Abstract
We previously showed that PAUF is involved in tumor development and metastases in cervical cancer. This study was conducted to discover novel molecular markers linked with PAUF in cervical cancer using genomic network analysis and to assess their prognostic value in cervical cancer. Three PAUF-related genes were identified using in-silico network-based analysis of the open genome datasets. To assess the expression of these genes and their relationship to the outcome of cervical cancer, immunohistochemical analysis was performed using cervical cancer TMA. The associations of the identified proteins with clinicopathologic characteristics and prognosis were examined. AGR2, BRD7, and POM121 were identified as interconnected with PAUF through in-silico network-based analysis. AGR2 (r = 0.213, p < 0.001) and POM121 (r = 0.135, p = 0.013) protein expression were positively correlated with PAUF. BRD7High and AGR2Low were significantly associated with favorable disease-free survival (DFS) (p = 0.009 and p < 0.001, respectively), and in combination with PAUFHigh, even more significantly favorable DFS observed (p < 0.001 for both). In multivariate analysis, AGR2High (HR = 3.16, p = 0.01) and BRD7High (HR = 0.5, p = 0.025) showed independent prognostic value for DFS. In a random survival forest (RSF) model, the combined clinical and molecular variable model predicted DFS with significantly improved power compared with that of the clinical variable model (C-index of 0.79 vs. 0.75, p < 0.001). In conclusion, AGR2 and BRD7 expression have prognostic significance in cervical cancer and provide opportunities for improved treatment options. Genomic network-based approaches using the cBioPortal may facilitate the discovery of additional biomarkers for the prognosis of cervical cancer and may provide new insights into the biology of cervical carcinogenesis.