Screening Of Ferroptosis-Related Functional Genes In Head And Neck Cancer Based On Bioinformatics Analysis And The Relationship Between COL4A1 And The Occurrence And Development Of Head And Neck Cancer

Head and neck cancer is a highly heterogeneous and complex malignant tumor with a relatively high incidence.After comprehensive treatment,15%-40% of patients still have local recurrence and metastasis,and the prognosis is poor.Ferroptosis is a new form of cell death,which is closely related to the occurrence and development of various tumors,but the mechanism of ferroptosis in head and neck cancer is less reported.In this study,we first downloaded the sequencing data and clinicopathological data of head and neck cancer patients from the TCGA database,downloaded the microarray data of the head and neck cancer patients and the corresponding clinical information of the patients from the GEO database,and performed differential gene analysis on the sample data set to obtain the difference in co-expression.The KEGG pathway,GO enrichment and GSEA enrichment were used to analyze the biological functions and related signaling pathways involved.Through the mutual construction of PPI network,25 HUB genes were screened.Through correlation analysis,the key genes of head and neck cancer were screened,and the role of key genes in the occurrence and development of head and neck cancer were further verified through traditional molecular biology experiments.Part 1: Bioinformatics analysis and key gene screening of ferroptosis-related genes in head and neck cancer.Objective Downloaded head and neck cancer-related clinical data from public databases,screened differentially expressed genes through bioinformatics methods and took intersections,further obtain common differentially expressed genes,and perform related functional enrichment analysis.Methods 1.Acquisition of sequencing data and microarray data: The sequencing data and clinicopathological data of head and neck cancer were obtained from GEO(Gene Expression Omnibus,GEO)and TCGA dataset(The Cancer Genome Atlas,The TCGA data).2.Data processing: The data is preprocessed,filtered,and normalized by R language,and the background correction and data normalization are performed to obtain the gene-standardized expression matrices of the two data sets respectively.3.Differential expression analysis: head and neck cancer and normal were divided into two groups,using limma package to analyze differentially expressed RNA,and the results were represented by volcano map and heat map.4.Functional enrichment analysis: The differentially expressed m RNA target genes were analyzed for GO and KEGG signaling pathway enrichment analysis,and the biological functions of the target genes and related signaling pathways were preliminarily discussed.Results 1.In the three databases,GSE9714 has 2248 up-regulated genes and 579 down-regulated genes;GSE90761 has 3622 up-regulated genes and 649down-regulated genes;TCGA head and neck cancer radiotherapy data have1435 up-regulated genes and 780 down-regulated genes.The up-regulated differential genes were intersected,and there were 173 intersecting genes,111 ferroptosis marker genes,and 108 ferroptosis driving genes.2.The co-upregulated differentially expressed genes are mainly involved in the biological process of intracellular fatty acid metabolism,cytokine secretion and metabolism,tumor necrosis pathway,and classical oncogenic pathways such as NIK/NF-kappa B signaling and PI3K-Akt signaling pathway and affect the growth of head and neck cancer cells.proliferation and apoptosis,thereby affecting the occurrence and development of head and neck cancer.Part 2: Construction and screening of key genes with diagnostic or prognostic value based on PPI networkObjective A PPI network of common DEGs was constructed through the STRING database,and Cyto Hubba was used to analyze the hub genes in the network.Performed WGCNA analysis to obtain meaningful gene modules,and performed ROC prediction analysis on the screened meaningful HUB key genes by using the PROC package.Then,the clinicopathological features and survival information and gene expression levels of the head and neck cancer patient cohort in the TGCA database were combined to further screen out key genes with diagnostic and/or prognostic value.Methods 1.PPI network construction:On this basis,this study will construct a PPI network of common DEGs through the STRING database,and used a plug-in of Cytoscape software:Cyto Hubba to analyze the hub genes in the network.Performed WGCNA analysis to obtain meaningful gene modules,and performed ROC prediction analysis on the screened meaningful HUB