Evidence map›Paper›PMID 39379704›Full record

ArticleNature medicine2025

Prediction of brain metastasis development with DNA methylation signatures.

Jeffrey A Zuccato, Yasin Mamatjan, Farshad Nassiri, Andrew Ajisebutu, Jeffrey C Liu, Ammara Muazzam, Olivia Singh, Wen Zhang, Mathew Voisin, Shideh Mirhadi and 11 more

Abstract read
In one paragraph

Article in Nature medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.

0numbers the graph read from it
0cells of the map it votes in
36citing 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

36 citing papers in PubMed.

  1. Article
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  9. Cells · 2026
    Article
  10. Article
  11. Review
  12. Article
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  15. Article
  16. Review
  17. Article
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  19. Review
  20. Identifying the genomic landscape of EGFR-mutant lung cancers with central nervous system metastases.Annals of oncology : official journal of the European Society for Medical Oncology · 2025
    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

21 authors.

Jeffrey A ZuccatoMacFeeters Hamilton Neuro-Oncology Program, Princess Margaret Cancer Centre, University Health Network and University of Toronto, Toronto, Ontario, Canada.ORCID 0000-0001-5418-8238
Yasin Mamatjan *MacFeeters Hamilton Neuro-Oncology Program, Princess Margaret Cancer Centre, University Health Network and University of Toronto, Toronto, Ontario, Canada.ORCID 0000-0002-8807-2927
Farshad Nassiri *MacFeeters Hamilton Neuro-Oncology Program, Princess Margaret Cancer Centre, University Health Network and University of Toronto, Toronto, Ontario, Canada.
Andrew Ajisebutu *MacFeeters Hamilton Neuro-Oncology Program, Princess Margaret Cancer Centre, University Health Network and University of Toronto, Toronto, Ontario, Canada.
Jeffrey C Liu *MacFeeters Hamilton Neuro-Oncology Program, Princess Margaret Cancer Centre, University Health Network and University of Toronto, Toronto, Ontario, Canada.
Ammara MuazzamProgram in Cell Biology, Hospital for Sick Children, Toronto, Ontario, Canada.ORCID 0000-0001-7035-411X
Olivia SinghMacFeeters Hamilton Neuro-Oncology Program, Princess Margaret Cancer Centre, University Health Network and University of Toronto, Toronto, Ontario, Canada.
Wen ZhangProgram in Cell Biology, Hospital for Sick Children, Toronto, Ontario, Canada.
Mathew VoisinMacFeeters Hamilton Neuro-Oncology Program, Princess Margaret Cancer Centre, University Health Network and University of Toronto, Toronto, Ontario, Canada.ORCID 0000-0002-1191-9579
Shideh MirhadiProgram in Cell Biology, Hospital for Sick Children, Toronto, Ontario, Canada.
Suganth SuppiahMacFeeters Hamilton Neuro-Oncology Program, Princess Margaret Cancer Centre, University Health Network and University of Toronto, Toronto, Ontario, Canada.
Leanne Wybenga-GrootProgram in Cell Biology, Hospital for Sick Children, Toronto, Ontario, Canada.ORCID 0000-0002-7073-9041
Alireza TajikMacFeeters Hamilton Neuro-Oncology Program, Princess Margaret Cancer Centre, University Health Network and University of Toronto, Toronto, Ontario, Canada.
Craig SimpsonProgram in Cell Biology, Hospital for Sick Children, Toronto, Ontario, Canada.ORCID 0000-0003-4535-5000
Olli SaarelaDivision of Biostatistics, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada.
Ming S TsaoDepartment of Pathology, The Princess Margaret Cancer Centre, Toronto, Ontario, Canada.ORCID 0000-0002-9160-5405
Thomas KislingerPrincess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada.
Kenneth D AldapeLaboratory of Pathology, Center for Cancer Research, National Cancer Institute, Bethesda, MD, USA.ORCID 0000-0001-5119-7550
Michael F MoranProgram in Cell Biology, Hospital for Sick Children, Toronto, Ontario, Canada.
Vikas PatilMacFeeters Hamilton Neuro-Oncology Program, Princess Margaret Cancer Centre, University Health Network and University of Toronto, Toronto, Ontario, Canada. vikas.patil@uhn.ca.ORCID 0000-0002-8696-530X
Gelareh ZadehMacFeeters Hamilton Neuro-Oncology Program, Princess Margaret Cancer Centre, University Health Network and University of Toronto, Toronto, Ontario, Canada. gelareh.zadeh@uhn.ca.ORCID 0000-0002-6637-4502

Funding

Establishing the clinical utility of cell-free tumor DNA methylation profiling as a reliable liquid biopsy approach in brain tumorsR01CA263196 · NCI · UNIVERSITY HEALTH NETWORK · PI Daniel De Carvalho, Gelareh Zadeh · 2022 to 2026
$1.9M
Canadian Cancer Society Research Institute (Société Canadienne du Cancer) 707139, 707701Gouvernement du Canada | Canadian Institutes of Health Research (Instituts de Recherche en Santé du Canada) 175335, 707139, 707701NCI NIH HHS R01 CA263196U.S. Department of Health & Human Services | National Institutes of Health (NIH) 1R01CA263196-01
6 · The paper itself

Abstract

Brain metastases (BMs) are the most common and among the deadliest brain tumors. Currently, there are no reliable predictors of BM development from primary cancer, which limits early intervention. Lung adenocarcinoma (LUAD) is the most common BM source and here we obtained 402 tumor and plasma samples from a large cohort of patients with LUAD with or without BM (n = 346). LUAD DNA methylation signatures were evaluated to build and validate an accurate model predicting BM development from LUAD, which was integrated with clinical factors to provide comprehensive patient-specific BM risk probabilities in a nomogram. Additionally, immune and cell interaction gene sets were differentially methylated at promoters in BM versus paired primary LUAD and had aligning dysregulation in the proteome. Immune cells were differentially abundant in BM versus LUAD. Finally, liquid biomarkers identified from methylated cell-free DNA sequenced in plasma were used to generate and validate accurate classifiers for early BM detection. Overall, LUAD methylomes can be leveraged to predict and noninvasively identify BM, moving toward improved patient outcomes with personalized treatment.

Indexed as

Adenocarcinoma of LungBrain NeoplasmsDNA MethylationLung NeoplasmsAgedBiomarkers, TumorFemaleGene Expression Regulation, NeoplasticHumansMaleMiddle AgedNomogramsBiomarkers, Tumor

Identifiers

PMID39379704
PMCPMC11750707

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.