miR-221/222 Targeting of Trichorhinophalangeal 1 (TRPS1) Promotes Epithelial-to-Mesenchymal Transition in Breast CancerA presentation from the Keystone Symposium on Epithelial Plasticity and Epithelial to Mesenchymal Transition, Vancouver, Canada, 21 to 26 January 2011. This Presentation also complements the <i>Science Signaling</i> Research Article by Stinson <i>et al.</i> published 14 June 2011.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Compared with the luminal subtype, the basal-like subtype of breast cancer has an aggressive clinical behavior, but the reasons for this difference between the two subtypes are poorly understood. We identified microRNAs (miRNAs) miR-221 and miR-222 (miR-221/222) as basal-like subtype-specific miRNAs that decrease expression of epithelial-specific genes and increase expression of mesenchymal-specific genes. In addition, expression of these miRNAs increased cell migration and invasion, which collectively are characteristics of the epithelial-to-mesenchymal transition (EMT). The basal-like transcription factor FOSL1 (also known as Fra-1) directly stimulated the transcription of miR-221/222, and the abundance of these miRNAs decreased with inhibition of MEK (mitogen-activated or extracellular signal-regulated protein kinase kinase), placing miR-221/222 downstream of the RAS pathway. The miR-221/222-mediated reduction in E-cadherin abundance depended on their targeting of the 3' untranslated region (3'UTR) of TRPS1 (trichorhinophalangeal syndrome type 1), which is a member of the GATA family of transcriptional repressors. TRPS1 inhibited EMT by directly repressing expression of ZEB2 (Zinc finger E-box-binding homeobox 2). Therefore, miR-221/222 may contribute to the aggressive clinical behavior of basal-like breast 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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it