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pmid:33217824
Identification of grade-related genes and construction of a robust genomic-clinicopathologic nomogram for predicting recurrence of bladder cancer.
Xiqi Peng · Jingyao Wang · Dongna Li · Xuan Chen · Kaihao Liu · Chunduo Zhang · Yongqing Lai
Medicine · 2020 doi:10.1097/MD.0000000000023179
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Complete file
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The individualized treatment and follow-up after surgery is the key to a successful outcome. Currently, the surveillance strategies are mainly depending on tumor stage and grade. Previous evidence has proved that tumor grade was a significant and independent risk factor of BC recurrence. Exploring the grade-related genes may provide us a new approach to predict prognosis and guide the post-operative treatment in BC patients.\nMETHODS: In this study, the weighted gene co-expression network analysis was applied to identify the hub gene module correlated with BC grade using GSE71576. After constructing a protein-protein interaction (PPI) network with the hub genes inside the hub gene module, we identified some potential core genes. TCGA and another independent dataset were used for further validation.\nRESULTS: The results revealed that the expression of AURKA, CCNA2, CCNB1, KIF11, TTK, BUB1B, BUB1, and CDK1 were significantly higher in high-grade BC, showing a strong ability to distinguish BC grade. The expression levels of the 8 genes in normal, paracancerous, tumorous, and recurrent bladder tissues were progressively increased. By conducting survival analysis, we proved their prognostic value in predicting the recurrence of BC. Eventually, we constructed a prognostic nomogram by combining the 8-core-gene panel with clinicopathologic features, which had shown great performance in predicting the recurrence of BC.\nCONCLUSION: We identified 8 core genes that revealed a significant correlation with the tumor grade as well as the recurrence of BC. 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