Evidence map›Paper›PMID 34555175›Full record

ArticleNeuro-oncology2022

Impact of the methylation classifier and ancillary methods on CNS tumor diagnostics.

Zhichao Wu, Zied Abdullaev, Drew Pratt, Hye-Jung Chung, Shannon Skarshaug, Valerie Zgonc, Candice Perry, Svetlana Pack, Lola Saidkhodjaeva, Sushma Nagaraj and 20 more

Abstract read
In one paragraph

Article in Neuro-oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 66 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
66citing papers in PubMed, 2 pooled it
–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

66 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. Review
  12. Article
  13. Article
  14. Article
  15. Review
  16. Article
  17. Article
  18. Article
  19. DNA Methylation-Based Classification of Kidney Neoplasms.Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc · 2025
    Article
  20. Article

6 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

30 authors.

Zhichao WuLaboratory of Pathology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA.ORCID 0000-0002-3006-043X
Zied AbdullaevLaboratory of Pathology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA.
Drew PrattDepartment of Pathology, University of Michigan, Ann Arbor, Michigan, USA.ORCID 0000-0003-3583-8308
Hye-Jung ChungLaboratory of Pathology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA.
Shannon SkarshaugLaboratory of Pathology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA.
Valerie ZgoncLaboratory of Pathology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA.
Candice PerryLaboratory of Pathology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA.
Svetlana PackLaboratory of Pathology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA.
Lola SaidkhodjaevaLaboratory of Pathology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA.
Sushma NagarajLaboratory of Pathology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA.
Manoj TyagiLaboratory of Pathology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA.
Vineela GangalapudiLaboratory of Pathology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA.
Kristin ValdezLaboratory of Pathology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA.
Rust TurakulovLaboratory of Pathology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA.
Liqiang XiLaboratory of Pathology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA.
Mark RaffeldLaboratory of Pathology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA.
Antonios Papanicolau-SengosLaboratory of Pathology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA.
Kayla O'DonnellLaboratory of Pathology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA.
Michael NewfordLaboratory of Pathology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA.
Mark R GilbertNeuro-Oncology Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA.
Felix SahmDepartment of Neuropathology, Institute of Pathology, University Hospital of Heidelberg, Heidelberg, Germany.
Abigail K SuwalaDepartment of Neuropathology, Institute of Pathology, University Hospital of Heidelberg, Heidelberg, Germany.
Andreas von DeimlingDepartment of Neuropathology, Institute of Pathology, University Hospital of Heidelberg, Heidelberg, Germany.
Yasin MamatjanDivision of Neurosurgery, Department of Surgery, University of Toronto, Toronto, Ontario, Canada.ORCID 0000-0002-8807-2927
Shirin KarimiDivision of Neurosurgery, Department of Surgery, University of Toronto, Toronto, Ontario, Canada.
Farshad NassiriDivision of Neurosurgery, Department of Surgery, University of Toronto, Toronto, Ontario, Canada.
Gelareh ZadehDivision of Neurosurgery, Department of Surgery, University of Toronto, Toronto, Ontario, Canada.ORCID 0000-0002-6637-4502
Eytan RuppinCancer Data Science Laboratory, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA.
Martha QuezadoLaboratory of Pathology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA.
Kenneth AldapeLaboratory of Pathology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA.ORCID 0000-0001-5119-7550

Funding

Brain Tumor Clinical and Clinical Research Program (Clinical Support Services)ZIDBC011642 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI OZER, BYRAM · 2015 to 2025
$23.4M
Discovery of genetic interactions in cancerZIABC011802 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI RUPPIN, EYTAN · 2018 to 2025
$19.6M
Genomic Biomarkers of CancerZIABC011850 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI ALDAPE, KENNETH · 2019 to 2025
$5.1M
Classification of tumors using whole-genome methylation profilingZIDBC012090 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI ABDULLAEV, ZIED · 2022 to 2025
$2.9M
DNA methylation-based machine classification of cancerZIABC012117 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI PRATT, DREW · 2022 to 2025
$2.3M
6 · The paper itself

Abstract

backgroundAccurate CNS tumor diagnosis can be challenging, and methylation profiling can serve as an adjunct to classify diagnostically difficult cases.

methodsAn integrated diagnostic approach was employed for a consecutive series of 1258 surgical neuropathology samples obtained primarily in a consultation practice over 2-year period. DNA methylation profiling and classification using the DKFZ/Heidelberg CNS tumor classifier was performed, as well as unsupervised analyses of methylation data. Ancillary testing, where relevant, was performed.

resultsAmong the received cases in consultation, a high-confidence methylation classifier score (>0.84) was reached in 66.4% of cases. The classifier impacted the diagnosis in 46.7% of these high-confidence classifier score cases, including a substantially new diagnosis in 26.9% cases. Among the 289 cases received with only a descriptive diagnosis, methylation was able to resolve approximately half (144, 49.8%) with high-confidence scores. Additional methods were able to resolve diagnostic uncertainty in 41.6% of the low-score cases. Tumor purity was significantly associated with classifier score (P = 1.15e-11). Deconvolution demonstrated that suspected glioblastomas (GBMs) matching as control/inflammatory brain tissue could be resolved into GBM methylation profiles, which provided a proof-of-concept approach to resolve tumor classification in the setting of low tumor purity.

conclusionsThis work assesses the impact of a methylation classifier and additional methods in a consultative practice by defining the proportions with concordant vs change in diagnosis in a set of diagnostically challenging CNS tumors. We address approaches to low-confidence scores and confounding issues of low tumor purity.

Indexed as

Central Nervous System NeoplasmsGlioblastomaDNA MethylationHumansbrain tumor classificationdeconvolutionDNA methylation profileneuropathologytumor purity

Identifiers

PMID34555175
PMCPMC8972234

What OpenQuestion holds

Textmetadata
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.