Evidence map›Paper›PMID 41098933›Full record

ArticleCureus2025

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

Naoki Katase, Yae Sakamoto, Hiroki Suda, Rin Miyahara, Shuichi Fujita

Abstract read
In one paragraph

Article in Cureus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Naoki KataseDepartment of Oral Pathology, Nagasaki University, Graduate School of Biomedical Sciences, Nagasaki, JPN.
Yae SakamotoDepartment of Oral Pathology, Nagasaki University, Graduate School of Biomedical Sciences, Nagasaki, JPN.
Hiroki SudaDental School, Nagasaki University, Nagasaki, JPN.
Rin MiyaharaDental School, Nagasaki University, Nagasaki, JPN.
Shuichi FujitaDepartment of Oral Pathology, Nagasaki University, Graduate School of Biomedical Sciences, Nagasaki, JPN.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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 (

Indexed as

bioinformaticsdeseq2head and neck squamous cell carcinomasquamous cell carcinomatcga database

Identifiers

PMID41098933
PMCPMC12519442

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.