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Record W2732249235 · doi:10.1101/159905

Ponatinib shows potent antitumor activity in small cell carcinoma of the ovary hypercalcemic type (SCCOHT) through multi-kinase inhibition

2017· preprint· en· W2732249235 on OpenAlexaffabout
Jessica D. Lang, William P.D. Hendricks, Holly Yin, Jeffrey Kiefer, Pilar Ramos, Ritin Sharma, Patrick Pirrotte, Elizabeth A. Raupach, Chris Sereduk, Nanyun Tang, Winnie S. Liang, Megan Washington, Salvatore Facista, Victoria Zismann, Emily Cousins, Michael B. Major, Yemin Wang, Anthony N. Karnezis, Krystal A. Orlando, Aleksandar Sekulić, Ralf Hass, Barbara C. Vanderhyden, Kesavannair Praveen, Bernard E. Weissman, David G. Huntsman, Jeffrey M. Trent

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2017
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicChromatin Remodeling and Cancer
Canadian institutionsUniversity of OttawaOntario Institute for Cancer ResearchOttawa HospitalUniversity of British Columbia
Fundersnot available
KeywordsPonatinibCancer researchBiologySMARCA4Ovarian cancerKinaseCancerTyrosine kinasePharmacologyDasatinibReceptorEpigeneticsGeneticsChromatin remodeling

Abstract

fetched live from OpenAlex

Structured Abstract Purpose: Subunits of the SWI/SNF chromatin-remodeling complex are tumor suppressors inactivated in ∼20% of all cancers. Yet, few targeted treatments for SWI/SNF-mutant cancers exist. Small cell carcinoma of the ovary, hypercalcemic type (SCCOHT) is a rare, aggressive ovarian cancer in young women that is universally driven by loss of the SWI/SNF ATPase subunits, SMARCA4 and SMARCA2. Given poor two-year survival rates for these women, a great need exists for effective targeted therapies. Experimental Design: To identify underlying therapeutic vulnerabilities in SCCOHT, we conducted high-throughput siRNA and drug screens. Complementary proteomics approaches comprehensively profiled kinases inhibited by ponatinib. Ponatinib was tested for efficacy in two PDX models and one cell line xenograft model of SCCOHT. Results: FGFRs and PDGFRs were overlapping hits between screens and the receptor tyrosine kinase (RTK) family was enriched in the siRNA screen hits. Evaluation of eleven RTK inhibitors in three SCCOHT cell lines identified ponatinib, an inhibitor of multiple RTKs, as the most effective clinically approved agent. Proteomics approaches confirmed inhibition of known targets of ponatinib and more than 20 non-canonical ponatinib targets. Ponatinib also delayed tumor doubling time 4-fold in SCCOHT-1 xenografts and reducing final tumor volumes in two SCCOHT patient-derived xenograft (PDX) models by 58.6% and 42.5%. Conclusion: Ponatinib is an effective agent for SCCOHT in both in vitro and in vivo preclinical models through its inhibition of multiple kinases. Clinical investigation of this FDA-approved oncology drug in SCCOHT is warranted. Additional Information This work was supported by research funds from the Canadian Cancer Society Research Institute 34 (#703458, D.G.H.), the National Institutes of Health (R01 CA195670-01, B.E.W., D.G.H., and 35 J.M.T., and T32 HL007106-39 to E.M.C), the Terry Fox Research Institute Initiative New Frontiers Program in Cancer (#1021, D.G.H.), the British Columbia Cancer Foundation (D.G.H.), the VGH & UBC Foundation (D.G.H.), the Anne Rita Monahan Foundation (P.R.), the Marsha Rivkin Center for Ovarian Cancer Research (J.M.T.), the Ovarian Cancer Alliance of Arizona (J.M.T.), the Small Cell Ovarian Cancer Foundation (P.R., J.D.L., B.V., and J.M.T.), and philanthropic support to the TGen Foundation (J.M.T.). COI disclosure statement: The authors declare no potential conflicts of interest.

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 categoriesMeta-epidemiology (narrow)
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 score0.091
Threshold uncertainty score1.000

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 science0.0010.001
Research integrity0.0010.001
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 head0.027
GPT teacher head0.244
Teacher spread0.217 · 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.

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

Citations8
Published2017
Admission routes2
Has abstractyes

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