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Record W2492313905 · doi:10.1158/1538-7445.am2016-3585

Abstract 3585: KIF11 silencing or inhibition induces chromosome instability

2016· article· en· W2492313905 on OpenAlexaff
Yasamin Asbaghi, Zelda Lichtensztejn, Laura L. Thompson, Kirk J. McManus

Bibliographic record

VenueCancer Research · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicrotubule and mitosis dynamics
Canadian institutionsResearch Institute in Oncology and HematologyUniversity of Manitoba
Fundersnot available
KeywordsGene silencingChromosome instabilityPropidium iodideBiologyDAPIMolecular biologyCancer researchFlow cytometryCancerGeneticsGeneChromosomeApoptosisProgrammed cell death

Abstract

fetched live from OpenAlex

Abstract Chromosome Instability (CIN) is defined as an increase in the rate at which whole chromosomes or large parts are gained or lost. CIN is not only associated with virtually all tumor types, but it is associated with aggressive tumors, the acquisition of multi-drug resistance and consequently poor patient prognosis. Despite these associations, the genes and molecular defects that contribute to CIN are only poorly understood. Recently, we performed a high content screen that identified KIF11, a microtubule associated motor protein, as a candidate CIN gene. Here, we couple RNAi-based gene silencing with biochemistry and cell biology to show that diminished KIF11 expression and/or function induce CIN. HCT116 cells were employed, as they are a karyotypically stable colorectal cancer cell line of epithelial origin that has been used for similar CIN studies. KIF11 was either silenced (both individual and pooled siRNA duplexes) or inhibited (Monostrol) and expression levels were determined by Western blots. To determine whether KIF11 silencing or inhibition affects DNA content, two phenotypes frequently associated with CIN, namely increases in nuclear area and micronucleus formation were evaluated. Fluorescence microscopy was employed on DAPI-counterstained samples and revealed statistically significant increases both nuclear area and micronucleus formation following KIF11 silencing and inhibition relative to controls. Next, flow cytometry was performed on propidium iodide labeled samples to assess whether increases in DNA content were associated with the changes in nuclear area. As predicted, increases in the proportion of cells with >G2/M DNA content occurred within the KIF11 silenced populations. Finally, mitotic chromosome spreads were generated and chromosomes were manually enumerated from 100 spreads per condition/control. Subsequent Kolmogorov-Smirnov tests identified statistically significant increases in the cumulative distribution frequencies of mitotic chromosome numbers within the spreads generated from the KIF11 silenced cells relative to controls. To extend our findings beyond the colorectal cancer cell context employed above, analogous studies were performed in hTERT cells (karyotypically stable fibroblast cell line) with very similar results. Collectively, these data indicate that KIF11 expression and function are normally required to maintain genome integrity. They further suggest that the loss of KIF11 expression and/or function may be a contributing factor in the etiology of tumorigenesis in colorectal cancer and perhaps other tumor types as well. Citation Format: Yasamin Asbaghi, Zelda Lichtensztejn, Laura Thompson, Kirk McManus. KIF11 silencing or inhibition induces chromosome instability. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 3585.

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 score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.063
GPT teacher head0.372
Teacher spread0.309 · 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
Published2016
Admission routes1
Has abstractyes

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