Abstract
We have identified nine highly connected and differentially expressed gene subnetworks between aggressive primary tumors and metastatic lesions in endometrial carcinomas. We implemented a novel pipeline combining gene set and network approaches, which here allows integration of protein-protein interactions and gene expression data. The resulting subnetworks are significantly associated with disease progression across tumor stages from complex atypical hyperplasia, primary tumors to metastatic lesions. The nine subnetworks include genes related to metastasizing features such as epithelial-mesenchymal transition (EMT), hypoxia and cell proliferation. TCF4 and TWIST2 were found as central genes in the subnetwork related to EMT. Two of the identified subnetworks display statistically significant association to patient survival, which were further supported by an independent validation in the data from The Cancer Genome Atlas data collection. The first subnetwork contains genes related to cell proliferation and cell cycle, while the second contains genes involved in hypoxia such as HIF1A and EGLN3. Our findings provide a promising context to elucidate the biological mechanisms of metastasis, suggest potential prognostic markers and further identify therapeutic targets. The pipeline R source code is freely available, including permutation tests to assess statistical significance of the identified subnetworks.
Highlights
Endometrial cancer is the most common female pelvic malignancy in industrialized countries
The method was designed to combine publicly available external gene-gene relations with internal gene-gene expression correlations of the data set under study, to target differential expression changes in gene modules specific to the conditions of interest
In all nine detected subnetworks, we found several genes that previously have been reported as relating to carcinogenic processes such as epithelial-mesenchymal transition (EMT), hypoxia and cell proliferation
Summary
Endometrial cancer is the most common female pelvic malignancy in industrialized countries. Improved patient treatment is within reach through better prediction of patients with high-risk for cancer recurrence and identification of therapeutic targets against metastatic diseases. High-throughput technologies for studying global expression e.g. microarray or RNA sequencing are potential platforms allowing better understanding of the complexity of cancer biology. The study of global expression in metastatic endometrial cancer will lead to a better understanding of its processes and eventually identification of therapeutic targets. Endometrial cancer studies were based only on tissue from primary lesions [3,4,5]. We perform a study of expression patterns within metastasizing tissue, with a focus on changes between aggressive primary tumors and metastatic lesions of endometrial cancer
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