BACKGROUND: Patients with intestinal-type sinonasal adenocarcinoma (ITAC) have an unfavorable prognosis and new therapeutic approaches are needed to improve clinical management. METHODS: Genetic analysis of 96 ITACs was performed by microarray comparative genomic hybridization and immunohistochemistry and correlated to previously obtained mutation, methylation, and protein expression data, and with pathological characteristics and clinical outcome. RESULTS: Seven copy number alterations (CNAs) were significantly associated with unfavorable clinical outcome: gains at 1q22-23, 3q28-29, 6p22, and 13q31-33, and losses at 4p15-16, 4q32-35, and 10q24. Unsupervised cluster analysis resulted in 5 subgroups of ITAC with significantly distinct genetic signatures and clinical outcomes, independently of disease stage or histological subtype. CONCLUSION: These data may guide studies to identify driver genes and signaling pathways involved in ITAC. In addition, the subclassification of genetic subgroups of patients with distinct clinical behavior can aid therapeutic decision making and may ultimately lead to personalized therapy with targeted inhibitors.
BACKGROUND:Patients with intestinal-type sinonasal adenocarcinoma (ITAC) have an unfavorable prognosis and new therapeutic approaches are needed to improve clinical management. METHODS: Genetic analysis of 96 ITACs was performed by microarray comparative genomic hybridization and immunohistochemistry and correlated to previously obtained mutation, methylation, and protein expression data, and with pathological characteristics and clinical outcome. RESULTS: Seven copy number alterations (CNAs) were significantly associated with unfavorable clinical outcome: gains at 1q22-23, 3q28-29, 6p22, and 13q31-33, and losses at 4p15-16, 4q32-35, and 10q24. Unsupervised cluster analysis resulted in 5 subgroups of ITAC with significantly distinct genetic signatures and clinical outcomes, independently of disease stage or histological subtype. CONCLUSION: These data may guide studies to identify driver genes and signaling pathways involved in ITAC. In addition, the subclassification of genetic subgroups of patients with distinct clinical behavior can aid therapeutic decision making and may ultimately lead to personalized therapy with targeted inhibitors.
Authors: Santiago Cabezas-Camarero; Virginia de la Orden García; Vanesa García-Barberán; Beatriz Mediero-Valeros; Ahmad Issa Subhi-Issa; Patricia Llovet García; Inmaculada Bando-Polaino; Salomé Merino Menéndez; Pedro Pérez-Segura; Eduardo Díaz-Rubio Journal: Oncologist Date: 2019-01-02
Authors: Paula Sánchez-Fernández; Cristina Riobello; María Costales; Blanca Vivanco; Virginia N Cabal; Rocío García-Marín; Laura Suárez-Fernández; Fernando López; Rubén Cabanillas; Mario A Hermsen; José Luis Llorente Journal: Sci Rep Date: 2021-01-26 Impact factor: 4.379