Autor(es):
Ribeiro, Ilda Patrícia ; Caramelo, Francisco ; Esteves, Luísa ; Menoita, Joana ; Marques, Francisco ; Barroso, Leonor ; Miguéis, Jorge ; Melo, Joana Barbosa ; Carreira, Isabel Marques
Data: 2017
Identificador Persistente: https://hdl.handle.net/10316/108378
Origem: Estudo Geral - Universidade de Coimbra
Assunto(s): Adult; Chromosomes, Human; Cohort Studies; Comparative Genomic Hybridization; Female; Humans; Male; Middle Aged; Neoplasm Metastasis; Prognosis; Recurrence; Squamous Cell Carcinoma of Head and Neck; Genomics; Models, Statistical
Descrição
The head and neck squamous cell carcinoma (HNSCC) population consists mainly of high-risk for recurrence and locally advanced stage patients. Increased knowledge of the HNSCC genomic profile can improve early diagnosis and treatment outcomes. The development of models to identify consistent genomic patterns that distinguish HNSCC patients that will recur and/or develop metastasis after treatment is of utmost importance to decrease mortality and improve survival rates. In this study, we used array comparative genomic hybridization data from HNSCC patients to implement a robust model to predict HNSCC recurrence/metastasis. This predictive model showed a good accuracy (>80%) and was validated in an independent population from TCGA data portal. This predictive genomic model comprises chromosomal regions from 5p, 6p, 8p, 9p, 11q, 12q, 15q and 17p, where several upstream and downstream members of signaling pathways that lead to an increase in cell proliferation and invasion are mapped. The introduction of genomic predictive models in clinical practice might contribute to a more individualized clinical management of the HNSCC patients, reducing recurrences and improving patients' quality of life. The power of this genomic model to predict the recurrence and metastases development should be evaluated in other HNSCC populations.
Ribeiro I.P. is a recipient of a PhD fellowship (SFRH/BD/52290/2013) from the Portuguese Foundation for Science and Technology. Tis work was in part supported by CIMAGO (Center of Investigation on Environment Genetics and Oncobiology - Faculty of Medicine, University of Coimbra).
