Identification and analysis of genes associated with head and neck squamous cell carcinoma by integrated bioinformatics methods.

Yu Jin,Ya Yang

doi:10.1002/mgg3.857

Abstract

BackgroundHead and neck squamous cell carcinoma (HNSCC) is one of the most common cancers worldwide, exhibiting high morbidity and mortality. The prognosis of HNSCC patients has remained poor, though considerable efforts have been made to improve the treatment of this cancer. Therefore, identifying significant differentially expressed genes (DEGs) involved in HNSCC progression and exploiting them as novel biomarkers or potential therapeutic targets for HNSCC is highly valuable.MethodsOverlapping differentially expressed genes (DEGs) were screened out from three independent gene expression omnibus (GEO) datasets and subjected to GO and kyoto encyclopedia of genes and genomes pathway enrichment analyses. The protein–protein interactions network of DEGs was constructed in the STRING database, and the top ten hub genes were selected using cytoHubba. The relative expression of hub genes was detected in GEPIA, Oncomine, and human protein atlas (HPA) databases. Furthermore, the relationship of hub genes with the overall survival and disease‐free survival in HNSCC patients was investigated using the cancer genome atlas data.ResultsThe top ten hub genes (SPP1, POSTN, COL1A2, FN1, IGFBP3, APP, MMP3, MMP13, CXCL8, and CXCL12) could be utilized as potential diagnostic indicators for HNSCC. The relative levels of FN1, APP, SPP1, and POSTN could be associated with the prognosis of HNSCC patients. The mRNA expression of APP and COL1A2 was validated in HNSCC samples.ConclusionThis study identified effective and reliable molecular biomarkers for diagnosis and prognosis by integrated bioinformatics analysis, suggesting novel and essential therapeutic targets for HNSCC.

Highlights

Head and neck squamous cell carcinoma (HNSCC) is ranked as the sixth most common cancer worldwide with approximately 550,000 new cases and 300,000 deaths each year (2016, & Jemal, 22016)
To further validate the mRNA level of hub genes in HNSCC, we examined the relative expression of these genes in two databases, namely, Oncomine and GEPIA
The results showed that fibronectin‐1 (FN1, OMIM:135600) was the most outstanding gene with connectivity degree = 40, followed by amyloid precursor protein (APP, OMIM:104760; degree = 26), interleukin‐8 (CXCL8, OMIM:146930; degree = 23), osteopontin (SPP1, OMIM: 166490; degree = 23), stromelysin‐1 (MMP3, OMIM:185250; degree = 20), periostin (POSTN, OMIM:608777; degree = 19), collagen alpha‐2 (COL1A2, OMIM:120160; degree = 19), collagenase 3 (MMP13, OMIM: 600108; degree = 18), insulin‐like

Summary

| INTRODUCTION

Head and neck squamous cell carcinoma (HNSCC) is ranked as the sixth most common cancer worldwide with approximately 550,000 new cases and 300,000 deaths each year (2016, & Jemal, 22016). Integrated analyses of multiple datasets may improve the accuracy and reliability of the analysis and produce a more comprehensive and well‐rounded discovery of DEGs in a variety of cancers. By analyzing the original data (GSE13911, GSE19826, GSE79973 and GSE29272) from the GEO database, the most significant genes and pathways associated with gastric cancer were identified, providing potential therapeutic targets to improve the clinical effects in patients with gastric cancer (Fei et al, 2018). What is more, dysregulated genes identified from four independent GEO datasets were found to be closely associated with hepatocellular carcinoma progression and may be exploited as potential biomarkers for diagnosis and prognosis (Yin et al, 2016). Original data from microarray analyses conducted on HNSCC samples were downloaded from the GEO database, and integrated analysis was implemented. The relative expression level of hub genes and their relationship with HNSCC patient survival were validated in multiple online databases

| Ethical compliance

| RESULTS

Findings

| DISCUSSION

| CONCLUSION