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Distinct molecular profiles characterize the spontaneous growth rate of IDHmt low-grade astrocytomas and oligodendrogliomas.

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Paper

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The authors' code

Markdown · 34 lines · 1.3 KB · GPL

  2. ## Description ##
  3. This R package contains additional tools for the analysis of methylation data (Infinium HM-27K and HM-450K).
  6. * Package: methyltools
  7. * Type: Package
  8. * Title: Additional tools for the analysis of methylation data
  9. * Version: 0.7
  10. * Date: 2014-06-23
  11. * Revision: 2016-02-11
  12. * Author: Pierre Bady <[email hidden]>
  13. * Maintainer: Pierre Bady <[email hidden]>
  14. * Depends: R (>= 3.2.2), CGHcall, CGHbase, minfi,preprocessCore, org.Hs.eg.db, TxDb.Hsapiens.UCSC.hg19.knownGene, lumi,mixtools, snowfall,RPMM,ade4
  15. * Suggests: boot
  16. * Description: Additional tools for the analysis of methylation data
  17. * License: GPL (>= 2)
  18. * URL: http://lausanne.isb-sib.ch/~pbady/Rpackages.html
  20. Documentation in preparation is available [here](https://github.com/badozor/methyltools/tree/master/trunk/Rdoc).
  22. ## Licence ##
  23. GPL version 2 or newer
  24. ```
  25. This program is free software; you can redistribute it and/or
  26. modify it under the terms of the GNU General Public License
  27. as published by the Free Software Foundation; either version 2
  28. of the License, or (at your option) any later version.
  30. This program is distributed in the hope that it will be useful,
  31. but WITHOUT ANY WARRANTY; without even the implied warranty of
  32. MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
  33. GNU General Public License for more details.
  34. '''

README.md at commit f367260, under GPL · at the source

Overview

Authors: Amélie Darlix1,2, Pierre Bady3, Jérémy Deverdun4, Emmanuelle Le Bars5, Arthur Coget6, Justine Meriadec6, Mathilde Carrière6, Hugues Duffau7, Monika E Hegi8
ORCID iDs: Amélie Darlix, Pierre Bady, Emmanuelle Le Bars, Hugues Duffau, Monika E Hegi
  1. Department of Medical Oncology, Institut Régional du Cancer de Montpellier, University of Montpellier, Montpellier, France
  2. Institute of Functional Genomics (IGF), University of Montpellier, CNRS, INSERM, Montpellier, France
  3. Neuroscience Research Center and Service of Neurosurgery, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
  4. Translational Data Science Facility, Swiss Institute of Bioinformatics, AGORA Cancer Research Centre, Lausanne, Switzerland
  5. I2FH, Institut d‘Imagerie Fonctionnelle Humaine, Department of Neuroradiology, Montpellier University Medical Center, Montpellier, France
  6. Department of Neuroradiology, Gui de Chauliac Hospital, Montpellier University Medical Center, Montpellier, France
  7. Department of Neurosurgery, Gui de Chauliac Hospital, Montpellier University Medical, Montpellier, France
  8. L. Lundin and Family Brain Tumor Research Center, Departments of Oncology and Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
Institutions: Centre National de la Recherche Scientifique (France); Inserm (France); Université de Montpellier (France); Institut de Génomique Fonctionnelle (France); Institut Regional du Cancer de Montpellier (France); Centre Hospitalier Universitaire Vaudois (Switzerland); University of Lausanne (Switzerland); SIB Swiss Institute of Bioinformatics (Switzerland); Hôpital Gui de Chauliac (France)
Journal: Neuro-oncology, volume 28, issue 4, pages 911-922
Dates: received 21 October 2025; accepted 28 December 2025; published online 29 December 2025; in print April 2026
Type: Research article · Language: English
License: CC BY-NC
Identifiers: DOI 10.1093/neuonc/noaf296 · PMID 41460180 · PMCID PMC13128452 · OpenAlex W7117457838
Open access: hybrid, a free copy (OpenAlex)
Status: code verified
Categories: genetics / omics (modality), human (organism), other condition (population), cellular / molecular (subfield)
Methods: Statistics, Machine learning, Connectivity, Smoothing, state filtering, decompositions
Keywords: IDHmt diffuse LGG WHO grade II, molecular signatures, tumor volume growth rate
MeSH: Astrocytoma*, Biomarkers, Tumor*, Brain Neoplasms*, Isocitrate Dehydrogenase*, Mutation*, Oligodendroglioma*, Adult, Aged, DNA Methylation, Female, Follow-Up Studies, Humans, Male, Middle Aged, Neoplasm Grading, Prognosis, Transcriptome, Young Adult (* major topic)
Journal subjects: Basic and Translational Investigations
Topic: Glioma Diagnosis and Treatment (Genetics, Medicine), according to OpenAlex
Funding: Brain Tumour Charity (CB_2019/1_10398, GN-000682); Swiss Cancer Research Foundation (KFS-5555-02-2022, 320030_215718)
Citations: cited by 1 paper (Europe PMC); 46 references in the paper

Abstract

Background: The life expectancy of patients with diffuse IDH-mutant low-grade gliomas (IDHmt LGG) ranges from 5 to over 20 years. Tumor behavior, including spontaneous growth rate, varies even within homogeneously classified subtypes of oligodendroglioma and astrocytoma. Risk-adjusted treatment strategies are needed to avoid therapy-related toxicities without compromising outcome. The spontaneous tumor volume growth rate (TVGR) serves as a prognostic marker and predicts response to therapy. Accurate prediction of TVGR through biomarkers would enable improved evidence-based risk management.

