Overexpression of SlC7A11: A Novel Oncogene and an Indicator of Unfavorable Prognosis for Liver Carcinoma

Zeng, Liang; Huang, Yi; Ling, Junjun; Wu, Zhuo; Zhen, Yu; Luo, Yunbo; Zhu, Yi

doi:10.2217/fon-2017-0540

Cited by 55 publications

(33 citation statements)

References 29 publications

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“…e results of our GO and KEGG analyses also suggested that the 6 mRNAs were mainly enriched in cell cycle pathways, including the cell cycle, regulation of the cell cycle, and cell cycle processes. CEP55, EZH2, and SLCA11 are highly expressed in HCC and play critical regulatory roles in cancers [21][22][23]. ey were key nodes that made up the stage I HCC ceRNA network in our study and were key potential prognostic genes in stage I HCC, results that are consistent with a Gene Expression Omnibus (GEO) database study by Yue et al [24].…”

Section: Discussionsupporting

confidence: 89%

Construction and Comprehensive Analyses of a Competing Endogenous RNA Network in Tumor-Node-Metastasis Stage I Hepatocellular Carcinoma

Sha

et al. 2020

BioMed Research International

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Background. Long noncoding RNAs (lncRNAs) can function as competing endogenous RNAs (ceRNAs) and interact with microRNAs (miRNAs) to regulate target gene expression, which can greatly influence tumor development and progression. Different tumor-node-metastasis (TNM) stages of hepatocellular carcinoma (HCC) defined by the American Joint Committee on Cancer (AJCC) have different clinical results. Our purpose was to comprehensively analyze differentially expressed (DE) lncRNAs, miRNAs, and mRNAs in stage I HCC and identify prognosis-associated RNAs. Methods. RNA-seq data were obtained from The Cancer Genome Atlas (TCGA) database. A stage I HCC-associated miRNA-lncRNA-mRNA network was constructed. Next, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment pathway analyses of ceRNA-associated DEmRNAs were performed using Database for Annotation, Visualization, and Integrated Discovery (DAVID) 6.8 and Clusterprofile in the R package. The protein-protein interaction (PPI) network of the above mRNAs was then constructed using STRING. Finally, the association between lncRNAs and mRNAs in the ceRNA network and prognosis of patients was further analyzed. Linear regression analysis of the above lncRNAs and mRNAs associated with overall survival was performed. Results. After a comparison between HCC and adjacent nontumor tissues, 778 lncRNAs, 1608 mRNAs, and 102 miRNAs that were abnormally expressed were identified. The ceRNA network was composed of 56 DElncRNAs, 14 DEmiRNAs, and 30 DEmRNAs. Functional analysis results showed that 30 DEmRNAs were enriched in 14 GO biological process categories and 6 KEGG categories (false discovery rate (FDR) < 0.05). A PPI network was composed of 22 nodes and 58 edges. We detected 4 DElncRNAs (BPESC1, AC061975.6, AC079341.1, and CLLU1) and 6 DEmRNAs (CEP55, E2F1, E2F7, EZH2, G6PD, and SLC7A11) that had significant influences on the overall survival (OS) of stage I HCC patients (P<0.05). lncRNA BPESC1 was positively correlated with mRNA CEP55 via miR-424, and lncRNA AC061975.6 was positively correlated with mRNA E2F1 via miR-519d. Conclusion. Our study identified novel lncRNAs and mRNAs that were associated with the progression and prognosis of stage I HCC and further investigated the regulatory mechanism of lncRNA-mediated ceRNAs in the development of stage I HCC.

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Section: Discussionsupporting

confidence: 89%

Construction and Comprehensive Analyses of a Competing Endogenous RNA Network in Tumor-Node-Metastasis Stage I Hepatocellular Carcinoma

Sha

et al. 2020

BioMed Research International

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“…We conducted qRT-PCR experiments on 20 pairs of HCC-and adjacent liver-tissue samples, and the result showed that expression levels of the 13 key potential prognostic genes were consistent with the result of our previous analysis. Among these key potential prognostic genes, CCNB1 ,20 CEP55 ,21 CHEK1 ,22 EZH2 ,23 KPNA2 ,24 LRRC1 ,25 PBK ,26 RRM2 ,27 SLC7A11 ,28 and ZWINT 29 have been validated as oncogenes in HCC according to previous studies. Interestingly, no studies have reported a relationship between SUCO gene expression and tumorigenesis, and we are planning to conduct experiments to explore the role of SUCO in the development and progression of HCC.…”

Section: Discussionmentioning

confidence: 99%

Comprehensive analysis of potential prognostic genes for the construction of a competing endogenous RNA regulatory network in hepatocellular carcinoma

Yue¹,

Ren²,

Ge³

et al. 2019

OTT

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Background: Hepatocellular carcinoma (HCC) is an extremely common malignant tumor with worldwide prevalence. The aim of this study was to identify potential prognostic genes and construct a competing endogenous RNA (ceRNA) regulatory network to explore the mechanisms underlying the development of HCC. Methods: Integrated analysis was used to identify potential prognostic genes in HCC with R software based on the GSE14520, GSE17548, GSE19665, GSE29721, GSE60502, and the Cancer Genome Atlas databases. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway-enrichment analyses were performed to explore the molecular mechanisms of potential prognostic genes. Differentially expressed miRNAs (DEMs) and lncRNAs (DELs) were screened based on the Cancer Genome Atlas database. An lncRNA-miRNA-mRNA ceRNA regulatory network was constructed based on information about interactions derived from the miRcode, TargetScan, miRTarBase, and miRDB databases. Results: A total of 152 potential prognostic genes were screened that were differentially expressed in HCC tissue and significantly associated with overall survival of HCC patients. There were 13 key potential prognostic genes in the ceRNA regulatory network: eleven upregulated genes (CCNB1,

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“…SLC7A11 is the functional light chain subunit of the cystine/glutamate antiporter system x c and confers specificity for cystine uptake, a major rate-limiting factor in glutathione biosynthesis (19). SLC7A11 is overexpressed in several cancer types, including glioma, liver carcinoma, non-small cell lung cancer, and triple-negative breast cancer, and serves as an independent prognostic factor (20)(21)(22)(23)(24). SLC7A11 also contributes to glutathione-based drug resistance (25)(26)(27).…”

Section: Introductionmentioning

confidence: 99%

Suppression of the SLC7A11/glutathione axis causes synthetic lethality in KRAS-mutant lung adenocarcinoma

et al. 2020

Journal of Clinical Investigation

234

196

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Overexpression of SlC7A11: A Novel Oncogene and an Indicator of Unfavorable Prognosis for Liver Carcinoma

Abstract: SLC7A11 overexpression might be a novel biomarker and a potential unfavorable prognostic factor as well as a potential therapeutic target for liver carcinoma.

Cited by 55 publications

References 29 publications

Construction and Comprehensive Analyses of a Competing Endogenous RNA Network in Tumor-Node-Metastasis Stage I Hepatocellular Carcinoma

Construction and Comprehensive Analyses of a Competing Endogenous RNA Network in Tumor-Node-Metastasis Stage I Hepatocellular Carcinoma

Comprehensive analysis of potential prognostic genes for the construction of a competing endogenous RNA regulatory network in hepatocellular carcinoma

Suppression of the SLC7A11/glutathione axis causes synthetic lethality in KRAS-mutant lung adenocarcinoma

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