Cellular senescence and metabolic reprogramming model based on bulk/single-cell RNA sequencing reveals PTGER4 as a therapeutic target for ccRCC
Abstract Clear cell renal cell carcinoma (ccRCC) is the prevailing histological subtype of renal cell carcinoma and has unique metabolic reprogramming during its occurrence and development. Cell senescence is one of the newly identified tumor characteristics. However, there is a dearth of methodical...
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| Format: | Article |
| Language: | English |
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BMC
2024-04-01
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| Series: | BMC Cancer |
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| Online Access: | https://doi.org/10.1186/s12885-024-12234-5 |
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| author | Lijie Zhou Youmiao Zeng Yuanhao Liu Kaixuan Du Yongbo Luo Yiheng Dai Wenbang Pan Lailai Zhang Lei Zhang Fengyan Tian Chaohui Gu |
| author_facet | Lijie Zhou Youmiao Zeng Yuanhao Liu Kaixuan Du Yongbo Luo Yiheng Dai Wenbang Pan Lailai Zhang Lei Zhang Fengyan Tian Chaohui Gu |
| author_sort | Lijie Zhou |
| collection | DOAJ |
| description | Abstract Clear cell renal cell carcinoma (ccRCC) is the prevailing histological subtype of renal cell carcinoma and has unique metabolic reprogramming during its occurrence and development. Cell senescence is one of the newly identified tumor characteristics. However, there is a dearth of methodical and all-encompassing investigations regarding the correlation between the broad-ranging alterations in metabolic processes associated with aging and ccRCC. We utilized a range of analytical methodologies, such as protein‒protein interaction network analysis and least absolute shrinkage and selection operator (LASSO) regression analysis, to form and validate a risk score model known as the senescence-metabolism-related risk model (SeMRM). Our study demonstrated that SeMRM could more precisely predict the OS of ccRCC patients than the clinical prognostic markers in use. By utilizing two distinct datasets of ccRCC, ICGC-KIRC (the International Cancer Genome Consortium) and GSE29609, as well as a single-cell dataset (GSE156632) and real patient clinical information, and further confirmed the relationship between the senescence-metabolism-related risk score (SeMRS) and ccRCC patient progression. It is worth noting that patients who were classified into different subgroups based on the SeMRS exhibited notable variations in metabolic activity, immune microenvironment, immune cell type transformation, mutant landscape, and drug responsiveness. We also demonstrated that PTGER4, a key gene in SeMRM, regulated ccRCC cell proliferation, lipid levels and the cell cycle in vivo and in vitro. Together, the utilization of SeMRM has the potential to function as a dependable clinical characteristic to increase the accuracy of prognostic assessment for patients diagnosed with ccRCC, thereby facilitating the selection of suitable treatment strategies. |
| first_indexed | 2024-04-24T09:51:59Z |
| format | Article |
| id | doaj.art-32e6c73dec5c49faa7cd5306be8a5610 |
| institution | Directory Open Access Journal |
| issn | 1471-2407 |
| language | English |
| last_indexed | 2024-04-24T09:51:59Z |
| publishDate | 2024-04-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Cancer |
| spelling | doaj.art-32e6c73dec5c49faa7cd5306be8a56102024-04-14T11:19:03ZengBMCBMC Cancer1471-24072024-04-0124112310.1186/s12885-024-12234-5Cellular senescence and metabolic reprogramming model based on bulk/single-cell RNA sequencing reveals PTGER4 as a therapeutic target for ccRCCLijie Zhou0Youmiao Zeng1Yuanhao Liu2Kaixuan Du3Yongbo Luo4Yiheng Dai5Wenbang Pan6Lailai Zhang7Lei Zhang8Fengyan Tian9Chaohui Gu10Department of Urology, First Affiliated Hospital of Zhengzhou UniversityDepartment of Urology, First Affiliated Hospital of Zhengzhou UniversityDepartment of Urology, First Affiliated Hospital of Zhengzhou UniversityDepartment of