Cell Differentiation Trajectory Predicts Prognosis and Immunotherapeutic Response in Clear Cell Renal Cell Carcinoma
Clear cell renal cell carcinoma (ccRCC) is the main type of malignancy in kidney related to glucose metabolism. Primary single cell culture and single cell sequencing are novel research technologies. In this study, we explored the differentiation status of ccRCC cells and its significance in prognos...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2022-01-01
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| Series: | Genetics Research |
| Online Access: | http://dx.doi.org/10.1155/2022/8422339 |
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| _version_ | 1832551079392313344 |
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| author | Jin Xu Xi Chen Yinyu Chen Qiushuang Wang Yingliang Jin Huashuo Zhao |
| author_facet | Jin Xu Xi Chen Yinyu Chen Qiushuang Wang Yingliang Jin Huashuo Zhao |
| author_sort | Jin Xu |
| collection | DOAJ |
| description | Clear cell renal cell carcinoma (ccRCC) is the main type of malignancy in kidney related to glucose metabolism. Primary single cell culture and single cell sequencing are novel research technologies. In this study, we explored the differentiation status of ccRCC cells and its significance in prognosis and immunotherapeutic response through bioinformatics. We characterized distinct differentiation states and differentiation-related genes (DRGs) in ccRCC cells through single cell RNA sequencing (scRNA-seq) analysis. Combined with bulk RNA-seq data, we classified patients into two clusters and found that this classification was closely correlated with patient prognosis and immunotherapeutic responses. Based on machine learning, we identified a prognostic risk model composed of 14 DRGs, including BTG2, CDKN1A, COL6A1, CPM, CYB5D2, FOSB, ID2, ISG15, PLCG2, SECISBP2, SOCS3, TES, ZBTB16, and ZNF704, to predict the survival rate of patients and then constructed a nomogram model integrating clinicopathological characteristics and risk score for clinical practice. In the study of immune checkpoints, we found that patients in the high-risk group had a disposition to get worse prognosis and better effects of immune checkpoint blocking therapies. Finally, we found the expression level of model DRGs was associated with a tumor-immune microenvironment (TIME) pattern and the response of 83 compounds or inhibitors was significantly different in the two risk groups. In a word, our study highlights the potential contribution of cell differentiation in prognosis judgment and immunotherapy response and offers promising therapeutic options for ccRCC patients. |
| format | Article |
| id | doaj-art-ca0a4aea50cf401994d75bd658ee1c20 |
| institution | Kabale University |
| issn | 1469-5073 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Genetics Research |
| spelling | doaj-art-ca0a4aea50cf401994d75bd658ee1c202025-02-03T06:05:01ZengWileyGenetics Research1469-50732022-01-01202210.1155/2022/8422339Cell Differentiation Trajectory Predicts Prognosis and Immunotherapeutic Response in Clear Cell Renal Cell CarcinomaJin Xu0Xi Chen1Yinyu Chen2Qiushuang Wang3Yingliang Jin4Huashuo Zhao5Department of BiostatisticsDepartment of BiostatisticsSchool of StomatologyDepartment of BiostatisticsDepartment of BiostatisticsDepartment of BiostatisticsClear cell renal cell carcinoma (ccRCC) is the main type of malignancy in kidney related to glucose metabolism. Primary single cell culture and single cell sequencing are novel research technologies. In this study, we explored the differentiation status of ccRCC cells and its significance in prognosis and immunotherapeutic response through bioinformatics. We characterized distinct differentiation states and differentiation-related genes (DRGs) in ccRCC cells through single cell RNA sequencing (scRNA-seq) analysis. Combined with bulk RNA-seq data, we classified patients into two clusters and found that this classification was closely correlated with patient prognosis and immunotherapeutic responses. Based on machine learning, we identified a prognostic risk model composed of 14 DRGs, including BTG2, CDKN1A, COL6A1, CPM, CYB5D2, FOSB, ID2, ISG15, PLCG2, SECISBP2, SOCS3, TES, ZBTB16, and ZNF704, to predict the survival rate of patients and then constructed a nomogram model integrating clinicopathological characteristics and risk score for clinical practice. In the study of immune checkpoints, we found that patients in the high-risk group had a disposition to get worse prognosis and better effects of immune checkpoint blocking therapies. Finally, we found the expression level of model DRGs was associated with a tumor-immune microenvironment (TIME) pattern and the response of 83 compounds or inhibitors was significantly different in the two risk groups. In a word, our study highlights the potential contribution of cell differentiation in prognosis judgment and immunotherapy response and offers promising therapeutic options for ccRCC patients.http://dx.doi.org/10.1155/2022/8422339 |
| spellingShingle | Jin Xu Xi Chen Yinyu Chen Qiushuang Wang Yingliang Jin Huashuo Zhao Cell Differentiation Trajectory Predicts Prognosis and Immunotherapeutic Response in Clear Cell Renal Cell Carcinoma Genetics Research |
| title | Cell Differentiation Trajectory Predicts Prognosis and Immunotherapeutic Response in Clear Cell Renal Cell Carcinoma |
| title_full | Cell Differentiation Trajectory Predicts Prognosis and Immunotherapeutic Response in Clear Cell Renal Cell Carcinoma |
| title_fullStr | Cell Differentiation Trajectory Predicts Prognosis and Immunotherapeutic Response in Clear Cell Renal Cell Carcinoma |
| title_full_unstemmed | Cell Differentiation Trajectory Predicts Prognosis and Immunotherapeutic Response in Clear Cell Renal Cell Carcinoma |
| title_short | Cell Differentiation Trajectory Predicts Prognosis and Immunotherapeutic Response in Clear Cell Renal Cell Carcinoma |
| title_sort | cell differentiation trajectory predicts prognosis and immunotherapeutic response in clear cell renal cell carcinoma |
| url | http://dx.doi.org/10.1155/2022/8422339 |
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