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Record W3217222663 · doi:10.1093/neuonc/noab196.463

PATH-11. PDGFA INITIATES ABERRANT MITOSIS AND MALIGNANT TRANSFORMATION OF NEURAL PROGENITOR CELLS

2021· article· en· W3217222663 on OpenAlexaff
Michael Blough, Hiba Omairi, Cameron J. Grisdale, J. Gregory Cairncross

Bibliographic record

VenueNeuro-Oncology · 2021
Typearticle
Languageen
FieldMedicine
TopicGlioma Diagnosis and Treatment
Canadian institutionsUniversity of British ColumbiaUniversity of Calgary
Fundersnot available
KeywordsBiologyMitosisProgenitor cellCell biologyPlatelet-derived growth factor receptorGrowth factorCell cycleSubventricular zoneStem cellCancer researchImmunologyCellGeneticsReceptor

Abstract

fetched live from OpenAlex

Abstract BACKGROUND Imagining ways to prevent or treat glioblastoma (GBM) have been hindered by a lack of understanding of its pathogenesis. Although platelet derived growth factor-A (PDGFA) overexpression may be an early event, critical details of the biology of GBM, and tools to study its initiation have been lacking. Indeed, many PDGF-driven models replicate its microscopic appearance, but not genomic architecture. Recently, we reported an in vitro model of GBM initiation that overcomes this barrier to authenticity. METHODS We used a method developed to establish neural stem cell cultures to investigate the effects of PDGF-A on cells derived from the subventricular zone (SVZ), a putative region where the cells of origins for GBM are derived. We micro-dissect SVZ tissue from p53-null and wild-type adult mice, culture cells in media supplemented with PDGF-A, and assess cell viability, proliferation, mitotic capacity, and genome stability. RESULTS Paradoxical to its canonical role as a growth factor, we observe abrupt and substantial cell death in PDGF-A. Abnormal mitosis was the first observable alteration and occurred immediately in cells of both p53 wild-type and null genotypes: wild-type cells did not survive in PDGF-A, whereas a fraction of null cells evade apoptosis. Evading cells displayed attenuated proliferation accompanied by early chromosomal gains and losses. After approximately 100 days in PDGF-A, surviving cells suddenly proliferate rapidly, acquire growth factor independence, and become tumorigenic in immune-competent mice. Transformed cells continue to display highly abnormal mitotic phenotypes with complex karyotypes similar to GBM, had a neural progenitor cell (NPC) lineage profile, and were resistant to PDGFR-alpha inhibition. CONCLUSION Abnormal mitosis induced by PDGF-A initiates and perpetuates the genome instability that transforms p53-null neural progenitor cells to yield cancers with the types of recurring chromosomal gains and losses that characterize human GBM.

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 score0.005

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 head0.023
GPT teacher head0.279
Teacher spread0.256 · 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
Published2021
Admission routes1
Has abstractyes

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