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Decodificación de todo el quínoma de mutaciones que atacan la red que recablean la señalización del cáncer

Pau Creixell¹, Erwin M Schoof¹, Craig D Simpson²

¹Department of Systems Biology, Technical University of Denmark, 2800 Lyngby, Denmark.

|September 22, 2015

Resumen

Los investigadores identificaron mutaciones que atacan la red (NAM) en el cáncer, revelando nuevas formas en que las mutaciones interrumpen la señalización celular. Este descubrimiento podría conducir a mejores formas de dirigirse a las redes de cáncer terapéuticamente.

Área de la Ciencia:

En el campo de la oncología
Biología molecular
La bioinformática

Sus antecedentes:

Las células cancerosas desarrollan rasgos anormales al acumular mutaciones que interrumpen las redes de señalización celular.
El análisis integral de estas mutaciones y su impacto en las vías de señalización sigue siendo un desafío.

Objetivo del estudio:

Identificar y caracterizar las mutaciones que atacan la red (NAM) que impulsan los fenotipos patológicos en el cáncer.
Desarrollar y aplicar herramientas computacionales para el análisis sistemático de las mutaciones del cáncer y sus efectos en las redes de señalización.

Principales métodos:

Desarrolló ReKINect, una plataforma computacional para identificar seis tipos de NAM.
Exomas analizados y proteomas cuantitativos (fosfo) de líneas celulares de cáncer de ovario y el repositorio global del genoma del cáncer.
Las NAM identificadas validadas experimentalmente, incluidas las mutaciones específicas de la quinasa.

Principales resultados:

Se identificaron seis clases de NAM, incluida la modulación de la quinasa / SH2, el recableado de la red y los cambios en el sitio de fosforilación.
Descubrió puertas de lógica molecular mutantes, un cambio hacia la señalización de fosfotreonina y motivos de fosforilación debilitados.
Se encontraron puntos calientes de inactivación de la quinasa en el cáncer y se validaron NAM específicos como PKCγ M501I y PKD1 D665N.

Conclusiones:

La plataforma ReKINect identifica eficazmente los NAM funcionales a través de complejos genomas de cáncer y redes de señalización.
Estos hallazgos proporcionan información sobre la lógica molecular específica del cáncer y ofrecen potencial para terapias dirigidas al cáncer.

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