Triple-Negative Primary Breast Tumors Induce Supportive Premetastatic Changes in the Extracellular Matrix and Soluble Components of the Lung Microenvironment
Bibliographic record
Abstract
The lung is one of the deadliest sites of breast cancer metastasis, particularly in patients with triple-negative (TN) disease. We hypothesized that the presence of a TN primary breast tumor induces changes in the extracellular matrix (ECM) and soluble components of the lung microenvironment that support metastatic behavior. SUM159 (TN) and MCF7 (luminal A) breast cancer cells were injected into mice, and primary breast tumors were established prior to assessing metastatic niche changes. We observed increased CD117+ hematopoietic progenitor cells in the bone marrow of SUM159 mice versus MCF7 or control mice (p < 0.05). Relative to mice bearing MCF7 tumors and non-tumor controls, mice bearing SUM159 tumors demonstrated enhanced expression of ECM proteins in the lung (fibronectin, tenascin-c and periostin), with similar changes observed in lung fibroblasts treated with extracellular vesicles (EVs) from TN breast cancer cells (p < 0.05). Exposure to lung-conditioned media (LCM) from SUM159 tumor-bearing mice resulted in increased migration/proliferation of both SUM159 and MCF7 cells relative to the control (p < 0.05). In contrast, LCM from MCF-7 tumor-bearing mice had no such effect. LCM from SUM159 tumor-bearing mice contained 16 unique proteins relative to other LCM conditions, including the metastasis-associated proteins CCL7, FGFR4, GM-CSF, MMP3, thrombospondin-1 and VEGF. These findings suggest for the first time that the TN breast cancer molecular subtype may be an important determinant of premetastatic changes to both the ECM and soluble components of the lung, potentially mediated via breast cancer-derived EVs.
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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 | 0.000 | 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 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".