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Record W2025569005 · doi:10.1158/1535-7163.targ-11-a22

Abstract A22: A genome-wide shRNA screen identifies α/β hydrolase domain containing 4 (ABHD4) as a novel regulator of anoikis resistance.

2011· article· en· W2025569005 on OpenAlexaff
Craig D. Simpson, Rose Hurren, Neil MacLean, Yanina Eberhard, Troy Ketela, Jason Moffat, Aaron D. Schimmer

Bibliographic record

VenueMolecular Cancer Therapeutics · 2011
Typearticle
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsUniversity of TorontoOntario Institute for Cancer Research
Fundersnot available
KeywordsAnoikisSmall hairpin RNAGene knockdownBiologyPopulationMolecular biologyProgrammed cell deathCell cultureCell biologyCancer researchGeneticsApoptosisMedicine

Abstract

fetched live from OpenAlex

Abstract Acquisition of resistance to anchorage dependant cell death, a process termed anoikis, is a requirement for cancer cell metastasis. However, the molecular determinants of anoikis resistance and sensitivity are poorly understood. To better understand resistance to anoikis we conducted a genome wide lentiviral shRNA screen to identify genes whose knockdown render RWPE-1 prostate cells resistant to anoikis. RWPE-1 cells are a non-malignant prostate cell line that undergo cell death upon detachment from extracellular matrix. To identify genetic regulators of anoikis, RWPE-1 cells were infected with a pooled lentiviral hairpin shRNA library with 54,021 hairpins targeting 11,255 genes. After infection, cells were cultured in suspension conditions for three weeks and an anoikis-resistant cell population was selected. From this population, genomic DNA was isolated and shRNA sequences were amplified and sequenced. Thirty four shRNA sequences reproducibly protected RWPE-1 cells from anoikis after culture under suspension conditions. We selected α/β hydrolase domain containing 4 (ABHD4) for further analysis as it conferred the greatest protection to anoikis in our screening assays. To validate the effects of ABHD4 knockdown on anoikis resistance, we infected RWPE-1 with 2 independent shRNA targeting ABHD4 or control sequences. We also over-expressed ABHD4 in wild type cells. Finally, we co-infected cells with ABDH4 cDNA and shRNA as a rescue experiment to demonstrate on-target activity. Target knockdown or over-expression after infection was confirmed by Q-RTPCR or immunoblotting. Using two independent shRNA, knockdown of ABHD4 inhibited anoikis as evidence by increased clonogenic growth compared to cells infected with control sequences. Demonstrating an on-target effect, rescue of ABHD4 expression returned levels of clonogenic growth to wild type levels. Finally, over-expression of ABHD4 increased sensitivity to anoikis and less clonogenic growth was observed in these cells compared to control cells. Resistance to anoikis after ABHD4 knockdown was associated with decreased cleavage of PARP and decreased activation of caspases-3, 8 and 9, but was independent in changes of FLIP expression. Interesting, resistance to anoikis after ABHD4 knockdown was independent of the known role of ABHD4 in the anandamide synthesis pathway and the generation of glycerophospho-N-acyl ethanolamines. Thus, reductions in the levels of ABHD4 confer resistance to anoikis while over-expression of the target enhances anoikis in the anoikis-sensitive cell line RWPE-1. As such, we have identified a novel genetic regulator of anoikis sensitivity. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2011 Nov 12-16; San Francisco, CA. Philadelphia (PA): AACR; Mol Cancer Ther 2011;10(11 Suppl):Abstract nr A22.

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 score0.001
Threshold uncertainty score0.005

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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.037
GPT teacher head0.302
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".

Quick stats

Citations0
Published2011
Admission routes1
Has abstractyes

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