Related Experiment Video
Updated: Dec 1, 2025
The Use of Reverse Phase Protein Arrays RPPA to Explore Protein Expression Variation within Individual Renal Cell Cancers
Published on: January 22, 2013
Integrated analysis of the functions of RNA binding proteins in clear cell renal cell carcinoma
Xiaoliang Hua1, Juan Chen2, Shengdong Ge1
1Department of Urology, The First Affiliated Hospital of Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Genitourinary Diseases, Anhui Medical University, Hefei, China; The Institute of Urology, Anhui Medical University, Hefei, China.
Abstract:
RNA binding proteins (RBPs) dysregulation is involved in the processes of various tumors. However, the roles of RBPs in clear cell renal cell carcinoma (ccRCC) remain poorly understand. In present study, we first performed consensus clustering and identified two clusters, of which cluster 2 was closely correlated with the malignancy of ccRCC. Differentially expressed RBPs between normal and tumor tissues were obtained, comprising 71 up-regulated and 44 down-regulated ones. Then, ten hub genes were selected and validated using The Human Protein Atlas database and receiver operating characteristic curves, showing good diagnostic value for cancers. Besides, we identified ten RBPs with the most useful prognostic values, and were used to construct a risk score model. The model could be used to stratify patients with different prognosis and phenotype distributions. The model showed good performance and can be used as a complementation for clinical factors to guide clinical practice in the future.
Insights
RNA binding proteins (RBPs) are crucial in cancer. This study identifies key RBPs and develops a prognostic model for clear cell renal cell carcinoma (ccRCC) patients, aiding clinical decisions.
Area of Science:
- Oncology
- Molecular Biology
- Bioinformatics
Background:
- Dysregulation of RNA binding proteins (RBPs) is implicated in various cancers.
- The specific roles of RBPs in clear cell renal cell carcinoma (ccRCC) are not well understood.
Purpose of the Study:
- To investigate the role of RBPs in ccRCC.
- To identify diagnostic and prognostic biomarkers for ccRCC.
- To develop a risk score model for ccRCC patient stratification.
Main Methods:
- Consensus clustering to identify ccRCC subtypes.
- Differential expression analysis of RBPs between normal and tumor tissues.
- Hub gene identification and validation using The Human Protein Atlas and ROC curves.
- Construction and evaluation of a prognostic risk score model.
Main Results:
- Identified two ccRCC clusters, with cluster 2 associated with higher malignancy.
- Discovered 71 up-regulated and 44 down-regulated RBPs in ccRCC.
- Validated ten hub RBPs with significant diagnostic value for ccRCC.
- Developed a risk score model using ten prognostic RBPs, demonstrating good performance in stratifying patients by prognosis and phenotype.
Conclusions:
- RBPs play a significant role in ccRCC development and progression.
- Identified RBPs serve as potential diagnostic and prognostic biomarkers for ccRCC.
- The developed risk score model can aid in stratifying ccRCC patients and guiding clinical practice.
