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Oncotarget ; 5(10): 3159-67, 2014 May 30.
Artículo en Inglés | MEDLINE | ID: mdl-24931643

RESUMEN

Inflammation is an important component of various cancers and its inflammatory cells and mediators have been shown to have prognostic potential. Tumor-infiltrating mast cells can promote tumor growth and angiogenesis, but the mechanism of mast cell activation is unclear. In earlier studies, we demonstrated that immunoglobulin free light chains (FLC) can trigger mast cells in an antigen-specific manner. Increased expression of FLC was observed within stroma of various human cancers including those of breast, colon, lung, pancreas, kidney and skin, and FLC expression co-localized with areas of mast cell infiltration. In a large cohort of breast cancer patients, FLC expression was shown associated with basal-like cancers with an aggressive phenotype. Moreover, lambda FLC was found expressed in areas of inflammatory infiltration and its expression was significantly associated with poor clinical outcome. Functional importance of FLCs was shown in a murine B16F10 melanoma model, where inhibition of FLC-mediated mast cell activation strongly reduced tumor growth. Collectively, this study identifies FLCs as a ligand in the pro-tumorigenic activation of mast cells. Blocking this pathway may open new avenues for the inhibition of tumor growth, while immunohistochemical staining of FLC may be helpful in the diagnosis and prognosis of cancer.


Asunto(s)
Biomarcadores de Tumor/inmunología , Neoplasias de la Mama/inmunología , Cadenas Ligeras de Inmunoglobulina/inmunología , Inflamación/patología , Mastocitos/inmunología , Adulto , Anciano , Animales , Neoplasias de la Mama/patología , Degranulación de la Célula/inmunología , Modelos Animales de Enfermedad , Femenino , Humanos , Cadenas Ligeras de Inmunoglobulina/análisis , Inmunohistoquímica , Estimación de Kaplan-Meier , Melanoma/inmunología , Melanoma/patología , Ratones , Ratones Endogámicos C57BL , Persona de Mediana Edad , Neoplasias Experimentales , Pronóstico , Modelos de Riesgos Proporcionales , Análisis de Matrices Tisulares
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