Constructing a prognostic model for head and neck squamous cell carcinoma based on glucose metabolism related genes
BackgroundGlucose metabolism (GM) plays a crucial role in cancer cell proliferation, tumor growth, and survival. However, the identification of glucose metabolism-related genes (GMRGs) for effective prediction of prognosis in head and neck squamous cell carcinoma (HNSC) is still lacking.MethodsWe co...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2023-10-01
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| Series: | Frontiers in Endocrinology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fendo.2023.1245629/full |
| _version_ | 1827796853715894272 |
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| author | Yu Liu Nana Liu Xue Zhou Lingqiong Zhao Wei Wei Jie Hu Zhibin Luo |
| author_facet | Yu Liu Nana Liu Xue Zhou Lingqiong Zhao Wei Wei Jie Hu Zhibin Luo |
| author_sort | Yu Liu |
| collection | DOAJ |
| description | BackgroundGlucose metabolism (GM) plays a crucial role in cancer cell proliferation, tumor growth, and survival. However, the identification of glucose metabolism-related genes (GMRGs) for effective prediction of prognosis in head and neck squamous cell carcinoma (HNSC) is still lacking.MethodsWe conducted differential analysis between HNSC and Normal groups to identify differentially expressed genes (DEGs). Key module genes were obtained using weighted gene co-expression network analysis (WGCNA). Intersection analysis of DEGs, GMRGs, and key module genes identified GMRG-DEGs. Univariate and multivariate Cox regression analyses were performed to screen prognostic-associated genes. Independent prognostic analysis of clinical traits and risk scores was implemented using Cox regression. Gene set enrichment analysis (GSEA) was used to explore functional pathways and genes between high- and low-risk groups. Immune infiltration analysis compared immune cells between the two groups in HNSC samples. Drug prediction was performed using the Genomics of Drug Sensitivity in Cancer (GDSC) database. Quantitative real-time fluorescence PCR (qRT-PCR) validated the expression levels of prognosis-related genes in HNSC patients.ResultsWe identified 4973 DEGs between HNSC and Normal samples. Key gene modules, represented by black and brown module genes, were identified. Intersection analysis revealed 76 GMRG-DEGs. Five prognosis-related genes (MTHFD2, CDKN2A, TPM2, MPZ, and DNMT1) were identified. A nomogram incorporating age, lymph node status (N), and risk score was constructed for survival prediction in HNSC patients. Immune infiltration analysis showed significant differences in five immune cell types (Macrophages M0, memory B cells, Monocytes, Macrophages M2, and Dendritic resting cells) between the high- and low-risk groups. GDSC database analysis identified 53 drugs with remarkable differences between the groups, including A.443654 and AG.014699. DNMT1 and MTHFD2 were up-regulated, while MPZ was down-regulated in HNSC.ConclusionOur study highlights the significant association of five prognosis-related genes (MTHFD2, CDKN2A, TPM2, MPZ, and DNMT1) with HNSC. These findings provide further evidence of the crucial role of GMRGs in HNSC. |
| first_indexed | 2024-03-11T19:12:57Z |
| format | Article |
| id | doaj.art-47131a3e45a24f03b3fd8def265fc274 |
| institution | Directory Open Access Journal |
| issn | 1664-2392 |
| language | English |
| last_indexed | 2024-03-11T19:12:57Z |
| publishDate | 2023-10-01 |
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| series | Frontiers in Endocrinology |
