Identification and validation of RNA‐binding protein‐related gene signature revealed potential associations with immunosuppression and drug sensitivity in glioma

Chen, Zhuohui; Wu, Hong; Yang, Haojun; Fan, Yishu; Zhao, Songfeng; Zhang, Mengqi

doi:10.1002/cam4.4248

Cited by 15 publications

(7 citation statements)

References 71 publications

(127 reference statements)

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“…These data strongly suggest that LARP4B acts as a tumor-suppressor gene of gliomas, as confirmed in our work, as LARP4B expression was negatively correlated with SC2I. Interestingly, there were also reports of LARP4B helping to predict prognosis and immunotherapy in glioma patients [ 33 , 34 ]. In summary, LARP4B is a tumor-suppressor gene of glioma; the potential mechanisms involved, however, remain to be probed further.…”

Section: Discussionsupporting

confidence: 88%

SARS-CoV-2 Pattern Provides a New Scoring System and Predicts the Prognosis and Immune Therapeutic Response in Glioma

Jiang

Zhan

et al. 2022

Cells

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Objective: Glioma is the most common primary malignancy of the adult central nervous system (CNS), with a poor prognosis and no effective prognostic signature. Since late 2019, the world has been affected by the rapid spread of SARS-CoV-2 infection. Research on SARS-CoV-2 is flourishing; however, its potential mechanistic association with glioma has rarely been reported. The aim of this study was to investigate the potential correlation of SARS-CoV-2-related genes with the occurrence, progression, prognosis, and immunotherapy of gliomas. Methods: SARS-CoV-2-related genes were obtained from the human protein atlas (HPA), while transcriptional data and clinicopathological data were obtained from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) databases. Glioma samples were collected from surgeries with the knowledge of patients. Differentially expressed genes were then identified and screened, and seven SARS-CoV-2 related genes were generated by LASSO regression analysis and uni/multi-variate COX analysis. A prognostic SARS-CoV-2-related gene signature (SCRGS) was then constructed based on these seven genes and validated in the TCGA validation cohort and CGGA cohort. Next, a nomogram was established by combining critical clinicopathological data. The correlation between SCRGS and glioma related biological processes was clarified by Gene set enrichment analysis (GSEA). In addition, immune infiltration and immune score, as well as immune checkpoint expression and immune escape, were further analyzed to assess the role of SCRGS in glioma-associated immune landscape and the responsiveness of immunotherapy. Finally, the reliability of SCRGS was verified by quantitative real-time polymerase chain reaction (qRT-PCR) on glioma samples. Results: The prognostic SCRGS contained seven genes, REEP6, CEP112, LARP4B, CWC27, GOLGA2, ATP6AP1, and ERO1B. Patients were divided into high- and low-risk groups according to the median SARS-CoV-2 Index. Overall survival was significantly worse in the high-risk group than in the low-risk group. COX analysis and receiver operating characteristic (ROC) curves demonstrated excellent predictive power for SCRGS for glioma prognosis. In addition, GSEA, immune infiltration, and immune scores indicated that SCRGS could potentially predict the tumor microenvironment, immune infiltration, and immune response in glioma patients. Conclusion: The SCRGS established here can effectively predict the prognosis of glioma patients and provide a potential direction for immunotherapy.

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Section: Discussionsupporting

confidence: 88%

SARS-CoV-2 Pattern Provides a New Scoring System and Predicts the Prognosis and Immune Therapeutic Response in Glioma

Jiang

Zhan

et al. 2022

Cells

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“…Eventually, we constructed an AR-related signature, which comprised five AR-related genes (BRCA1, ABI1, CAPG, FLNA and EIF3D). BRCA1 promoted the GBM cell growth and negatively decreased the survival of gliomas [ 27 , 28 ]. It was noted that BRCA1 was a risk prognostic factor for LGGs but not for GBM patients [ 29 ].…”

Section: Discussionmentioning

confidence: 99%

Development of a Hallmark Pathway-Related Gene Signature Associated with Immune Response for Lower Grade Gliomas

