Identification and analysis of genes associated with head and neck squamous cell carcinoma by integrated bioinformatics methods
Abstract Background Head 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, id...
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| Format: | Article |
| Language: | English |
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Wiley
2019-08-01
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| Series: | Molecular Genetics & Genomic Medicine |
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| Online Access: | https://doi.org/10.1002/mgg3.857 |
| _version_ | 1797988218524663808 |
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| author | Yu Jin Ya Yang |
| author_facet | Yu Jin Ya Yang |
| author_sort | Yu Jin |
| collection | DOAJ |
| description | Abstract Background Head 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. Methods Overlapping 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. Results The 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. Conclusion This study identified effective and reliable molecular biomarkers for diagnosis and prognosis by integrated bioinformatics analysis, suggesting novel and essential therapeutic targets for HNSCC. |
| first_indexed | 2024-04-11T08:00:36Z |
| format | Article |
| id | doaj.art-a76e6e40bb5b417d83e0da0b41222753 |
| institution | Directory Open Access Journal |
| issn | 2324-9269 |
| language | English |
| last_indexed | 2024-04-11T08:00:36Z |
| publishDate | 2019-08-01 |
| publisher | Wiley |
| record_format | Article |
| series | Molecular Genetics & Genomic Medicine |
| spelling | doaj.art-a76e6e40bb5b417d83e0da0b412227532022-12-22T04:35:45ZengWileyMolecular Genetics & Genomic Medicine2324-92692019-08-0178n/an/a10.1002/mgg3.857Identification and analysis of genes associated with head and neck squamous cell carcinoma by integrated bioinformatics methodsYu Jin0Ya Yang1Department of General Dentistry Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine Shanghai PR ChinaDepartment of General Dentistry Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine Shanghai PR ChinaAbstract Background Head 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. Methods Overlapping 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. Results The 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. Conclusion This study identified effective and reliable molecular biomarkers for diagnosis and prognosis by integrated bioinformatics analysis, suggesting novel and essential therapeutic targets for HNSCC.https://doi.org/10.1002/mgg3.857biomarkerGEOhead and neck squamous cell carcinomaprognosisTCGA |
| spellingShingle | Yu Jin Ya Yang Identification and analysis of genes associated with head and neck squamous cell carcinoma by integrated bioinformatics methods Molecular Genetics & Genomic Medicine biomarker GEO head and neck squamous cell carcinoma prognosis TCGA |
| title | Identification and analysis of genes associated with head and neck squamous cell carcinoma by integrated bioinformatics methods |
| title_full | Identification and analysis of genes associated with head and neck squamous cell carcinoma by integrated bioinformatics methods |
| title_fullStr | Identification and analysis of genes associated with head and neck squamous cell carcinoma by integrated bioinformatics methods |
| title_full_unstemmed | Identification and analysis of genes associated with head and neck squamous cell carcinoma by integrated bioinformatics methods |
| title_short | Identification and analysis of genes associated with head and neck squamous cell carcinoma by integrated bioinformatics methods |
| title_sort | identification and analysis of genes associated with head and neck squamous cell carcinoma by integrated bioinformatics methods |
| topic | biomarker GEO head and neck squamous cell carcinoma prognosis TCGA |
| url | https://doi.org/10.1002/mgg3.857 |
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