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Record W4385153952 · doi:10.1093/braincomms/fcad197

The comparable tumour microenvironment in sporadic and<i>NF2</i>-related schwannomatosis vestibular schwannoma

2023· article· en· W4385153952 on OpenAlexfundno aff
Grace E. Gregory, Adam P. Jones, Michael Haley, Christopher Hoyle, Leo Zeef, I‐Hsuan Lin, David Coope, Andrew T. King, D. Gareth Evans, Pawel Paszek, Kevin N. Couper, David Brough, Omar Pathmanaban

Bibliographic record

VenueBrain Communications · 2023
Typearticle
Languageen
FieldMedicine
TopicNeurofibromatosis and Schwannoma Cases
Canadian institutionsnot available
FundersBiotechnology and Biological Sciences Research CouncilMedical Research Council CanadaManchester Biomedical Research CentreDowager Countess Eleanor Peel TrustMedical Research CouncilNational Institute for Health and Care Research
KeywordsSchwannomaNeurofibromatosis type 2MedicinePathologyAcoustic neuromaAudiology

Abstract

fetched live from OpenAlex

Abstract Bilateral vestibular schwannoma is the hallmark of NF2-related schwannomatosis, a rare tumour predisposition syndrome associated with a lifetime of surgical interventions, radiotherapy and off-label use of the anti-angiogenic drug bevacizumab. Unilateral vestibular schwannoma develops sporadically in non-NF2-related schwannomatosis patients for which there are no drug treatment options available. Tumour-infiltrating immune cells such as macrophages and T-cells correlate with increased vestibular schwannoma growth, which is suggested to be similar in sporadic and NF2-related schwannomatosis tumours. However, differences between NF2-related schwannomatosis and the more common sporadic disease include NF2-related schwannomatosis patients presenting an increased number of tumours, multiple tumour types and younger age at diagnosis. A comparison of the tumour microenvironment in sporadic and NF2-related schwannomatosis tumours is therefore required to underpin the development of immunotherapeutic targets, identify the possibility of extrapolating ex vivo data from sporadic vestibular schwannoma to NF2-related schwannomatosis and help inform clinical trial design with the feasibility of co-recruiting sporadic and NF2-related schwannomatosis patients. This study drew together bulk transcriptomic data from three published Affymetrix microarray datasets to compare the gene expression profiles of sporadic and NF2-related schwannomatosis vestibular schwannoma and subsequently deconvolved to predict the abundances of distinct tumour immune microenvironment populations. Data were validated using quantitative PCR and Hyperion imaging mass cytometry. Comparative bioinformatic analyses revealed close similarities in NF2-related schwannomatosis and sporadic vestibular schwannoma tumours across the three datasets. Significant inflammatory markers and signalling pathways were closely matched in NF2-related schwannomatosis and sporadic vestibular schwannoma, relating to the proliferation of macrophages, angiogenesis and inflammation. Bulk transcriptomic and imaging mass cytometry data identified macrophages as the most abundant immune population in vestibular schwannoma, comprising one-third of the cell mass in both NF2-related schwannomatosis and sporadic tumours. Importantly, there were no robust significant differences in signalling pathways, gene expression, cell type abundance or imaging mass cytometry staining between NF2-related schwannomatosis and sporadic vestibular schwannoma. These data indicate strong similarities in the tumour immune microenvironment of NF2-related schwannomatosis and sporadic vestibular schwannoma.

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 score0.001
Threshold uncertainty score0.003

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.029
GPT teacher head0.282
Teacher spread0.252 · 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".

Quick stats

Citations24
Published2023
Admission routes1
Has abstractyes

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