Перейти к основному содержанию
AkademIndex

Продукты

Для разработчиков

AkademBaseОткрытый API экосистемы
Статья

Computational analysis of TP53 mutational landscape unveils key prognostic signatures and distinct pathobiological pathways in head and neck squamous cell cancer

Vito Carlo Alberto CaponioDepartment of Clinical and Experimental Medicine, University of Foggia, Foggia, ItalyGiuseppe TroianoDepartment of Clinical and Experimental Medicine, University of Foggia, Foggia, ItalyIolanda AdipietroDepartment of Clinical and Experimental Medicine, University of Foggia, Foggia, ItalyKhrystyna ZhurakivskaDepartment of Clinical and Experimental Medicine, University of Foggia, Foggia, ItalyClaudia ArenaDepartment of Clinical and Experimental Medicine, University of Foggia, Foggia, ItalyDomenica MangieriDepartment of Medical and Surgical Sciences, Biomedical Unit ‘E. Altomare’, University of Foggia, Foggia, ItalyMarco MascittiDepartment of Clinical Specialistic and Dental Sciences, Marche Polytechnic University, Ancona, ItalyNicola CirilloMelbourne Dental School, The University of Melbourne, Melbourne, VIC, AustraliaLorenzo Lo MuzioDepartment of Clinical and Experimental Medicine, University of Foggia, Foggia, Italy
2020en
ABI

Аннотация

Abstract Background Mutations of the tumour-suppressor gene TP53 are the most frequent somatic genomic alterations in head and neck squamous cell carcinoma (HNSCC). However, it is not yet clear whether specific TP53 mutations bear distinct clinical and pathophysiological significance in different HNSCC subgroups. Methods A systematic bioinformatics appraisal of TP53 mutations was performed on 415 HNSCC cases available on The Cancer Genome Atlas (TCGA). The following features were analysed and correlated with known clinicopathological variables: mutational profile of TP53, location (within secondary structure and predicted domains of p53 protein) and well-known hotspot mutations. Interactome–genome–transcriptome network analysis highlighted different gene networks. An algorithm was generated to develop a new prognostic classification system based on patients’ overall survival. Results TP53 mutations in HNSCCs exhibited distinct differences in different anatomical sites. The mutational profile of TP53 was an independent prognostic factor in HNSCC. High risk of death mutations, identified by our novel classification algorithm, was an independent prognostic factor in TCGA HNSCC database. Finally, network analysis suggested that distinct p53 molecular pathways exist in a site- and mutation-specific manner. Conclusions The mutational profile of TP53 may serve as an independent prognostic factor in HNSCC patients, and is associated with distinctive site-specific biological networks.

Перевод пока недоступен

Идентификаторы

Цитирования и источники

Цитирований: 2Использованных источников: 0