TBX3 promotes progression of pre‐invasive breast cancer cells by inducing EMT and directly up‐regulating SLUG
Bibliographic record
Abstract
The acquisition of cellular invasiveness by breast epithelial cells and subsequent transition from ductal carcinoma in situ (DCIS) to invasive breast cancer is a critical step in breast cancer progression. Little is known about the molecular dynamics governing this transition. We have previously shown that overexpression of the transcriptional regulator TBX3 in DCIS-like cells increases survival, growth, and invasiveness. To explore this mechanism further and assess direct transcriptional targets of TBX3 in a high-resolution, isoform-specific context, we conducted genome-wide chromatin-immunoprecipitation (ChIP) arrays coupled with transcriptomic analysis. We show that TBX3 regulates several epithelial-mesenchymal transition (EMT)-related genes, including SLUG and TWIST1. Importantly, we demonstrate that TBX3 is a direct regulator of SLUG expression, and SLUG expression is required for TBX3-induced migration and invasion. Assessing TBX3 by immunohistochemistry in early-stage (stage 0 and stage I) breast cancers revealed high expression in low-grade lesions. Within a second independent early-stage non-high-grade cohort, we observed an association between TBX3 level in the DCIS and size of the invasive focus. Additionally, there was a positive correlation between TBX3 and SLUG, and TBX3 and TWIST1 in the invasive carcinoma. Pathway analysis revealed altered expression of several proteases and their inhibitors, consistent with the ability to degrade basement membrane in vivo. These findings strongly suggest the involvement of TBX3 in the promotion of invasiveness and progression of early-stage pre-invasive breast cancer to invasive carcinoma through the low-grade molecular pathway. © 2019 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.
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 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 | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".