Identification of lncRNA‐associated competing endogenous RNA networks for occurrence and prognosis of gastric carcinoma

Ye, Lianmin; Jin, Wumin

doi:10.1002/jcla.24028

Cited by 9 publications

(10 citation statements)

References 61 publications

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“…Finally, we constructed the LINC00702-miR-181b-5p-SPP1 axis and showed that this signal axis could regulate the development of CAVD. As one of the miRNA sponges, LINC00702 could interact with different miRNAs in various diseases (60)(61)(62)(63). By constructing a cardiac hypertrophyrelated LncRNA-mRNA network, Song et al reported that LINC00702 was one of the ten hub nodes (64).…”

Section: Discussionmentioning

confidence: 99%

Transcriptome Sequencing Data Reveal LncRNA-miRNA-mRNA Regulatory Network in Calcified Aortic Valve Disease

Huang

Gao

et al. 2022

Front. Cardiovasc. Med.

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BackgroundCalcified aortic valve disease (CAVD) is one of the most common valvular heart diseases in the elderly population. However, no effective medical treatments have been found to interfere with the progression of CAVD, and specific molecular mechanisms of CAVD remain unclear.Materials and MethodsTranscriptome sequencing data of GSE55492 and GSE148219 were downloaded from the European Nucleotide Archive, and the microarray dataset, GSE12644 was acquired from the Gene Expression Omnibus database. Software, including FastQC, HISAT2, samtools, and featureCounts was applied to generate the read count matrix. The “Limma” package in R was utilized to analyze differentially expressed genes (DEGs). Thereafter, weighted gene co-expression network analysis, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, and the protein-protein interaction (PPI) network were used to identify hub genes associated with CAVD, which were further validated by receiver operating characteristic curve (ROC) analysis using GSE12644. The long non-coding RNA (LncRNA)-mediated regulatory network was established based on the differentially expressed LncRNAs and hub genes, which were detected using quantitative real-time PCR (qRT-PCR) in clinical samples and valve interstitial cells. Moreover, CIBERSORT was used to calculate the expression distribution of immune cell infiltration in CAVD.ResultsA total of 126 DEGs were included in the PPI network. PI3K-Akt signaling pathway, ECM-receptor interaction, hematopoietic cell lineage, cell adhesion molecules, and focal adhesion were the most enriched pathways revealed by KEGG. Four LncRNAs, including TRHDE-AS1, LINC00092, LINC01094, and LINC00702 were considered the differentially expressed LncRNA. SPP1, TREM1, GPM6A, CCL19, CR1, NCAM1, CNTN1, TLR8, SDC1, and COL6A6 were the 10 hub genes identified to be associated with CAVD. Moreover, the calcified aortic valve samples had a greater level of Tregs, naïve B cells, and M0 macrophages than the noncalcified ones, whereas CAVD samples had a lower M2 macrophage expression compared to the noncalcified valve tissues.ConclusionThe current study identified SPP1, TREM1, TLR8, SDC1, GPM6A, and CNTN1 as hub genes that could potentially be associated with CAVD. The LINC00702–miR-181b-5p–SPP1 axis might participate in the development of CAVD. Additionally, M2 macrophages, Tregs, naïve B cells, and M0 macrophages might possibly play a role in the initiation of CAVD.

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Section: Discussionmentioning

confidence: 99%

Transcriptome Sequencing Data Reveal LncRNA-miRNA-mRNA Regulatory Network in Calcified Aortic Valve Disease

Huang

Gao

et al. 2022

Front. Cardiovasc. Med.

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“…Clinical information was gathered, including TNM stage, pathological grade, age, gender, follow-up period, and survival status. In this study, 22 genes associated with cuproptosis were chosen for examination based on previously published studies [ 7 , 12 , 13 , 14 ].…”

Section: Methodsmentioning

confidence: 99%

Cuproptosis-Related lncRNA Gene Signature Establishes a Prognostic Model of Gastric Adenocarcinoma and Evaluate the Effect of Antineoplastic Drugs

