Open Access
ARTICLE
Correlating Transcriptional Networks to Papillary Renal Cell Carcinoma Survival: A Large-Scale Coexpression Analysis and Clinical Validation
Xingliang Feng*1, Meng Zhang*†1, Jialin Meng*, Yongqiang Wang†, Yi Liu*, Chaozhao Liang*, Song Fan*
* Department of Urology, The First Affiliated Hospital of Anhui Medical University, Institute of Urology,
Anhui Province Key Laboratory of Genitourinary Diseases, Anhui Medical University, Hefei, China
† Urology Institute of Shenzhen University, The Third Affiliated Hospital of Shenzhen University,
Shenzhen University, Shenzhen, China
Oncology Research 2020, 28(3), 285-297. https://doi.org/10.3727/096504020X15791676105394
Abstract
We aimed to investigate the potential mechanisms of progression and identify novel prognosis-related biomarkers for papillary renal cell carcinoma (PRCC) patients. The related data were derived from The Cancer Genome
Atlas (TCGA) and then analyzed by weighted gene coexpression network analysis (WGCNA). The correlation
between each module and the clinical traits were analyzed by Pearson’s correlation analysis. Pathway analysis
was conducted to reveal potential mechanisms. Hub genes within each module were screened by intramodule analysis, and visualized by Cytoscape software. Furthermore, important hub genes were validated in an
external dataset and clinical samples. A total of 5,839 differentially expressed genes were identified. By using
WGCNA, we identified 21 coregulatory gene clusters based on 289 PRCC samples. We found many modules
were significantly associated with clinicopathological characteristics. The gray, pink, light yellow, and salmon
modules served as prognosis indicators for PRCC patients. Pathway enrichment analyses found that the hub
genes were significantly enriched in the cancer-related pathways. With the external Gene Expression Omnibus
(GEO) validation dataset, we found that PCDH12, GPR4, and KIF18A in the pink and yellow modules were
continually associated with the survival status of PRCC, and their expressions were positively correlated with
pathological grade. Notably, we randomly chose PCDH12 for validation, and the results suggested that the
PRCC patients with higher pathological grades (II + III) mostly had higher PCDH12 protein expression levels
compared with those patients in grade I. These validated hub genes play critical roles in the prognosis prediction of PRCC and serve as potential biomarkers for future personalized treatment.
Keywords
Cite This Article
Feng, X., Zhang, M., Meng, J., Wang, Y., Liu, Y. et al. (2020). Correlating Transcriptional Networks to Papillary Renal Cell Carcinoma Survival: A Large-Scale Coexpression Analysis and Clinical Validation.
Oncology Research, 28(3), 285–297. https://doi.org/10.3727/096504020X15791676105394