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Record W4213328697 · doi:10.1101/2022.02.15.479934

Rock inhibitors target <i>SRSF2</i> leukemia by disrupting cell mitosis and nuclear morphology

2022· preprint· en· W4213328697 on OpenAlexaff
Ming Su, T.A. Fleisher, Inna Grosheva, Melanie Bokstad Horev, Malgorzata Olszewska, Haim Barr, A.N. Plotnikov, Sílvia Carvalho, Yoni Moskovich, MD Minden, Noa Chapal-Ilani, EP Papapetrou, Nili Dezorella, Tao Cheng, Nathali Kaushansky, B Geiger, LI Shlush

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2022
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicNuclear Structure and Function
Canadian institutionsPrincess Margaret Cancer CentreUniversity Health Network
FundersNational Institutes of HealthBIRAXNational Natural Science Foundation of ChinaIsrael Science FoundationRising Tide FoundationWeizmann Institute of ScienceApplebaum FoundationLeukemia and Lymphoma Society
KeywordsMitosisCell biologyNuclear poreMicrotubuleBiologyNucleoporinNuclear transportMitotic catastropheInterphaseMyeloid leukemiaCancer researchCellCytoplasmCell nucleusGeneticsCell cycle

Abstract

fetched live from OpenAlex

Abstract Spliceosome machinery mutations are common early mutations in myeloid malignancies, however effective targeted therapies against them are still lacking. In the current study, we used an in vitro high-throughput drug screen among four different isogenic cell lines and identified ROCK inhibitors (ROCKi) as selective inhibitors of SRSF2 mutants. ROCKi targeted SRSF2 Mut primary human samples in a xenografts model and were not toxic to mice nor human cells. ROCKi induced mitotic catastrophe through their apparent effects on microtubules and nuclear organization. Transmission electron microscopy revealed that SRSF2 mutations induce deep nuclear indentation and segmentation, driven by microtubule-rich cytoplasmic intrusions, which were exacerbated by ROCKi. The severe nuclear deformation driven by the combination of SRSF2 Mut and ROCKi prevent cells from completing mitosis. These findings shed light on new ways to target SRSF2 and on the role of the microtubule system in SRSF2 Mut cells.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.373
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.004
GPT teacher head0.182
Teacher spread0.178 · 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 teacher head, not a consensus.

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
Published2022
Admission routes1
Has abstractyes

Explore more

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