Heterogeneity of vascular and progenitor cell compartments in tumours from MMTV-PyVmT transgenic mice during mammary cancer progression
Bibliographic record
Abstract
Transgenic mice are important tools for our study of breast cancer pathobiology. In order to evaluate changes in cell phenotype with breast cancer progression, we examined vascular and progenitor cell characteristics in tumours derived from MMTV-PyVmT mice. We performed dual-immunofluorescence staining for Tie2, pTie2Y1100, VEGFR2 and PDGFR-β and the pan-endothelial marker PECAM-1 (CD31) in 39 tumours from MMTV-PyVmT transgenic mice grouped by nuclear grade and tumour morphology. Immunohistochemical staining for Aldh1a1 was performed in MMTV-PyVmT-derived tumours and in non-transgenic mouse mammary glands. Tumour blood vessels were heterogeneous in all samples analysed, with the proportion of Tie2-, pTie2 (Y1100)-, VEGFR2- and PDGFR-β-positive tumour blood vessels ranging from 18-98%, 7-40%, 19-86% and 16-94% respectively. We observed a statistically significant difference in vascular pTie2Y1100 levels between low-nuclear-grade tumours and intermediate-/high-nuclear-grade tumours (P=0.03) and an increase in the proportion of PDGFR-β-positive tumour blood vessels in tumours with high vs. Intermediate-nuclear grade tumours (P<0.01). Aldh1a1-positive mammary epithelial cells were observed in the terminal end buds of non-transgenic mammary glands and Aldh1a1-positive mammary tumour cells were observed in tumours from MMTV-PyVmT transgenic mice. We observed a decrease in the average number of Aldh1a1-positive cells in tumours with a non-invasive vs. solid morphology (P=0.03), and in the average number of Aldh1a1-positive mammary tumour cells in low vs. intermediate and low vs. High-nuclear grade tumours (P<0.001). Our findings suggest heterogeneous expression of several molecules important for tumour angiogenesis and tumour progression that are currently under investigation as therapeutic targets for metastatic breast cancer.
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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".