ArticleCell & bioscience2024
Single-cell multi-omics analysis reveals candidate therapeutic drugs and key transcription factor specifically for the mesenchymal subtype of glioblastoma.
Article in Cell & bioscience, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
13 citing papers in PubMed.
- Integrating Single-Cell Sequencing and Proteomics to Unravel Stem Cell Heterogeneity: Implications for Precision Regenerative Medicine.Stem cell reviews and reports · 2026Review
- Multi-omics profiling-derived signature links cellular ecosystem to glioblastoma prognosis.iScience · 2026Article
- Immune checkpoint crosstalk between LAG-3 and CD39/CD73 in glioblastoma: dual-pathway regulation of metabolic exhaustion and therapeutic reversal strategies.Journal of the Egyptian National Cancer Institute · 2026Review
- A CREM-ITGA2B-MAPK axis drives proliferation and invasiveness in gastric cancer: insights from single-cell analysis.Cellular oncology (Dordrecht, Netherlands) · 2026Article
- Cancer Neuroscience: Linking Neuronal Plasticity with Brain Tumor Growth and Resistance.Biology · 2026Review
- Multi-Omics Integration for Advancing Glioma Precision Medicine.Annals of clinical and translational neurology · 2026Review
- Exploring the impact of endocrine-disrupting chemicals on erectile dysfunction through network toxicology and machine learning.BMC pharmacology & toxicology · 2025Article
- Machine learning-enhanced discovery of a basement membrane-related gene signature in glioblastoma via single-cell and Spatial transcriptomics.Journal of translational medicine · 2025Article
- Large-scale bulk and single-cell RNA sequencing combined with machine learning reveals glioblastoma-associated neutrophil heterogeneity and establishes a VEGFABiology direct · 2025Article
- GADD45G as a novel prognostic biomarker and therapeutic target in glioma: integrative analysis of bulk and single-cell RNA sequencing.Frontiers in oncology · 2025Article
- Integrative single-cell and machine learning analysis predicts lactylation-driven therapy resistance in prostate cancer: a molecular docking and experiments-validated framework for treatment optimization.Frontiers in immunology · 2025Article
- Intercellular adhesion molecule 1 links glioblastoma biology to a scalable prognostic model integrating clinical, imaging, and molecular features.Neuro-oncology advancesArticle
- Integration of Single-Cell RNA and Bulk RNA Sequencing Reveals Cellular Heterogeneity and Identifies Survival-Associated Regulatory Networks in Glioblastoma.IET systems biologyArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
The inherent heterogeneity of tumor cells impedes the development of targeted therapies for specific glioblastoma (GBM) subtypes. This study aims to investigate the mesenchymal subtype of GBM to uncover detailed characteristics, potential therapeutic strategies, and improve precision treatment for GBM patients. We integrated single-cell RNA sequencing (scRNA-seq), single-nucleus assay for transposase-accessible chromatin sequencing (snATAC-seq), and bulk RNA sequencing datasets to identify core gene modules, candidate therapeutic drugs, and key transcription factors specific to mesenchymal subtype GBM tumor cells which we validated in vitro and human samples. Our analysis encompassed a heterogeneous single-cell landscape of 55,845 cells from tumor and adjacent normal tissues, focusing on the mesenchymal subtype's adverse prognosis and its association with hypoxia. We identified a core gene module composed of 38 genes and, through pharmacogenomic analysis, found that Trametinib and Dasatinib exhibit increased effectiveness against mesenchymal subtype GBM cells. Furthermore, by incorporating snATAC-seq data, we delineated a crucial regulatory network and pinpointed the key transcription factor CEBPG. Our research has highlighted the strong link between the mesenchymal-like (MES-like) properties of GBM and hypoxia, providing valuable insights into candidate drugs and pivotal targets for precision treatment of the mesenchymal subtype.
Indexed as
Identifiers
What Socratic holds
Registered trials
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 Socratic graph.