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Increased blood draws for ultrasensitive ctDNA and CTCs detection in early breast cancer patients

Authors :
Alfonso Alba-Bernal
Ana Godoy-Ortiz
María Emilia Domínguez-Recio
Esperanza López-López
María Elena Quirós-Ortega
Victoria Sánchez-Martín
María Dunia Roldán-Díaz
Begoña Jiménez-Rodríguez
Jesús Peralta-Linero
Estefanía Bellagarza-García
Laura Troyano-Ramos
Guadalupe Garrido-Ruiz
M. Isabel Hierro-Martín
Luis Vicioso
Álvaro González-Ortiz
Noelia Linares-Valencia
Jesús Velasco-Suelto
Guillermo Carbajosa
Alicia Garrido-Aranda
Rocío Lavado-Valenzuela
Martina Álvarez
Javier Pascual
Iñaki Comino-Méndez
Emilio Alba
Source :
npj Breast Cancer, Vol 10, Iss 1, Pp 1-14 (2024)
Publication Year :
2024
Publisher :
Nature Portfolio, 2024.

Abstract

Abstract Early breast cancer patients often experience relapse due to residual disease after treatment. Liquid biopsy is a methodology capable of detecting tumor components in blood, but low concentrations at early stages pose challenges. To detect them, next-generation sequencing has promise but entails complex processes. Exploring larger blood volumes could overcome detection limitations. Herein, a total of 282 high-volume plasma and blood-cell samples were collected for dual ctDNA/CTCs detection using a single droplet-digital PCR assay per patient. ctDNA and/or CTCs were detected in 100% of pre-treatment samples. On the other hand, post-treatment positive samples exhibited a minimum variant allele frequency of 0.003% for ctDNA and minimum cell number of 0.069 CTCs/mL of blood, surpassing previous investigations. Accurate prediction of residual disease before surgery was achieved in patients without a complete pathological response. A model utilizing ctDNA dynamics achieved an area under the ROC curve of 0.92 for predicting response. We detected disease recurrence in blood in the three patients who experienced a relapse, anticipating clinical relapse by 34.61, 9.10, and 7.59 months. This methodology provides an easily implemented alternative for ultrasensitive residual disease detection in early breast cancer patients.

Details

Language :
English
ISSN :
23744677
Volume :
10
Issue :
1
Database :
Directory of Open Access Journals
Journal :
npj Breast Cancer
Publication Type :
Academic Journal
Accession number :
edsdoj.bd142254ea644db1a1eebb2a629ad70a
Document Type :
article
Full Text :
https://doi.org/10.1038/s41523-024-00642-6