RESUMEN
Proteasome inhibitors have revolutionized outcomes in multiple myeloma, but they are used empirically, and primary and secondary resistance are emerging problems. We have identified TJP1 as a determinant of plasma cell proteasome inhibitor susceptibility. TJP1 suppressed expression of the catalytically active immunoproteasome subunits LMP7 and LMP2, decreased proteasome activity, and enhanced proteasome inhibitor sensitivity in vitro and in vivo. This occurred through TJP1-mediated suppression of EGFR/JAK1/STAT3 signaling, which modulated LMP7 and LMP2 levels. In the clinic, high TJP1 expression in patient myeloma cells was associated with a significantly higher likelihood of responding to bortezomib and a longer response duration, supporting the use of TJP1 as a biomarker to identify patients most likely to benefit from proteasome inhibitors.
Asunto(s)
Receptores ErbB/metabolismo , Janus Quinasa 1/metabolismo , Mieloma Múltiple/tratamiento farmacológico , Complejo de la Endopetidasa Proteasomal/metabolismo , Inhibidores de Proteasoma/uso terapéutico , Factor de Transcripción STAT3/metabolismo , Proteína de la Zonula Occludens-1/metabolismo , Animales , Antineoplásicos/farmacología , Biomarcadores de Tumor/genética , Biomarcadores de Tumor/metabolismo , Western Blotting , Bortezomib/farmacología , Bortezomib/uso terapéutico , Línea Celular Tumoral , Cisteína Endopeptidasas/metabolismo , Supervivencia sin Enfermedad , Clorhidrato de Erlotinib/farmacología , Clorhidrato de Erlotinib/uso terapéutico , Perfilación de la Expresión Génica/métodos , Regulación Neoplásica de la Expresión Génica/efectos de los fármacos , Humanos , Ratones SCID , Mieloma Múltiple/genética , Mieloma Múltiple/metabolismo , Inhibidores de Proteasoma/farmacología , Interferencia de ARN , Reacción en Cadena de la Polimerasa de Transcriptasa Inversa , Transducción de Señal/efectos de los fármacos , Ensayos Antitumor por Modelo de Xenoinjerto/métodos , Proteína de la Zonula Occludens-1/genéticaRESUMEN
Breast cancer is one of the most common malignant tumours. However, the existing functional knowledge about the proteins related to the breast cancer is too general to promote the following study. To find their finer functions, we suggest using the function-specific interaction sub-networks by integrating the functional knowledge of Gene Ontology and the protein-protein interaction network. The results show that the proposed approach is able to reliably find finer functions for these proteins with high precision. The predicted finer functions are highly valuable for guiding the follow-up wet-lab re-search to study the molecular mechanism of breast cancer.