Evidence map›Paper›PMID 34834399›Full record

ArticleJournal of personalized medicine2021

Identification of Differentially Expressed Genes in Different Glioblastoma Regions and Their Association with Cancer Stem Cell Development and Temozolomide Response.

Justin Bo-Kai Hsu, Tzong-Yi Lee, Sho-Jen Cheng, Gilbert Aaron Lee, Yung-Chieh Chen, Nguyen Quoc Khanh Le, Shiu-Wen Huang, Duen-Pang Kuo, Yi-Tien Li, Tzu-Hao Chang and 1 more

Open access · goldAbstract read
In one paragraph

Article in Journal of personalized medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
4.0field-weighted citation impact, top 5% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed, 27 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 2 institutions in 2 countries.

Justin Bo-Kai HsuDepartment of Medical Research, Taipei Medical University Hospital, Taipei 110, Taiwan.ORCID 0000-0002-4563-2672
Tzong-Yi LeeWarshel Institute for Computational Biology, The Chinese University of Hong Kong, Shenzhen 518172, China.
Sho-Jen ChengTranslational Imaging Research Center, Taipei Medical University Hospital, Taipei 110, Taiwan.
Gilbert Aaron LeeDepartment of Medical Research, Taipei Medical University Hospital, Taipei 110, Taiwan.
Yung-Chieh ChenTranslational Imaging Research Center, Taipei Medical University Hospital, Taipei 110, Taiwan.
Nguyen Quoc Khanh LeTranslational Imaging Research Center, Taipei Medical University Hospital, Taipei 110, Taiwan.ORCID 0000-0003-4896-7926
Shiu-Wen HuangDepartment of Medical Research, Taipei Medical University Hospital, Taipei 110, Taiwan.
Duen-Pang KuoTranslational Imaging Research Center, Taipei Medical University Hospital, Taipei 110, Taiwan.
Yi-Tien LiTranslational Imaging Research Center, Taipei Medical University Hospital, Taipei 110, Taiwan.ORCID 0000-0003-3834-2615
Tzu-Hao ChangGraduate Institute of Biomedical Informatics, Taipei Medical University, Taipei 110, Taiwan.ORCID 0000-0001-7011-3754
Cheng-Yu ChenTranslational Imaging Research Center, Taipei Medical University Hospital, Taipei 110, Taiwan.ORCID 0000-0003-0428-4373
Taipei Medical University Hospital · TWChinese University of Hong Kong, Shenzhen · CN

Funding

Ministry of Science and Technology 110-2314-B-038 -004Ministry of Science and Technology 110-2314-B-038 -092National Health Research Institutes NHRI-EX108-10732NINational Health Research Institutes NHRI-EX109-10732NI
6 · The paper itself

Abstract

The molecular heterogeneity of gene expression profiles of glioblastoma multiforme (GBM) are the most important prognostic factors for tumor recurrence and drug resistance. Thus, the aim of this study was to identify potential target genes related to temozolomide (TMZ) resistance and GBM recurrence. The genomic data of patients with GBM from The Cancer Genome Atlas (TCGA; 154 primary and 13 recurrent tumors) and a local cohort (29 primary and 4 recurrent tumors), samples from different tumor regions from a local cohort (29 tumor and 25 peritumoral regions), and Gene Expression Omnibus data (GSE84465, single-cell RNA sequencing; 3589 cells) were included in this study. Critical gene signatures were identified based an analysis of differentially expressed genes (DEGs). DEGs were further used to evaluate gene enrichment levels among primary and recurrent GBMs and different tumor regions through gene set enrichment analysis. Protein-protein interactions (PPIs) were incorporated into gene regulatory networks to identify the affected metabolic pathways. The enrichment levels of 135 genes were identified in the peritumoral regions as being risk signatures for tumor recurrence. Fourteen genes (

Indexed as

biomarkerglioblastomaTMZ resistancetumor recurrence

Identifiers

PMID34834399
PMCPMC8625522
OpenAlexW3209005489

What OpenQuestion holds

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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.