LncRNA as potential biomarker and therapeutic target in glioma

Xu, Xun; Liang, Yuan; Gareev, Ilgiz; Liang, Yanchao; Li, Rui; Wang, Ning; Yang, Guang

doi:10.1007/s11033-022-08056-y

Cited by 12 publications

(4 citation statements)

References 99 publications

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“…The ideal biomarker should be highly sensitive and specific, and the heterogeneity of gliomas makes it challenging to identify useful common biomarkers (Tamai et al., 2023). Specific lncRNAs are abnormally expressed in the cerebrospinal fluid, peripheral circulation, and brain tissue of glioma patients as biomarkers (Xu et al., 2023). We obtained a combination of nine glioma prognostic genes based on the parthanatos gene, including CD58, H19, TNFAIP6, FTLP3, TNFRSF11B, SFRP2, LOXL1, COL8A1, and FABP5P7.…”

Section: Discussionmentioning

confidence: 99%

Molecular prognostic of nine parthanatos death‐related genes in glioma, particularly in COL8A1 identification

Fan,

Li,

Liu

2024

Journal of Neurochemistry

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Post‐operative progression and chemotherapy resistance are the main causes of treatment failure in glioma patients. There is a lack of ideal prediction models for post‐operative glioma patient progression and drug sensitivity. We aimed to develop a prognostic model of parthanatos mRNA biomarkers for glioma outcomes. A total of 11 parthanatos genes were obtained from ParthanatosCluster database. ConsensusClusterPlus and R “Limma” package were used to cluster The Cancer Genome Atlas (TCGA)‐glioma cohort and analyze the differential mRNAs. Univariate Cox regression analysis, random survival forest model, and least absolute shrinkage and selection operator (LASSO) regression analysis were used to determine the nine ParthanatosScore prognostic genes combination. ParthanatosScore was verified by 656 patients and 979 patients in TCGA and CGCA‐LGG/GBM datasets. Differences in genomic mutations, tumor microenvironments, and functional pathways were assessed. Drug response prediction was performed using pRRophetic. Kaplan–Meier survival analysis was analyzed. Finally, COL8A1 was selected to evaluate its potential biological function and drug sensitivity of temozolomide and AZD3759 in glioma cells. ParthanatosScore obtained a combination of nine glioma prognostic genes, including CD58, H19, TNFAIP6, FTLP3, TNFRSF11B, SFRP2, LOXL1, COL8A1, and FABP5P7. In the TCGA‐LGG/GBM dataset, glioma prognosis was poor in high ParthanatosScore. Low‐score glioma patients were sensitive to AZD3759_1915, AZD5582_1617, AZD8186_1918, Dasatinib_1079, and Temozolomide_1375, while high‐score patients were less sensitive to these drugs. Compared with HA cells, COL8A1 was significantly over‐expressed in LN229 and U251 cells. Silencing COL8A1 inhibited the malignant characterization of LN229 and U251 cells. Temozolomide and AZD3759 also promoted parthanatos gene expression in glioma cells. Temozolomide and AZD3759 inhibited COL8A1 expression and cell viability and promoted apoptosis in glioma cells and PGM cells. ParthanatosScore can accurately predict clinical prognosis and drug sensitivity after glioma surgery. Silencing COL8A1 inhibited the malignant characterization. Temozolomide and AZD3759 inhibited COL8A1 expression and cell viability and promoted apoptosis and parthanatos gene expression, which is a target to improve glioma.

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Section: Discussionmentioning

confidence: 99%

Molecular prognostic of nine parthanatos death‐related genes in glioma, particularly in COL8A1 identification

Fan,

Li,

Liu

2024

Journal of Neurochemistry

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“…Frontiers in Physiology frontiersin.org et al, Xu et al, 2022). The high expression of lncRNA ZNFX1 antisense RNA 1 (ZFAS1) in gastric cardia adenocarcinoma (GCA) assists EPAS1 to enhance the epigenetic silencing of HIF-1α and promote the proliferation and metastasis of cancer cells (Zhu et al, 2020).…”

Section: Regulation Of Oxygen Adaptive Metabolism By Ncrnasmentioning

confidence: 99%

Investigations into the impact of non-coding RNA on the sensitivity of gastric cancer to radiotherapy

Usman

Beilerli²,

Sufianov³

et al. 2023

Front. Physiol.

