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Record W4312097582 · doi:10.1101/2022.12.07.519545

Increased mRNA expression of CDKN2A is a transcriptomic marker of clinically aggressive meningiomas

2022· preprint· en· W4312097582 on OpenAlexaff
Justin Z. Wang, Vikas Patil, Jeff Liu, Helin Dogin, Felix Behling, Marco Skardelly, Marcos Tatagiba, Elgin Hoffman, Severa Bunda, Rebecca Yakubov, Ramneet Kaloti, Sebastian Brandner, Andrew Gao, Aaron-Cohen Gadol, Jennifer Barnholtz-Sloan, David R. Raleigh, Felix Sahm, Paul C. Boutros, Ghazaleh Tabatabai, Kenneth Aldape, Farshad Nassiri, Gelareh Zadeh

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2022
Typepreprint
Languageen
FieldMedicine
TopicMeningioma and schwannoma management
Canadian institutionsPrincess Margaret Cancer CentreUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsCDKN2ACancer researchDNA methylationBiologyMethylationMeningiomaTranscriptomeOncologyMessenger RNACancerGene expressionInternal medicineGeneMedicinePathologyGenetics

Abstract

fetched live from OpenAlex

Abstract Background Homozygous loss of CDKN2A/B is a genetic alteration found in many cancer types including meningiomas, where it is associated with poor clinical outcome. It is now also a diagnostic criterion for grade 3 meningiomas in the 2021 WHO classification for central nervous system tumors. However, as in other cancers, the relationship between copy number loss of CDKN2A/B and expression of its gene product is unclear and may be either commensurate or paradoxical in nature. Therefore, we aimed to investigate the association of CDKN2A mRNA expression with clinical prognosis, WHO grade, and other molecular biomarkers in meningiomas such as DNA methylation, molecular group, and proteomics. Methods We used multidimensional molecular data of 490 meningioma samples from 4 independent cohorts to examine the relationship between mRNA expression of CDKN2A and copy number status, its correlation to clinical outcome, the transcriptomic pathways altered in differential CDKN2A expression, and its relationship with DNA methylation, and proteomics using an integrated molecular approach. Results Meningiomas without any copy number loss were dichotomized into high (CDKN2A high ) and low (CDKN2A low ) CDKN2A mRNA expression groups. Patients with CDKN2A high meningiomas had poorer progression free survival (PFS) compared to those with CDKN2A low meningiomas. CDKN2A mRNA expression was increased in more aggressive molecular groups, and in higher WHO grade meningiomas across all cohorts. CDKN2A high meningiomas and meningiomas with CDKN2A copy number loss shared common up-regulated cell cycling pathways. CDK4 mRNA expression was increased in CDKN2A high meningiomas and both p16 and CDK4 protein were more abundant in CDKN2A high meningiomas. CDKN2A high meningiomas were frequently hypermethylated at the gene body and UTR compared to CDKN2A low meningiomas and found be more commonly Rb-deficient. Conclusions An intermediate level of CDKN2A mRNA expression appears to be optimal as significantly low (CDKN2A deleted) or high expression (CDKN2A high ) are associated with poorer outcomes clinically. Though CDK4 is elevated in CDKN2A high meningiomas, Rb-deficiency may be more common in this group, leading to lack of response to CDK inhibitors.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
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 communication0.0000.000
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 head0.020
GPT teacher head0.259
Teacher spread0.238 · 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

Citations8
Published2022
Admission routes1
Has abstractyes

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