ArticleScientific data2023
Patient-derived glioblastoma cell lines with conserved genome profiles of the original tissue.
Article in Scientific data, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 7 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
7 citing papers in PubMed.
- AAV transduction of human glioblastoma cell lines induces perturbation in cell proliferation.Molecular therapy. Oncology · 2026Article
- Modelling brain tumours with organoids: towards precision medicine in neuro-oncology.Nature reviews. Neurology · 2026Review
- Inflammasomes in glioblastoma.Journal of neuroinflammation · 2026Review
- Opportunities and challenges for patient-derived models of brain tumors in functional precision medicine.NPJ precision oncology · 2025Review
- Intratumoral Cell Heterogeneity in Patient-Derived Glioblastoma Cell Lines Revealed by Single-Cell RNA-Sequencing.International journal of molecular sciences · 2024Article
- Patient-derived glioblastoma cell lines with conserved genome profiles of the original tissue.Scientific data · 2023Article
- Successes and challenges in modeling heterogeneous BRAFFrontiers in oncology · 2023Review
Corrections and comments
- Erratum issued
Authors and funding
11 authors.
Funding
Abstract
Glioblastoma (GBM) is the most lethal intracranial tumor. Sequencing technologies have supported personalized therapy for precise diagnosis and optimal treatment of GBM by revealing clinically actionable molecular characteristics. Although accumulating sequence data from brain tumors and matched normal tissues have facilitated a comprehensive understanding of genomic features of GBM, these in silico evaluations could gain more biological credibility when they are verified with in vitro and in vivo models. From this perspective, GBM cell lines with whole exome sequencing (WES) datasets of matched tumor tissues and normal blood are suitable biological platforms to not only investigate molecular markers of GBM but also validate the applicability of druggable targets. Here, we provide a complete WES dataset of 26 GBM patient-derived cell lines along with their matched tumor tissues and blood to demonstrate that cell lines can mostly recapitulate genomic profiles of original tumors such as mutational signatures and copy number alterations.
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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 OpenQuestion graph.