Frontiers in Genetics (Aug 2020)

Identification of the Six-RNA-Binding Protein Signature for Prognosis Prediction in Bladder Cancer

  • Yucai Wu,
  • Yucai Wu,
  • Yucai Wu,
  • Yucai Wu,
  • Yi Liu,
  • Anbang He,
  • Anbang He,
  • Anbang He,
  • Anbang He,
  • Bao Guan,
  • Bao Guan,
  • Bao Guan,
  • Bao Guan,
  • Shiming He,
  • Shiming He,
  • Shiming He,
  • Shiming He,
  • Cuijian Zhang,
  • Cuijian Zhang,
  • Cuijian Zhang,
  • Cuijian Zhang,
  • Zhengjun Kang,
  • Yanqing Gong,
  • Yanqing Gong,
  • Yanqing Gong,
  • Yanqing Gong,
  • Xuesong Li,
  • Xuesong Li,
  • Xuesong Li,
  • Xuesong Li,
  • Liqun Zhou,
  • Liqun Zhou,
  • Liqun Zhou,
  • Liqun Zhou

DOI
https://doi.org/10.3389/fgene.2020.00992
Journal volume & issue
Vol. 11

Abstract

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RNA-binding proteins (RBPs) are a kind of gene regulatory factor that presents a significant biological effect in the initiation and development of various tumors, including bladder cancer (BLCA). However, the RBP-based prognosis signature for BLCA has not been investigated. In this study, we attempted to develop an RBP-based classifier to predict overall survival (OS) for BLCA based on transcriptome analysis. We extracted data of BLCA patients from The Cancer Genome Atlas database (TCGA) and UCSC Xena. Finally, a total of 398 cases without missing clinical data were enrolled and six RBPs (FLNA, HSPG2, AHNAK, FASTKD3, POU5F1, and PCSK9) associated with OS of BLCA were identified through univariate and multivariate Cox regression analysis. Online analyses and immunohistochemistry validated the prognostic value and expression of six RBPs. Risk scores were calculated to divide patients into high-risk and low-risk level, and patients in the high-risk group tended to have a poor prognosis. In addition, the receiver operating characteristic (ROC) curve analysis was performed to assess the prognostic value of RBPs, and the area under the curve (AUC) values were 0.711 and 0.706, respectively, in the training set and validating set. The findings were further validated in an external validation set. Subsequently, the 6-RBP-based signature and pathological stage were used to construct the nomogram to predict the 3- and 5-years OS of BLCA patients. Also, this 6-RBP-based signature was highly related to recurrence-free survival of BLCA. Weighted co-expression network analysis (WGCNA) combined with functional enrichment analysis contributed to study the potential pathways of six RBPs, including keratinocyte differentiation, RHO GTPases activate PNKs, epithelial tube morphogenesis, establishment or maintenance of cell polarity, and so on. In summary, the 6-RBP-based signature holds the potentiality to serve as a novel prognostic predictor of OS for BLCA.

Keywords