Bibliographic record
Abstract
The advances in genomic technologies have made it possible to examine the effects of altered gene expression in the context of specific cellular compartments within the whole organism. As such, transgenic mice have proven to be an invaluable tool to investigate genes involved in many human diseases, including genes implicated in the induction and progression of breast cancer. Human breast cancer is heterogeneous and no single mouse model recapitulates all aspects of the disease. In this regard, various mouse models are necessary to investigate specific characteristics of human breast cancer. In this chapter, we discuss various transgenic mouse strains that have been developed for the purpose of modeling breast cancer and will address their relevance to observations made in human breast tumors. Breast cancer is the most commonly diagnosed form of cancer and it is estimated that one in eight women will develop breast cancer in her lifetime. Once initiated, cancer progresses as a result of an accumulation of genetic abnormalities within cells, the most frequently observed lesions of which can be divided into two categories: (a) DNA amplification and/or overexpression of genes responsible for the generation of proliferative and survival signals, and (b) loss of heterozygosity (LOH), in genes involved in preventing unrestrained cell growth. Genetically modified animals generated by transgenic and gene-targeting knockout technology have contributed immensely to our understanding of gene function and regulation at the molecular level in the context of the whole organism. Since the first transgenic mouse model describing mammary tumors in 1984 (1), a wealth of transgenic mice for modeling breast cancer have been reported. Transgenic models encompassing a wide array of targets including growth factors, receptors, cell cycle regulators, oncogenes, and tumor suppressor genes have been generated for use in breast cancer research. In addition to conventional transgenic overexpression and germline knockouts, the advent of increasingly complex technology has allowed for the generation of more elaborate mouse models including conditional knockouts, conditional activating mutations, and inducible oncogenes or knockouts. Studies of the pathology of mammary carcinomas in genetically modified mice have demonstrated neoplasms that are morphologically similar to human breast cancer (2). While this chapter will describe a variety of genetically engineered mouse models of human breast cancer, it is by no means comprehensive and will not cover the entire spectrum of transgenic mouse models generated to date.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.004 |
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 source (direct Gemma or distilled Codex), 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".