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Record W3047362268 · doi:10.1158/1538-7445.pedca19-b06

Abstract B06: Candidate differentiation stall in epithelial mesenchymal transition in H3K27M diffuse midline glioma

2020· article· en· W3047362268 on OpenAlexaboutno aff
Allison Cheney, Lauren Sanders, Lucas Seninge, Holly C. Beale, Ellen Kephart, Jacob Pfeil, Katrina Learned, A. Geoffrey Lyle, Isabel Bjork, David Haussler, Sofie R. Salama, Olena M. Vaske

Bibliographic record

VenueCancer Research · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer-related molecular mechanisms research
Canadian institutionsnot available
Fundersnot available
KeywordsCarcinogenesisGliomaBiologyEpithelial–mesenchymal transitionCancer researchGenePathologyMedicineTransition (genetics)Genetics

Abstract

fetched live from OpenAlex

Abstract The purpose of our study was to elucidate the molecular mechanisms by which the histone H3 K27M mutation drives tumorigenesis of pediatric gliomas. Though it has potential implications on the treatment of diffuse midline glioma as a disease driver, the timing, cell type of origin, and effect of the H3K27M mutation on early embryonic brain development are not fully characterized. Here, we performed differential expression analysis on a cohort of H3K27M and H3WT pediatric gliomas, revealing that genes in the epithelial-mesenchymal transition (EMT) pathway were significantly differentially expressed. SNAI1, the EMT master regulator, was significantly overexpressed in the H3K27M tumor cohort. Overall, pre-EMT genes were overexpressed in H3K27M tumors while post-EMT genes were underexpressed. We hypothesized that H3K27M may lead to gliomagenesis by stalling an EMT in early brain development and employed single-cell and bulk RNA sequencing data from cerebral organoids at multiple developmental timepoints to test this hypothesis. We observed that a long noncoding RNA (lncRNA) signature identified as transiently expressed in early brain development was preferentially expressed in H3K27M tumors. Cell type-specific lncRNA signatures had higher expression in H3K27M tumors for pre-EMT cell types, and higher expression in H3WT tumors for post-EMT cell types. Finally, t-SNE clustering of single-cell glioma RNA sequencing data with single-cell organoid data revealed transcriptional similarities between H3K27M and pre-EMT neural stem cells. In conclusion, we observed aberrant activity of the EMT in H3K27M gliomas. Our data suggest that the H3K27M mutation is associated with a pre-EMT cell phenotype, and that this mutation may cause EMT arrest or de-differentiation. Citation Format: Allison R. Cheney, Lauren M. Sanders, Lucas Seninge, Holly C. Beale, Ellen Towle Kephart, Jacob Pfeil, Katrina Learned, A. Geoffrey Lyle, Isabel Bjork, David Haussler, Sofie R. Salama, Olena M. Vaske. Candidate differentiation stall in epithelial mesenchymal transition in H3K27M diffuse midline glioma [abstract]. In: Proceedings of the AACR Special Conference on the Advances in Pediatric Cancer Research; 2019 Sep 17-20; Montreal, QC, Canada. Philadelphia (PA): AACR; Cancer Res 2020;80(14 Suppl):Abstract nr B06.

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: Bench or experimental · Consensus signal: Bench or experimental
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
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.035
GPT teacher head0.348
Teacher spread0.312 · 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 designBench or experimental
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

Citations0
Published2020
Admission routes1
Has abstractyes

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