Research Paper Volume 16, Issue 4 pp 3647—3673

Comprehensive analysis of disulfidptosis-related genes: a prognosis model construction and tumor microenvironment characterization in clear cell renal cell carcinoma

Bocun Yi1, *, , Xifeng Wei2, *, , Dongze Liu1, *, , Liwei Jing1, , Shengxian Xu1, , Man Zhang3, , Zhengxin Liang1, , Ranlu Liu1, , Zhihong Zhang1, ,

  • 1 Department of Urology, Tianjin Institute of Urology, The Second Hospital of Tianjin Medical University, Tianjin, China
  • 2 Department of Urology, People’s Hospital of Ningxia Hui Autonomous Region, Yinchuan, China
  • 3 Tianjin Key Laboratory of Metabolic Diseases, Tianjin Institute of Endocrinology, Chu Hsien-I Memorial Hospital of Tianjin Medical University, Tianjin, China
* Equal contribution and shared first authorship

Received: July 25, 2023       Accepted: December 1, 2023       Published: February 14, 2024      

https://doi.org/10.18632/aging.205550
How to Cite

Copyright: © 2024 Yi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

Background: Disulfidptosis, a form of cell death induced by abnormal intracellular accumulation of disulfides, is a newly recognized variety of cell death. Clear cell renal cell carcinoma (ccRCC) is a usual urological tumor that poses serious health risks. There are few studies of disulfidptosis-related genes (DRGs) in ccRCC so far.

Methods: The expression, transcriptional variants, and prognostic role of DRGs were assessed. Based on DRGs, consensus unsupervised clustering analysis was performed to stratify ccRCC patients into various subtypes and constructed a DRG risk scoring model. Patients were stratified into high or low-risk groups by this model. We focused on assessing the discrepancy in prognosis, TME, chemotherapeutic susceptibility, and landscape of immune between the two risk groups. Finally, we validated the expression and explored the biological function of the risk scoring gene FLRT3 through in vitro experiments.

Results: The different subtypes had significantly different gene expression, immune, and prognostic landscapes. In the two risk groups, the high-risk group had higher TME scores, more significant immune cell infiltration, and a higher probability of benefiting from immunotherapy, but had a worse prognosis. There were also remarkable differences in chemotherapeutic susceptibility between the two risk groups. In ccRCC cells, the expression of FLRT3 was shown to be lower and its overexpression caused a decrease in cell proliferation and metastatic capacity.

Conclusions: Starting from disulfidptosis, we established a new risk scoring model which can provide new ideas for doctors to forecast patient survival and determine clinical treatment plans.

Abbreviations

AUC: area under the curve; CCK-8: cell counting kit-8; ccRCC: clear cell renal cell carcinoma; CNV: copy number variation; DEGs: differentially expressed genes; DRGs: disulfidptosis-related genes; EdU: ethynyl-2-deoxyuridine; GEO: gene expression omnibus; GO: gene ontology; HPA: human protein atlas; IC50: 50% maximal inhibitory concentration; ICIs: immune checkpoint inhibitors; IPS: immunophenotypic scoring; KIRC: kidney renal clear cell carcinoma; KM: Kaplan-Meier; LASSO: least absolute shrinkage and selection operator; MDSCs: myeloid-derived suppressor cells; NKT: natural killer T; OS: overall survival; RCC: renal cell carcinoma; ROC: receiver operator curve; ssGSEA: single sample gene set enrichment analysis; TCGA: the cancer genome atlas; TCIA: the cancer immunome atlas; TMB: tumor mutation burden.