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Record W4404237122 · doi:10.1093/neuonc/noae165.0527

DDDR-42. LEVERAGING GENOME-WIDE CRISPR/CAS9 KNOCKOUT DRUG SCREENS TO IDENTIFY SENSITIZERS FOR PROTEOSOME INHIBITORS IN GLIOBLASTOMA

2024· article· en· W4404237122 on OpenAlexaff
Alisha Anand, Muhammad Vaseem Shaikh, Chirayu Chokshi, Benjamin Brakel, Will Maich, Shan Grewal, Chitra Venugopal, Sheila K. Singh

Bibliographic record

VenueNeuro-Oncology · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Degradation and Inhibitors
Canadian institutionsMcMaster University
Fundersnot available
KeywordsCRISPRGlioblastomaDrug discoveryComputational biologyDrugGenomeDrug targetCancer researchBiologyGeneticsPharmacologyBioinformaticsGene

Abstract

fetched live from OpenAlex

Abstract Glioblastoma (GBM) is the most common primary brain tumor with a poor prognosis despite aggressive treatment. Patient outcomes remain abysmal with 95% of patients relapsing and a median overall survival of 15 months. This necessitates the rapid search for personalized therapeutics and agents to enhance current treatments. One pathway that demonstrates dysregulated functioning is the ubiquitin-proteasome pathway (UPP). Literature has shown that UPP dependent proteolysis remains constitutively upregulated in cancer cells leading to the rapid degradation of proteins that regulate oncogenic pathways. Despite robust preclinical evaluations for the usage of proteasome inhibitors against GBM, most proteasome inhibitors failed in clinical trials, indicating resistance. We conducted an unbiased genome wide CRISPR-Cas9 screen in HAP1 cells treated with the proteasome inhibitor, Bortezomib (BTZ), to identify genes leading to a BTZ-resistant phenotype. We identified several genes that when perturbed, sensitized cells to BTZ including N-glycanase-1 (NGLY-1), Nuclear factor Erythroid 2-Like-1 (NFE2L1), and DNA damage inducible 1 homolog 2 (DDI2). Herein, we sought to evaluate the effects of perturbing these identified genes in our patient derived GBM cell lines by utilizing CRISPR/Cas9 knockout technology in vitro and in vivo. The generation of NGLY-1, DDI2, and NFE2L1 KO cell lines demonstrated functional sensitivity to the proteasome inhibitor Marizomib (MZB) as observed through a significant reduction of the IC50 in the KO cell lines compared to an adeno-associated virus integration site 1 (AAVS1) control. Functional evaluation also demonstrated reduced proliferation capacity and sphere formation in our KO GBM lines. Ongoing in vivo work will aim to evaluate the mitigation of this resistant pathway in our NSG mouse models orthotopically transplanted with our patient derived KO cell lines. In an ongoing collaborative effort, we aim to functionally assess a novel small molecule NGLY-1 inhibitor for preclinical sensitivity to MZB in our in vitro and in vivo models.

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)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.015
GPT teacher head0.305
Teacher spread0.290 · 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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