Patients and Methods: A cohort of 77 patients treated in Montpellier, France, for IDHmt LGG grade II (WHO 2016) (29 oligodendrogliomas and 48 astrocytomas) was constituted (age >18 years; MRI scans, frozen tumor tissue). The DNA methylome (Illumina, EPIC array) and transcriptome (RNAseq) were established. TVGR was determined based on serial MRIs collected over the “watch & wait” period before the first treatment beyond surgery. Transcriptomic and methylome data were analyzed for signatures associated with TVGR using rank-rank regression followed by preranked gene set enrichment analysis.

Results: The median TVGR was lower in IDHmt codeleted compared to non-codeleted LGG (0.241 year−1 range 0.082-0.366 vs. 0.424 year−1 range 0.264-0.609, P < .001). In codeleted IDHmt LGG, TVGR was associated with upregulated gene signatures for neuronal systems, synaptic activity, and activation of repressed or poised signatures of neural progenitor cells, while the TVGR in non-codeleted IDHmt LGG was dominated by upregulated proliferation-related signatures, including DNA replication and repair.

Conclusion: Spontaneous TVGR of codeleted and non-codeleted IDHmt LGG involves distinct biological processes, suggesting possible differences in response to therapies.

Reproduced under the paper's license (CC BY-NC), from the paper cited above.

Repository

Its files are read in the Code ↔ Paper reader above.

badozor/methyltools

License: GPL
State: the link answers, verified on 28 September 2026
Evidence: files inventoried
Commit: f3672603307115dc72a557f082ca84cfa73dde89, 11 February 2016
Size: 11 files
Software Heritage: archived
Found in: the text, “DNA Copy Number Assessment and 1p/19q Codeletion”
Holds: README
Not found: license file, CITATION.cff, environment file, tests, continuous integration, documentation
Availability: 1 check, the latest on 28 September 2026: the link answers
  • 28 September 2026: the link answers
1 file
At the source: github.com/badozor/methyltools

Tracing map

Proposed by the machine: these links were found in the paper and verified at the source, without human review. The map will receive a Zenodo DOI once one of the paper's authors has validated it with their ORCID.

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  • 1 repository of the authors' code, each at its verified commit, with its license and how the link was found in the paper;
  • 0 scripts, each with its path and the digest of its content;
  • no match between paragraphs and code yet;
  • neither the text of the paper nor the code itself.

Its JSON (tracing-map.json) is deposited on Zenodo with its DOI once the map is validated.

Data

Datasets cited

Other data links

Data Availability

Due to privacy reasons the RNA sequencing data will be made available upon reasonable request under a Data Transfer Agreement. The methylome data from the Montpellier cohort are available under the GEO accession number GSE279950 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi? acc=GSE279950 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE279950)). The external datasets used comprised methylome and RNA sequencing (Level 3) data from the LGG dataset of The Cancer Genome Atlas dbGaP accession number phs000178.v9.p8; http://cancergenome.nih.gov).

Reproduced under the paper's license (CC BY-NC), from the paper cited above.

Versions

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Version 1, 28 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 9 authors, 3 keywords, 18 MeSH terms, 2 funders, 41 references.

Cite

This paper

Darlix, A., Bady, P., Deverdun, J., Bars, E. L., Coget, A., Meriadec, J., Carrière, M., Duffau, H., & Hegi, M. E. (2026). Distinct molecular profiles characterize the spontaneous growth rate of IDHmt low-grade astrocytomas and oligodendrogliomas. Neuro-oncology, 28(4), 911-922. https://doi.org/10.1093/neuonc/noaf296

BibTeX

@article{darlix2026distinct,
author = {Darlix, Amélie and Bady, Pierre and Deverdun, Jérémy and Bars, Emmanuelle Le and Coget, Arthur and Meriadec, Justine and Carrière, Mathilde and Duffau, Hugues and Hegi, Monika E},
title = {{Distinct molecular profiles characterize the spontaneous growth rate of IDHmt low-grade astrocytomas and oligodendrogliomas}},
journal = {Neuro-oncology},
year = {2026},
month = apr,
volume = {28},
number = {4},
pages = {911--922},
publisher = {Oxford University Press},
issn = {1522-8517},
doi = {10.1093/neuonc/noaf296},
url = {https://doi.org/10.1093/neuonc/noaf296},
pmid = {41460180},
pmcid = {PMC13128452}
}

RIS

TY - JOUR
AU - Darlix, Amélie
AU - Bady, Pierre
AU - Deverdun, Jérémy
AU - Bars, Emmanuelle Le
AU - Coget, Arthur
AU - Meriadec, Justine
AU - Carrière, Mathilde
AU - Duffau, Hugues
AU - Hegi, Monika E
TI - Distinct molecular profiles characterize the spontaneous growth rate of IDHmt low-grade astrocytomas and oligodendrogliomas
T2 - Neuro-oncology
J2 - Neuro Oncol
PY - 2026
DA - 2026/04/01
VL - 28
IS - 4
SP - 911
EP - 922
SN - 1522-8517
PB - Oxford University Press
DO - 10.1093/neuonc/noaf296
UR - https://doi.org/10.1093/neuonc/noaf296
LA - en
ER -

CSL-JSON

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