Correlating Transcriptional Networks to Papillary Renal Cell Carcinoma Survival: A Large-Scale Co-expression Analysis and Clinical Validation

We aimed to investigate the potential mechanisms of progression and identify novelprognosis-related biomarkers for papillary renal cell carcinoma (PRCC) patients. The relateddata were derived from The Cancer Genome Atlas (TCGA), and then, analyzed by Weightedgene co-expression network analysis (WGCNA). The correlation between each module andthe clinical traits were analyzed by Pearson's correlation analysis. Pathway analysis wasconducted to reveal potential mechanisms. Hub genes within each module were screenedby intra-module analysis, and visualized by Cytoscape software. Furthermore, importanthub-genes were validated in an external dataset and clinical samples. A total of 5,839differentially expressed genes were identified. By using Weighted gene co-expressionnetwork analysis (WGCNA), we identified 21 coregulatory gene clusters based on 289papillary renal cell carcinoma (PRCC) samples. We found many modules were significantlyassociated with clinicopathological characteristics. The gray, pink, light yellow and salmonmodules were served as prognosis indicators for papillary renal cell carcinoma (PRCC)patients. Pathway enrichment analyses found that the hub-genes were significantly enrichedin the cancer-related pathways. With the external Gene Expression Omnibus (GEO)validation dataset, we found that PCDH12, GPR4, and KIF18A in pink and yellow moduleswere continually associated with the survival status of papillary renal cell carcinoma(PRCC) , and their expressions were positively correlated with pathological grade. Notably,we randomly chose the PCDH12 for validation, and the results suggested that the papillaryrenal cell carcinoma (PRCC) patients with higher pathological grades (II+III) mostly hadCopyright (c) 2020 Cognizant Communication Corporation3ORM-A-3019 Oncology Research E-pubhigher PCDH12 protein expression levels compared with those patients in Grade I. Thesevalidated hub-genes play critical roles in the prognosis prediction of papillary renal cellcarcinoma (PRCC) , and serve as potential biomarkers for future personalized treatment.