J Cancer 2021; 12(16):4971-4984. doi:10.7150/jca.57225
Integrating 13 Microarrays to Construct a 6 RNA-binding proteins Prognostic Signature for Gastric Cancer patients
Department of General Surgery, The Second Affiliated Hospital of Nanchang University, Nanchang 330006, Jiangxi, China.
*These authors contributed equally to this work.
Zhou L, Zhou Q, Wu Y, Xin L. Integrating 13 Microarrays to Construct a 6 RNA-binding proteins Prognostic Signature for Gastric Cancer patients. J Cancer 2021; 12(16):4971-4984. doi:10.7150/jca.57225. Available from https://www.jcancer.org/v12p4971.htm
Background: It has been confirmed in many tumors that RNA-binding proteins (RBPs) will affect the progress of cancer, but there is still a lack of large-scale research in gastric cancer (GC).
Methods: We obtained 13 microarray mRNA expression profiles of the GPL570 platform, and extracted expression from them after integration to analyze the expression differences of RBPs. Enrichment analysis studies the role of these RBPs in GC. Univariate, Lasso and multivariate Cox regression analysis are used to identify independent prognostic hub RBPs, thereby constructing and verifying a prognostic signature. External data and rt-PCR verified the expression of hub RBPs.
Results: We have identified 51 dysregulated RBPs in GC. Enrichment analysis shows that it can mainly participate in RNA decomposition, modification, processing, etc. and affect the progress of GC. After multiple statistical analysis, six independent prognostic RBPs of GC were determined and a prognostic signature was developed. According to the median risk value, the training cohort was divided into high-risk and low-risk groups. Considering the clinical characteristics, in training, testing, and complete cohorts, the overall survival rate of the high-risk group was significantly lower than that of the low-risk group, which was confirmed by the time-dependent receiver operating characteristic curve. Univariate and multivariate Cox regression analysis of independent prognostic ability of risk score. In addition, we constructed and verified a nomogram based on the prognostic signature, showing accurate prediction performance. rt-PCR and external data verification are consistent with our conclusions.
Conclusion: This study analyzed the overall expression of RPBs in GC and explored its mechanism. A new prognostic signature was developed and verified. A nomogram has also been established and verified, which helps to improve the treatment strategy for GC.
Keywords: gastric cancer, RNA-binding protein, prognosis, signature, nomogram, survival