Development and characterisation of a 3D multi-cellular<i>in vitro</i>model of normal human breast: a tool for cancer initiation studies
Bibliographic record
Abstract
// Claire E. Nash 1,5 , Georgia Mavria 1 , Euan W. Baxter 1 , Deborah L. Holliday 1 , Darren C. Tomlinson 2 , Darren Treanor 1,3 , Vera Novitskaya 4 , Fedor Berditchevski 4 , Andrew M. Hanby 1 and Valerie Speirs 1 1 Leeds Institute of Cancer and Pathology, University of Leeds, Leeds, UK 2 Leeds Institute of Biomedical and Clinical Sciences, University of Leeds, Leeds, UK 3 Leeds Teaching Hospitals NHS Trust, Leeds, UK 4 School of Cancer Sciences, University of Birmingham, Birmingham, UK 5 Current address: The Research Institute of the McGill University Health Centre, Montreal, Quebec, Canada Correspondence to: Valerie Speirs, email: // Keywords : 3D cell culture, breast, HER2 Received : January 09, 2015 Accepted : March 18, 2015 Published : April 12, 2015 Abstract Multicellular 3-dimensional (3D) in vitro models of normal human breast tissue to study cancer initiation are required. We present a model incorporating three of the major functional cell types of breast, detail the phenotype and document our breast cancer initiation studies. Myoepithelial cells and fibroblasts were isolated and immortalised from breast reduction mammoplasty samples. Tri-cultures containing non-tumorigenic luminal epithelial cells HB2, or HB2 overexpressing different HER proteins, together with myoepithelial cells and fibroblasts were established in collagen I. Phenotype was assessed morphologically and immunohistochemically and compared to normal breast tissue. When all three cell types were present, polarised epithelial structures with lumens and basement membrane production were observed, akin to normal human breast tissue. Overexpression of HER2 or HER2/3 caused a significant increase in size, while HER2 overexpression resulted in development of a DCIS-like phenotype. In summary, we have developed a 3D tri-cellular model of normal human breast, amenable to comparative analysis after genetic manipulation and with potential to dissect the mechanisms behind the early stages of breast cancer initiation.
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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".