Zhang

Xue

et al. 2022

Genes

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Background: One of the most frequent malignancies of the digestive system is stomach adenocarcinoma (STAD). Recent research has demonstrated how cuproptosis (copper-dependent cell death) differs from other cell death mechanisms that were previously understood. Cuproptosis regulation in tumor cells could be a brand-new treatment strategy. Our goal was to create a cuproptosis-related lncRNA signature. Additionally, in order to evaluate the possible immunotherapeutic advantages and drug sensitivity, we attempted to study the association between these lncRNAs and the tumor immune microenvironment of STAD tumors. Methods: The TCGA database was accessed to download the RNA sequencing data, genetic mutations, and clinical profiles for TCGA STAD. To locate lncRNAs related to cuproptosis and build risk-prognosis models, three techniques were used: co-expression network analysis, Cox-regression techniques, and LASSO techniques. Additionally, an integrated methodology was used to validate the models’ predictive capabilities. Then, using GO and KEGG analysis, we discovered the variations in biological functions between each group. The link between the risk score and various medications for STAD treatment was estimated using the tumor mutational load (TMB) and tumor immune dysfunction and rejection (TIDE) scores. Result: We gathered 22 genes linked to cuproptosis based on the prior literature. Six lncRNAs related to cuproptosis were used to create a prognostic marker (AC016394.2, AC023511.1, AC147067.2, AL590705.3, HAGLR, and LINC01094). After that, the patients were split into high-risk and low-risk groups. A statistically significant difference in overall survival between the two groups was visible in the survival curves. The risk score was demonstrated to be an independent factor affecting the prognosis by both univariate and multivariate Cox regression analysis. Different risk scores were substantially related to the various immunological states of STAD patients, as further evidenced by immune cell infiltration and ssGSEA analysis. The two groups had differing burdens of tumor mutations. In addition, immunotherapy was more effective for STAD patients in the high-risk group than in the low-risk group, and risk scores for STAD were substantially connected with medication sensitivity. Conclusions: We discovered a marker for six cuproptosis-associated lncRNAs linked to STAD as prognostic predictors, which may be useful biomarkers for risk stratification, evaluation of possible immunotherapy, and assessment of treatment sensitivity for STAD.

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“…Two studies with unclear basis of HR calculation and the reference group (even after mailing) were excluded in meta-analysis (15,16). The pooled examination of HRs with 95% CI of univariate survival results was performed based on the 11 studies, in which sample sizes were reported (17)(18)(19)(20)(21)(22)(23)(24)(25)(26)(27). Besides, according to the information of multivariate survival analysis, the pooled HRs with 95% CI was calculated.…”

Section: Discussionmentioning

confidence: 99%

“…Among studies with univariate survival analysis, 11 studies with reported sample size, HR (with clear basis of calculation), and CI were identified for meta-analysis (17)(18)(19)(20)(21)(22)(23)(24)(25)(26)(27). These studies included 70 lncRNAs (including unique and repeated lncRNAs).…”

Section: The Prognostic Significance Of Lncrnasmentioning

confidence: 99%

Competing endogenous RNA networks reveal long non-coding RNAs as potential prognostic biomarkers in gastric cancer: A systematic review and meta-analysis

Salehi-Mazandarani¹,

Donyavi

Vedaei

et al. 2023

Preprint

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Aims: Gastric cancer (GC) represents a global health-care challenge. In recent years, a large number of competing endogenous RNA (ceRNA) network studies have elucidated critical long non-coding RNAs (lncRNAs) as potential prognostic biomarkers in GC. Nevertheless, there is no systematic review and meta-analysis regarding them. Here, we propose a systematic review and meta-analysis for lncRNAs as prognostic biomarkers based on the ceRNA network studies in GC. Main methods: The Web of Science, Embase, PubMed, Scopus, ProQuest and Google Scholar databases were searched to collect eligible ceRNA network studies in which lncRNAs were reported as prognostic biomarkers until 27th June 2022. The pooled hazard ratios (HRs) were assessed to evaluate the prognostic effect of the lncRNAs. Prognostic values of highly reported lncRNAs were also examined. Furthermore, sensitivity analysis, and publication bias were evaluated. Key findings: Totally, 35 studies were included in the systematic review among which 13 studies were eligible for meta-analysis. Pooled examination of HRs based on the univariate and multivariate reports revealed that the expression changes of the lncRNAs correlate with overall survival (OS) of GC patients. Two lncRNAs including CCDC144NL-AS1 and LINC01094 were highly reported as potential prognostic biomarkers based on the ceRNA network studies. Prognostic value of these two lncRNAs was furthermore confirmed by meta-analysis. Significance: Our meta-analysis demonstrated potential application of lncRNAs introduced based on the ceRNA network studies as promising prognostic biomarkers in GC. Further functional studies are needed to elucidate the molecular mechanisms underlying these lncRNAs' functions in GC.

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Identification of lncRNA‐associated competing endogenous RNA networks for occurrence and prognosis of gastric carcinoma

Cited by 9 publications

References 61 publications

Transcriptome Sequencing Data Reveal LncRNA-miRNA-mRNA Regulatory Network in Calcified Aortic Valve Disease

Transcriptome Sequencing Data Reveal LncRNA-miRNA-mRNA Regulatory Network in Calcified Aortic Valve Disease

Cuproptosis-Related lncRNA Gene Signature Establishes a Prognostic Model of Gastric Adenocarcinoma and Evaluate the Effect of Antineoplastic Drugs

Competing endogenous RNA networks reveal long non-coding RNAs as potential prognostic biomarkers in gastric cancer: A systematic review and meta-analysis

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