Abstract 5173: Heterozygous <i>Ppp2r1a</i> mutations with concurrent loss of Tp53 drive invasive high-grade uterine cancer
Bibliographic record
Abstract
Abstract Uterine cancer is the only cancer type for which survival has fallen in the past four decades. This year in the United States, over 13,000 women will die from this disease, surpassing ovarian cancer for the first time: making uterine cancer the deadliest gynecological cancer. Mortality from uterine cancer is primarily due to the aggressive, non-endometrioid subtypes of the disease which include uterine serous carcinomas and uterine carcinosarcomas (high-grade subtypes). Molecularly, high-grade uterine tumors harbor few mutations, however, almost every high-grade uterine tumor harbors a Tp53 mutation, and 30-40% of tumors also harbor a heterozygous PPP2R1A mutation, most commonly - P179R, S256F, or R183W. PPP2R1A encodes for the Aα scaffolding subunit of the heterotrimeric protein phosphatase 2A (PP2A). Previous literature from our group and others has shown that these mutations occur very early in uterine cancer development and that these mutations modulate PP2A function in a manner that impairs the formation of tumor-suppressive PP2A holoenzymes. However, a lack of models, particularly transgenic mouse models, of high-grade uterine cancers has limited our understanding of the disease as well as the preclinical testing of targeted therapeutics to the underlying drivers of disease development and progression. Knockout of p53 in mouse uterine epithelium has been shown to result in the formation of uterine tumors (uterine serous and carcinosarcomas) at 16-20 months of age. Our group has generated novel conditional Ppp2r1a-P179R and R183W knock-in mice. Because these mutations exclusively co-occur with Tp53 alterations, we crossed these mice to the Tp53fl/fl and Ksp1.3-Cre mouse to generate uterine epithelium-specific knockout of Tp53 and knock-in of either Aα-P179R or R183W PP2A mutant alleles. Our preliminary data demonstrate that these mice develop advanced high-grade uterine cancers as early as 6 months, compared to 16 months with Tp53 KO alone, showing that PPP2R1A mutations significantly accelerate uterine tumor formation. Pathological analysis of these tumors has shown that they are high-grade and resemble high-grade uterine tumors in humans. Combined, our data definitively show that PPP2R1A mutations are drivers of high-grade uterine cancers for the first time and provide a novel mouse model of high-grade uterine cancer that can be used to develop a better understanding of this deadly cancer. Citation Format: Caitlin M. O'Connor, Kelsey Barrie, Kaitlin Zawacki, Ingrid L. Bergin, Gabrielle Hodges Onishi, Analisa DiFeo, Kathleen Cho, Thom Saunders, Goutham Narla. Heterozygous Ppp2r1a mutations with concurrent loss of Tp53 drive invasive high-grade uterine cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 5173.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".