Objective:

To identify potential prognostic genes to improve patient survival prediction and provide insights into the pathogenesis and treatment of clear cell renal cell carcinoma (ccRCC).

Approach:

• Data Analysis: Utilized whole transcriptomic data from TCGA-KIRC and GSE96574 to identify differentially expressed mRNAs and long non-coding RNAs, followed by prognostic gene screening and risk model construction.
• Validation: Validated expression levels of key genes using reverse transcription quantitative PCR (RT−qPCR) on clinical samples.

Key Findings:

• Identifiedeightprognosticgenes:IFNG,CXCL13,KLRK1,LAG3,ITGAX,TNFRSF9,CD2,CD8B.Developedariskstratificationmodelbasedonthesegenes.Geneswereenrichedinimmune-relatedpathways,particularlyantigenprocessingandpresentation.Aregulatorynetworkinvolvingtranscriptionfactors,miRNAs,lncRNAPVT1,andcircRNAswasconstructed.Drugpredictionsuggestedpotentialtargeteddrugs,includingamitriptylinehydrochlorideforCD8BandIFNG,andrituximabforCXCL13andIFNG,withstrongbindingaffinitiesnotedforITGAXandKLRK1.RT−qPCRvalidationconfirmedsignificantlyelevatedexpressionofIFNG,LAG3,TNFRSF9,andCD8BinccRCCpatients.

Interpretation:

The identified eight-gene signature indicates its involvement in the tumor immune microenvironment.

Limitations:

• The study relies on publicly available datasets, which may have inherent biases.
• Further validation in larger, independent cohorts is necessary.

Conclusion:

The findings provide insights into ccRCC pathogenesis and highlight potential therapeutic targets.