Computational analysis of TP53 mutational landscape unveils key prognostic signatures and distinct pathobiological pathways in head and neck squamous cell cancer
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2020-10-13
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British Journal of Cancer
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SPRINGERNATURE
Melbourne Authors
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Melbourne Dental School
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Journal Article
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Caponio, V. C. A., Troiano, G., Adipietro, I., Zhurakivska, K., Arena, C., Mangieri, D., Mascitti, M., Cirillo, N. & Lo Muzio, L. (2020). Computational analysis of TP53 mutational landscape unveils key prognostic signatures and distinct pathobiological pathways in head and neck squamous cell cancer. British Journal of Cancer, 123 (8), pp.1302-1314. https://doi.org/10.1038/s41416-020-0984-6.
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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.