TNFRSF12A and a new prognostic model identified from methylation combined with expression profiles to predict overall survival in hepatocellular carcinoma

Fang, Yu; Lin, Xinhua; Chen, La-Mei; Sun, Wenxue; Zhai, Yujia; Fan, Yu–Chen; Wang, Kai

doi:10.21037/tcr-20-1342

Cited by 4 publications

(5 citation statements)

References 37 publications

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“…In other studies, the preferential expression of the gamma-globin genes was regulated by NFE4, which is an indispensable component in the prognostic model of clear cell renal cell carcinoma [29,30]. LINC00989 was con rmed to be associated with the OS prognosis of patients with breast cancer and hepatocellular carcinoma [31,32]. These ndings suggest that cuproptosis might play biological roles in solid tumors other than AML.…”

Section: Discussionmentioning

confidence: 69%

Cuproptosis-related lncRNA signature for prognostic prediction in patients with acute myeloid leukemia

Zhu

et al. 2022

Preprint

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Background Long non-coding RNAs (lncRNAs) have been reported to have a crucial impact on the pathogenesis of acute myeloid leukemia (AML). Cuproptosis, a copper-triggered modality of mitochondrial cell death, might be a promising therapeutic target for cancer treatment. Nevertheless, the role of cuproptosis-related lncRNAs in AML remains unexplored. Methods AML RNA sequencing data and demographical characteristics were downloaded from The Cancer Genome Atlas (TCGA) database. Pearson correlation analysis, the least absolute shrinkage and selection operator (LASSO) regression algorithm, and univariable and multivariable Cox regression analyses were applied to identify the cuproptosis-related lncRNA signature and determine its feasibility it for AML prognosis prediction. The performance of the proposed signature was measured via Kaplan-Meier survival analysis, receiver operating characteristic (ROC) curves, and principal component analysis (PCA). Functional analysis was implemented to uncover the potential prognostic mechanisms. Moreover, quantitative real-time PCR (qRT-PCR) was used to validate the expression of the prognostic lncRNAs in clinical samples. Results A signature consisting of seven cuproptosis-related lncRNA (NFE4, LINC00989, LINC02062, AC006460.2, AL353796.1, PSMB8-AS1, and AC000120.1) was identified. Multivariable cox regression analysis revealed that the proposed lncRNA signature was an independent prognostic factor for AML, the nomogram based on this signature showed excellent accuracy in predicting 1-, 3-, and 5-year survival [Area Under Curve (AUC) = 0.846, 0.801, and 0.895, respectively]. Functional analysis suggested a significant association between the prognostic signature and the immune-related pathways. The expression pattern of the lncRNAs was validated in AML samples, which suggested the robustness of these findings. Conclusion In this study, we constructed a prediction model based on seven cuproptosis-related lncRNAs for AML prognosis. The obtained risk score may be connected with tumor immunity.

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Section: Discussionmentioning

confidence: 69%

Cuproptosis-related lncRNA signature for prognostic prediction in patients with acute myeloid leukemia

Zhu

et al. 2022

Preprint

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“…Moreover, the preferential expression of the gamma-globin genes was regulated by NFE4, which was an indispensable component in the prognostic model of clear-cell renal-cell carcinoma [39,40]. LINC00989 was confirmed to be associated with the OS prognosis of patients with breast cancer and hepatocellular carcinoma [41,42]. These findings suggest that these lncRNAs play biological roles in the pathogenesis of solid tumors, but their functional role in AML needs further investigation.…”

Section: Discussionmentioning

confidence: 88%

Cuproptosis-related lncRNA signature for prognostic prediction in patients with acute myeloid leukemia

