ArticleAging2019
Genomic landscapes by multiregion sequencing combined with circulation tumor DNA detection contribute to molecular diagnosis in glioblastomas.
Article in Aging, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. 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, 10 citations in OpenAlex.
- Exploring hub genes related to adipocytokines in keloids: a combined analysis integrating single-cell, Mendelian randomization and bulk transcriptome data with experimental verification.Frontiers in molecular biosciences · 2026Article
- The genetic landscape of primary malignant melanoma of the cervix using integrated bioinformatics analysis and whole-exome sequencing.Frontiers in oncology · 2025Article
- Epidemiology and risk factors for adult gliomas died by respiratory diseases during the COVID-19 pandemic: a population-based study.Neurosurgical review · 2024Article
- Temporal and spatial stability of the EM/PM molecular subtypes in adult diffuse glioma.Frontiers of medicine · 2023Article
- Human Malignant Rhabdoid Tumor Antigens as Biomarkers and Potential Therapeutic Targets.Cancers · 2022Article
- Whole genome sequencing of Malaysian colorectal cancer patients reveals specific druggable somatic mutations.Frontiers in molecular biosciences · 2022Article
- Precision Oncology Beyond Genomics: The Future Is Here-It Is Just Not Evenly Distributed.Cells · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Glioblastoma is a highly aggressive brain malignancy with a poor prognosis. Its high intratumor heterogeneity contributes to therapeutic resistance, tumor progression and recurrence. We sequenced 31 loci in 11 patients with glioblastoma (including one patient with samples available from the primary and recurrent tumors) to determine the genetic basis and intratumor heterogeneity of glioblastoma. By analyzing the somatic mutations, known driver genes were identified, including EGFR, PTEN and TP53, and the MUC16 gene exhibited the highest mutation rate in the samples examined. Through an evolutionary analysis of the sequencing results, the EGFR p.L861Q mutation was determined to play a role in the progression from the primary tumor to a relapsing tumor in one patient. We analyzed 1403 genes in blood-derived ctDNA that were previously revealed to play a role in tumorigenesis and the progression of cancer. Somatic mutations identified through ctDNA sequencing that match the results of multipoint exon sequencing in tumor tissues were detected, such as EGFR p.L861Q. These findings provide new insights into the intratumor heterogeneity and evolution of glioblastoma. In addition, ctDNA detection in blood samples represents a convenient method to dynamically identify the genetic changes and new therapeutic targets during the treatment of glioblastoma.
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What OpenQuestion 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 OpenQuestion graph.