A Novel Immune-Related Gene Signature to Identify the Tumor Microenvironment and Prognose Disease Among Patients With Oral Squamous Cell Carcinoma Patients Using ssGSEA: A Bioinformatics and Biological Validation Study
Oral squamous cell carcinoma (OSCC) is the most invasive oral malignancy in adults and is associated with a poor prognosis. Accurate prognostic models are urgently needed, however, knowledge of the probable mechanisms behind OSCC tumorigenesis and prognosis remain limited. The clinical importance of...
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Frontiers Media S.A.
2022-07-01
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| Series: | Frontiers in Immunology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fimmu.2022.922195/full |
| _version_ | 1811290176065896448 |
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| author | Yun Chen Yunzhi Feng Fei Yan Yaqiong Zhao Han Zhao Han Zhao Han Zhao Yue Guo |
| author_facet | Yun Chen Yunzhi Feng Fei Yan Yaqiong Zhao Han Zhao Han Zhao Han Zhao Yue Guo |
| author_sort | Yun Chen |
| collection | DOAJ |
| description | Oral squamous cell carcinoma (OSCC) is the most invasive oral malignancy in adults and is associated with a poor prognosis. Accurate prognostic models are urgently needed, however, knowledge of the probable mechanisms behind OSCC tumorigenesis and prognosis remain limited. The clinical importance of the interplay between the immune system and tumor microenvironment has become increasingly evident. This study explored immune-related alterations at the multi-omics level to extract accurate prognostic markers linked to the immune response and presents a more accurate landscape of the immune genomic map during OSCC. The Cancer Genome Atlas (TCGA) OSCC cohort (n = 329) was used to detect the immune infiltration pattern of OSCC and categorize patients into two immunity groups using single-sample gene set enrichment analysis (ssGSEA) and hierarchical clustering analysis. Multiple strategies, including lasso regression (LASSO), Cox proportional hazards regression, and principal component analysis (PCA) were used to screen clinically significant signatures and identify an incorporated prognosis model with robust discriminative power on the survival status of both the training and testing set. We identified two OSCC subtypes based on immunological characteristics: Immunity-high and immunity low, and verified that the categorization was accurate and repeatable. Immunity_ high cluster with a higher immunological and stromal score. 1047 differential genes (DEGs) integrate with immune genes to obtain 319 immue-related DEGs. A robust model with five signatures for OSCC patient prognosis was established. The GEO cohort (n = 97) were used to validate the risk model’s predictive value. The low-risk group had a better overall survival (OS) than the high-risk group. Significant prognostic potential for OSCC patients was found using ROC analysis and immune checkpoint gene expression was lower in the low-risk group. We also investigated at the therapeutic sensitivity of a number of frequently used chemotherapeutic drugs in patients with various risk factors. The underlying biological behavior of the OSCC cell line was preliminarily validated. This study characterizes a reliable marker of OSCC disease progression and provides a new potential target for immunotherapy against this disease. |
| first_indexed | 2024-04-13T04:08:17Z |
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| institution | Directory Open Access Journal |
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| language | English |
| last_indexed | 2024-04-13T04:08:17Z |
| publishDate | 2022-07-01 |
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| series | Frontiers in Immunology |
| spelling | doaj.art-ea47c8ed2c434bb8a8198d2571df6f392022-12-22T03:03:11ZengFrontiers Media S.A.Frontiers in Immunology1664-32242022-07-011310.3389/fimmu.2022.922195922195A Novel Immune-Related Gene Signature to Identify the Tumor Microenvironment and Prognose Disease Among Patients With Oral Squamous Cell Carcinoma Patients Using ssGSEA: A Bioinformatics and Biological Validation StudyYun Chen0Yunzhi Feng1Fei Yan2Yaqiong Zhao3Han Zhao4Han Zhao5Han Zhao6Yue Guo7Department of Stomatology, The Second Xiangya Hospital, Central South University, Changsha, ChinaDepartment of Stomatology, The Second Xiangya Hospital, Central South University, Changsha, ChinaHunan Key Laboratory of Oral Health Research, Hunan 3D Printing Engineering Research Center of Oral Care, Hunan Clinical Research Center of Oral Major Diseases and Oral Health, Xiangya Stomatological Hospital, Xiangya School of Stomatology, Central South University, Changsha, ChinaDepartment of Stomatology, The Second Xiangya Hospital, Central South University, Changsha, ChinaDepartment of Ophthalmology, Eye, Ear, Nose, and Throat Hospital of Fudan University, Shanghai, ChinaLaboratory of Myopia, National Health