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Identification of FZD5 as Genetic Vulnerability in <i>RNF43</i> Mutant Cancer

2018· article· en· W3173540831 on OpenAlexafffundabout
Zachary Steinhart, Zvezdan Pavlovic, Megha Chandrashekhar, Keith Mascall, Traver Hart, Xiaowei Wang, Xiaoyu Zhang, Kevin R. Brown, Jarrett Adams, James Pan, Sachdev S. Sidhu, Jason Moffat, Stéphane Angers

Bibliographic record

VenueThe FASEB Journal · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics and Neurodevelopmental Disorders
Canadian institutionsUniversity of Toronto
FundersUniversity of Toronto
KeywordsWnt signaling pathwayBiologyMutantFrizzledCancer researchCancerGeneGenetics

Abstract

fetched live from OpenAlex

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers and novel effective treatments are greatly needed. Recent research revealed that a subset of PDAC cell lines is dependent on the Wnt cell‐signaling pathway for cell proliferation and survival. Wnt‐dependent PDAC all contain mutations in the gene encoding RNF43 . RNF43 acts as a negative regulator of the Wnt pathway through ubiquitination and degradation of the Frizzled (FZD) family of Wnt receptors. RNF43 mutation status may therefore serve as a suitable biomarker for targeted therapy against the Wnt pathway in PDAC. In order to find novel genetic vulnerabilities in RNF43 mutant PDAC, we used genome‐wide CRISPR/Cas9 knockout screens in RNF43 mutant and wild‐type PDAC cell lines. Comparison of essential genes between RNF43 mutant and wild‐type groups was used to find context‐dependent essential genes for the RNF43 mutant genotype. This revealed the unexpected unique requirement of FZD5 (one of ten FZD homologs in humans) as a common genetic vulnerability in RNF43 mutant PDAC lines. This finding was validated through cell proliferation assays in vitro in both established cell lines and a primary patient derived cell line containing RNF43 mutation. Monoclonal antibodies derived against FZD5 were found to be remarkably effective as a single agent therapy both in vitro and in vivo, in subcutaneous and orthotopic xenograft models . Anti‐FZD5 biologics represent a novel potential targeted therapy in RNF43 mutant pancreatic cancers. Support or Funding Information This work was supported from grants funded by the Canadian Institutes for Health Research to S.A. (CIHR‐273548) and J.M. (CIHR‐342551) and by the Ontario Research Fund to S.S. J.M. holds a Canada Research Chair in Functional Genomics of Cancer and S.A. holds a Canada Research Chair in Functional Architecture of Signal Transduction. Z.S. is supported by a scholarship from the Centre for Pharmaceutical Oncology at the Leslie Dan Faculty of Pharmacy, University of Toronto. This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .

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 score0.002

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 head0.011
GPT teacher head0.267
Teacher spread0.256 · 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
Published2018
Admission routes3
Has abstractyes

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