Evidence map›Paper›PMID 32704022›Full record

ArticleScientific reports2020

Gene expression profiling of glioblastoma cell lines depending on TP53 status after tumor-treating fields (TTFields) treatment.

Yeon-Joo Lee, Hyun Wook Seo, Jeong-Hwa Baek, Sun Ha Lim, Sang-Gu Hwang, Eun Ho Kim

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed
3.2field-weighted citation impact, top 7% 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

33 citing papers in PubMed, 47 citations in OpenAlex.

  1. Article
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  4. ModularFrontiers in toxicology · 2026
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  7. Review
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  15. Role of scaffold proteins in the heterogeneity of glioblastoma.Cell communication and signaling : CCS · 2024
    Review
  16. Article
  17. Article
  18. Review
  19. Review
  20. Heliyon · 2024
    Article
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

6 authors at 3 institutions in 1 country.

Yeon-Joo LeeDivision of Radiation Biomedical Research, Korea Institute of Radiological and Medical Sciences (KIRAMS), Seoul, South Korea.ORCID http://orcid.org/0000-0002-6605-8761
Hyun Wook SeoDivision of Radiation Biomedical Research, Korea Institute of Radiological and Medical Sciences (KIRAMS), Seoul, South Korea.
Jeong-Hwa BaekRadiation Biology Research Team, Research Center, Dongnam Institute of Radiological and Medical Sciences, Busan, 46033, Republic of Korea.
Sun Ha LimDepartment of Biochemistry, School of Medicine, Daegu Catholic University, 33, 17-gil, Duryugongwon-ro, Nam-gu, Daegu, Korea.
Sang-Gu HwangDivision of Radiation Biomedical Research, Korea Institute of Radiological and Medical Sciences (KIRAMS), Seoul, South Korea. sgh63@kcch.re.kr.
Eun Ho KimDepartment of Biochemistry, School of Medicine, Daegu Catholic University, 33, 17-gil, Duryugongwon-ro, Nam-gu, Daegu, Korea. eh140149@cu.ac.kr.
Korea Institute of Radiological and Medical Sciences · KRDaegu Catholic University · KRDongnam Institute of Radiological & Medical Sciences · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Glioblastoma is frequently associated with TP53 mutation, which is linked to a worse prognosis and response to conventional treatments (chemoradiotherapy). Therefore, targeting TP53 is a promising strategy to overcome this poor therapeutic response. Tumor-treating fields (TTFields) are a recently approved treatment for newly diagnosed glioblastoma, which involves direct application of low-intensity, intermediate-frequency alternating electric fields to the tumor, thereby offering a local tumor-killing effect. However, the influence of TP53 mutation status on the effectiveness of TTFields is controversial. Here, we identified the key gene signatures and pathways associated with TTFields in four glioblastoma cell lines varying in TP53 mutation status using gene profiling and functional annotation. Overall, genes associated with the cell cycle, cell death, and immune response were significantly altered by TTFields regardless of TP53 status. TTFields appeared to exert enhanced anti-cancer effects by altering the immune system in the inflammatory environment and regulating cell cycle- and cell death-related genes, but the precise genes influenced vary according to TP53 status. These results should facilitate detailed mechanistic studies on the molecular basis of TTFields to further develop this modality as combination therapy, which can improve the therapeutic effect and minimize side effects of chemoradiotherapy.

Indexed as

Gene Expression ProfilingBiomarkers, TumorCell CycleComputational BiologyGene Expression Regulation, NeoplasticGene OntologyGene Regulatory NetworksGlioblastomaHumansNeoplasm StagingPrognosisTranscriptomeTumor Suppressor Protein p53Biomarkers, TumorTP53 protein, humanTumor Suppressor Protein p53

Identifiers

PMID32704022
PMCPMC7378235
OpenAlexW3044220809

What OpenQuestion holds

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LicenceCC BY
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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.