Abstract
It is of great urgency to explore useful prognostic markers and develop a robust prognostic model for patients with clear-cell renal cell carcinoma (ccRCC). Three independent patient cohorts were included in this study. We applied a high-level neural network based on TensorFlow to construct the robust model by using the deep learning algorithm. The deep learning-based model (FB-risk) could perform well in predicting the survival status in the 5-year follow-up, which could also significantly distinguish the patients with high overall survival risk in three independent patient cohorts of ccRCC and a pan-cancer cohort. High FB-risk was found to be partially associated with negative regulation of the immune system. In addition, the novel phenotyping of ccRCC based on the F-box gene family could robustly stratify patients with different survival risks. The different mutation landscapes and immune characteristics were also found among different clusters. Furthermore, the novel phenotyping of ccRCC based on the F-box gene family could perform well in the robust stratification of survival and immune response in ccRCC, which might have potential for application in clinical practices.
Highlights
Renal cancer ranks sixth in terms of incidence rate among all male malignancies, accounting for almost 5% of all male cancer patients [1]
receiver operating characteristic (ROC) curves in the E-MTAB-1980 cohort and the Clinical Proteomic Tumor Analysis Consortium (CPTAC) cohort revealed that our deep learning-based model (FB-risk) performed better than some machine learning-based models in external validation cohorts, including Least Absolute Shrinkage and Selection Operator (LASSO), k-nearest neighbor (KNN), XGBoost, and random forest in predicting the survival status in a 5-year follow-up
Under the comprehensive utilization of both TNM staging and the International Society of Urological Pathology (ISUP) grading system, we found that some clear-cell renal cell carcinoma (ccRCC) patients still show unexpectedly poor prognosis, such as ccRCC patients with sarcomatous lesion and rhabdoid differentiation
Summary
Renal cancer ranks sixth in terms of incidence rate among all male malignancies, accounting for almost 5% of all male cancer patients [1]. In China, there were about 74,000 new tumor cases estimated in renal in 2015 [2]. Renal cancer could be classified into different pathological subtypes according to various histological features, among which clear-cell renal cell carcinoma (ccRCC) accounts for about 80% of malignant cases in renal cancer [3]. Prognosis of ccRCC mainly depends on tumor characteristics, and some patients with ccRCC might suffer from quite poor prognosis with the overall survival rate less than 25% in 5 years [4]. It becomes necessary to find out practical prognostic markers for patients with ccRCC
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