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Identification of a potential prognostic panel of biomarkers for stratification of head and neck squamous cell carcinoma based on HPV status and TP53 mutational status

Authors :
Oriana Barros
Rita Ferreira
Vito G. D'Agostino
Francisco Amado
Lucio Santos
Rui Vitorino
Source :
Oral Oncology Reports, Vol 5, Iss , Pp 100018- (2023)
Publication Year :
2023
Publisher :
Elsevier, 2023.

Abstract

Head and Neck Squamous Cell Carcinoma (HNSCC) is a malignant cancer with poor prognosis. Currently, the prognosis of HNSCC is determined by clinical and histopathological criteria. This work focused on identifying a panel of genes that have the potential to be used for prognosis of HNSCC and to improve patient stratification for treatment. To this end, a bibliometric analysis (VosViewer) was applied to identify candidate genes that were further characterized by applying several bioinformatics tools (UALCAN, ToPP). The prognostic potential of the genes of interest was evaluated using the univariate and the multivariate Cox proportional regression models and the transcriptional expression analysis among HNSCC and normal tissues. In HNSCC, the transcriptional levels of candidate genes, were analyzed in HPV-driven HNSCC, HPV-non-driven HNSCC, TP53-mutant HNSCC and TP53-nonmutant HNSCC for selecting the best set of genes for discrimination of HNSCC based on both HPV status and TP53 mutational status. These analyses revealed a signature based on four genes with greater HNSCC prognostic potential: CDKN2A, TGFB1, CD44 and MMP9, being p16 the sole biomarker currently tested. In the future, a molecular signature could facilitate the stratification of patients into high- and low-risk groups as well the wiser adjustment of therapies to each individual response allowing a personalized treatment.

Details

Language :
English
ISSN :
27729060
Volume :
5
Issue :
100018-
Database :
Directory of Open Access Journals
Journal :
Oral Oncology Reports
Publication Type :
Academic Journal
Accession number :
edsdoj.11d2e2d4e20b420d830cbfe2abb23d3c
Document Type :
article
Full Text :
https://doi.org/10.1016/j.oor.2023.100018