Lung-derived soluble factors support stemness/plasticity and metastatic behaviour of breast cancer cells via the FGF2-DACH1 axis
Bibliographic record
Abstract
Abstract Patients with triple-negative breast cancer (TNBC) have an increased propensity to develop lung metastasis. Our previous studies demonstrated that stem-like ALDH hi CD44 + breast cancer cells interact with lung-derived soluble factors, resulting in enhanced migration and lung metastasis particularly in TNBC models. We have also observed that the presence of a primary TNBC tumor can ‘prime’ the lung microenvironment in preparation for metastasis. In this study, we hypothesized that soluble lung-derived factors secreted in the presence of a primary TNBC tumor can influence stemness/plasticity of breast cancer cells. Using an ex vivo pulmonary metastasis assay (PuMA), we observed that the lung microenvironment supports colonization and growth of ALDH hi CD44 + TNBC cells, potentially via interactions with lung-derived FGF2. Exposure of TNBC cells to lung-conditioned media (LCM) generated from mice bearing TNBC primary tumors (tbLCM) significantly enhanced the proportion of ALDH hi CD44 + cells compared to control or LCM from tumor-naïve mice (tnLCM). Further analysis using a human cancer stem cell qPCR array revealed that, relative to tnLCM or control, exposure of TNBC cells to tbLCM leads to downregulation of the transcription factor and putative tumor suppressor Dachshund homolog 1 (DACH1), a downstream regulator of FGF2. In addition, inhibition of DACH1 using siRNA or treatment with recombinant FGF2 enhanced the ALDH hi CD44 + phenotype. Taken together, our findings suggest that the FGF2-DACH1 signaling axis supports stemness/plasticity of TNBC cells in the lung microenvironment and lays the foundation for future evaluation of FGF2 as a potential novel therapeutic target for treatment or prevention of breast cancer metastasis to the lung.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.000 | 0.002 |
| 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".