic model based on metabolism-associated lncRNA to analyze the prognosis of bladder cancer.MethodsGene expression, lncRNA sequencing data, and related clinical information were extracted from The Cancer Genome Atlas (TCGA). And we downloaded metabolism-related gene sets from the human metabolism database. Differential expression analysis is used to screen differentially expressed metabolism-related genes and lncRNAs between tumors and paracancer tissues. We then obtained metabolism-related lncRNAs associated with prognosis by correlational analyses, univariate Cox analysis, and logistic least absolute shrinkage and selection operator (LASSO) regression. A risk scoring model is constructed based on the regression coefficient corresponding to lncRNA calculated by multivariate Cox analysis. According to the median risk score, patients were divided into a high-risk group and a low-risk group. Then, we developed and evaluated a nomogram including risk scores and Clinical baseline data to predict the prognosis. Furthermore, we performed gene-set enrichment analysis (GSEA) to explore the role of these metabolism-related lncRNAs in the prognosis of bladder cancer.ResultsBy analyzing the extracted data, our research screened out 12 metabolism-related lncRNAs. There are significant differences in survival between high and low-risk groups divided by the median risk scoring model, and the low-risk group has a more favorable prognosis than the high-risk group. Univariate and multivariate Cox regression analysis showed that the risk score was closely related to the prognosis of bladder cancer. Then we established a nomogram based on multivariate analysis. After evaluation, the modified model has good predictive efficiency and clinical application value. Furthermore, the GSEA showed that these lncRNAs affected bladder cancer prognosis through multiple links.ConclusionsA predictive model was established and validated based on 12 metabolism-related lncRNAs and clinical information, and we found these lncRNA affected bladder cancer prognosis through multiple links.

show abstract

“…Lymphoid-specific helicase can inhibit ferroptosis in lung cancer cells, and LSH knockout decreases SLC2A3 and induces ferroptosis, which implies that SLC2A3 may be involved in inhibiting ferroptosis ( Jiang et al, 2017 ). Double homeobox A pseudogene 8 (DUXAP8), as a novel, long noncoding RNA, is associated with a number of cancers, including liver, colorectal, bladder, oral, ovarian, lung, and pancreatic tumors ( Xue et al, 2021 ). However, it is rarely studied in ferroptosis and, whether the DUXAP8-hsa-miR-378e/378f-SLC2A3 ceRNA network we constructed is involved in the regulation of ferroptosis, remains to be verified.…”

Section: Discussionmentioning

confidence: 99%

Bioinformatics analysis constructs potential ferroptosis-related ceRNA network involved in the formation of intracranial aneurysm

Zhu

Tan

Wang

et al. 2022

Front. Cell. Neurosci.

View full text Add to dashboard Cite

BackgroundIntracranial aneurysm (IA) causes more than 80% of nontraumatic subarachnoid hemorrhages (SAHs). The mechanism of ferroptosis involved in IA formation remains unclear. The roles played by competitive endogenous RNA (ceRNA) regulation networks in many diseases are becoming clearer. The goal of this study was to understand more fully the ferroptosis-related ceRNA regulation network in IA.Materials and methodsTo identify differentially expressed genes (DEGs), differentially expressed miRNAs (DEMs), and differentially expressed lncRNAs (DELs) across IA and control samples, the GEO datasets GSE122897 and GSE66239 were downloaded and analyzed with the aid of R. Ferroptosis DEGs were discovered by exploring the DEGs of ferroptosis-related genes of the ferroptosis database. Potentially interacting miRNAs and lncRNAs were predicted using miRWalk and StarBase. Enrichment analysis was also performed. We utilized the STRING database and Cytoscape software to identify protein-protein interactions and networks. DAB-enhanced Prussian blue staining was used to detect iron in IA tissues.ResultsIron deposition was evident in IA tissue. In all, 30 ferroptosis DEGs, 5 key DEMs, and 17 key DELs were screened out for constructing a triple regulatory network. According to expression regulation of DELs, DEMs, and DEGs, a hub triple regulatory network was built. As the functions of lncRNAs are determined by their cellular location, PVT1-hsa-miR-4644-SLC39A14 ceRNA and DUXAP8-hsa-miR-378e/378f-SLC2A3 ceRNA networks were constructed.ConclusionCeRNA (PVT1-hsa-miR-4644-SLC39A14 and DUXAP8-hsa-miR-378e/378f-SLC2A3) overexpression networks associated with ferroptosis in IA were established.

show abstract

Long Non-coding RNA Double Homeobox A Pseudogene 8: A Novel Oncogenic Propellant in Human Cancer

Cited by 4 publications

References 54 publications

Construction of an oxidative stress-related lncRNAs signature to predict prognosis and the immune response in gastric cancer

Construction of an oxidative stress-related lncRNAs signature to predict prognosis and the immune response in gastric cancer

A Prognostic Model of Bladder Cancer Based on Metabolism-Related Long Non-Coding RNAs

Bioinformatics analysis constructs potential ferroptosis-related ceRNA network involved in the formation of intracranial aneurysm

Contact Info

Product

Resources

About