Large-scale bulk RNA-seq analysis defines immune evasion mechanism related to mast cell in gliomas

Chen, Rui; Wu, Wantao; Liu, Tao; Zhao, Yihan; Wang, Yifan; Zhang, Hao; Wang, Zeyu; Dai, Ziyu; Zhou, Xiaoxi; Luo, Peng; Zhang, Jian; Han, Xinwei; Zhang, Liyang; Cheng, Quan

doi:10.3389/fimmu.2022.914001

Cited by 9 publications

(7 citation statements)

References 63 publications

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“…This gene encodes a GTP-binding protein which catalyzes the conversion of GTP to GDP and is known to be involved in the regulation of cell growth and differentiation. Although its function in glioma is still not completely elucidated, it was recently demonstrated to be positively correlated with several steps in anti-tumor immune response, 53 and its depletion was shown to promote survival. 54 In the case of KCND2 , it showed a lower level of methylation and a higher expression level in astrocytoma.…”

Section: Discussionmentioning

confidence: 99%

Integration of Multi-Omics Data for the Classification of Glioma Types and Identification of Novel Biomarkers

Vieira,

Bispo,

Lopes

2024

Bioinform Biol Insights

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Glioma is currently one of the most prevalent types of primary brain cancer. Given its high level of heterogeneity along with the complex biological molecular markers, many efforts have been made to accurately classify the type of glioma in each patient, which, in turn, is critical to improve early diagnosis and increase survival. Nonetheless, as a result of the fast-growing technological advances in high-throughput sequencing and evolving molecular understanding of glioma biology, its classification has been recently subject to significant alterations. In this study, we integrate multiple glioma omics modalities (including mRNA, DNA methylation, and miRNA) from The Cancer Genome Atlas (TCGA), while using the revised glioma reclassified labels, with a supervised method based on sparse canonical correlation analysis (DIABLO) to discriminate between glioma types. We were able to find a set of highly correlated features distinguishing glioblastoma from lower-grade gliomas (LGGs) that were mainly associated with the disruption of receptor tyrosine kinases signaling pathways and extracellular matrix organization and remodeling. Concurrently, the discrimination of the LGG types was characterized primarily by features involved in ubiquitination and DNA transcription processes. Furthermore, we could identify several novel glioma biomarkers likely helpful in both diagnosis and prognosis of the patients, including the genes PPP1R8, GPBP1L1, KIAA1614, C14orf23, CCDC77, BVES, EXD3, CD300A, and HEPN1. Collectively, this comprehensive approach not only allowed a highly accurate discrimination of the different TCGA glioma patients but also presented a step forward in advancing our comprehension of the underlying molecular mechanisms driving glioma heterogeneity. Ultimately, our study also revealed novel candidate biomarkers that might constitute potential therapeutic targets, marking a significant stride toward personalized and more effective treatment strategies for patients with glioma.

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Section: Discussionmentioning

confidence: 99%

Integration of Multi-Omics Data for the Classification of Glioma Types and Identification of Novel Biomarkers

Vieira,

Bispo,

Lopes

2024

Bioinform Biol Insights

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“…Mast cells are believed to play an important role in angiogenesis and TME remodeling (Huang et al, 2008;Liu et al, 2011). The high level of mast cells may cause a better prognosis (Chen et al, 2022). The increases of neutrophils and M2 macrophages were also observed in a IDH-WT cohort, which means may be poor prognosis (Wang et al, 2017).…”

Section: Discussionmentioning

confidence: 99%

Identification of cuproptosis-related subtypes and the development of a prognostic model in glioma

Li²,

Zhu³

et al. 2023

Front. Genet.

