Establishment of patient-derived organoids for guiding personalized therapies in breast cancer patients.
Int J Cancer
; 155(2): 324-338, 2024 Jul 15.
Article
en En
| MEDLINE
| ID: mdl-38533706
ABSTRACT
Breast cancer has become the most commonly diagnosed cancer. The intra- and interpatient heterogeneity induced a considerable variation in treatment efficacy. There is an urgent requirement for preclinical models to anticipate the effectiveness of individualized drug responses. Patient-derived organoids (PDOs) can accurately recapitulate the architecture and biological characteristics of the origin tumor, making them a promising model that can overtake many limitations of cell lines and PDXs. However, it is still unclear whether PDOs-based drug testing can benefit breast cancer patients, particularly those with tumor recurrence or treatment resistance. Fresh tumor samples were surgically resected for organoid culture. Primary tumor samples and PDOs were subsequently subjected to H&E staining, immunohistochemical (IHC) analysis, and whole-exome sequencing (WES) to make comparisons. Drug sensitivity tests were performed to evaluate the feasibility of this model for predicting patient drug response in clinical practice. We established 75 patient-derived breast cancer organoid models. The results of H&E staining, IHC, and WES revealed that PDOs inherited the histologic and genetic characteristics of their parental tumor tissues. The PDOs successfully predicted the patient's drug response, and most cases exhibited consistency between PDOs' drug susceptibility test results and the clinical response of the matched patient. We conclude that the breast cancer organoids platform can be a potential preclinical tool used for the selection of effective drugs and guided personalized therapies for patients with advanced breast cancer.
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Bases de datos:
MEDLINE
Asunto principal:
Neoplasias de la Mama
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Organoides
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Medicina de Precisión
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Secuenciación del Exoma
Límite:
Adult
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Aged
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Female
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Humans
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Middle aged
Idioma:
En
Revista:
Int J Cancer
Año:
2024
Tipo del documento:
Article