Cancer Cell International · 2019 · 52 citations · 31 references
MedicineBioinformaticsOncologyCancer GeneticsMolecular OncologyTranscriptomicsCancer BiomarkersCancer GenomicsCancer TranscriptomicsNoncoding Rna In CancerNoncoding Rna TranscriptomicsRenal Cell CarcinomaNoncoding Rna Expression ProfilingPrognostic Expression SignaturesPrognostic Gene SignaturesPrognostic PredictionPrognostic Prediction ModelsPrognostic Rna BiomarkersRenal Cell Carcinoma BiomarkersSurvival Probability
Abnormal expressions of long noncoding RNAs (lncRNAs) are very common in clear cell renal cell carcinoma (ccRCC), and some of these have been reported to be highly correlated with prognosis of ccRCC patients. “edgeR” AND “DEseq” R packages were used to explore differentially expressed genes (DEGs) between normal and tumor tissues of ccRCC samples from The Cancer Genome Atlas (TCGA). Univariable Cox survival analysis, robust likelihood-based survival model and multivariable Cox regression analysis were used to identify prognostic lncRNAs and construct lncRNAs signature. Finally, a graphic nomogram based on the lncRNAs signature was developed to predict 1-, 3- and 5-year survival probability of ccRCC patients by using rms R package. 8413 DEGs including 2740 lncRNAs and 4530 mRNAs were identified between normal and tumor tissues. 395 lncRNAs were found to be associated with prognosis of ccRCC patients (P < 0.05). Among these 395 prognostic lncRNAs, 9 key prognostic lncRNAs (RP13-463N16.6, CTD-2201E18.5, RP11-430G17.3, AC005785.2, RP11-2E11.9, TFAP2A-AS1, RP11-133F8.2, RP11-297L17.2 and RP11-348J24.2) were identified by using robust likelihood-based survival model. A 9-lncRNAs signature was constructed by using estimated regression coefficients of the 9 key prognostic lncRNAs. Results of χ 2 -test or Fisher’s exact test indicated that the 9-lncRNAs signature was significantly associated with clinicopathological characteristics such as tumor grade, T stage, N stage, M stage, TNM stage and survival outcome of ccRCC patients. Multivariate analysis showed that the 9-lncRNAs signature, age and M stage were independent prognostic factors. Finally, a graphic nomogram based on the lncRNAs signature, age and M stage was developed to predict 1-, 3- and 5-year survival probability of ccRCC patients by using rms R package. A 9-lncRNAs signature associated with prognosis of ccRCC patients was constructed and a promising prognostic nomogram based on the 9-lncRNAs signature was developed for 1-, 3- and 5-year OS prediction of ccRCC patients in this study.
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