Differentially Expressed Genes in Head and Neck Squamous Cell Carcinoma: Exploratory Research Using the Cancer Genome Atlas (TCGA) RNA Sequence Data and DESeq2 Package

头颈部鳞状细胞癌中差异表达基因:基于癌症基因组图谱(TCGA)RNA序列数据和DESeq2软件包的探索性研究

阅读:2

Abstract

Introduction Head and neck squamous cell carcinoma (HNSCC) is the most common cancer of the head and neck region, including the oral cavity, larynx, pharynx, nasal cavity, and paranasal sinuses. Cancer arises because of cumulative genetic and epigenetic alterations in cancer-associated genes. It is important to understand the genetic/epigenetic background of the tumors to establish molecular targeted therapies. So far, the knowledge of key genes or molecules, which are closely associated with the carcinogenesis and development of HNSCC, is insufficient for targeted therapies. On the other hand, recent advances in next-generation sequencing (NGS) have greatly contributed to cancer genome research. In this research, using RNA sequence data of HNSCC stored in The Cancer Genome Atlas (TCGA) database, we identified differentially expressed genes (DEGs), functionally enriched gene sets, and new prognostic markers or candidate therapeutic targets. This exploratory study investigated whether novel prognostic markers and candidate therapeutic targets for HNSCC could be identified from TCGA RNA-seq data. Methods The RNA sequence data were downloaded from TCGA, including 504 cases from cancer and 44 cases from corresponding normal tissue. The DEGs between cancer and normal samples were detected using the DESeq2 package in R software. Differences with | log2 fold change (FC) | > 1.0 and p-value <0.05 were considered as DEGs. Functional enrichment analyses were performed by ShinyGO 0.85 with Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. A gene set enrichment analysis (GSEA) was also performed using GSEA software. We also analyzed the top 10 up- and down-regulated genes, which were sorted by adjusted p-value, by using Kaplan-Meier analysis to assess their potential as prognostic markers. Results Using the DESeq2 package, 10,976 DEGs were detected, including 6,932 up-regulated genes and 4,044 down-regulated genes in cancer. As expected, functional enrichment analyses revealed enrichment of KEGG terms associated with cancers, including "Pathway in Cancer", "Human Papillomavirus infection", and "PI3K-Akt signaling pathway" in up-regulated genes, whereas KEGG terms enriched in down-regulated genes were mainly "Metabolic pathways". GO terms for "Cell differentiation (GOBP)" and "Extracellular region (GOCC)" were enriched both in up- and down-regulated genes, suggesting aberrant expression of genes associated with cell differentiation and remodeling of the extracellular matrix. GSEA data supported the enrichment analyses data. Kaplan-Meier analyses revealed that high expression of homeobox C6 (HOXC6) (p=0.048), nucleobindin 2 (NUCB2) (p=0.007), IL12A antisense RNA 1 (IL12A-AS1) (p=0.001), calcium-binding protein 39-like (CAB39L)(p=0.038), nitric oxide synthase trafficking (NOSTRIN) (p=0.024), SLC8A1 antisense RNA 1 (SLC8A1-AS1) (p=0.016), were the significantly correlated with poorer prognosis. Conclusions Based on bioinformatical approaches, we identified significantly enriched gene sets and novel candidates for prognostic markers or therapeutic targets in HNSCC. Further investigation would aid in determining the anti-cancer effects of these candidates.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。