Analyzing and validating the prognostic value and immune microenvironment of clear cell renal cell carcinoma
Tumor immune microenvironment (TIME) plays an important role in tumor diagnosis, prevention, treatment and prognosis. However, the correlation and potential mechanism between clear cell renal cell carcinoma (ccRCC) and its TIME are not clear. Therefore, we aimed to identify potential prognostic biom...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2022-03-01
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| Series: | Animal Cells and Systems |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/19768354.2022.2056635 |
| _version_ | 1818022997802352640 |
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| author | Jingwei Ke Jie Chen Xin Liu |
| author_facet | Jingwei Ke Jie Chen Xin Liu |
| author_sort | Jingwei Ke |
| collection | DOAJ |
| description | Tumor immune microenvironment (TIME) plays an important role in tumor diagnosis, prevention, treatment and prognosis. However, the correlation and potential mechanism between clear cell renal cell carcinoma (ccRCC) and its TIME are not clear. Therefore, we aimed to identify potential prognostic biomarkers related to TIME of ccRCC. Unsupervised consensus clustering analysis was performed to divide patients into different immune subgroups according to their single-sample gene set enrichment analysis (ssGSEA) scores. Then, we validated the differences in immune cell infiltration, prognosis, clinical characteristics and expression levels of HLA and immune checkpoint genes between different immune subgroups. Weighted gene coexpression network analysis (WGCNA) was used to identify the significant modules and hub genes that were related to the immune subgroups. A nomogram was established to predict the overall survival (OS) outcomes after independent prognostic factors were identified by least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox regression analyses. Five clusters (immune subgroups) were identified. There was no significant difference in age, sex or N stage. And there were significant differences in race, T stage, M stage, grade, prognosis and tumor microenvironment. WGCNA revealed that the red module has an important relationship with TIME, and obtained 14 hub genes. In addition, the nomogram containing LAG3 and GZMK accurately predicted OS outcomes of ccRCC patients. LAG3 and GZMK have a certain correlation with the prognosis of ccRCC patients, and play an important role in the TIME. These two hub genes deserve further study as biomarkers of the TIME. |
| first_indexed | 2024-12-10T03:37:19Z |
| format | Article |
| id | doaj.art-3ff0cddcfcbd440e811063dbd82aec17 |
| institution | Directory Open Access Journal |
| issn | 1976-8354 2151-2485 |
| language | English |
| last_indexed | 2024-12-10T03:37:19Z |
| publishDate | 2022-03-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Animal Cells and Systems |
| spelling | doaj.art-3ff0cddcfcbd440e811063dbd82aec172022-12-22T02:03:40ZengTaylor & Francis GroupAnimal Cells and Systems1976-83542151-24852022-03-01262526110.1080/19768354.2022.2056635Analyzing and validating the prognostic value and immune microenvironment of clear cell renal cell carcinomaJingwei Ke0Jie Chen1Xin Liu2Department of urology, The Affiliated Traditional Chinese Medicine Hospital of Southwest Medical University, Luzhou, People’s Republic of ChinaGraduate School of Southwest Medical University, Luzhou, People’s Republic of ChinaDepartment of urology, The Affiliated Traditional Chinese Medicine Hospital of Southwest Medical University, Luzhou, People’s Republic of ChinaTumor immune microenvironment (TIME) plays an important role in tumor diagnosis, prevention, treatment and prognosis. However, the correlation and potential mechanism between clear cell renal cell carcinoma (ccRCC) and its TIME are not clear. Therefore, we aimed to identify potential prognostic biomarkers related to TIME of ccRCC. Unsupervised consensus clustering analysis was performed to divide patients into different immune subgroups according to their single-sample gene set enrichment analysis (ssGSEA) scores. Then, we validated the differences in immune cell infiltration, prognosis, clinical characteristics and expression levels of HLA and immune checkpoint genes between different immune subgroups. Weighted gene coexpression network analysis (WGCNA) was used to identify the significant modules and hub genes that were related to the immune subgroups. A nomogram was established to predict the overall survival (OS) outcomes after independent prognostic factors were identified by least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox regression analyses. Five clusters (immune subgroups) were identified. There was no significant difference in age, sex or N stage. And there were significant differences in race, T stage, M stage, grade, prognosis and tumor microenvironment. WGCNA revealed that the red module has an important relationship with TIME, and obtained 14 hub genes. In addition, the nomogram containing LAG3 and GZMK accurately predicted OS outcomes of ccRCC patients. LAG3 and GZMK have a certain correlation with the prognosis of ccRCC patients, and play an important role in the TIME. These two hub genes deserve further study as biomarkers of the TIME.https://www.tandfonline.com/doi/10.1080/19768354.2022.2056635Clear cell renal cell carcinomamicroenvironmentprognosisnomogrambioinformatics |
| spellingShingle | Jingwei Ke Jie Chen Xin Liu Analyzing and validating the prognostic value and immune microenvironment of clear cell renal cell carcinoma Animal Cells and Systems Clear cell renal cell carcinoma microenvironment prognosis nomogram bioinformatics |
| title | Analyzing and validating the prognostic value and immune microenvironment of clear cell renal cell carcinoma |
| title_full | Analyzing and validating the prognostic value and immune microenvironment of clear cell renal cell carcinoma |
| title_fullStr | Analyzing and validating the prognostic value and immune microenvironment of clear cell renal cell carcinoma |
| title_full_unstemmed | Analyzing and validating the prognostic value and immune microenvironment of clear cell renal cell carcinoma |
| title_short | Analyzing and validating the prognostic value and immune microenvironment of clear cell renal cell carcinoma |
| title_sort | analyzing and validating the prognostic value and immune microenvironment of clear cell renal cell carcinoma |
| topic | Clear cell renal cell carcinoma microenvironment prognosis nomogram bioinformatics |
| url | https://www.tandfonline.com/doi/10.1080/19768354.2022.2056635 |
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