Abstract
Background
Patients with clear cell renal cell carcinoma (ccRCC) with venous tumor thrombus have a poor prognosis, high surgical risk, and lack of targeted therapeutic agents.
Methods
Genes with consistent differential expression trends in tumor tissues and VTT groups were first screened, and then differential genes associated with disulfidptosis were found by correlation analysis. Subsequently, identifying ccRCC subtypes and constructing risk models to compare the differences in prognosis and the tumor microenvironment in different subgroups. Finally, constructing a nomogram to predict the prognosis of ccRCC and validate key gene expression levels in cells and tissues.
Results
We screened 35 differential genes related to disulfidptosis and identified 4 ccRCC subtypes. Risk models were constructed based on the 13 genes, and the high-risk group had a higher abundance of immune cell infiltration, tumor mutational load, and microsatellite instability scores, predicting high sensitivity to immunotherapy. The 1-year AUC = 0.869 for predicting OS by nomogram has a high application value. The expression level of the key gene AJAP1 was low in both tumor cell lines and cancer tissues.
Conclusions
Our study not only constructed an accurate prognostic nomogram for ccRCC patients but also identified an AJAP1 biomarker as a potential biomarker for the disease.
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Availability of data and materials
Our data are sourced from the TCGA database(https://portal.gdc.cancer.gov/), and the ArrayExpress database (https://www.ebi.ac.uk/biostudies/arrayexpress) If necessary, we can provide raw data.
Abbreviations
- ccRCC:
-
Clear cell renal cell carcinoma
- VTT:
-
Venous tumor thrombus
- TME:
-
Tumor microenvironment
- TCGA:
-
The cancer genome atlas
- FC:
-
Fold change
- DEGs:
-
Differentially expressed genes
- DEAD:
-
DEGs associated with disulfidptosis
- CDF:
-
Cumulative distribution function
- OS:
-
Overall survival
- HLA:
-
Human leukocyte antigen
- TMB:
-
Tumor mutational load
- K-M:
-
Kaplan–Meier
- LASSO:
-
Least absolute shrinkage and selector operation analysis
- PCA:
-
Principal component analysis
- GSEA:
-
Gene set enrichment analysis
- IPS:
-
Immunophenotype score
- TCIA:
-
The cancer immunome atlas
- ROC:
-
Receiver operating characteristics
- AUC:
-
Area under curve
- TF:
-
Transcription factors
- PFI:
-
Progression-free interval
- DSS:
-
Disease-specific survival
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Acknowledgements
The authors are grateful to the TCGA and ArrayExpress databases for providing high-quality data.
Funding
This study was supported by the Jiangxi Provincial "Double Thousand Plan" Fund Project (Grant No. jxsq2019201027), Key Project of Natural Science Foundation of Jiangxi Province (20212ACB206013), Youth Project of Natural Science Foundation of Jiangxi Province (20212BAB216037), Jiangxi Provincial Health Technology Project (202210339), and the National Natural Science Foundation of China (82172921).
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LY, JX, and JHL: data curation, formal analysis, writing—original draft, writing—review & editing. SL, XQL, and FCZ: data curation, formal analysis. BF and SHX: conceptualized research, writing—review & editing. They all agreed to publish.
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Lin Yang, Jiahao Liu, Sheng Li, and Xiaoqiang Liu are the co-first authors of this article.
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Yang, L., Liu, J., Li, S. et al. Based on disulfidptosis, revealing the prognostic and immunological characteristics of renal cell carcinoma with tumor thrombus of vena cava and identifying potential therapeutic target AJAP1. J Cancer Res Clin Oncol 149, 9787–9804 (2023). https://doi.org/10.1007/s00432-023-04877-x
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DOI: https://doi.org/10.1007/s00432-023-04877-x