Commission (NHC) Key Laboratory of Myopia (Fudan University), Chinese Academy of Medical Sciences, Shanghai, ChinaShanghai Key Laboratory of Visual Impairment and Restoration, Fudan University, Shanghai, ChinaDepartment of Stomatology, The Second Xiangya Hospital, Central South University, Changsha, ChinaOral squamous cell carcinoma (OSCC) is the most invasive oral malignancy in adults and is associated with a poor prognosis. Accurate prognostic models are urgently needed, however, knowledge of the probable mechanisms behind OSCC tumorigenesis and prognosis remain limited. The clinical importance of the interplay between the immune system and tumor microenvironment has become increasingly evident. This study explored immune-related alterations at the multi-omics level to extract accurate prognostic markers linked to the immune response and presents a more accurate landscape of the immune genomic map during OSCC. The Cancer Genome Atlas (TCGA) OSCC cohort (n = 329) was used to detect the immune infiltration pattern of OSCC and categorize patients into two immunity groups using single-sample gene set enrichment analysis (ssGSEA) and hierarchical clustering analysis. Multiple strategies, including lasso regression (LASSO), Cox proportional hazards regression, and principal component analysis (PCA) were used to screen clinically significant signatures and identify an incorporated prognosis model with robust discriminative power on the survival status of both the training and testing set. We identified two OSCC subtypes based on immunological characteristics: Immunity-high and immunity low, and verified that the categorization was accurate and repeatable. Immunity_ high cluster with a higher immunological and stromal score. 1047 differential genes (DEGs) integrate with immune genes to obtain 319 immue-related DEGs. A robust model with five signatures for OSCC patient prognosis was established. The GEO cohort (n = 97) were used to validate the risk model’s predictive value. The low-risk group had a better overall survival (OS) than the high-risk group. Significant prognostic potential for OSCC patients was found using ROC analysis and immune checkpoint gene expression was lower in the low-risk group. We also investigated at the therapeutic sensitivity of a number of frequently used chemotherapeutic drugs in patients with various risk factors. The underlying biological behavior of the OSCC cell line was preliminarily validated. This study characterizes a reliable marker of OSCC disease progression and provides a new potential target for immunotherapy against this disease.https://www.frontiersin.org/articles/10.3389/fimmu.2022.922195/fulloral squamous cell carcinomaimmune-related geneimmune infiltrationprognostic biomarkersingle-sample gene set enrichment analysis |
| spellingShingle | Yun Chen Yunzhi Feng Fei Yan Yaqiong Zhao Han Zhao Han Zhao Han Zhao Yue Guo A Novel Immune-Related Gene Signature to Identify the Tumor Microenvironment and Prognose Disease Among Patients With Oral Squamous Cell Carcinoma Patients Using ssGSEA: A Bioinformatics and Biological Validation Study Frontiers in Immunology oral squamous cell carcinoma immune-related gene immune infiltration prognostic biomarker single-sample gene set enrichment analysis |
| title | A Novel Immune-Related Gene Signature to Identify the Tumor Microenvironment and Prognose Disease Among Patients With Oral Squamous Cell Carcinoma Patients Using ssGSEA: A Bioinformatics and Biological Validation Study |
| title_full | A Novel Immune-Related Gene Signature to Identify the Tumor Microenvironment and Prognose Disease Among Patients With Oral Squamous Cell Carcinoma Patients Using ssGSEA: A Bioinformatics and Biological Validation Study |
| title_fullStr | A Novel Immune-Related Gene Signature to Identify the Tumor Microenvironment and Prognose Disease Among Patients With Oral Squamous Cell Carcinoma Patients Using ssGSEA: A Bioinformatics and Biological Validation Study |
| title_full_unstemmed | A Novel Immune-Related Gene Signature to Identify the Tumor Microenvironment and Prognose Disease Among Patients With Oral Squamous Cell Carcinoma Patients Using ssGSEA: A Bioinformatics and Biological Validation Study |
| title_short | A Novel Immune-Related Gene Signature to Identify the Tumor Microenvironment and Prognose Disease Among Patients With Oral Squamous Cell Carcinoma Patients Using ssGSEA: A Bioinformatics and Biological Validation Study |
| title_sort | novel immune related gene signature to identify the tumor microenvironment and prognose disease among patients with oral squamous cell carcinoma patients using ssgsea a bioinformatics and biological validation study |
| topic | oral squamous cell carcinoma immune-related gene immune infiltration prognostic biomarker single-sample gene set enrichment analysis |
| url | https://www.frontiersin.org/articles/10.3389/fimmu.2022.922195/full |
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