{"title":"E2F1 Promotes the Occurrence of Head and Neck Squamous Cell Carcinoma and Serves as a Prognostic Biomarker.","authors":"Jinhang Wang, Zifeng Cui, Naiheng Hei, Qian Yang, Shixiong Peng","doi":"10.1007/s12010-024-05097-w","DOIUrl":null,"url":null,"abstract":"<p><p>Head and neck squamous cell carcinoma (HNSCC) is a common malignant tumor occurring in various sites such as the oral cavity, pharynx, larynx, and nasal cavity. This study aimed to explore the biological functions and prognostic value of E2F transcription factor 1 (E2F1) in HNSCC. Transcriptome and single-cell sequencing (scRNA-seq) data of HNSCC patients were analyzed using data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). All samples were divided into high and low expression groups based on the expression levels of E2F1. A risk model was constructed based on Lasso-Cox regression, and the differences between the two groups in terms of prognosis were explored. The scRNA-seq data of HNSCC samples were analyzed using the Seurat package to identify cell types. AUCell was used to score different types of cells, and subsequently, the interaction pathways between the high-scoring cell population and other cell populations were explored using the CellChat package. The expression level of E2F1 in tumor tissues was higher than that in normal tissues, which was confirmed by in vitro experiments. Analysis of transcriptome data from TCGA revealed significant differences in overall survival (OS) between the high and low expression groups. Prognostic genes were selected based on DEGs between the two groups, and a risk model was constructed. Subsequently, a nomogram model was constructed based on clinical factors and risk scores, which exhibited good predictive performance. The expression landscape of prognostic genes in different cell types was explored using scRNA-seq data of HNSCC samples. Dendritic cell populations were identified as high-scoring cell populations, and the pathways of interaction between this cell population and other cell populations were explored. We identified E2F1 as an independent prognostic factor closely associated with the prognosis and immune response of HNSCC.</p>","PeriodicalId":465,"journal":{"name":"Applied Biochemistry and Biotechnology","volume":" ","pages":""},"PeriodicalIF":3.1000,"publicationDate":"2024-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Biochemistry and Biotechnology","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1007/s12010-024-05097-w","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Head and neck squamous cell carcinoma (HNSCC) is a common malignant tumor occurring in various sites such as the oral cavity, pharynx, larynx, and nasal cavity. This study aimed to explore the biological functions and prognostic value of E2F transcription factor 1 (E2F1) in HNSCC. Transcriptome and single-cell sequencing (scRNA-seq) data of HNSCC patients were analyzed using data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). All samples were divided into high and low expression groups based on the expression levels of E2F1. A risk model was constructed based on Lasso-Cox regression, and the differences between the two groups in terms of prognosis were explored. The scRNA-seq data of HNSCC samples were analyzed using the Seurat package to identify cell types. AUCell was used to score different types of cells, and subsequently, the interaction pathways between the high-scoring cell population and other cell populations were explored using the CellChat package. The expression level of E2F1 in tumor tissues was higher than that in normal tissues, which was confirmed by in vitro experiments. Analysis of transcriptome data from TCGA revealed significant differences in overall survival (OS) between the high and low expression groups. Prognostic genes were selected based on DEGs between the two groups, and a risk model was constructed. Subsequently, a nomogram model was constructed based on clinical factors and risk scores, which exhibited good predictive performance. The expression landscape of prognostic genes in different cell types was explored using scRNA-seq data of HNSCC samples. Dendritic cell populations were identified as high-scoring cell populations, and the pathways of interaction between this cell population and other cell populations were explored. We identified E2F1 as an independent prognostic factor closely associated with the prognosis and immune response of HNSCC.
期刊介绍:
This journal is devoted to publishing the highest quality innovative papers in the fields of biochemistry and biotechnology. The typical focus of the journal is to report applications of novel scientific and technological breakthroughs, as well as technological subjects that are still in the proof-of-concept stage. Applied Biochemistry and Biotechnology provides a forum for case studies and practical concepts of biotechnology, utilization, including controls, statistical data analysis, problem descriptions unique to a particular application, and bioprocess economic analyses. The journal publishes reviews deemed of interest to readers, as well as book reviews, meeting and symposia notices, and news items relating to biotechnology in both the industrial and academic communities.
In addition, Applied Biochemistry and Biotechnology often publishes lists of patents and publications of special interest to readers.