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Record W4367281579 · doi:10.47611/jsrhs.v12i1.4352

Identification of Target Proteins for Promoting Nuclear Envelope Rupture in Cancer Cells

2023· article· en· W4367281579 on OpenAlexaff
Donghyun Won, Hyunwoo Jin, Serom Kwon, Joon Kim

Bibliographic record

VenueJournal of Student Research · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicNuclear Structure and Function
Canadian institutionsKootenay Association for Science & Technology
FundersMinistry of Science and ICT, South KoreaKorea Advanced Institute of Science and Technology
KeywordsDNA damageLaminDNA repairCancer researchNuclear proteinBiologyCancer cellProgrammed cell deathCell biologyNuclear laminaRNA interferenceCancerApoptosisDNAGeneticsRNAGeneNucleusTranscription factor

Abstract

fetched live from OpenAlex

The nuclear envelope separates and protects DNA from the cytoplasm. In cancer cells, frequent nuclear morphological abnormalities and transient rupture of the nuclear membrane promote DNA damage and cancer malignancy. However, nuclear envelope instability, acting as a tumor-promotion factor, can be viewed as a fatal weakness of cancer cells. Although the exact mechanism is not clear, it is known that the loss of the tumor suppressor gene TP53 is involved in nuclear envelope instability in cancer cells. In this study, we demonstrate that the inhibition of NUP93, which is a subunit of the nuclear pore complex, induces cell death by enhancing nuclear envelope instability. The RNA interference (RNAi) inhibiting NUP93 expression in the human cell line RPE1 caused nuclear envelope rupture, and DNA damage, leading to cell death. Under the condition in which the tumor suppressor gene TP53 was simultaneously suppressed with NUP93, nuclear envelope rupture and DNA damage were significantly increased. Conversely, cell death was slightly decreased. The decrease in cell death may be ascribed to the fact that TP53 is involved in the induction of apoptosis by DNA damage. We speculate that amplification of nuclear envelope instability may induce cancer cell-specific synthetic lethality in the context of TP53-independent nuclear envelope instability. Moreover, our results suggest that nuclear pore proteins can be promising targets for the development of synthetic lethal anticancer drugs.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.134
Threshold uncertainty score0.169

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.053
GPT teacher head0.400
Teacher spread0.347 · 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.

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
Published2023
Admission routes1
Has abstractyes

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