2. Academic Validation
  3. Cellular senescence and metabolic reprogramming model based on bulk/single-cell RNA sequencing reveals PTGER4 as a therapeutic target for ccRCC

Cellular senescence and metabolic reprogramming model based on bulk/single-cell RNA sequencing reveals PTGER4 as a therapeutic target for ccRCC

  • BMC Cancer. 2024 Apr 11;24(1):451. doi: 10.1186/s12885-024-12234-5.
Lijie Zhou # 1 2,  Youmiao Zeng # 3 4,  Yuanhao Liu # 3 5,  Kaixuan Du 3 5,  Yongbo Luo 3 5,  Yiheng Dai 3 4,  Wenbang Pan 3 5,  Lailai Zhang 3 5,  Lei Zhang 6,  Fengyan Tian 7,  Chaohui Gu 8 9
Affiliations

Affiliations

  • 1 Department of Urology, First Affiliated Hospital of Zhengzhou University, 450052, Zhengzhou, Henan Province, China. zhouxiaozhou29@126.com.
  • 2 Unit of Day Surgery Center, First Affiliated Hospital of Zhengzhou University, 450052, Zhengzhou, Henan Province, China. zhouxiaozhou29@126.com.
  • 3 Department of Urology, First Affiliated Hospital of Zhengzhou University, 450052, Zhengzhou, Henan Province, China.
  • 4 Department of Urology, Zhengzhou Key Laboratory for Molecular Biology of Urological Tumor Research, Henan Institute of Urology, First Affiliated Hospital of Zhengzhou University, 450052, Zhengzhou, Henan Province, China.
  • 5 Unit of Day Surgery Center, First Affiliated Hospital of Zhengzhou University, 450052, Zhengzhou, Henan Province, China.
  • 6 Department of Thoracic Surgery, The First Affiliated Hospital of Zhengzhou University, 450052, Zhengzhou, Henan Province, China. zhanglei_address@163.com.
  • 7 Department of Pediatrics, The First Affiliated Hospital of Zhengzhou University, 450052, Zhengzhou, Henan Province, China. fccguzh@zzu.edu.cn.
  • 8 Department of Urology, First Affiliated Hospital of Zhengzhou University, 450052, Zhengzhou, Henan Province, China. zgwhgch@hotmail.com.
  • 9 Unit of Day Surgery Center, First Affiliated Hospital of Zhengzhou University, 450052, Zhengzhou, Henan Province, China. zgwhgch@hotmail.com.
  • # Contributed equally.
PMID: 38605343 DOI: 10.1186/s12885-024-12234-5
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.

Keywords

Cellular senescence; Metabolism; PTGER4; Renal cell carcinoma.

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