key genes by using the PROC package.Then,the clinicopathological characteristics,survival information and gene expression levels of the head and neck cancer patient cohort in the TCGA database were combined to further screen out key genes with diagnostic and/or prognostic value for further molecular level verification.2.Immune infiltration analysis:24 kinds of immune cell marker genes were extracted by CIBERSORT,24 kinds of immune cell infiltration in tumors were analyzed by TIMER2(TIMER2.0.org)method,and the degree of correlation between HUB gene and expression matrix and these 24 kinds of cells was analyzed by Spearman correlation method.And the correlation with CD8+ T cells was analyzed.3.ROC diagnostic prediction and risk assessment of HUB gene By using the PROC package [12] to perform ROC prediction analysis on the screened meaningful HUB key genes;using the Survival package to perform the survival prognosis analysis;using the GEPIA website for online analysis to obtain the correlation of key genes with OS survival prognosis.4.Transcription factor screening and WGCNA analysis Targeted transcription factor screening of key genes was performed through the public database Knock TF;key gene modules and phenotype correlations were analyzed through WGCNA.5.Pathway analysis of differential genes The resulting differential genes were further visualized through GOplot,and the differential genes were subjected to KEEG/GO pathway enrichment analysis.6.Obtaining the ferroptosis gene set The ferroptosis driver gene set and marker gene set were downloaded from the online database Ferr Db,and correlation analysis was performed,and finally the genes with high correlation with ferroptosis genes were selected.Results 1.In this study,the first 25 hub genes were obtained through the mutual construction of PPI network.Comprehensive WGCNA analysis and hub gene screening showed that MMP10,MMP1,COL4A1,IFI27,INHBA,IFI6 and other genes have obvious diagnostic value in head and neck cancer.2.Based on the difference in expression and prognosis analysis,we screened out IL1 B,INHBA,COL4A1,IFI27 and other genes have a great correlation with the clinicopathological characteristics of head and neck cancer,and are closely related to the clinical stage,tumor grade,and radiotherapy level of patients.(p<0.05)3.By using the tools in the TIMER2.0 online website to determine the infiltration correlation between CD8+ T cells and key target genes(INHBA,MMP10,COL4A1,IFI27,MMP1)in 522 TCGA head and neck cancer samples,it was found that INHBA,MMP10,COL4A1,MMP1 and immune infiltration were all significantly negatively correlated,indicating that patients with radiotherapy resistance or who did not receive radiotherapy were significantly negatively correlated with immune infiltration,and significantly positively correlated with tumor invasion and metastasisPart 3: The effect of COL4A1 gene on the biological behavior of head and neck cancerObjective In the second part,we found that the expression of COL4A1 gene is closely related to the clinicopathological characteristics of head and neck cancer patients.In this part of the study,we further study the expression of COL4A1 gene in head and neck cancer tissues and cells,and explore the effect of COL4A1 gene expression on head and neck cancer.effects on cell biological function.Methods 1.Using the Oncomine database to analyze the expression difference of COL4A1 gene in head and neck cancer tissues and adjacent tissues.The expression of COL4A1 protein was detected by immunohistochemical staining,and its expression differences in head and neck cancer tissues and adjacent tissues were analyzed.2.The expression of COL4A1 in laryngeal cancer cells was inhibited by constructing a chronic viral vector of RNA interference,and the expression of COL4A1 was detected by PCR and western blot.The effect of COL4A1 gene on the proliferation of laryngeal cancer cells was observed by CCK-8 assay;the effect of COL4A1 gene on the invasion and migration of laryngeal cancer cells was observed by transwell assay.The effect of COL4A1 gene on apoptosis of laryngeal cancer cells was observed by flow cytometry.Results 1.COL4A1 protein is highly expressed in head and neck cancer tissues,and the expression level is significantly higher than that in adjacent normal tissues.2.The expression level of COL4A1 was significantly correlated with the clinical stage,radiotherapy level and pathological grade of head and neck cancer patients.3.In vitro experiments show that inhibiting the expression level of COL4A1 can significantly reduce the proliferation,migration and invasion ability of head and neck cancer cells,and vice versa.