&lt;p&gt;IFI30 Is a Novel Immune-Related Target with Predicting Value of Prognosis and Treatment Response in Glioblastoma&lt;/p&gt;

Zhu, Chen; Chen, Xin; Guan, Gefei; Zou, Cunyi; Guo, Qing; Peng, Cheng; Cheng, Wen; Wu, Anhua

doi:10.2147/ott.s237162

Cited by 28 publications

(28 citation statements)

References 42 publications

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“…Among them, DCBLD2 [ 26 ], FNDC3B [ 27 ], PLP2 [ 28 ], SERPINH1 [ 29 , 30 ], STEAP1 [ 31 , 32 ], and TNFRSF1A [ 33 ] were found to be abnormally expressed in a series of human tumors. IFI30 is the most stable prognostic gene among interferon-stimulated genes in glioma[ 34 ]. CFI is a potential therapeutic target for nonmelanoma skin cancer[ 35 ].…”

Section: Discussionmentioning

confidence: 99%

Construction of a competitive endogenous RNA network and analysis of potential regulatory axis targets in glioblastoma

Yang

et al. 2021

Cancer Cell Int

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Background Glioblastoma is the most common primary malignant brain tumor. Because of the limited understanding of its pathogenesis, the prognosis of glioblastoma remains poor. This study was conducted to explore potential competing endogenous RNA (ceRNA) network chains and biomarkers in glioblastoma by performing integrated bioinformatics analysis. Methods Transcriptome expression data from The Cancer Genome Atlas database and Gene Expression Omnibus were analyzed to identify differentially expressed genes between glioblastoma and normal tissues. Biological pathways potentially associated with the differentially expressed genes were explored by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis, and a protein-protein interaction network was established using the STRING database and Cytoscape. Survival analysis using Gene Expression Profiling Interactive Analysis was based on the Kaplan–Meier curve method. A ceRNA network chain was established using the intersection method to align data from four databases (miRTarBase, miRcode, TargetScan, and lncBace2.0), and expression differences and correlations were verified by quantitative reverse-transcription polymerase chain reaction analysis and by determining the Pearson correlation coefficient. Additionally, an MTS assay and the wound-healing and transwell assays were performed to evaluate the effects of complement C1s (C1S) on the viability and migration and invasion abilities of glioblastoma cells, respectively. Results We detected 2842 differentially expressed (DE) mRNAs, 2577 DE long non-coding RNAs (lncRNAs), and 309 DE microRNAs (miRNAs) that were dysregulated in glioblastoma. The final ceRNA network consisted of six specific lncRNAs, four miRNAs, and four mRNAs. Among them, four DE mRNAs and one DE lncRNA were correlated with overall survival (p < 0.05). C1S was significantly correlated with overall survival (p= 0.015). In functional assays, knockdown of C1S inhibited the proliferation and invasion of glioblastoma cell lines. Conclusions We established four ceRNA networks that may influence the occurrence and development of glioblastoma. Among them, the MIR155HG/has-miR-129-5p/C1S axis is a potential marker and therapeutic target for glioblastoma. Knockdown of C1S inhibited the proliferation, migration, and invasion of glioblastoma cells. These findings clarify the role of the ceRNA regulatory network in glioblastoma and provide a foundation for further research.

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Section: Discussionmentioning

confidence: 99%

Construction of a competitive endogenous RNA network and analysis of potential regulatory axis targets in glioblastoma

Yang

et al. 2021

Cancer Cell Int

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“…It plays a significant role in regulating the transport of cholesterol through the late endosomal/lysosomal system in the past researches (Lauber et al, 2018;Liu et al, 2020). Its predicting value of prognosis and treatment response in glioblastoma as a novel immune-related target was also verified (Zhu et al, 2020).…”

Section: Discussionmentioning

confidence: 95%

“…After searching in Pubmed, we found that the expression and function of LSP1 ( Park et al, 2014 ), LY96 ( Rajaraman et al, 2009 ), IFI30 ( Liu et al, 2020 ; Zhu et al, 2020 ), and ARPC1B ( Lauber et al, 2018 ) in GBM has been reported, and research about NPC2 in GBM are remain rescue. Hence, we focus on investing the clinical prognostic significance of the NPC2 genes in GBM.…”

Section: Resultsmentioning

confidence: 99%

“…Eight DEGs were identified to be the potential protective prognostic marker of GBM while patients with a higher expression of these eight common DEGs showed shorter survival rate ( Figures 3 , 4 ). After searching in Pubmed, we found out that the expression and function of LSP1 ( Park et al, 2014 ), LY96 ( Rajaraman et al, 2009 ), IFI30 ( Liu et al, 2020 ; Zhu et al, 2020 ), and ARPC1B ( Lauber et al, 2018 ) in GBM has been reported, while research about NPC2 in GBM remain rescue. Gao et al identified LSP1 as an independent predictive factor for progressive malignancy in glioma ( Cao et al, 2020a ).…”

Section: Discussionmentioning

confidence: 99%

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NPC2 as a Prognostic Biomarker for Glioblastoma Based on Integrated Bioinformatics Analysis and Cytological Experiments

Shen

Lin

et al. 2021

Front. Genet.