| spelling | doaj.art-47131a3e45a24f03b3fd8def265fc2742023-10-09T10:33:23ZengFrontiers Media S.A.Frontiers in Endocrinology1664-23922023-10-011410.3389/fendo.2023.12456291245629Constructing a prognostic model for head and neck squamous cell carcinoma based on glucose metabolism related genesYu Liu0Nana Liu1Xue Zhou2Lingqiong Zhao3Wei Wei4Jie Hu5Zhibin Luo6Department of Oncology, Chongqing General Hospital, Chongqing, ChinaDepartment of Onclogy, People’s Hospital of Chongqing Hechuan, Chongqing, ChinaDepartment of Oncology, The Affiliated Hospital of Southwest Medical University, Luzhou, ChinaDepartment of Oncology, Chongqing General Hospital, Chongqing, ChinaDepartment of Oncology, Chongqing General Hospital, Chongqing, ChinaDepartment of Otolaryngology Head and Neck Surgery, Chongqing General Hospital, Chongqing, ChinaDepartment of Oncology, Chongqing General Hospital, Chongqing, ChinaBackgroundGlucose metabolism (GM) plays a crucial role in cancer cell proliferation, tumor growth, and survival. However, the identification of glucose metabolism-related genes (GMRGs) for effective prediction of prognosis in head and neck squamous cell carcinoma (HNSC) is still lacking.MethodsWe conducted differential analysis between HNSC and Normal groups to identify differentially expressed genes (DEGs). Key module genes were obtained using weighted gene co-expression network analysis (WGCNA). Intersection analysis of DEGs, GMRGs, and key module genes identified GMRG-DEGs. Univariate and multivariate Cox regression analyses were performed to screen prognostic-associated genes. Independent prognostic analysis of clinical traits and risk scores was implemented using Cox regression. Gene set enrichment analysis (GSEA) was used to explore functional pathways and genes between high- and low-risk groups. Immune infiltration analysis compared immune cells between the two groups in HNSC samples. Drug prediction was performed using the Genomics of Drug Sensitivity in Cancer (GDSC) database. Quantitative real-time fluorescence PCR (qRT-PCR) validated the expression levels of prognosis-related genes in HNSC patients.ResultsWe identified 4973 DEGs between HNSC and Normal samples. Key gene modules, represented by black and brown module genes, were identified. Intersection analysis revealed 76 GMRG-DEGs. Five prognosis-related genes (MTHFD2, CDKN2A, TPM2, MPZ, and DNMT1) were identified. A nomogram incorporating age, lymph node status (N), and risk score was constructed for survival prediction in HNSC patients. Immune infiltration analysis showed significant differences in five immune cell types (Macrophages M0, memory B cells, Monocytes, Macrophages M2, and Dendritic resting cells) between the high- and low-risk groups. GDSC database analysis identified 53 drugs with remarkable differences between the groups, including A.443654 and AG.014699. DNMT1 and MTHFD2 were up-regulated, while MPZ was down-regulated in HNSC.ConclusionOur study highlights the significant association of five prognosis-related genes (MTHFD2, CDKN2A, TPM2, MPZ, and DNMT1) with HNSC. These findings provide further evidence of the crucial role of GMRGs in HNSC.https://www.frontiersin.org/articles/10.3389/fendo.2023.1245629/fullglucose metabolismhead and neck squamous cell carcinomaimmune microenvironmenttherapeutic targetdrug sensitivityprognosis |
| spellingShingle | Yu Liu Nana Liu Xue Zhou Lingqiong Zhao Wei Wei Jie Hu Zhibin Luo Constructing a prognostic model for head and neck squamous cell carcinoma based on glucose metabolism related genes Frontiers in Endocrinology glucose metabolism head and neck squamous cell carcinoma immune microenvironment therapeutic target drug sensitivity prognosis |
| title | Constructing a prognostic model for head and neck squamous cell carcinoma based on glucose metabolism related genes |
| title_full | Constructing a prognostic model for head and neck squamous cell carcinoma based on glucose metabolism related genes |
| title_fullStr | Constructing a prognostic model for head and neck squamous cell carcinoma based on glucose metabolism related genes |
| title_full_unstemmed | Constructing a prognostic model for head and neck squamous cell carcinoma based on glucose metabolism related genes |
| title_short | Constructing a prognostic model for head and neck squamous cell carcinoma based on glucose metabolism related genes |
| title_sort | constructing a prognostic model for head and neck squamous cell carcinoma based on glucose metabolism related genes |
| topic | glucose metabolism head and neck squamous cell carcinoma immune microenvironment therapeutic target drug sensitivity prognosis |
| url | https://www.frontiersin.org/articles/10.3389/fendo.2023.1245629/full |
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