RESUMEN
We report the case of a 60-year-old Japanese man with a metastatic brain tumor that caused ataxia. As a consequence of resection of a cerebellar tumor, the tumor was diagnosed as a poorly differentiated adenocarcinoma with choriocarcinomatous features. The patient underwent bronchoscopy, leading to a diagnosis of the same histology as the brain tumor. After the administration of first-line chemotherapy and maintenance therapy due to progressive disease, he was given nivolumab and obtained a partial response; however, 11-months later, computed tomography showed tumor progression. Our experience suggests that nivolumab has strong activity, even in patients with a rare form of lung cancer.
Asunto(s)
Adenocarcinoma/tratamiento farmacológico , Anticuerpos Monoclonales/uso terapéutico , Neoplasias Encefálicas/patología , Coriocarcinoma/patología , Neoplasias Pulmonares/tratamiento farmacológico , Adenocarcinoma/secundario , Adenocarcinoma del Pulmón , Antineoplásicos/uso terapéutico , Humanos , Neoplasias Pulmonares/secundario , Masculino , Persona de Mediana Edad , Nivolumab , Tomografía Computarizada por Rayos XRESUMEN
Personalized medicine allows the selection of treatments best suited to an individual patient and disease phenotype. To implement personalized medicine, effective tests predictive of response to treatment or susceptibility to adverse events are needed, and to develop a personalized medicine test, both high quality samples and reliable data are required. We review key features of state-of-the-art proteomic profiling and introduce further analytic developments to build a proteomic toolkit for use in personalized medicine approaches. The combination of novel analytical approaches in proteomic data generation, alignment and comparison permit translation of identified biomarkers into practical assays. We further propose an expanded statistical analysis to understand the sources of variability between individuals in terms of both protein expression and clinical variables and utilize this understanding in a predictive test.