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Identification of potential candidate genes for lip and oral cavity cancer using network analysis

ABSTRACT: Lip and oral cavity cancer, which can occur in any part of the mouth, is the 11th most common type of cancer worldwide. The major obstacles to patients’ survival are the poor prognosis, lack of specific biomarkers, and expensive therapeutic alternatives. This study aimed to identify the main genes and pathways associated with lip and oral cavity carcinoma using network analysis and to analyze its molecular mechanism and prognostic significance further. In this study, 472 genes causing lip and oral cavity carcinoma were retrieved from the DisGeNET database. A protein-protein interaction network was developed for network analysis using the STRING database. VEGFA, IL6, MAPK3, INS, TNF, MAPK8, MMP9, CXCL8, EGF, and PTGS2 were recognized as network hub genes using the maximum clique centrality algorithm available in cytoHubba, and nine potential drug candidates (ranibizumab, siltuximab, sulindac, pomalidomide, dexrazoxane, endostatin, pamidronic acid, cetuximab, and apricoxib) for lip and oral cavity cancer were identified from the DGIdb database. Gene enrichment analysis was also performed to identify the gene ontology categorization of cellular components, biological processes, molecular functions, and biological pathways. The genes identified in this study could furnish a new understanding of the underlying molecular mechanisms of carcinogenesis and provide more reliable biomarkers for early diagnosis, prognostication, and treatment of lip and oral cavity cancer.

SUBMITTER: Mathavan S

PROVIDER: S-EPMC8042300 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Introduction: Cleft lip ± cleft palate (CL/P) is one of the most common birth defects. Although research has identified multiple genetic risk loci for different types of CL/P (i.e., syndromic or non-syndromic forms), determining the respective causal genes and understanding the relevant functional networks remain challenging. The recent introduction of single-cell RNA sequencing (scRNA-seq) has provided novel opportunities to study gene expression patterns at cellular resolution. The aims of our study were to: (i) aggregate available scRNA-seq data from embryonic mice and provide this as a resource for the craniofacial community; and (ii) demonstrate the value of these data in terms of the investigation of the gene expression patterns of CL/P candidate genes. Methods and Results: First, two published scRNA-seq data sets from embryonic mice were re-processed, i.e., data representing the murine time period of craniofacial development: (i) facial data from embryonic day (E) E11.5; and (ii) whole embryo data from E9.5-E13.5 from the Mouse Organogenesis Cell Atlas (MOCA). Marker gene expression analyses demonstrated that at E11.5, the facial data were a high-resolution representation of the MOCA data. Using CL/P candidate gene lists, distinct groups of genes with specific expression patterns were identified. Among others we identified that a co-expression network including Irf6, Grhl3 and Tfap2a in the periderm, while it was limited to Irf6 and Tfap2a in palatal epithelia, cells of the ectodermal surface, and basal cells at the fusion zone. The analyses also demonstrated that additional CL/P candidate genes (e.g., Tpm1, Arid3b, Ctnnd1, and Wnt3) were exclusively expressed in Irf6+ facial epithelial cells (i.e., as opposed to Irf6- epithelial cells). The MOCA data set was finally used to investigate differences in expression profiles for candidate genes underlying different types of CL/P. These analyses showed that syndromic CL/P genes (syCL/P) were expressed in significantly more cell types than non-syndromic CL/P candidate genes (nsCL/P). Discussion: The present study illustrates how scRNA-seq data can empower research on craniofacial development and disease.

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Identification of potential candidate genes for lip and oral cavity cancer using network analysis

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