Urology, First Affiliated Hospital of Zhengzhou UniversityDepartment of Urology, First Affiliated Hospital of Zhengzhou UniversityDepartment of Urology, First Affiliated Hospital of Zhengzhou UniversityDepartment of Urology, First Affiliated Hospital of Zhengzhou UniversityDepartment of Urology, First Affiliated Hospital of Zhengzhou UniversityDepartment of Thoracic Surgery, The First Affiliated Hospital of Zhengzhou UniversityDepartment of Pediatrics, The First Affiliated Hospital of Zhengzhou UniversityDepartment of Urology, First Affiliated Hospital of Zhengzhou UniversityAbstract Clear cell renal cell carcinoma (ccRCC) is the prevailing histological subtype of renal cell carcinoma and has unique metabolic reprogramming during its occurrence and development. Cell senescence is one of the newly identified tumor characteristics. However, there is a dearth of methodical and all-encompassing investigations regarding the correlation between the broad-ranging alterations in metabolic processes associated with aging and ccRCC. We utilized a range of analytical methodologies, such as protein‒protein interaction network analysis and least absolute shrinkage and selection operator (LASSO) regression analysis, to form and validate a risk score model known as the senescence-metabolism-related risk model (SeMRM). Our study demonstrated that SeMRM could more precisely predict the OS of ccRCC patients than the clinical prognostic markers in use. By utilizing two distinct datasets of ccRCC, ICGC-KIRC (the International Cancer Genome Consortium) and GSE29609, as well as a single-cell dataset (GSE156632) and real patient clinical information, and further confirmed the relationship between the senescence-metabolism-related risk score (SeMRS) and ccRCC patient progression. It is worth noting that patients who were classified into different subgroups based on the SeMRS exhibited notable variations in metabolic activity, immune microenvironment, immune cell type transformation, mutant landscape, and drug responsiveness. We also demonstrated that PTGER4, a key gene in SeMRM, regulated ccRCC cell proliferation, lipid levels and the cell cycle in vivo and in vitro. Together, the utilization of SeMRM has the potential to function as a dependable clinical characteristic to increase the accuracy of prognostic assessment for patients diagnosed with ccRCC, thereby facilitating the selection of suitable treatment strategies.https://doi.org/10.1186/s12885-024-12234-5Renal cell carcinomaCellular senescenceMetabolismPTGER4 |
| spellingShingle | Lijie Zhou Youmiao Zeng Yuanhao Liu Kaixuan Du Yongbo Luo Yiheng Dai Wenbang Pan Lailai Zhang Lei Zhang Fengyan Tian Chaohui Gu Cellular senescence and metabolic reprogramming model based on bulk/single-cell RNA sequencing reveals PTGER4 as a therapeutic target for ccRCC BMC Cancer Renal cell carcinoma Cellular senescence Metabolism PTGER4 |
| title | Cellular senescence and metabolic reprogramming model based on bulk/single-cell RNA sequencing reveals PTGER4 as a therapeutic target for ccRCC |
| title_full | Cellular senescence and metabolic reprogramming model based on bulk/single-cell RNA sequencing reveals PTGER4 as a therapeutic target for ccRCC |
| title_fullStr | Cellular senescence and metabolic reprogramming model based on bulk/single-cell RNA sequencing reveals PTGER4 as a therapeutic target for ccRCC |
| title_full_unstemmed | Cellular senescence and metabolic reprogramming model based on bulk/single-cell RNA sequencing reveals PTGER4 as a therapeutic target for ccRCC |
| title_short | Cellular senescence and metabolic reprogramming model based on bulk/single-cell RNA sequencing reveals PTGER4 as a therapeutic target for ccRCC |
| title_sort | cellular senescence and metabolic reprogramming model based on bulk single cell rna sequencing reveals ptger4 as a therapeutic target for ccrcc |
| topic | Renal cell carcinoma Cellular senescence Metabolism PTGER4 |
| url | https://doi.org/10.1186/s12885-024-12234-5 |
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