Unlocking personalized endometrial cancer treatment: the critical role of the BBIRE biobank in sample collection and distribution - Bruno, V.; Betti, M.; Ciuffreda, L.; Arteni, A. M. B.; Ferretti, M.; Rossi, F.; Accetta, C.; Mandoj, C.; Laquintana, V.; De Nicola, F.; Donzelli, S.; Vaccarella, S.; et al. (Frontiers in Molecular Biosciences, 2026)
IntroductionEndometrial cancer (EC) is the most common gynecological malignancy and the sixth most common cancer in women. Although it primarily affects women around or after menopause, an increasing number of cases are now being found in women of reproductive age. This shift highlights the need for fertility-sparing treatments and research.MethodsThe tumor biobank of the Regina Elena National Cancer Institute (BBIRE) has played a central role in EC research by simplifying the collection and distribution of high-quality samples linked to clinical data. BBIRE follows strict protocols and uses secure databases to protect patient privacy, meet regulations, and keep clinical information accurate. These steps help maintain sample quality and reduce errors before analysis.ResultsThis research highlights the importance of the BBIRE-tissue processing group in the coordinated management of 545 gynecological tumor samples, comprising 321 EC samples, underscoring its importance as a crucial instrument for translational research. The biobank supports a complete research process, from patient enrollment to molecular data analysis. Its flexible, standardized structure helps ensure reliable results in different research settings.DiscussionAs a gynecologic oncology resource, BBIRE facilitates large-scale studies and collaboration among team researchers. This support is essential for identifying new biomarkers, tailoring treatments, and advancing precision medicine. The development of personalized care and improved outcomes for women with EC can be accelerated when work is performed collaboratively by surgeons, biobanks, and researchers.Statement of SignificanceThe BBIRE Biobank is a game changer in cancer research that enables the integration of annotated samples, multiomics data, and organoid models to identify molecular drivers and accelerate personalized care.