Abstract
Background: In previous studies, the prognostic model of clear cell renal cell carcinoma (ccRCC) was constructed through all racial subjects, however, the intrinsic genomic differences between races may lead to disparity in survival outcomes, hence the accurate prognostic model of white patients in ccRCC was needed to be explored. This research aimed to identify and validate the potential long non-coding RNAs (lncRNAs) and clinical factors model to predict overall survival of ccRCC in white patients. Methods:LncRNA expression data and clinical factors of 459 white racial ccRCC subjects were downloaded from The Cancer Genome Atlas database. According to the exclusion criteria, 76 patients were excluded from the analytical dataset, hence 383 ccRCC participants were covered in present study. Then, 383 subjects were randomized into training series (n = 255) and test series (n = 128). The model was constructed using the training series, and validated in the test series. In the training series, the prognostic lncRNA model was constructed through univariate and multivariate Cox regression analysis, and least absolute shrinkage and selection operator regression analysis. Subsequently, the clinical variables were combined with lncRNA model to better predict the prognosis. The prognostic power of the models was verified by concordance index (95%CI) and area under time-dependent receiver operator characteristic curve (95%CI). Finally, the constructed models were validated in the test and entire series.Results:In the training series, 12 lncRNAs were confirmed as prognostic related biomarkers of ccRCC patients, among which AC012404.1, AC092296.1, AC099684.2, AC108752.1, AC131097.1, AL606519.1, and LINC02475 were seven novel candidate prognostic biomarkers. The performance evaluation of combined model incorporating 12-lncRNAs, age, and the tumor node metastasis stage showed that concordance index (95%CI) in the training, test and entire series were 0.863(0.830-0.896), 0.863(0.814-0.912) and 0.841(0.812-0.870), respectively, the 5-year area under time-dependent receiver operator characteristic curve (95%CI) in the training, test and entire series were 0.923(0.879-0.967), 0.861(0.777-0.945) and 0.879(0.834-0.924), respectively. Conclusion:This novel signature incorporating 12-lncRNAs, age, and the tumor node metastasis stage can be applied as an accurate tool for ccRCC prognostic evaluation in white patients.