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Introduction: A copper-dependent cell death, cuproptosis, involves copper binding with lipoylated tricarboxylic acid (TCA) cycle components. In cuproptosis, ferredoxin 1 (FDX1) and lipoylation act as key regulators. The mechanism of cuproptosis differs from the current knowledge of cell death, which may invigorate investigations into copper’s potential as a cancer treatment. An extremely dismal prognosis is associated with gliomas, the most prevalent primary intracranial tumor. In patients with glioma, conventional therapies, such as surgery and chemotherapy, have shown limited improvement. A variety of cell death modes have been confirmed to be operative in glioma oncogenesis and participate in the tumor microenvironment (TME), implicated in glioma development and progression. In this study, we aimed to explore whether cuproptosis influences glioma oncogenesis.Methods: Gene expression profiles related to cuproptosis were comprehensively evaluated by comparing adjacent tissues from glioma tissues in The Cancer Genome Atlas (TCGA) (https://portal.gdc.cancer.gov/) database. Gene expression, prognostic, clinical, and pathological data of lower-grade gliomas (LGG) and glioblastoma were retrieved from TCGA and Gene Expression Omnibus (GEO) (https://www.ncbi.nlm.nih.gov/geo/) databases. The datasets were managed by “Combat” algorithm to eliminate batch effects and then combined. A consensus clustering algorithm based on the Partitioning Around Medoid (PAM) algorithm was used to classified 725 patients with LGG and glioblastoma multiforme (GBM) into two cuproptosis subtypes. According to the differentially expressed genes in the two cuproptosis subtypes, 725 patients were divided into 2 gene subtypes. Additionally, a scoring system that associated with TME was constructed to predict patient survival and patient immunotherapy outcomes. Furthermore, we constructed a prognostic CRG-score and nomogram system to predict the prognosis of glioma patients. 95 tissue specimens from 83 glioma patients undergoing surgical treatment were collected, including adjacent tissues. Using immunohistochemistry and RT-qPCR, we verified cuproptosis-related genes expression and CRG-score predictive ability in these clinical samples.Results: Our results revealed extensive regulatory mechanisms of cuproptosis-related genes in the cell cycle, TME, clinicopathological characteristics, and prognosis of glioma. We also developed a prognostic model based on cuproptosis. Through the verifications of database and clinical samples, we believe that cuproptosis affects the prognosis of glioma and potentially provides novel glioma research approaches.Conclusion: We suggest that cuproptosis has potential importance in treating gliomas and could be utilized in new glioma research efforts.

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“…164,170 MC activation was positively linked to OS, 166 including prognostic MC-related genes in predicting survival. 171 However, increased infiltrating MCs are detectable in GBM compared to LGG. 172 Antihistamine usage was reported to have little impact on survival or prognosis, although further research is required.…”

Section: Studies Of Allergy and Glioma Prognosismentioning

confidence: 98%

“…Observations for basophils are inconsistent and limited to a few studies 164,170 . MC activation was positively linked to OS, 166 including prognostic MC‐related genes in predicting survival 171 . However, increased infiltrating MCs are detectable in GBM compared to LGG 172 …”

Section: Epidemiological Clinical and Pre‐clinical Studies Of Allergy...mentioning

confidence: 99%

AllergoOncology: Biomarkers and refined classification for research in the allergy and glioma nexus—A joint EAACI‐EANO position paper

Turner,

Radzikowska,

Ferastraoaru

et al. 2024

Allergy

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Epidemiological studies have explored the relationship between allergic diseases and cancer risk or prognosis in AllergoOncology. Some studies suggest an inverse association, but uncertainties remain, including in IgE‐mediated diseases and glioma. Allergic disease stems from a Th2‐biased immune response to allergens in predisposed atopic individuals. Allergic disorders vary in phenotype, genotype and endotype, affecting their pathophysiology. Beyond clinical manifestation and commonly used clinical markers, there is ongoing research to identify novel biomarkers for allergy diagnosis, monitoring, severity assessment and treatment. Gliomas, the most common and diverse brain tumours, have in parallel undergone changes in classification over time, with specific molecular biomarkers defining glioma subtypes. Gliomas exhibit a complex tumour‐immune interphase and distinct immune microenvironment features. Immunotherapy and targeted therapy hold promise for primary brain tumour treatment, but require more specific and effective approaches. Animal studies indicate allergic airway inflammation may delay glioma progression. This collaborative European Academy of Allergy and Clinical Immunology (EAACI) and European Association of Neuro‐Oncology (EANO) Position Paper summarizes recent advances and emerging biomarkers for refined allergy and adult‐type diffuse glioma classification to inform future epidemiological and clinical studies. Future research is needed to enhance our understanding of immune–glioma interactions to ultimately improve patient prognosis and survival.

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Large-scale bulk RNA-seq analysis defines immune evasion mechanism related to mast cell in gliomas

Cited by 9 publications

References 63 publications

Integration of Multi-Omics Data for the Classification of Glioma Types and Identification of Novel Biomarkers

Integration of Multi-Omics Data for the Classification of Glioma Types and Identification of Novel Biomarkers

Identification of cuproptosis-related subtypes and the development of a prognostic model in glioma

AllergoOncology: Biomarkers and refined classification for research in the allergy and glioma nexus—A joint EAACI‐EANO position paper

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