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El cribado masivo paralelo agrupado revela determinantes genómicos de la entrega de nanopartículas
Natalie Boehnke1,2, Joelle P Straehla1,2,3,4, Hannah C Safford1
1Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02142, USA.
Science (New York, N.Y.)
|July 21, 2022
Resumen
Los investigadores identificaron factores clave que influyen en la entrega de nanopartículas en el cáncer. Encontraron un biomarcador, la expresión génica SLC46A3, que predice qué tan bien las nanopartículas entran en las células, ayudando en el diseño de mejores nanomedicinas contra el cáncer.
Área de la Ciencia:
- Ingeniería biomédica
- La genómica
- Nanotecnología
Sus antecedentes:
- Acelerar la traducción clínica de la nanomedicina del cáncer requiere una comprensión más profunda de las interacciones entre las nanopartículas y las células.
- Los enfoques actuales a menudo carecen de la escala para investigar exhaustivamente los factores complejos que rigen el tráfico de nanopartículas.
Objetivo del estudio:
- Para aclarar los procesos celulares que rigen el tráfico de nanopartículas utilizando un enfoque genómico integrado.
- Identificar las propiedades de los materiales y las características intrínsecas de las células que median la asociación entre las nanopartículas y las células.
- Desarrollar biomarcadores predictivos para la entrega de nanopartículas.
Principales métodos:
- Desarrolló una pantalla masivamente paralela utilizando líneas de células cancerosas codificadas y agrupadas con datos multiómicos.
- Investigó patrones de asociación celular a través de una biblioteca de nanopartículas diversas.
- Aprendizaje automático aplicado para construir redes de tráfico de nanopartículas genómicas.
Principales resultados:
- Identificaron las propiedades críticas del material y las características intrínsecas de la célula que influyen en la asociación de nanopartículas.
- Descubrió biomarcadores específicos de nanopartículas a través del análisis de la red genómica.
- Expresión genética SLC46A3 validada como predictor inverso de la absorción de nanopartículas basadas en lípidos in vitro e in vivo.
Conclusiones:
- Las pantallas genómicas integradas son herramientas poderosas para optimizar los sistemas de entrega de nanopartículas.
- El biomarcador identificado, SLC46A3, permite el diseño racional de nanoformulaciones para mejorar la traducción de la nanomedicina del cáncer.
- Este trabajo proporciona un marco para utilizar biomarcadores para mejorar la orientación y la eficacia de las nanopartículas.
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