RESUMEN
BACKGROUND: The advance of new treatment strategies for more effective management of oral cancer requires identification of novel biological targets. Therefore, the purpose of this study is to identify novel biomarkers associated with oral tumorigenesis and prognostic signature by comparing gene expression profile of oral squamous cell carcinomas (OSCCs). METHODS: Four datasets including GSE25099, GSE30784, GSE37991, and GSE41613 were collected from Gene Expression Omnibus (GEO) database. Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, Cox model analysis, identification of key genes, and Kaplan-Meier analysis were also performed. The xCell was utilized to analyze the infiltration levels of immune cells. RESULTS: A total of 235 differentially expressed genes (DEGs) were found to be dysregulated in OSCC. These genes were mainly enriched in ECM receptor interaction and focal adhesion. Cox regression analysis identified 10 genes considered as key genes. Kaplan-Meier analysis showed that low expression of SERPINE1 (also known as PAI-1), high expression of CD1C, and C-X3-C motif chemokine receptor 1 (CX3CR1) were associated with well prognostic status in OSCC patients. In addition, we constructed a 3-immune-cell signature (myeloid dendritic cell, T cell CD4+ central memory, and common myeloid progenitor) that may be used to predict the survival status of OSCC patients. CONCLUSION: Three key genes and 3-immune-cell signature were potential biomarkers for the prognosis of OSCC, and they may serve as potential targets for the treatment of OSCC patients.
Asunto(s)
Neoplasias de la Boca/genética , Neoplasias de la Boca/inmunología , Carcinoma de Células Escamosas de Cabeza y Cuello/genética , Carcinoma de Células Escamosas de Cabeza y Cuello/inmunología , Biomarcadores de Tumor/genética , Biología Computacional , Bases de Datos Genéticas/estadística & datos numéricos , Regulación Neoplásica de la Expresión Génica , Ontología de Genes , Redes Reguladoras de Genes , Humanos , Células de Memoria Inmunológica/inmunología , Estimación de Kaplan-Meier , Pronóstico , Modelos de Riesgos Proporcionales , Transducción de Señal/genética , Transducción de Señal/inmunología , Transcriptoma , Microambiente Tumoral/genética , Microambiente Tumoral/inmunologíaRESUMEN
BACKGROUND: Patients with oral squamous carcinoma (OSCC) present difficulty in precise diagnosis and poor prognosis. OBJECTIVE: We aimed to identify the diagnostic and prognostic indicators in OSCC and provide basis for molecular mechanism investigation of OSCC. METHODS: We collected sequencing data and clinical data from TCGA database and screened the differentially expressed mRNAs (DEmRNAs) and lncRNAs (DElncRNAs) in OSCC. Machine learning and modeling were performed to identify the optimal diagnostic markers. In order to determine lncRNAs with prognostic value, survival analysis was performed through combing the expression profiles with the clinical data. Finally, co-expressed DEmRNAs of lncRNAs were identified by interacted network construction and functional annotated by GO and KEGG analysis. RESULTS: A total of 1114 (345 up- and 769 down-regulated) DEmRNAs and 156 (86 up- and 70 down-regulated) DElncRNAs were obtained in OSCC. Following the machine learning and modeling, 15 lncRNAs were identified to be the optimal diagnostic indicators of OSCC. Among them, FOXD2.AS1 was significantly associated with survival rate of patients with OSCC. In addition, Focal adhesion and ECM-receptor interaction pathways were found to be involved in OSCC. CONCLUSIONS: FOXD2.AS1 might be a prognostic marker for OSCC and our study may provide more information to the further study in OSCC.