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Record W4404230874 · doi:10.1093/neuonc/noae165.0629

IMMU-36. MULTI-OMIC CHARACTERIZATION OF A SYNGENEIC MOUSE CANCER STEM CELL MODEL OF GBM FOR PRECLINICAL APPLICATIONS

2024· article· en· W4404230874 on OpenAlexaff
Kyle Heemskerk, Samir Assaf, Xiaoguang Hao, Mathieu Meode, Smriti Kala, James M. Pemberton, Reza Mirzaei, J. Gregory Cairncross, Peter Forsyth, V. Wee Yong, Samuel Weiss, Franz J. Zemp, H. Artee Luchman

Bibliographic record

VenueNeuro-Oncology · 2024
Typearticle
Languageen
FieldMedicine
TopicCancer Cells and Metastasis
Canadian institutionsCanadian Standards AssociationUniversity of Calgary
Fundersnot available
KeywordsCancerCancer researchComputational biologyCancer stem cellBiologyGenetics

Abstract

fetched live from OpenAlex

Abstract Glioblastoma (GBM) is resistant to many therapies including immunotherapies. There is an urgent need to explore the role of the microenvironment in resistance to therapy with tailored pre-clinical models. Using multi-omic approaches we describe a syngeneic cancer stem cell mouse model of GBM, with a spontaneous amplification of Igf2. We investigate whether Igf2 influences tumour and microenvironment cells to promote immunosuppression in GBM. Three cell lines were previously established from spontaneous brain tumours in C57Bl/6 Trp53+/-/Nf1+/- mice and maintained under neural stem cell culture conditions. Whole genome sequencing (WGS) was used to determine single nucleotide, copy number, and structural variation, revealing loss of both copies of Trp53 and Nf1 in all three cell lines. However only one cell line, mBT0309, developed tumors when orthotopically allografted. Analysis of genomic alterations and transcriptomics revealed that mBT309 exhibits amplification of the Igf2 loci and overexpression was confirmed at the RNA and protein level. Spatial and single cell transcriptomics showed that Igf2 is overexpressed in mBT0309 allografted tumours and correlated with specific transcriptomic programs. A high-parameter Imaging Mass Cytometry (IMCTM) panel was used for spatial proteomic analysis, to monitor the development of tumours in a time-course experiment. In vitro growth characteristics and stem marker expression in both transcriptomic and spatial IMC data suggest that high levels of Igf2 may regulate GBM stemness features. Analysis of human GBM datasets revealed that Igf2 amplified tumours have reduced CXCL11 expression. These findings suggest that high levels of Igf2 may influence immunosuppression by reducing T-cell recruitment. This syngeneic immunocompetent GBM stem cell model harbouring Igf2 amplification adds to the suite of models to study the GBM microenvironment and its role in immunosuppression and resistance to therapy.

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)0.001
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 score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.002

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 head0.076
GPT teacher head0.377
Teacher spread0.301 · 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
Published2024
Admission routes1
Has abstractyes

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