Abstract 299: Characterization of a senescence phenotype induced by advanced glycation end products in prostate cancer
Bibliographic record
Abstract
Prostate cancer (PCa) represents a worldwide leading cause of cancer-related mortality in men. Diabetes is also a highly prevalent and a rapidly growing pathology. Intriguingly, diabetes is associated with decreasing PCa incidence, and at the same time, it is linked to increased mortality rates for men already afflicted by the disease. A plausible mediator causing this effect are Advanced Glycation End Products (AGEs), products of the Maillard reaction, occurring between sugars and proteins at body temperature. AGEs, known to be elevated in diabetic patients, have been reported to increase the Extracellular Matrix (ECM) stiffness via ECM-crosslinking, potentially explaining the tumor-promoting effects of diabetes in cancer progression. Nonetheless, the protective role of diabetes in prostate cancer is not yet fully understood. Interestingly, we demonstrated that AGEs, produced by mixing sugars and an abundant circulating protein in the blood decreased PCa cell proliferation in vitro in a dose-dependent and irreversible manner across a panel of human PCa cell lines. Importantly, through transcriptomic analysis, we found that AGEs-mediated cell proliferation blocking correlate with a senescence transcriptional signature. Accordingly, treatment with AGEs lead to increased beta-galactosidase activity, a hallmark of senescence, and to the upregulation of senescent markers linked to cell cycle arrest (p21WAF1/Cip1) and pro-inflammatory cytokines (IL-8) at the transcriptional and translational levels. We also confirmed the expression of the senescence-associated secretory phenotype (SASP, e.g., IL, CXCL, CCL) in AGEs-treated PCa cells. Finally, our validation of key transcriptomics analysis confirmed the upregulation of HMOX1, an enzyme reported to be induced during cellular senescence, upon AGEs treatment. Altogether, our results suggest that AGEs-mediated senescence could underlie the lower incidence of PCa among diabetic patients. This sets the stage for combination treatments between AGEs and senolytics, drugs that selectively target and induce cell death in senescent cells, as a novel therapeutic strategy in PCa. Citation Format: Luisa Bacca, Tarek Hallal, Carole Luthold, Nadia Boufaied, François Bordeleau, David Labbé. Characterization of a senescence phenotype induced by advanced glycation end products in prostate 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 299.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".