Identification of potential biomarkers and survival analysis for oral squamous cell carcinoma: A transcriptomic study

ObjectiveOral squamous cell carcinoma (OSCC) is one of the most common neoplasms worldwide. The current study aimed to identify potential biomarkers associated with OSCC survival.Materials and MethodsDifferentially expressed genes (DEGs) in atypical OSCC cases were identified using two public datase...

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Published in:Oral diseases 2023-10, Vol.29 (7), p.2658-2666
Main Authors: de Paula Souza, Daniela Paola Santos, dos Reis Pereira Queiroz, Lorena, de Souza, Marcela Gonçalves, de Jesus, Sabrina Ferreira, Gomes, Emisael Stênio Batista, Vitorino, Rogério Trancoso, Santos, Sérgio Henrique Sousa, Farias, Lucyana Conceição, de Paula, Alfredo Maurício Batista, D'Angelo, Marcos Flávio Silveira Vasconcelos, de Carvalho Fraga, Carlos Alberto, Guimarães, André Luiz Sena
Format: Article
Language:English
Subjects:
Biomarkers
Fibroblast growth factor receptor 2
Gene expression
Genomes
Medical prognosis
Oral cancer
Oral carcinoma
Oral squamous cell carcinoma
Receptor activity modifying proteins
Squamous cell carcinoma
Survival analysis
Transcriptomics
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Summary:ObjectiveOral squamous cell carcinoma (OSCC) is one of the most common neoplasms worldwide. The current study aimed to identify potential biomarkers associated with OSCC survival.Materials and MethodsDifferentially expressed genes (DEGs) in atypical OSCC cases were identified using two public datasets: The Cancer Genome Atlas and the Gene Expression Omnibus database. Receiver operating characteristic (ROC) analysis was performed to identify the cutoff, and the candidate DEGs related to survival. Kaplan–Meier and Cox regression analysis using the categorized genes were employed to identify genes that impact the overall survival in OSCC.ResultsA total of 263 OSCC samples and 105 healthy tissues were used to identify 295 upregulated and 131 downregulated genes expressed only in non‐smokers. ROC analyses identified 25 candidate genes associated with death. Survival analyses demonstrated that the following DEGs, namely CSTA, FGFR2, MMP19, OLR1, PCSK1, RAMP2, and CGB5, are potential OSCC prognostic factors.ConclusionWe found that CSTA, FGFR2, MMP19, OLR1, PCSK1, RAMP2, and CGB5 are associated with a low survival rate in OSCC. However, further studies are needed to validate our findings and facilitate the development of these factors as potential biomarkers for OSCC survival.
ISSN:1354-523X
1601-0825
DOI:10.1111/odi.14302