Head and neck squamous cell carcinoma (HNSCC) is one of the most common malignant cancers in the world. In advanced stages, the mortality rate is high. Stratification of HNSCC patients by molecular characteristics allows optimization of clinical management of these patients. Here, we explored the GEO and PRIDE Databases to identify putative prognostic biomarkers for HNSCC. Thus, an integrated transcriptome analysis was performed to identify the major differentially expressed genes in HNSCC tissues (using GSE12452, GSE13597, GSE31056, GSE6631 and GSE3524 GEO Datasets) in combination with a proteomic analysis to identify the overrepresented proteins in saliva samples from HNSCC patients (using PRIDE PXD012436 dataset). The panel of identified biomarkers was characterized using web tools, namely UALCAN, ToPP and PINAv3.0. From the combinatorial analysis of these Omics data, the salivary biomarkers with the greatest potential for clinical application for prognostic stratification were identified: ADH7, MMP9, and S100A14. Overall, this Multi-Omics approach provides comprehensive information on the potential value of combining ADH7, MMP9, and S100A14 as prognostic biomarker panel for risk stratification. Future studies should validate this panel of biomarkers in saliva samples from a large cohort of patients using targeted approaches, envisioning its translation into the clinical setting.
Multi-omics approach reveals promising salivary protein markers for head and neck squamous cell carcinoma prognosis / Barros, Oriana; D'Agostino, Vito G.; Santos, Lucio; Ferreira, Rita; Vitorino, Rui. - In: ORAL ONCOLOGY REPORTS. - ISSN 2772-9060. - 7:(2023), pp. 1000841-1000848. [10.1016/j.oor.2023.100084]
Multi-omics approach reveals promising salivary protein markers for head and neck squamous cell carcinoma prognosis
Vito G. D'Agostino;
2023-01-01
Abstract
Head and neck squamous cell carcinoma (HNSCC) is one of the most common malignant cancers in the world. In advanced stages, the mortality rate is high. Stratification of HNSCC patients by molecular characteristics allows optimization of clinical management of these patients. Here, we explored the GEO and PRIDE Databases to identify putative prognostic biomarkers for HNSCC. Thus, an integrated transcriptome analysis was performed to identify the major differentially expressed genes in HNSCC tissues (using GSE12452, GSE13597, GSE31056, GSE6631 and GSE3524 GEO Datasets) in combination with a proteomic analysis to identify the overrepresented proteins in saliva samples from HNSCC patients (using PRIDE PXD012436 dataset). The panel of identified biomarkers was characterized using web tools, namely UALCAN, ToPP and PINAv3.0. From the combinatorial analysis of these Omics data, the salivary biomarkers with the greatest potential for clinical application for prognostic stratification were identified: ADH7, MMP9, and S100A14. Overall, this Multi-Omics approach provides comprehensive information on the potential value of combining ADH7, MMP9, and S100A14 as prognostic biomarker panel for risk stratification. Future studies should validate this panel of biomarkers in saliva samples from a large cohort of patients using targeted approaches, envisioning its translation into the clinical setting.File | Dimensione | Formato | |
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