Evidence map›Paper›PMID 38595234›Full record

ArticleBeijing da xue xue bao. Yi xue ban = Journal of Peking University. Health sciences2024

[Dynamic trajectory and cell communication of different cell clusters in malignant progression of glioblastoma].

Xiang Cai, Rendong Wang, Shijia Wang, Ziqi Ren, Qiuhong Yu, Dongguo Li

Open access · greenAbstract readEnglish Abstract
In one paragraph

Article in Beijing da xue xue bao. Yi xue ban = Journal of Peking University. Health sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

6 authors at 1 institution in 1 country.

Xiang CaiDepartment of Intelligent Medical Engineering, School of Biomedical Engineering, Capital Medical University, Beijing 100069, China.
Rendong WangDepartment of Intelligent Medical Engineering, School of Biomedical Engineering, Capital Medical University, Beijing 100069, China.
Shijia WangDepartment of Intelligent Medical Engineering, School of Biomedical Engineering, Capital Medical University, Beijing 100069, China.
Ziqi RenDepartment of Hyperbaric Oxygen, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China.
Qiuhong YuDepartment of Hyperbaric Oxygen, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China.
Dongguo LiDepartment of Intelligent Medical Engineering, School of Biomedical Engineering, Capital Medical University, Beijing 100069, China.
Capital Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo delve deeply into the dynamic trajectories of cell subpopulations and the communication network among immune cell subgroups during the malignant progression of glioblastoma (GBM), and to endeavor to unearth key risk biomarkers in the GBM malignancy progression, so as to provide a more profound understanding for the treatment and prognosis of this disease by integrating transcriptomic data and clinical information of the GBM patients.

methodsUtilizing single-cell sequencing data analysis, we constructed a cell subgroup atlas during the malignant progression of GBM. The Monocle2 tool was employed to build dynamic progression trajectories of the tumor cell subgroups in GBM. Through gene enrichment analysis, we explored the biological processes enriched in genes that significantly changed with the malignancy progression of GBM tumor cell subpopulations. CellChat was used to identify the communication network between the different immune cell subgroups. Survival analysis helped in identifying risk molecular markers that impacted the patient prognosis during the malignant progression of GBM. This method ological approach offered a comprehensive and detailed examination of the cellular and molecular dynamics within GBM, providing a robust framework for understanding the disease' s progression and potential therapeutic targets.

resultsThe analysis of single-cell sequencing data identified 6 different cell types, including lymphocytes, pericytes, oligodendrocytes, macrophages, glioma cells, and microglia. The 27 151 cells in the single-cell dataset included 3 881 cells from the patients with low-grade glioma (LGG), 10 166 cells from the patients with newly diagnosed GBM, and 13 104 cells from the patients with recurrent glioma (rGBM). The pseudo-time analysis of the glioma cell subgroups indicated significant cellular heterogeneity during malignant progression. The cell interaction analysis of immune cell subgroups revealed the communication network among the different immune subgroups in GBM malignancy, identifying 22 biologically significant ligand-receptor pairs across 12 key biological pathways. Survival analysis had identified 8 genes related to the prognosis of the GBM patients, among which

conclusionThis research comprehensively and profoundly reveals the dynamic changes in glioma cell subpopulations and the communication patterns among the immune cell subgroups during the malignant progression of GBM. These findings are of significant importance for understanding the complex biological processes of GBM, providing crucial new insights for precision medicine and treatment decisions in GBM. Through these studies, we hope to provide more effective treatment options and more accurate prognostic assessments for the patients with GBM.

Indexed as

Brain NeoplasmsGlioblastomaGliomaCarboxypeptidasesCell CommunicationHumansNeoplasm Recurrence, LocalPrognosisRepressor ProteinsAEBP1 protein, humanCarboxypeptidasesRepressor ProteinsCell-cell interactionCell communicationGlioblastomaPseudo-time analysisSingle-cell sequencing

Identifiers

PMID38595234
PMCPMC11004966
OpenAlexW4394739932

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.