Objective: To screen several immune-related long non-coding RNAs (lncRNAs) and construct a prognostic model for papillary renal cell carcinoma (pRCC).
Methods: Transcriptome-sequencing data of pRCC was downloaded and a prognostic model was constructed. Time-dependent receiver operating characteristic (ROC) curve was plotted and the area under curve (AUC) was calculated. We conducted quantitative reverse transcription polymerase chain reaction (RT-PCR) to verify the model. The gene set enrichment analysis (GSEA) was used to show the connection of our model with immune pathways.
Result: We identified four lncRNAs to constructed the model. The model was significantly associated with the survival time and survival state. The expression-levels of the four lncRNAs were measured and the prognosis of high-risk patients was significantly worse. The two immune-gene sets had an active performance in the high-risk patients.
Conclusion: We constructed a prognostic model in pRCC which provided more reference for treatment.
Keywords: Bioinformatics; Immune; Long non-coding RNA; Papillary renal cell carcinoma; Prognosis.
Copyright © 2020. Published by Elsevier Inc.