Inactivation of TRP53, PTEN, RB1, and/or CDH1 in the ovarian surface epithelium induces ovarian cancer transformation and metastasis
Bibliographic record
Abstract
Ovarian cancer (OvCa) remains the most common cause of death from gynecological malignancies. Genetically engineered mouse models have been used to study initiation, origin, progression, and/or mechanisms of OvCa. Based on the clinical features of OvCa, we examined a quadruple combination of pathway perturbations including PTEN, TRP53, RB1, and/or CDH1. To characterize the cancer-promoting events in the ovarian surface epithelium (OSE), Amhr2cre/+ mice were used to ablate floxed alleles of Pten, Trp53, and Cdh1, which were crossed with TgK19GT121 mice to inactivate RB1 in KRT19-expressing cells. Inactivation of PTEN, TRP53, and RB1 with or without CDH1 led to the development of type I low-grade OvCa with enlarged serous papillary carcinomas and some high-grade serous carcinomas (HGSCs) in older mice. Initiation of epithelial hyperplasia and micropapillary carcinoma started earlier at 1 month in the triple mutations of Trp53, Pten, and Rb1 mice as compared to 2 months in quadruple mutations of Trp53, Pten, Rb1, and Cdh1 mice, whereas both genotypes eventually developed enlarged proliferating tumors that invaded into the ovary at 3-4 months. Mice with triple and quadruple mutations developed HGSC and/or metastatic tumors, which disseminated into the peritoneal cavity at 4-6 months. In summary, inactivation of PTEN, TRP53, and RB1 initiates OvCa from the OSE. Additional ablation of CDH1 further increased persistence of tumor dissemination and ascites fluid accumulation enhancing peritoneal metastasis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".