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Record W3033074253 · doi:10.1158/1535-7163.mct-19-0977

NRG1/ERBB3 Pathway Activation Induces Acquired Resistance to XPO1 Inhibitors

2020· article· en· W3033074253 on OpenAlexfundno aff
Takahito Miyake, Sunila Pradeep, Emine Bayraktar, Elaine Stur, Katelyn F. Handley, Sherry Y. Wu, Cristian Rodriguez‐Aguayo, Ju‐Seog Lee, Gabriel Lopez‐Berestein, Robert L. Coleman, Anil K. Sood

Bibliographic record

VenueMolecular Cancer Therapeutics · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicNuclear Structure and Function
Canadian institutionsnot available
FundersCanadian Breast Cancer Research AllianceNational Cancer InstituteOvarian Cancer Research AllianceNational Institutes of HealthCancer Prevention and Research Institute of Texas
KeywordsERBB3Neuregulin 1In vivoOvarian cancerCancer researchDownregulation and upregulationBiomarkerCancerSineBiologySignal transductionMedicinePharmacologyGeneInternal medicineCell biologyBiochemistryGenetics

Abstract

fetched live from OpenAlex

Abstract XPO1 inhibitors have shown promise in cancer treatment, but mechanisms of resistance to these drugs are not well understood. In this study, we established selective inhibitors of nuclear export (SINE)-resistant ovarian cancer cell lines from in vivo mouse tumors and determined the mechanisms of adaptive XPO1 inhibitor resistance using protein and genomic arrays. Pathway analyses revealed upregulation of the NRG1/ERBB3 pathway in SINE-resistant cells. Depletion of ERBB3 using siRNAs restored the antitumor effect of SINE in vitro and in vivo. Furthermore, exogenous NRG1 decreased the antitumor effect of SINE in ovarian cancer cell lines with high ERBB3 expression, but not in those with low expression. These results suggest that NRG1 and ERBB3 expression is a potential biomarker of response to SINE treatment. The antitumor effect of SINE was reduced by exogenous NRG1 in an ERBB3-dependent manner. These findings suggest that NRG1 and ERBB3 are effective biomarkers that should be evaluated in future clinical trials and are relevant therapeutic targets for the treatment of SINE-resistant cancers.

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 score0.312
Threshold uncertainty score0.767

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 head0.019
GPT teacher head0.251
Teacher spread0.232 · 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

Citations10
Published2020
Admission routes1
Has abstractyes

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