The cyclin-like protein, SPY1, regulates the ERα and ERK1/2 pathways promoting tamoxifen resistance
Bibliographic record
Abstract
// Rosa-Maria Ferraiuolo 1 , Janice Tubman 1, 3 , Indrajit Sinha 3 , Caroline Hamm 1, 2 , Lisa Ann Porter 1 1 Department of Biological Sciences, University of Windsor, Windsor, ON N9B 3P4, Canada 2 Windsor Regional Hospital, Windsor, ON N8W 1L9, Canada 3 Acenzia Inc, Tecumseh, ON N9A 6J3, Canada Correspondence to: Lisa Ann Porter, email: lporter@uwindsor.ca Keywords: Cdk, cyclin, cell cycle, estrogen, tamoxifen Received: February 15, 2016 Accepted: February 12, 2017 Published: February 21, 2017 ABSTRACT The Ras/Raf/MEK/ERK pathway conveys growth factor and mitogen signalling to control the phosphorylation of a plethora of substrates regulating proliferation, survival, and migration. The Ras signalling pathway is frequently associated with poor prognosis and drug resistance in various cancers including those of the blood, breast and prostate. Activation of the downstream effector ERK does not always occur via a linear cascade of events; complicating the targeting of this pathway therapeutically. This work describes a novel positive feedback loop where the cell cycle regulatory factor Spy1 (RINGO; gene SPDYA ) activates ERK1/2 in a MEK-independent fashion. Spy1 was originally isolated for the ability to stimulate Xenopus oocyte maturation via a MAPK-signalling pathway and is known to override apoptosis triggered by the DNA damage response. We demonstrate that mammalian Spy1-mediated ERK activation increases ligand-independent phosphorylation and activation of estrogen receptor α, correlating with a decrease in tamoxifen sensitivity. This could define a novel druggable mechanism driving proliferation and resistance in select cancers.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".