JUNB suppresses distant metastasis by influencing the initial metastatic stage
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 complex interactions between cells of the tumor microenvironment and cancer cells are considered a major determinant of cancer progression and metastasis. Yet, our understanding of the mechanisms of metastatic disease is not sufficient to successfully treat patients with advanced-stage cancer. JUNB is a member of the AP-1 transcription factor family shown to be frequently deregulated in human cancer and associated with invasion and metastasis. A strikingly high stromal JUNB expression in human breast cancer samples prompted us to functionally investigate the consequences of JUNB loss in cells of the tumor microenvironment on cancer progression and metastasis in mice. To adequately mimic the clinical situation, we applied a syngeneic spontaneous breast cancer metastasis model followed by primary tumor resection and identified stromal JUNB as a potent suppressor of distant metastasis. Comprehensive characterization of the JUNB-deficient tumor microenvironment revealed a strong influx of myeloid cells into primary breast tumors and lungs at early metastatic stage. In these infiltrating neutrophils, BV8 and MMP9, proteins promoting angiogenesis and tissue remodeling, were specifically upregulated in a JUNB-dependent manner. Taken together, we established stromal JUNB as a strong suppressor of distant metastasis. Consequently, therapeutic strategies targeting AP-1 should be carefully designed not to interfere with stromal JUNB expression as this may be detrimental for cancer patients.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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