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Record W1829681352 · doi:10.18632/oncotarget.4817

Genome-wide RNAi analysis reveals that simultaneous inhibition of specific mevalonate pathway genes potentiates tumor cell death

2015· article· en· W1829681352 on OpenAlex
Aleksandra A. Pandyra, Peter Mullen, Carolyn A. Goard, Elke Ericson, Piyush Sharma, Manpreet Kalkat, Rosemary Yu, Janice T. Pong, Kevin R. Brown, Traver Hart, Marinella Gebbia, Karl S. Lang, Guri Giaever, Corey Nislow, Jason Moffat, Linda Z. Penn

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueOncotarget · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Lipids, and Metabolism
Canadian institutionsUniversity of British ColumbiaPrincess Margaret Cancer CentreUniversity of Toronto
FundersCure Brain Cancer FoundationUniversity of Pennsylvania
KeywordsMevalonate pathwayRNA interferenceCancerMedicineSmall hairpin RNACancer researchApoptosisGene knockdownBiologyGeneGeneticsInternal medicineRNA

Abstract

fetched live from OpenAlex

// Aleksandra A. Pandyra 1, 2, 4 , Peter J. Mullen 1 , Carolyn A. Goard 1, 2 , Elke Ericson 3, 5 , Piyush Sharma 4 , Manpreet Kalkat 1, 2 , Rosemary Yu 1, 2 , Janice T. Pong 1, 2 , Kevin R. Brown 3 , Traver Hart 3 , Marinella Gebbia 3 , Karl S. Lang 4 , Guri Giaever 3, 6 , Corey Nislow 3, 6 , Jason Moffat 3 , Linda Z. Penn 1, 2 1 Princess Margaret Cancer Centre, Toronto, ON, Canada 2 Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada 3 Donnelly Centre and Banting & Best Department of Medical Research, University of Toronto, Toronto, Canada 4 Institute of Immunology, Medical Faculty, University of Duisburg-Essen, Essen, Germany 5 Now located at AstraZeneca R&D, Mölndal Sweden 6 Now located at Faculty of Pharmaceutical Sciences, University of British Columbia, Vancouver, BC, Canada Correspondence to: Linda Z. Penn, e-mail: lpenn@uhnres.utoronto.ca Keywords: SREBP2, statins, mevalonate pathway, feedback inhibition, tumor metabolism Received: June 17, 2015      Accepted: August 12, 2015      Published: August 22, 2015 ABSTRACT The mevalonate (MVA) pathway is often dysregulated or overexpressed in many cancers suggesting tumor dependency on this classic metabolic pathway. Statins, which target the rate-limiting enzyme of this pathway, 3-hydroxy-3-methylglutaryl-CoA reductase (HMGCR), are promising agents currently being evaluated in clinical trials for anti-cancer efficacy. To uncover novel targets that potentiate statin-induced apoptosis when knocked down, we carried out a pooled genome-wide short hairpin RNA (shRNA) screen. Genes of the MVA pathway were amongst the top-scoring targets, including sterol regulatory element binding transcription factor 2 (SREBP2), 3-hydroxy-3-methylglutaryl-coenzyme A synthase 1 (HMGCS1) and geranylgeranyl diphosphate synthase 1 (GGPS1). Each gene was independently validated and shown to significantly sensitize A549 cells to statin-induced apoptosis when knocked down. SREBP2 knockdown in lung and breast cancer cells completely abrogated the fluvastatin-induced upregulation of sterol-responsive genes HMGCR and HMGCS1. Knockdown of SREBP2 alone did not affect three-dimensional growth of lung and breast cancer cells, yet in combination with fluvastatin cell growth was disrupted. Taken together, these results show that directly targeting multiple levels of the MVA pathway, including blocking the sterol-feedback loop initiated by statin treatment, is an effective and targetable anti-tumor strategy.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.509
Threshold uncertainty score0.907

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.016
GPT teacher head0.232
Teacher spread0.215 · 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