Evidence map›Paper›PMID 38762534›Full record

ArticleScientific reports2024

Evaluation of the clinical use of MGMT methylation in extracellular vesicle-based liquid biopsy as a tool for glioblastoma patient management.

Rocío Rosas-Alonso, Julian Colmenarejo-Fernández, Olga Pernía, Miranda Burdiel, Carlos Rodríguez-Antolín, Itsaso Losantos-García, Tania Rubio, Rocío Moreno-Velasco, Isabel Esteban-Rodríguez, Virginia Martínez-Marín and 11 more

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–field-weighted citation impact
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

14 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. Review
  5. Review
  6. Article
  7. Review
  8. Review
  9. Article
  10. Review
  11. Review
  12. Review
  13. Article
  14. 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

21 authors.

Rocío Rosas-AlonsoCancer Epigenetics Laboratory, INGEMM, La Paz University Hospital, Paseo La Castellana 261, Edificio Bloque Quirúrgico Planta-2, 28046, Madrid, Spain. rosas.alonso.rocio@gmail.com.
Julian Colmenarejo-FernándezCancer Epigenetics Laboratory, INGEMM, La Paz University Hospital, Paseo La Castellana 261, Edificio Bloque Quirúrgico Planta-2, 28046, Madrid, Spain.
Olga PerníaCancer Epigenetics Laboratory, INGEMM, La Paz University Hospital, Paseo La Castellana 261, Edificio Bloque Quirúrgico Planta-2, 28046, Madrid, Spain.
Miranda BurdielCancer Epigenetics Laboratory, INGEMM, La Paz University Hospital, Paseo La Castellana 261, Edificio Bloque Quirúrgico Planta-2, 28046, Madrid, Spain.
Carlos Rodríguez-AntolínCancer Epigenetics Laboratory, INGEMM, La Paz University Hospital, Paseo La Castellana 261, Edificio Bloque Quirúrgico Planta-2, 28046, Madrid, Spain.
Itsaso Losantos-GarcíaBiostatistics Unit, IdiPaz, Madrid, Spain.
Tania RubioCancer Epigenetics Laboratory, INGEMM, La Paz University Hospital, Paseo La Castellana 261, Edificio Bloque Quirúrgico Planta-2, 28046, Madrid, Spain.
Rocío Moreno-VelascoCancer Epigenetics Laboratory, INGEMM, La Paz University Hospital, Paseo La Castellana 261, Edificio Bloque Quirúrgico Planta-2, 28046, Madrid, Spain.
Isabel Esteban-RodríguezBiomarkers and Experimental Therapeutics in Cancer, IdiPAZ, Madrid, Spain.
Virginia Martínez-MarínDepartment of Medical Oncology, La Paz University Hospital, Madrid, Spain.
Paloma YuberoDepartment of Medical Oncology, La Paz University Hospital, Madrid, Spain.
Nicolas Costa-FragaCancer Epigenomics Laboratory, Epigenomics Unit, Translational Medical Oncology Group (ONCOMET), IDIS, University Clinical Hospital of Santiago (CHUS/SERGAS), Santiago de Compostela, Spain.
Angel Díaz-LagaresCancer Epigenomics Laboratory, Epigenomics Unit, Translational Medical Oncology Group (ONCOMET), IDIS, University Clinical Hospital of Santiago (CHUS/SERGAS), Santiago de Compostela, Spain.
Rafael López-LópezCancer Epigenomics Laboratory, Epigenomics Unit, Translational Medical Oncology Group (ONCOMET), IDIS, University Clinical Hospital of Santiago (CHUS/SERGAS), Santiago de Compostela, Spain.
Eva Díaz-MartinMD Anderson International Foundation, Madrid, Spain.
Juan F GarcíaMD Anderson International Foundation, Madrid, Spain.
Catalina Vivancos SánchezDepartment of Neurosurgery, La Paz University Hospital, Madrid, Spain.
Maria Luisa Gandía-GonzálezDepartment of Neurosurgery, La Paz University Hospital, Madrid, Spain.
Gema Moreno-BuenoCentro de Investigación Biomédica en Red de Cáncer (CIBERONC), Instituto de Salud Carlos III, Madrid, Spain.
Javier de CastroBiomarkers and Experimental Therapeutics in Cancer, IdiPAZ, Madrid, Spain.
Inmaculada Ibánez de CáceresCancer Epigenetics Laboratory, INGEMM, La Paz University Hospital, Paseo La Castellana 261, Edificio Bloque Quirúrgico Planta-2, 28046, Madrid, Spain. inma.ibanezca@salud.madrid.org.

Funding

Instituto de Salud Carlos III CIBERONC-CB16/12/0295Instituto de Salud Carlos III FI19/000061Instituto de Salud Carlos III JR17/000016Instituto de Salud Carlos III JR21/000003Instituto de Salud Carlos III PI18/000050Ministerio de Ciencia e Innovación PID19-104644RB-I00Ministerio de Ciencia e Innovación PLEC2021-08034
6 · The paper itself

Abstract

Glioblastoma (GB) is a devastating tumor of the central nervous system characterized by a poor prognosis. One of the best-established predictive biomarker in IDH-wildtype GB is O6-methylguanine-DNA methyltransferase (MGMT) methylation (mMGMT), which is associated with improved treatment response and survival. However, current efforts to monitor GB patients through mMGMT detection have proven unsuccessful. Small extracellular vesicles (sEVs) hold potential as a key element that could revolutionize clinical practice by offering new possibilities for liquid biopsy. This study aimed to determine the utility of sEV-based liquid biopsy as a predictive biomarker and disease monitoring tool in patients with IDH-wildtype GB. Our findings show consistent results with tissue-based analysis, achieving a remarkable sensitivity of 85.7% for detecting mMGMT in liquid biopsy, the highest reported to date. Moreover, we suggested that liquid biopsy assessment of sEV-DNA could be a powerful tool for monitoring disease progression in IDH-wildtype GB patients. This study highlights the critical significance of overcoming molecular underdetection, which can lead to missed treatment opportunities and misdiagnoses, possibly resulting in ineffective therapies. The outcomes of our research significantly contribute to the field of sEV-DNA-based liquid biopsy, providing valuable insights into tumor tissue heterogeneity and establishing it as a promising tool for detecting GB biomarkers. These results have substantial implications for advancing predictive and therapeutic approaches in the context of GB and warrant further exploration and validation in clinical settings.

Indexed as

Biomarkers, TumorBrain NeoplasmsDNA MethylationDNA Modification MethylasesDNA Repair EnzymesExtracellular VesiclesGlioblastomaTumor Suppressor ProteinsAdultAgedFemaleHumansLiquid BiopsyMaleMiddle AgedPrognosisBiomarkers, TumorDNA Modification MethylasesDNA Repair EnzymesMGMT protein, humanTumor Suppressor ProteinsGlioblastomaLiquid biopsyMethylationMGMTSmall extracellular vesicles (sEVs)

Identifiers

PMID38762534
PMCPMC11102540

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.