Role of metadherin in estrogen-regulated gene expression
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
The disruption of estrogen signaling is widely associated with the development of breast, endometrial and ovarian cancers. As a multifunctional mediator of carcinogenesis, metadherin (MTDH)/astrocyte elevated gene-1 (AEG-1) overexpression has been associated with numerous types of cancer, with reported roles in tumor initiation, proliferation, invasion, metastasis and chemoresistance. At the molecular level, MTDH has been shown to interact with proteins that drive tumorigenesis, including nuclear factor-κB (NF-κB), promyelocytic leukaemia zinc finger (PLZF), BRCA2- and CDKN1A (p21Cip1/Waf-1/mda-6)-interacting protein α (BCCIPα) and staphylococcal nuclease and tudor domain containing 1 (SND1). Through the analysis of the Cancer Genome Atlas (TCGA) datasets for estrogen receptor (ER)-positive endometrial and breast cancers, we found that over 25% of all gene expression correlated with MTDH. Using Affymetrix microarrays, we characterized the differences in gene expression between estrogen-treated parental and MTDH-deficient endometrial and breast cancer cells. We also explored a possible interaction between MTDH and ER by immunoprecipitation, and found that MTDH and ER associated in both breast and endometrial cancer cells in response to estrogen. Reciprocal co-immunoprecipitation analysis demonstrated that acute estrogen stimulation promoted the interaction of MTDH with ER in the nucleus. These data, to the best of our knowledge, provide the first evidence that MTDH and ERα interact in the nucleus with estrogen treatment to regulate gene expression.
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 | 0.000 | 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) | 0.000 | 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