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. 2020 May 2;12(5):1146. doi: 10.3390/cancers12051146

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© 2020 by the authors.

Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

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Establishment of a CCP-related gene signature for CSS. (A) Volcano plot showed that 64 promising candidates were filtered out. (B) Least absolute shrinkage and selection operator (LASSO) algorithm was used to identify the most robust prognostic genes for CSS. Cross-validation was applied to overcome over-fitting effect. (C) An optimal λ value of 0.0585 was selected. (D) Distribution of LASSO coefficients of the established gene signature. (E) Non-negative matrix factorization (NMF) consensus clustering was used to divide the training cohort into two subgroups based on the expression matrix of the established gene signature when k = 2. (F) GSEA analysis confirmed the positive regulation role of the gene signature in cell cycle process in BCa samples. (G) Cell cycle process-related risk score (CCPRS) was significantly positively correlated with MKI67 in 165 BCa samples (r = 0.8033, p < 0.0001). (H) CCPRS was significantly elevated in muscle-invasive bladder cancer (MIBC) samples, especially in more advanced stages (p < 0.0001).