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Record W3047405871 · doi:10.1158/1538-7445.pedca19-a62

Abstract A62: A cerebral organoid model of pediatric glioma

2020· article· en· W3047405871 on OpenAlexaboutno aff
Amin Ismail, Demis Balamatsias

Bibliographic record

VenueCancer Research · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPluripotent Stem Cells Research
Canadian institutionsnot available
Fundersnot available
KeywordsATRXOrganoidBiologyEpigeneticsInduced pluripotent stem cellCancer researchEmbryonic stem cellGliomaCancerBrain tumorPathologyCell biologyMedicineMutationGeneticsGene

Abstract

fetched live from OpenAlex

Abstract Glioblastoma is the most devastating brain cancer with dismal prognosis both in adults and children and accounts for 16% of primary brain tumors. Despite aggressive therapeutic approaches, the majority of patients die within one year after diagnosis. Current in vivo modeling of glioblastoma involves xenografts either of cultured cell lines or human biopsies transplanted into mice. These models do not faithfully recapitulate the complex biology/pathogenesis of cancer. Here we used human pluripotent embryonic stem cells (or young children fibroblast-driven induced pluripotent stem cells) to create 3D structures with histology reminiscent of human fetal brain (the so-called cerebral organoids). Cerebral organoids combine the accurate multilineage differentiation and physiology of a developing brain with the easiness of manipulation of an in vitro system. We engineered these mini-brains to develop tumors by forced expression of combinations of epigenetic and genetic hits that have previously been shown to drive pediatric glioblastoma multiform (GMB). These include the expression of a mutant histone H3 variant H3F3A (mutated at K27M or G34R) or a gain of function of a mutant form of isocitrate dehydrogenase (IDH1R132H) in combination with the loss of ATRX histone remodeling factor and/or p53 tumor suppressor. Lentiviral transfection was used to express combination of these genetic and epigenetic hits into cerebral organoids. The mutated organoids exhibited tumorigenic growth that was histologically characterized. For example, the expression of H3K27M in combination with loss of both p53 and ATRX showed a remarkable dysplasia reminiscent of primary glioblastoma. Moreover, these organoids exhibited tumor rosette structures resembling those found in ependymoma. In contrast, organoids expressing K27M alone did not show such structures. Interestingly, IDH1R132H combined with p53 and ATRX loss resulted in different tumor morphology, suggestive of a possibility to model oncogenic dependence in pediatric GBM. Cerebral organoids could also be used as a model to study tumor invasion starting with glioma stem-like cells (GSCs, which are believed to be the tumor-initiating cells in GBM). Interestingly, the GSC cell line 923 (which does not invade mouse brain in vivo) invaded and formed a focal lesion in a cocultured organoid. The organoid-based cancer model presented here carries a promising potential to uncover the initiation and pathogenesis of pediatric tumors early in the developing brain. Note: This abstract was not presented at the conference. Citation Format: Amin Ismail, Demis Balamatsias. A cerebral organoid model of pediatric 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 A62.

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 score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.081
GPT teacher head0.364
Teacher spread0.283 · 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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