Lai

Zhong

Liu

et al. 2022

IJMS

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Although some biomarkers have been used to predict prognosis of lower-grade gliomas (LGGs), a pathway-related signature associated with immune response has not been developed. A key signaling pathway was determined according to the lowest adjusted p value among 50 hallmark pathways. The least absolute shrinkage and selection operator (LASSO) and stepwise multivariate Cox analyses were performed to construct a pathway-related gene signature. Somatic mutation, drug sensitivity and prediction of immunotherapy analyses were conducted to reveal the value of this signature in targeted therapies. In this study, an allograft rejection (AR) pathway was considered as a crucial signaling pathway, and we constructed an AR-related five-gene signature, which can independently predict the prognosis of LGGs. High-AR LGG patients had higher tumor mutation burden (TMB), Immunophenscore (IPS), IMmuno-PREdictive Score (IMPRES), T cell-inflamed gene expression profile (GEP) score and MHC I association immunoscore (MIAS) than low-AR patients. Most importantly, our signature can be validated in four immunotherapy cohorts. Furthermore, IC50 values of the six classic chemotherapeutic drugs were significantly elevated in the low-AR group compared with the high-AR group. This signature might be regarded as an underlying biomarker in predicting prognosis for LGGs, possibly providing more therapeutic strategies for future clinical research.

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“…Furthermore, we compared the prognostic predictive abilities of 20 different risk signatures of gliomas in TCGA from published articles, including inflammatory response-related gene (IRRG) signature ( Yan et al, 2022 ), DNA damage and repair-related gene (DDRRG) signature ( Li et al, 2022c ), CXCR members signature ( He et al, 2022 ), pyroptosis-related gene signature ( Zhang M. et al, 2021b ; Chao et al, 2022 ; Yang et al, 2022 ; Zhang et al, 2022 ), ECM-related gene (ECMRG) signature ( Li et al, 2022b ), tripartite motif (TRIM) family gene signature ( Xiao et al, 2022 ), antigen presentation machinery (APM) signature ( Chen et al, 2022 ), natural killer cell-related gene (NKRG) signature ( Li C. et al, 2022a ), IL-4-related gene (IL4RG) signature ( Qi et al, 2022 ), hypoxia-related gene (HRG) signature ( Gao et al, 2021 ), S100 family-based signature ( Hu et al, 2021 ), TIME signature ( Zhang C. et al, 2021a ), focal adhesion-related gene (FARG) signature ( Li et al, 2021 ), m6A RNA methylation regulator signature ( Cong et al, 2021 ), HDAC1-related signature ( Fan et al, 2021 ), RNA-binding protein (RBP)-based signature ( Chen et al, 2021a ) and ferroptosis-related gene (FRG) signature ( Chen et al, 2021b ). The results of univariate and multivariate Cox analyses showed that our ARG signature had independent predictive ability ( p < 0.001, Table 1 ).…”

Section: Resultsmentioning

confidence: 99%

Construction and validation of an angiogenesis-related gene expression signature associated with clinical outcome and tumor immune microenvironment in glioma

Wang

et al. 2022

Front. Genet.

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Background: Glioma is the most prevalent malignant intracranial tumor. Many studies have shown that angiogenesis plays a crucial role in glioma tumorigenesis, metastasis, and prognosis. In this study, we conducted a comprehensive analysis of angiogenesis-related genes (ARGs) in glioma.Methods: RNA-sequencing data of glioma patients were obtained from TCGA and CGGA databases. Via consensus clustering analysis, ARGs in the sequencing data were distinctly classified into two subgroups. We performed univariate Cox regression analysis to determine prognostic differentially expressed ARGs and least absolute shrinkage and selection operator Cox regression to construct a 14-ARG risk signature. The CIBERSORT algorithm was used to explore immune cell infiltration, and the ESTIMATE algorithm was applied to calculate immune and stromal scores.Results: We found that the 14-ARG signature reflected the infiltration characteristics of different immune cells in the tumor immune microenvironment. Additionally, total tumor mutational burden increased significantly in the high-risk group. We combined the 14-ARG signature with patient clinicopathological data to construct a nomogram for predicting 1-, 3-, and 5-year overall survival with good accuracy. The predictive value of the prognostic model was verified in the CGGA cohort. SPP1 was a potential biomarker of glioma risk and was involved in the proliferation, invasion, and angiogenesis of glioma cells.Conclusion: In conclusion, we established and validated a novel ARG risk signature that independently predicted the clinical outcomes of glioma patients and was associated with the tumor immune microenvironment.

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Identification and validation of RNA‐binding protein‐related gene signature revealed potential associations with immunosuppression and drug sensitivity in glioma

Cited by 15 publications

References 71 publications

SARS-CoV-2 Pattern Provides a New Scoring System and Predicts the Prognosis and Immune Therapeutic Response in Glioma

SARS-CoV-2 Pattern Provides a New Scoring System and Predicts the Prognosis and Immune Therapeutic Response in Glioma

Development of a Hallmark Pathway-Related Gene Signature Associated with Immune Response for Lower Grade Gliomas

Construction and validation of an angiogenesis-related gene expression signature associated with clinical outcome and tumor immune microenvironment in glioma

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