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Abstract 1739: Diminished<i>SKP1</i>or<i>CUL1</i>expression induces chromosome instability in high-grade serous ovarian cancer precursor cells

2019· article· en· W2953961461 on OpenAlexaff
Chloe C. Lepage, Mark W. Nachtigal, Kirk J. McManus

Bibliographic record

VenueMolecular and Cellular Biology / Genetics · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicUbiquitin and proteasome pathways
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsCancer researchUbiquitin ligaseGenome instabilityBiologyCyclin DCell cycleCyclin D2Serous fluidCyclin E1CancerCyclinMedicineDNA damageUbiquitinInternal medicineGeneticsGeneDNA

Abstract

fetched live from OpenAlex

High-grade serous ovarian cancer (HGSOC) is the most common ovarian cancer subtype as well as the most lethal. High mortality rates associated with HGSOC are in part due to a lack of reliable early detection methods and effective therapies. Importantly, chromosome instability (CIN; an increased rate of chromosome gains or losses), is causally implicated in cancer development, progression, and resistance to treatment, and is just beginning to be evaluated in an HGSOC context. Overexpression of Cyclin E1 protein induces CIN and genomic amplification contributes to HGSOC pathogenesis in 20% of HGSOC patients. Cyclin E1 protein levels are normally regulated in a cell cycle-dependent manner by the SCF (SKP1-CUL1-FBOX) complex, an E3 ubiquitin ligase that targets substrates for proteolytic degradation. In cases where genomic amplification is absent, we hypothesize that loss of SCF complex function stemming from diminished expression of individual SCF complex components underlies increases in Cyclin E1 levels and induces CIN. The current study focuses on the SCF complex components SKP1 and CUL1 and characterizes their role in early HGSOC pathogenesis within a fallopian tube secretory epithelial cell model (FT; a cell of origin for HGSOC). Using siRNA-based approaches, we show that diminished SKP1 and CUL1 expression results in increased Cyclin E1 protein levels in FT cells. Using quantitative imaging microscopy techniques, we further identify statistically significant changes in CIN-associated phenotypes within the silenced populations, including changes in nuclear areas, increases in micronucleus formation (i.e. small DNA-containing bodies outside of the primary nucleus), and increases in numerical chromosome abnormalities identified in mitotic chromosome spreads. Thus, the current study explores the early origins of HGSOC and identifies SKP1 and CUL1 as two promising new molecular players that may contribute to CIN to drive FT cell transformation, drug resistance and disease recurrence.Citation Format: Chloe C. Lepage, Mark W. Nachtigal, Kirk J. McManus. Diminished SKP1 or CUL1 expression induces chromosome instability in high-grade serous ovarian cancer precursor cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1739.

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 score0.010

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)0.0030.001

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 head0.012
GPT teacher head0.244
Teacher spread0.232 · 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
Published2019
Admission routes1
Has abstractyes

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