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Record W2883441629 · doi:10.1055/s-0038-1633428

Differential Gene Expression and Pathway Analysis of Radiation-Induced Meningiomas

2018· article· en· W2883441629 on OpenAlexaff
Suganth Suppiah, Jeff Liu, Shirin Karimi, Ken Aldape, Gelareh Zadeh

Bibliographic record

VenueJournal of Neurological Surgery Part B Skull Base · 2018
Typearticle
Languageen
FieldMedicine
TopicMeningioma and schwannoma management
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSequelaMeningiomaGeneBiologyFusion geneGeneticsCancer researchMedicinePathology

Abstract

fetched live from OpenAlex

Background Radiation-induced meningiomas (RIMs), a long-term sequela of cranial radiation therapy, are often clinically more aggressive and develop as multiple distinct tumors. Biologically, RIMs have been shown to have a distinct genomic landscape compared with their sporadic counterparts. Notably, RIMs have a lower frequency of NF2 mutations and absence of mutations in TRAF7, KLF4, PIK3CA, and SMO, which are commonly observed in sporadic meningiomas. A subset of RIMs has large genomic rearrangements resulting in NF2 inactivation through a fusion event with a reciprocal gene. We aimed to compare and contrast the clinical and biological profiles of RIMs with and without the NF2-fusion event. Methods A comprehensive clinical database of 50 RIMs was created. Seven RIMs with NF2 fusion and 12 RIMs with wild-type NF2 underwent RNA sequencing on the Illumina HiSeq platform. RNA-seq expression profiles were analyzed using edgeR, available through BioConductor, and Gene Set Enrichment Analysis was performed using Cytoscape. Differential gene expression presented as log2 of fold change (logFC). Immunohistochemistry (IHC) was performed on formalin-fixed paraffin-embedded tissue samples to validate differentially expressed genes identified in pathway analysis. Results IGF-1 (logFC = 4.14, p = 2.65E-05), MME (logFC = 3.03, p = 3.56E-03), MMP16 (logFC = 2.47, p = 8.14E-03), and AQP1 (logFC = 2.33, p = 1.19E-03) were among the top genes overexpressed in RIMs with NF2 fusion. Pathway analysis from gene expression data identified increased activity of immune and inflammatory pathways. IHC staining identified decreased expression of PD-L1 in NF2-fusion RIMs compared with NF2 wild-type RIMs (10 vs. 45%). In contrast, CCL2 had increased expression in NF2-fusion RIMs (60 vs. 10%). Imaging analysis also demonstrated a 3.8× faster growth rate in NF2-fusion RIMs compared with NF2 wild type. Conclusion RIMs with the NF2-fusion event have a distinct gene expression profile, with upregulation of inflammatory pathways. Possibly, the increased inflammatory activity in NF2-fusion RIMs may play a role in growth rate and aggressiveness of tumor. Further studies need to be performed to validate these findings using immunohistochemistry.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.048
GPT teacher head0.268
Teacher spread0.221 · 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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Citations1
Published2018
Admission routes1
Has abstractyes

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