Cooperation between <i>Pik3ca</i> and p53 Mutations in Mouse Mammary Tumor Formation
Bibliographic record
Abstract
PIK3CA, which codes for the p110α catalytic subunit of phosphatidylinositol 3-kinase, is one of the most frequently mutated genes in human breast cancer. Here, we describe a mouse model for PIK3CA-induced breast cancer by using the ROSA26 (R26) knock-in system, in which targeted Pik3ca alleles can be activated through transgenic expression of Cre recombinase. We mated Pik3ca(H1047R) and Pik3ca(wt) knock-in lines with MMTV-Cre transgenics, which express Cre in mammary epithelium. Starting at approximately 5 months of age, female R26-Pik3ca(H1047R);MMTV-Cre mice, but not control R26-Pik3ca(wt);MMTV-Cre mice, developed mammary tumors, as well as lymphoid and skin malignancies. R26-Pik3ca(H1047R);MMTV-Cre mammary tumors were typically either adenosquamous carcinoma or adenomyoepithelioma. As p53 is the most commonly mutated gene in breast cancer, we tested for genetic interaction between Pik3ca(H1047R) and p53 loss-of-function mutations in R26-Pik3ca(H1047R);p53(loxP/+);MMTV-Cre mice. This led to decreased survival of double-mutant animals, which developed lymphoma and mammary tumors with rapid kinetics. Mammary tumors that formed in p53(loxP/+);MMTV-Cre conditional mutants were either poorly differentiated adenocarcinoma or spindle cell/EMT, whereas R26-Pik3ca(H1047R);p53(loxP/+);MMTV-Cre mammary tumors were mostly adenosquamous carcinoma or spindle cell/EMT indicating that double-mutant mice develop a distinct spectrum of mammary tumors. Thus, an oncogenic variant of PIK3CA implicated in multiple human breast cancer subtypes can induce a very diverse spectrum of mammary tumors in mice. Furthermore, Pik3ca(H1047R) shows cooperation with p53, which altered the specific tumors that formed. Thus, the two most frequently mutated genes in human breast cancer show cooperation in mammary tumor formation.
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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".