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Record W4392005970 · doi:10.1055/s-0044-1779839

DNA Methylation Subgroup and CNV Predict Response to Radiotherapy

2024· article· en· W4392005970 on OpenAlexaff
Andrew Ajisebutu, Jeffery Zucatto, Vikas Patil, Gelareh Zadeh

Bibliographic record

VenueJournal of Neurological Surgery Part B Skull Base · 2024
Typearticle
Languageen
FieldMedicine
TopicLung Cancer Diagnosis and Treatment
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDNA methylationComputer scienceDNAMethylationComputational biologyBiologyGeneticsGeneGene expression

Abstract

fetched live from OpenAlex

Background: Chordomas are rare aggressive primary bone cancers affecting the skull-base and spine. Standard of care treatment includes radical surgical resection and radiotherapy. Despite this, the overall survival at 10 years is only 40%, with most patients experiencing disease recurrence. Radiotherapy is a cornerstone in the treatment of chordomas, however the impact of radiotherapy remains incompletely described: not all patients appear to benefit, and many studies fail to replicate the finding of improvement in overall survival. Herein, we utilized our previously described DNA Methylation subgroups to examine sensitivity to radiation. Methods: We utilized a well annotated dataset of 68 patients from a multi-institutional 20-year series who had undergone whole genome DNA methylation profiling on the Illumina EPIC array. Copy number variance (CNVs) were extracted from the raw methylation data after normalization, with median intensity values calculated and converted to amplification and deletions defined as a log2 copy number ratio of over .3. Multivariable cox analysis and Kaplan Meyer analysis were then completed. Results: Within our cohort we found that patients with a cellular molecular subtype who had received radiation had a significantly improved overall survival on cox multivariate analysis (median survival 17.3 years, p = 0.0208) when compared to patients with a immune-infiltrative (median survival 6.0 years). The favorable nature of the cellular molecular subtype appeared to diminish if radiation was not given (median survival 1 year). This improvement in survival did not appear to be fully explained by simply delayed progression, as progression-free survival between irradiated immune-infiltrative and cellular subtypes did not differ significantly (p = 0.65). A panel of 30 target genes were investigated through CNV analysis for association with this phenomenon, for which 3 were identified: FGFR-1 heterozygous deletion ( p = 1.74e-6), GLI2 heterozygous deletion ( p = 0.0103) and KRAS homozygous amplification ( p = 0.0134). Conclusion: Overall, molecular subtype predicted through DNA methylation influenced the response to radiotherapy: patients with a cellular subtype have improved survival overall, which appears to be partially mediated through response to and enhanced response to radiotherapy which does not appear to be shared with their immune-infiltrative counterparts. Moreover, three target genes have been identified as potential targets that may be exploited to improve potentiate radiosensitivity in chordoma. Publication History Article published online: 05 February 2024 © 2024. Thieme. All rights reserved. Georg Thieme Verlag KG Rüdigerstraße 14, 70469 Stuttgart, Germany

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.032
GPT teacher head0.300
Teacher spread0.268 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2024
Admission routes1
Has abstractyes

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