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Abstract A012: Targeting proteasome vulnerabilities for the treatment of monosomy 7 associated blood disorders

2024· article· en· W4399505345 on OpenAlexaboutno aff
Haijiao Zhang, Basil Allen, Daniel Bottomly, Peter Ryabinin, Schannon K. Mcweeney

Bibliographic record

VenueMolecular Cancer Therapeutics · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Degradation and Inhibitors
Canadian institutionsnot available
Fundersnot available
KeywordsHaploinsufficiencyBiologyGene dosageProteasome inhibitorCancer researchGene expression profilingMonosomyGeneticsProteasomeGene expressionGenePhenotypeChromosomeKaryotype

Abstract

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Abstract Monosomy 7 is among the most frequent cytogenetic abnormalities in hematological disorders and is associated with short survival and drug resistance. Despite its high prevalence and detrimental impact, the therapeutic vulnerabilities underlying monosomy 7-associated blood disorders remain largely elusive, impeding progress toward improved patient care. The homeostatic cellular requirement for a normal dosage of essential genes creates an opportunity to target vulnerabilities that arise due to reduced levels of proteins encoded by a haploinsufficient essential gene. Briefly, the loss of one copy of a dosage-sensitive essential gene (gene X), in combination with the inhibition of itself or a related gene (gene Y), or an associated pathway results in lethal consequences for cells. The remarkable and selective clinical efficacy of lenalidomide for the treatment of del(5q) MDS has demonstrated how allelic haploinsufficiency underlies the sensitivity to this drug by synthetic lethality. Differential expression analysis of gene and protein expression in primary AML samples with monosomy 7 revealed significant downregulation of multiple proteasome pathway members at the protein level, but not at the RNA level. Primary AML samples with -7/del(7q) exhibited increased sensitivity (low IC50) to the proteasome inhibitor bortezomib, as evidenced by two independent ex vivo drug screening cohorts (the Beat AML and the FIMM study). Chromosome 7 harbors four proteasome subunits, PSMA2, PSMC2, PSMG3, and SEM1. We performed gene expression, protein expression, copy number analysis, and individual gene knockout experiments. The results have revealed PSMA2 to be a haploinsufficient essential gene on chromosome 7. PSMA2 knockout confers leukemia a growth disadvantage for multiple AML cell clines in both TP53 wild-type and knockout backgrounds. We generated PSMA2 isogenic hemizygous deletion and diploid single-cell clones. PSMA2 hemizygous deletion cells exhibited approximately half the protein expression compared to diploid controls, confirming that PSMA2 is a haploinsufficient gene. PSMA2hemizygous deletion single-cell clones showed significantly enhanced sensitivity to all three evaluated proteasome inhibitors (bortezomib, ixazomib, and carfilzomib), aligning with the sensitivity observed in primary -7/del(7q) leukemia samples. PSMA2 hemizygous deletion cell clones displayed increased p38 and decreased pERK levels upon treatment with proteasome inhibitors, potentially contributing to their increased sensitivity to proteasome inhibitors. Proteomics analysis and in vivo validation is ongoing. As such, we have identified haploinsufficient essential gene PSMA2 mediated proteasome pathway vulnerability in monosomy 7 associated leukemia and further showed that proteasome inhibitors as promising therapeutic approaches for treating hematological disorders associated with monosomy 7. Citation Format: Haijiao Zhang, Basil Allen, Daniel Bottomly, Peter Ryabinin, Schannon K. Targeting proteasome vulnerabilities for the treatment of monosomy 7 associated blood disorders [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Expanding and Translating Cancer Synthetic Vulnerabilities; 2024 Jun 10-13; Montreal, Quebec, Canada. Philadelphia (PA): AACR; Mol Cancer Ther 2024;23(6 Suppl):Abstract nr A012.

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 score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.017
GPT teacher head0.283
Teacher spread0.266 · 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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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