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Record W3172245929 · doi:10.1158/1557-3125.ras18-b38

Abstract B38: Ras clipping by bacterial toxin RRSP reduces viability and proliferation of Ras-dependent cancer cell lines in 2D and 3D in vitro models

2020· article· en· W3172245929 on OpenAlexaff
Vania Vidimar, Minyoung Park, Roman A. Melnyk, K.J.F. Satchell

Bibliographic record

VenueMolecular Cancer Research · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer Research and Treatments
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsBiologyKRASCancer researchCancer cellCell growthGuanine nucleotide exchange factorGrowth factor receptorGTPaseMolecular biologyCancerSignal transductionCell biologyBiochemistryGenetics

Abstract

fetched live from OpenAlex

Abstract Ras GTPases are critical molecular hubs regulating cell proliferation and survival and are among the most frequently mutated oncogenes in human cancers. In recent years, significant efforts have been made to develop Ras-targeting anticancer strategies. Although promising preclinical results were reported for approaches directed against specific KRas mutant variants (e.g., G12C), more effective tools for inhibiting the spectrum of common KRas mutants and/or aberrantly activated wild-type Ras oncoproteins are required to bring Ras-blocking strategies from the bench to the bedside. We discovered the Ras-Rap1-Specific Protease (RRSP) from bacterium Vibrio vulnificus. RRSP site-specifically cleaves the major Ras isoforms (H, N and K) and the most common mutated Ras oncoproteins (G12V, G13D and Q61R) within the Switch I region. In order to bring RRSP into cancer cells, the Melnyk’s group fused RRSP with diphtheria toxin binding subunit B (DTB). DTB is a novel tool for delivery of cargo proteins into the cytosol of target cells via binding to its receptor hHB-EGF (human heparin-binding epidermal growth factor-like growth factor), which is expressed on most human cell types. Successful RRSP intracellular delivery was assessed via Western blot as indicated by Ras cleavage and pERK1/2 dephosphorylation. In MDA-MB-436 (triple-negative breast cancer, KRAS WT) cells with hyperactive Ras signaling, RRSP-DTB efficiently cleaved Ras at concentrations as low as 1 pM. As a consequence of Ras cleavage, we observed pERK1/2 dephosphorylation and decrease in cell viability as shown by crystal violet assay. Similar results were observed in MDA-MB-231 (triple-negative breast cancer, KRAS G13D) cells. A catalytically dead mutant of RRSP carrying an amino acid substitution in its active site (H451A RRSP-DTB) did not show Ras clipping nor decrease in pERK1/2 expression. We also found that RRSP-DTB reduced viability and proliferation of HCT-116 (colorectal, KRAS G13D) cells in 2-dimensional monolayers and 3-dimensional (3D) spheroids in a time- and dose-dependent manner. Notably, 3D spheroids from HCT-116 cells showed a significant reduction in size following RRSP-DTB but not H451A RRSP-DTB treatment. Also, in vivo experiments are currently ongoing to corroborate our in vitro findings. All together our results revealed that, by physically clipping Ras, bacterial toxin RRSP strongly reduces viability and proliferation of Ras-dependent human cancer cell lines bearing either wild-type or mutant KRAS. This work supports further development of RRSP as a potential anticancer therapeutic for a wide variety of Ras-driven tumors. Citation Format: Vania Vidimar, Minyoung Park, Roman A. Melnyk, Karla J.F. Satchell. Ras clipping by bacterial toxin RRSP reduces viability and proliferation of Ras-dependent cancer cell lines in 2D and 3D in vitro models [abstract]. In: Proceedings of the AACR Special Conference on Targeting RAS-Driven Cancers; 2018 Dec 9-12; San Diego, CA. Philadelphia (PA): AACR; Mol Cancer Res 2020;18(5_Suppl):Abstract nr B38.

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 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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.997

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 head0.041
GPT teacher head0.355
Teacher spread0.314 · 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 teacher head, 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
Published2020
Admission routes1
Has abstractyes

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