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Glioblastoma (GBM) is one of the most common and fatal malignancies worldwide, while its prognostic biomarkers are still being explored. This study aims to identify potential genes with clinical and prognostic significance by integrating bioinformatics analysis and investigating their function in HNSCC. Based on the Single-cell RNA sequencing (scRNA-seq) results of H3K27M-glioma cells, computational bioinformatics methods were employed for selecting prognostic biomarker for GBM. The protein NPC2 (NPC Intracellular Cholesterol Transporter 2), which has been shown to be related to lipoprotein metabolism and innate immune system, was identified to be upregulated in GBM. NPC2 showed a relatively higher expression in GBM samples, and a negative correlation with tumor purity and tumor infiltrating immune cells. Additionally, NPC2 was knocked down in U87-MG and U251 cells line, and cell proliferation and migration capability were evaluated with CCK-8, scratch and transwell assay, respectively. Cytological experiments has shown that NPC2 overexpression inhibited GBM cells proliferation and migration, indicating its important role in GBM progression. This is the first investigation into the prognostic value of NPC2 interact with GBM. The potential molecular factor NPC2 have been identified as a prognostic biomarker for GBM.

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“…IFI30 is highly expressed in glioma and associated with chemotherapy response ( Zhu et al, 2020 ). Our analysis showed that IFI30 were specifically upregulated and this high expression predicted high RFS and OS ( p < 0.05) in Her2-subtype breast cancer, while high IFI30 expression predicted low RFS and OS ( p < 0.05) in all breast cancer.…”

Section: Discussionmentioning

confidence: 99%

Screening and Identification of Key Common and Specific Genes and Their Prognostic Roles in Different Molecular Subtypes of Breast Cancer

Sun

Gao

et al. 2021

Front. Mol. Biosci.

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Breast cancer is one of the most common cancers. Although the present molecular classification improves the treatment effect and prognosis of breast cancer, the heterogeneity of the molecular subtype remains very complex, and the applicability and effectiveness of treatment methods are still limited leading to poorer patient prognosis than expected. Further identification of more refined molecular typing based on gene expression profile will yield better understanding of the heterogeneity, improving treatment effects and prolonging prognosis of patients. Here, we downloaded the mRNA expression profiles and corresponding clinical data of patients with breast cancer from public databases and performed typical molecular typing using PAM50 (Prediction Analysis of Microarray 50) method. Comparative analyses were performed to screen the common and specific differentially expressed genes (DEGs) between cancer and corresponding para-cancerous tissues in each breast cancer subtype. The GO and KEGG analyses of the DEGs were performed to enrich the common and specific functional progress and signaling pathway involved in breast cancer subtypes. A total of 38 key common and specific DEGs were identified and selected based on the validated results, GO/KEGG enrichments, and the priority of expression, including four common DEGs and 34 specific DEGs in different subtypes. The prognostic value of these key common and specific DEGs was further analyzed to obtain useful potential markers in clinic. Finally, the potential roles and the specific prognostic values of the common and specific DEGs were speculated and summarized in total breast cancer and different subtype breast cancer based on the results of these analyses. The findings of our study provide the basis of more refined molecular typing of breast cancer, potential new therapeutic targets and prognostic markers for different breast cancer subtypes

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<p>IFI30 Is a Novel Immune-Related Target with Predicting Value of Prognosis and Treatment Response in Glioblastoma</p>

Cited by 28 publications

References 42 publications

Construction of a competitive endogenous RNA network and analysis of potential regulatory axis targets in glioblastoma

Construction of a competitive endogenous RNA network and analysis of potential regulatory axis targets in glioblastoma

NPC2 as a Prognostic Biomarker for Glioblastoma Based on Integrated Bioinformatics Analysis and Cytological Experiments

Screening and Identification of Key Common and Specific Genes and Their Prognostic Roles in Different Molecular Subtypes of Breast Cancer

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