Role of alternative splicing signatures in the prognosis of glioblastoma

Xie, Zucheng; Wu, Huayu; Dang, Yi‐Wu; Chen, Gang

doi:10.1002/cam4.2666

Cited by 27 publications

(22 citation statements)

References 76 publications

(160 reference statements)

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“…Thereafter, we uncovered FBXL19 as the downstream target of miR-532-3p in glioma. Importantly, Xie et al [ 31 ] recognized FBXL19 as one of the core genes in glioblastoma. Our study found that FBXL19 was up-regulated in glioma cells, and down-regulating FBXL19 could restrict the growth and stemness of glioma cells.…”

Section: Resultsmentioning

confidence: 99%

ETS1-activated SNHG10 exerts oncogenic functions in glioma via targeting miR-532-3p/FBXL19 axis

et al. 2020

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Background In past few years, long non-coding RNAs (lncRNAs) have been reported to play regulatory roles during cancer progression. LncRNA SNHG10 has been explored in several sorts of cancers. However, its detailed role and mechanism are still not well understood in glioma. Methods Expression levels of genes were evaluated by RT-qPCR. EdU, TUNEL, sphere formation, wound healing and transwell assays appraised the effect of SNHG10 on glioma cellular processes. The interaction between molecules was examined by ChIP, RIP, RNA pull down and luciferase reporter assays. Results High level of SNHG10 was detected in glioma cells. Functional assay confirmed that SNHG10 promoted the proliferation, migration, invasion and stemness of glioma cells. Moreover, miR-532-3p was validated to bind with SNHG10 and expressed at a low level in glioma cells. Importantly, miR-532-3p exerted inhibitory functions in glioma. Furthermore, it was found that FBXL19 targeted by miR-532-3p facilitated cell growth and stemness in glioma, and that SNHG10 worked in glioma by increasing FBXL19 expression through sequestering miR-532-3p. More importantly, ETS1 promoted the transcription of SNHG10 and it mediated contribution to the malignant behaviors of glioma cells by SNHG10/miR-532-3p/FBXL19 signaling. Conclusion SNHG10 was transcriptionally activated by ETS1 and played an oncogenic role in glioma by sponging miR-532-3p and up-regulating FBXL19.

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Section: Resultsmentioning

confidence: 99%

ETS1-activated SNHG10 exerts oncogenic functions in glioma via targeting miR-532-3p/FBXL19 axis

et al. 2020

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“…The present study used bioinformatics techniques to identify survival-associated AS events in order to construct splicing signatures for the prediction of prognosis, orchestrate SF-AS networks and assess their potential underlying molecular mechanism. Previously, SpliceSeq analyses have been adopted to establish AS profiling and construct prognostic models in glioma; several potential AS events were identified in pan-glioma and GBM cohorts, including adenine DNA glycosylase, metalloreductase STEAP3, SUMO-conjugating enzyme UBC9, von Hippel-Lindau disease tumor suppressor, BTB/POZ domain-containing protein KCTD7, protein S100-A4, endothelin-converting enzyme 2 and lymphocyte antigen 6K (29)(30)(31). Additionally, several prognostic models based on AS events have been constructed for prognosis prediction, which may complement the molecular classification, further identify potential glioma subgroups and highlight SFs as an important mechanism of splicing regulation in the carcinogenesis and aggressiveness of GBM (9,31-33).…”

Section: Discussionmentioning

confidence: 99%

Transcriptome analysis and prognostic model construction based on splicing profiling in glioblastoma

Qiu

Wang

et al. 2020

Oncol Lett

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Glioblastoma (GBM) is the most aggressive malignant brain tumour, with high morbidity and mortality rates. Currently, there is a lack of systematic and comprehensive analysis on the prognostic significance of alternative splicing (AS) profiling for GBM. The GBM data, including RNA-sequencing, corresponding clinical information and the expression levels of splicing factor genes, were downloaded from The Cancer Genome Atlas and the SpliceAid2 database. The prognostic models were assessed by the least absolute shrinkage and selection operator Cox regression analysis. The correlation network between survival-associated AS events and splicing factors was plotted. Prognostic models were built for every AS event type and performed well for risk stratification in patients with GBM. The final prognostic signature served as an independent prognostic factor [hazard ratio (HR), 4.61; 95% confidence interval (CI), 2.97–7.16; P=9.66×10 −12 ] for several clinical parameters, including age, sex, isocitrate dehydrogenase mutation, O 6 -methylguanine-DNA methyltransferase promoter methylation and risk score. The HR for risk score with GBM was 1.0063 (95% CI, 1.0024–1.0103). The splicing regulatory network indicated that heat shock protein b-1, protein arginine N-methyltransferase 5, protein FAM50B and endoplasmic reticulum chaperone BiP genes were independent prognostic factors for GBM. The results of the present study support the ongoing effort in developing novel genomic models and providing potentially more effective treatment options for patients with GBM.

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“…Genome-wide transcriptome analysis in GBM has revealed the presence of aberrant AS events in tumors that generate tumorspecific isoforms having enhanced oncogenic activities as compared to normal brain. Such isoforms are also involved in therapy resistance [17][18][19][20]. For example, splicing profiles of glioma subtypes proneural (PN) and mesenchymal (MES) glioma stem cell (GSC) lines have shown significant differences in the genes implicated in the hallmark characteristics of cancer, contributing to PN-MES transition and subsequent tumor heterogeneity and resistance [21].…”

Section: Introductionmentioning

confidence: 99%

The Many Facets of Therapy Resistance and Tumor Recurrence in Glioblastoma

Goenka

Tiek

Song

et al. 2021

Cells

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Glioblastoma (GBM) is the most lethal type of primary brain cancer. Standard care using chemo- and radio-therapy modestly increases the overall survival of patients; however, recurrence is inevitable, due to treatment resistance and lack of response to targeted therapies. GBM therapy resistance has been attributed to several extrinsic and intrinsic factors which affect the dynamics of tumor evolution and physiology thus creating clinical challenges. Tumor-intrinsic factors such as tumor heterogeneity, hypermutation, altered metabolomics and oncologically activated alternative splicing pathways change the tumor landscape to facilitate therapy failure and tumor progression. Moreover, tumor-extrinsic factors such as hypoxia and an immune-suppressive tumor microenvironment (TME) are the chief causes of immunotherapy failure in GBM. Amid the success of immunotherapy in other cancers, GBM has occurred as a model of resistance, thus focusing current efforts on not only alleviating the immunotolerance but also evading the escape mechanisms of tumor cells to therapy, caused by inter- and intra-tumoral heterogeneity. Here we review the various mechanisms of therapy resistance in GBM, caused by the continuously evolving tumor dynamics as well as the complex TME, which cumulatively contribute to GBM malignancy and therapy failure; in an attempt to understand and identify effective therapies for recurrent GBM.

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Role of alternative splicing signatures in the prognosis of glioblastoma

Cited by 27 publications

References 76 publications

ETS1-activated SNHG10 exerts oncogenic functions in glioma via targeting miR-532-3p/FBXL19 axis

ETS1-activated SNHG10 exerts oncogenic functions in glioma via targeting miR-532-3p/FBXL19 axis

Transcriptome analysis and prognostic model construction based on splicing profiling in glioblastoma

The Many Facets of Therapy Resistance and Tumor Recurrence in Glioblastoma

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