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Non-coding RNAs (ncRNAs) are a newly discovered functional RNA different from messenger RNA, which can participate in regulating the occurrence and development of tumors. More and more research results show that ncRNAs can participate in the regulation of gastric cancer (GC) radiotherapy response, and its mechanism may be related to its effect on DNA damage repair, gastric cancer cell stemness, cell apoptosis, activation of epidermal growth factor receptor signaling pathway, etc. This article summarizes the relevant mechanisms of ncRNAs regulating the response to radiotherapy in gastric cancer, which will be directly important for the introduction of ncRNAs particularly microRNAs (miRNAs), long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs) into clinical medicine as biomarkers and therapeutic targets.

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“…A number of studies have examined the expression and function of lncRNAs in various diseases based on co-expression analyses ( Liu et al, 2022 ; Wen et al, 2022 ). Although there is no commercial assay based on lncRNAs in TB diagnosis, many researches have confirmed that the abnormal expression of lncRNAs are associated with TB occurrence, development and prognosis, and have the potentials as diagnostic, prognostic biomarkers and therapeutic targets in TB ( Chen et al, 2017 ; Zhang et al, 2022 ; Xu et al, 2023 ). However, the expression patterns and pathogenesis of host lncRNAs in TB patients have not yet been fully elucidated, and mechanistic details regarding the regulatory network involving lncRNAs in TB remain unclear ( Chen et al, 2017 ; Agliano et al, 2019 ; Liang et al, 2022 ).…”

Section: Introductionmentioning

confidence: 99%

Identification of important modules and biomarkers in tuberculosis based on WGCNA

Dong,

Song,

Shang

et al. 2024

Front. Microbiol.

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BackgroundTuberculosis (TB) is a significant public health concern, particularly in China. Long noncoding RNAs (lncRNAs) can provide abundant pathological information regarding etiology and could include candidate biomarkers for diagnosis of TB. However, data regarding lncRNA expression profiles and specific lncRNAs associated with TB are limited.MethodsWe performed ceRNA-microarray analysis to determine the expression profile of lncRNAs in peripheral blood mononuclear cells (PBMCs). Weighted gene co-expression network analysis (WGCNA) was then conducted to identify the critical module and genes associated with TB. Other bioinformatics analyses, including Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology (GO), and co-expression networks, were conducted to explore the function of the critical module. Finally, real-time quantitative polymerase chain reaction (qPCR) was used to validate the candidate biomarkers, and receiver operating characteristic analysis was used to assess the diagnostic performance of the candidate biomarkers.ResultsBased on 8 TB patients and 9 healthy controls (HCs), a total of 1,372 differentially expressed lncRNAs were identified, including 738 upregulated lncRNAs and 634 downregulated lncRNAs. Among all lncRNAs and mRNAs in the microarray, the top 25% lncRNAs (3729) and top 25% mRNAs (2824), which exhibited higher median expression values, were incorporated into the WGCNA. The analysis generated 16 co-expression modules, among which the blue module was highly correlated with TB. GO and KEGG analyses showed that the blue module was significantly enriched in infection and immunity. Subsequently, considering module membership values (>0.85), gene significance values (>0.90) and fold-change value (>2 or < 0.5) as selection criteria, the top 10 upregulated lncRNAs and top 10 downregulated lncRNAs in the blue module were considered as potential biomarkers. The candidates were then validated in an independent validation sample set (31 TB patients and 32 HCs). The expression levels of 8 candidates differed significantly between TB patients and HCs. The lncRNAs ABHD17B (area under the curve [AUC] = 1.000) and ENST00000607464.1 (AUC = 1.000) were the best lncRNAs in distinguishing TB patients from HCs.ConclusionThis study characterized the lncRNA profiles of TB patients and identified a significant module associated with TB as well as novel potential biomarkers for TB diagnosis.

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LncRNA as potential biomarker and therapeutic target in glioma

Cited by 12 publications

References 99 publications

Molecular prognostic of nine parthanatos death‐related genes in glioma, particularly in COL8A1 identification

Molecular prognostic of nine parthanatos death‐related genes in glioma, particularly in COL8A1 identification

Investigations into the impact of non-coding RNA on the sensitivity of gastric cancer to radiotherapy

Identification of important modules and biomarkers in tuberculosis based on WGCNA

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