Evidence map›Paper›PMID 33547949›Full record

ArticleJournal of cancer research and clinical oncology2021

Using ultrasound-targeted microbubble destruction to enhance radiotherapy of glioblastoma.

Chanjuan Peng, Yong Wu, Yang Yang, Ningning Li, Xi Chen, Linhui Gu, Dong Xu, Chen Yang

Open access · hybridAbstract read
In one paragraph

Article in Journal of cancer research and clinical oncology, 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
1.0field-weighted citation impact, top 28% 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, 20 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Exploring the molecular mechanism of cancer radiosensitization: the impact of physical stimulation therapy.Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al] · 2025
    Review
  5. Review
  6. Article
  7. Review
  8. Review
  9. Review
  10. Application of Ultrasound Combined with Microbubbles for Cancer Therapy.International journal of molecular sciences · 2022
    Review
  11. Article
  12. Review
  13. Review
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

8 authors at 1 institution in 1 country.

Chanjuan Peng *Department of Ultrasound in Medicine, Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou, 310022, Zhejiang, China.
Yong Wu *Department of Medical Engineering, Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou, 310022, Zhejiang, China.
Yang YangDepartment of Radiation Oncology, Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou, 310022, Zhejiang, China.
Ningning LiDepartment of Pathology, Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou, 310022, Zhejiang, China.
Xi ChenDepartment of Ultrasound in Medicine, Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou, 310022, Zhejiang, China.
Linhui GuDepartment of Core Facility Service, Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou, 310022, Zhejiang, China.
Dong XuDepartment of Ultrasound in Medicine, Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou, 310022, Zhejiang, China. xudong@zjcc.org.cn.
Chen YangDepartment of Ultrasound in Medicine, Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou, 310022, Zhejiang, China. yangchen@zjcc.org.cn.ORCID http://orcid.org/0000-0002-9043-144X
Chinese Academy of Sciences · CN

Funding

National Natural Science Foundation of China 81702968Zhejiang Province Medical and Health Science and Technology Project 2017ZD009Zhejiang Province Medical and Health Science and Technology Project 2019KY334
6 · The paper itself

Abstract

objectiveTo investigate the efficacy and mechanism of ultrasound-targeted microbubble destruction (UTMD) combined with radiotherapy (XRT) on glioblastoma.

methodsThe enhanced radiosensitization by UTMD was assessed through colony formation and cell apoptosis in Human glioblastoma cells (U87MG). Subcutaneous transplantation tumors in 24 nude mice implanted with U87MG cells were randomly assigned to 4 different treatment groups (Control, UTMD, XRT, and UTMD + XRT) based on tumor sizes (100-300 mm

resultsWhen the radiotherapy dose was 4 Gy, the colony formation rate of U87MG cells in the UTMD + XRT group was 32 ± 8%, lower than the XRT group (54 ± 14%, p < 0.01). The early apoptotic rate of the UTMD + XRT group was 21.1 ± 3% at 48 h, higher than that of the XRT group (15.2 ± 4%). The tumor growth curve indicated that the tumor growth was inhibited in the UTMD + XRT group compared with other groups during 10 days of observation. In TUNEL experiment, the apoptotic cells of the UTMD + XRT group were higher than that of the XRT group (p < 0.05). The UTMD + XRT group had the lowest MVD value, but was not significantly different from other groups (p > 0.05). In addition, γH2AX increased due to the addition of UTMD to radiotherapy compared to XRT in immunohistochemistry (p < 0.05).

conclusionsOur study clearly demonstrated the enhanced destructive effect of UTMD combined with 4 Gy radiotherapy on glioblastoma. This could be partly achieved by the increased ability of DNA damage of tumor cells.

Indexed as

AnimalsApoptosisCell Line, TumorCell ProliferationGlioblastomaHumansImmunohistochemistryMaleMiceMice, Inbred BALB CMice, NudeMicrobubblesGlioblastomaMicrobubblesRadiation therapyUltrasoundUltrasound therapy

Identifiers

PMID33547949
PMCPMC8021517
OpenAlexW3126324189

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.