Abstract 2837: Mechanisms promoting chromosomal instability following the loss of p53 and Rb
Bibliographic record
Abstract
Abstract p53 and Rb co-mutations are common in several human cancers and are associated with the onset of aggressive tumors with complex karyotypes. Canonically, these tumor suppressors respond to DNA damage and cellular stress by inducing cell cycle arrest, activating pro-apoptotic and anti-proliferative signalling, and promoting cellular senescence. While these pathways are sufficient to partially explain the tumor suppressive abilities of p53 and Rb, recent studies in genetically engineered mouse models suggest additional, non-canonical means of tumor suppression, including modulation of cellular differentiation and DNA topology, and interestingly, influencing cellular response to chromosomal instability. Chromosomal instability (CIN) is a hallmark of aggressive, therapy-resistant cancers and is associated with mitotic dysfunction, faulty DNA damage responses, immune evasion, and cellular stress response pathways. While it is known that p53 and Rb maintain the integrity of the genomic landscape, the mechanisms by which they prevent CIN remain understudied. Here, we use mouse embryonic fibroblasts (MEFs) to show that p53 + Rb double knock-out (DKO) causes a dramatic increase in ploidy at very early passages, which stabilizes at tetraploid levels. These cells also harbour high levels of CIN, indicated by the presence of micronuclei, DNA double-stranded breaks, and lagging chromosomes. Additionally, we observed CIN in p5325, 26 transactivation domain (TAD) mutant MEFs that are unable to activate most canonical p53 targets yet retain the ability to suppress tumorigenesis in vivo, raising the possibility that the maintenance of chromosomal stability is dispensable to the tumor suppressive functions of p53. Using a combination of bulk and scRNA sequencing of aneuploid and diploid DKO MEFs, in future experiments we will identify p53- and Rb-dependent changes in gene expression associated with the onset and progression of CIN. Overall, the results of this study are expected to provide critical insights into the molecular mechanisms by which tumor suppressors p53 and Rb work together to repress CIN. Citation Format: Risha Banerjee, David G. Kirsch. Mechanisms promoting chromosomal instability following the loss of p53 and Rb [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 2837.
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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) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".