Digital Image Analysis Applied to Tumor Cell Proliferation, Aggressiveness, and Migration-Related Protein Synthesis in Neuroblastoma 3D Models.
Int J Mol Sci
; 21(22)2020 Nov 17.
Article
em En
| MEDLINE
| ID: mdl-33212997
ABSTRACT
Patient-derived cancer 3D models are a promising tool that will revolutionize personalized cancer therapy but that require previous knowledge of optimal cell growth conditions and the most advantageous parameters to evaluate biomimetic relevance and monitor therapy efficacy. This study aims to establish general guidelines on 3D model characterization phenomena, focusing on neuroblastoma. We generated gelatin-based scaffolds with different stiffness and performed SK-N-BE(2) and SH-SY5Y aggressive neuroblastoma cell cultures, also performing co-cultures with mouse stromal Schwann cell line (SW10). Model characterization by digital image analysis at different time points revealed that cell proliferation, vitronectin production, and migration-related gene expression depend on growing conditions and are specific to the tumor cell line. Morphometric data show that 3D in vitro models can help generate optimal patient-derived cancer models, by creating, identifying, and choosing patterns of clinically relevant artificial microenvironments to predict patient tumor cell behavior and therapeutic responses.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Biossíntese de Proteínas
/
Processamento de Imagem Assistida por Computador
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Movimento Celular
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Proliferação de Células
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Proteínas de Neoplasias
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Neuroblastoma
Tipo de estudo:
Guideline
/
Prognostic_studies
Limite:
Humans
Idioma:
En
Revista:
Int J Mol Sci
Ano de publicação:
2020
Tipo de documento:
Article
País de afiliação:
Espanha