Integrative Analysis Developing and Validating Potential Candidate Biomarkers for Cancer Stemness Features of...

Area of Science:

• Oncology
• Genomics
• Biomarker Discovery

Background:

• Renal cell carcinoma (RCC) exhibits stemness features that influence its progression and treatment resistance.
• Identifying molecular markers associated with RCC stemness is crucial for improving patient outcomes.

Purpose of the Study:

• To identify key genes associated with renal cell carcinoma (RCC) stemness.
• To develop and validate a molecular prognostic signature for pan-RCC based on stemness features.
• To identify potential hub biomarkers for RCC stemness.

Main Methods:

• Gene expression analysis to identify 49 key genes associated with RCC stemness.
• Development of a prognostic signature using these genes.
• Survival analysis and receiver operating characteristic (ROC) curve analysis for performance evaluation.
• Validation of the signature in The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) cohorts.
• Identification and validation of three hub genes as potential biomarkers.

Main Results:

• A prognostic signature comprising 49 key genes associated with RCC stemness was developed.
• The signature significantly differentiated between high- and low-risk groups in terms of overall survival (OS) (p < .05).
• The signature demonstrated good predictive accuracy with areas under the ROC curve of 0.759 (1-year OS), 0.712 (5-year OS), and 0.918 (10-year OS).
• Validation in independent cohorts confirmed the signature's predictive capability.
• Three hub genes were identified as potential biomarkers for pan-RCC stemness features.

Conclusions:

• A novel molecular prognostic signature associated with stemness features can predict overall survival in pan-renal cell carcinoma (RCC).
• The identified signature and three hub genes hold potential as reliable biomarkers for assessing prognosis and guiding treatment strategies in RCC.