Genomic Profiling of Uterine Aspirates and cfDNA as an Integrative Liquid Biopsy Strategy in Endometrial Cancer
Casas Arozamena, Carlos; Diaz, E.; Moiola, C. P.; Alonso-Alconada, L.; Ferreiros, A.; Abalo Piñeiro, Alicia; Gil, C. L.; Oltra, S. S.; de Santiago, J.; Cabrera, S.; Sampayo, V.; Bouso, M.; ARIAS BALTAR, MARIA EFIGENIA; Cueva Bañuelos, Juan Fernando; Colas, E.; Vilar Lagares, Ana; Gil-Moreno, A.; Abal Posada, Miguel; Moreno-Bueno, G.; Muinelo Romay , Laura
Identificadores
Identificadores
URI: http://hdl.handle.net/20.500.11940/16604
PMID: 32098121
DOI: 10.3390/jcm9020585
ISSN: 2077-0383
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Fecha de publicación
2020Título de revista
Journal of Clinical Medicine
Tipo de contenido
Journal Article
Resumen
The incidence and mortality of endometrial cancer (EC) have risen in recent years, hence more precise management is needed. Therefore, we combined different types of liquid biopsies to better characterize the genetic landscape of EC in a non-invasive and dynamic manner. Uterine aspirates (UAs) from 60 patients with EC were obtained during surgery and analyzed by next-generation sequencing (NGS). Blood samples, collected at surgery, were used for cell-free DNA (cfDNA) and circulating tumor cell (CTC) analyses. Finally, personalized therapies were tested in patient-derived xenografts (PDXs) generated from the UAs. NGS analyses revealed the presence of genetic alterations in 93% of the tumors. Circulating tumor DNA (ctDNA) was present in 41.2% of cases, mainly in patients with high-risk tumors, thus indicating a clear association with a more aggressive disease. Accordingly, the results obtained during the post-surgery follow-up indicated the presence of ctDNA in three patients with progressive disease. Moreover, 38.9% of patients were positive for CTCs at surgery. Finally, the efficacy of targeted therapies based on the UA-specific mutational landscape was demonstrated in PDX models. Our study indicates the potential clinical applicability of a personalized strategy based on a combination of different liquid biopsies to characterize and monitor tumor evolution, and to identify targeted therapies.