Zhu

et al. 2023

BMC Bioinformatics

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Background Long non-coding RNAs (lncRNAs) have been reported to have a crucial impact on the pathogenesis of acute myeloid leukemia (AML). Cuproptosis, a copper-triggered modality of mitochondrial cell death, might serve as a promising therapeutic target for cancer treatment and clinical outcome prediction. Nevertheless, the role of cuproptosis-related lncRNAs in AML is not fully understood. Methods The RNA sequencing data and demographic characteristics of AML patients were downloaded from The Cancer Genome Atlas database. Pearson correlation analysis, the least absolute shrinkage and selection operator algorithm, and univariable and multivariable Cox regression analyses were applied to identify the cuproptosis-related lncRNA signature and determine its feasibility for AML prognosis prediction. The performance of the proposed signature was evaluated via Kaplan–Meier survival analysis, receiver operating characteristic curves, and principal component analysis. Functional analysis was implemented to uncover the potential prognostic mechanisms. Additionally, quantitative real-time PCR (qRT-PCR) was employed to validate the expression of the prognostic lncRNAs in AML samples. Results A signature consisting of seven cuproptosis-related lncRNAs (namely NFE4, LINC00989, LINC02062, AC006460.2, AL353796.1, PSMB8-AS1, and AC000120.1) was proposed. Multivariable cox regression analysis revealed that the proposed signature was an independent prognostic factor for AML. Notably, the nomogram based on this signature showed excellent accuracy in predicting the 1-, 3-, and 5-year survival (area under curve = 0.846, 0.801, and 0.895, respectively). Functional analysis results suggested the existence of a significant association between the prognostic signature and immune-related pathways. The expression pattern of the lncRNAs was validated in AML samples. Conclusion Collectively, we constructed a prediction model based on seven cuproptosis-related lncRNAs for AML prognosis. The obtained risk score may reveal the immunotherapy response in patients with this disease.

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“…[33] TNFRSF12A is the smallest of TNF superfamily individuals, contains a short cytoplasmic death domain structure. [34] TNFRSF12A participation to stimulate multiple signal transduction pathways, including nuclear factor kB pathway and predominate in increasing angiogenesis. Studies have shown that QPCT, SCEL and TNFRSF12A have diagnostic value in papillary thyroid carcinoma.…”

Section: Discussionmentioning

confidence: 99%

Il1r2 and Tnfrsf12a in transcranial magnetic stimulation effect of ischemic stroke via bioinformatics analysis

Zhao,

Liu,

et al. 2024

Medicine

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Ischemic stroke refers to ischemic necrosis or softening of localized brain tissue. Transcranial magnetic stimulation (TMS) is a painless, noninvasive and green treatment method, which acts on the central nervous system through a pulsed magnetic field to assist in the treatment of central nervous system injury diseases. However, the role of Il1r2 and Tnfrsf12a in this is unknown. The ischemic stroke datasets GSE81302 and TMS datasets GSE230148 were downloaded from Gene Expression Omnibus database. Differentially expressed genes (DEGs) were screened and weighted gene co-expression network analysis (WGCNA) was performed. The construction and analysis of protein-protein interaction (PPI) network and functional enrichment analysis were performed. Draw heat map gene expression. Through the Comparative Toxicogenomics Database (CTD) to find the most relevant and core gene diseases. TargetScan was used to screen miRNAs regulating DEGs. A total of 39 DEGs were identified. According to gene ontology (GO) analysis results, in biological process (BP) analysis, they were mainly enriched in the positive regulation of apoptosis process, inflammatory response, positive regulation of p38MAPK cascade, and regulation of cell cycle. In cellular component (CC) analysis, they were mainly enriched in the cell surface, cytoplasm, and extracellular space. In Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, they were mainly enriched in nf-κB signaling pathway, fluid shear stress and atherosclerosis, P53 signaling pathway, TNF signaling pathway, and apoptosis. Among the enrichment items of metascape, negative regulation of T cell activation, hematopoietic cell lineage, positive regulation of apoptotic process, fluid shear stress and atherosclerosis were observed in GO enrichment items. Five core genes (Socs3, Irf1, Il1r2, Ccr1, and Tnfrsf12a) were obtained, which were highly expressed in ischemic stroke samples. Il1r2 and Tnfrsf12a were lowly expressed in TMS samples. CTD analysis found that the core gene (Socs3, Irf1 and Il1r2, Ccr1, Tnfrsf12a) and ischemic stroke, atherosclerosis, hypertension, hyperlipidemia, thrombosis, stroke, myocardial ischemia, myocardial infarction, and inflammation. Il1r2 and Tnfrsf12a are highly expressed in ischemic stroke, but lowly expressed in TMS samples.

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TNFRSF12A and a new prognostic model identified from methylation combined with expression profiles to predict overall survival in hepatocellular carcinoma

Cited by 4 publications

References 37 publications

Cuproptosis-related lncRNA signature for prognostic prediction in patients with acute myeloid leukemia

Cuproptosis-related lncRNA signature for prognostic prediction in patients with acute myeloid leukemia

Cuproptosis-related lncRNA signature for prognostic prediction in patients with acute myeloid leukemia

Il1r2 and Tnfrsf12a in transcranial magnetic stimulation effect of ischemic stroke via bioinformatics analysis

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