Sinapsos Podcast | Oncology

E43   |  15 min   |   Latest   |  Publication Link

• Podcast based on: Paratore, S.; Russo, A.; Lanzafame, K.; Blanco, G.; Giurato, E.; Bartoloni, G.; D’Asta, M.; Sapienza, M.; Bonanno, G.M.; Vallone, A.; Ettore, G.; Bordonaro, R. Prognostic Stratification of Multiple-Classifier Endometrial Cancers: Cohort Study and Meta-Analysis. Cancers 2026, 18, 929. https://doi.org/10.3390/cancers18060929
  Type: Article  |  Publication date: 12 March 2026
  
  
• Summary: The classification of endometrial cancer has evolved using molecular features, allowing for improved risk assessment and more personalized treatment strategies. However, a small proportion of tumors show more than one relevant molecular alteration, making their classification and clinical management more challenging. This study aimed to characterize molecular and clinicopathological profiles of multiple-classifier endometrial cancers, enhancing our understanding of their biological heterogeneity. In our patient cohort, POLEmut tumors with concurrent MMRd/MSI generally retained the POLE-associated ultramutated profile, while tumors with both MMRd/MSI and p53abn/TP53mut alterations were more often associated with more adverse clinicopathological characteristics compared to MMRd/MSI-only tumors. By integrating our data in a systematic literature review with meta-analysis, we observed that variability in reported incidence is largely driven by differences in testing strategies. These results highlight the limitations of current classification systems and emphasize the importance of more standardized molecular approaches to improve risk stratification and management in endometrial cancer.
  
  
• Keywords: endometrial cancer; molecular profile; clinicopathological features; multiple-classifier; POLE mutated; mismatch repair-deficient; TP53mutated; next generation sequencing

License and disclaimer:
Original article © 2026 by the authors. Licensed under the Creative Commons Attribution 4.0 (CC BY 4.0) license (https://creativecommons.org/licenses/by/4.0/). This episode is an AI-generated audio adaptation of the article: the script and the voices are synthetic, changes were made, and the adaptation is not endorsed by the authors, the journal, or the publisher. It may contain errors or omissions, so consult the original publication before relying on any detail. It is for educational purposes only and is not medical advice. The creators accept no liability for any use of this content.