Discovering the Deregulated Molecular Functions Involved in Malignant Transformation of Endometriosis to Endometriosis-Associated Ovarian Carcinoma Using a Data-Driven, Function-Based Analysis

Abstract

The clinical characteristics of clear cell carcinoma (CCC) and endometrioid carcinoma EC) are concomitant with endometriosis (ES), which leads to the postulation of malignant transformation of ES to endometriosis-associated ovarian carcinoma (EAOC). Different deregulated functional areas were proposed accounting for the pathogenesis of EAOC transformation, and there is still a lack of a data-driven analysis with the accumulated experimental data in publicly-available databases to incorporate the deregulated functions involved in the malignant transformation of EOAC. We used the microarray gene expression datasets of ES, CCC and EC downloaded from the National Center for Biotechnology Information Gene Expression Omnibus (NCBI GEO) database. Then, we investigated the pathogenesis of EAOC by a data-driven, function-based analytic model with the quantified molecular functions defined by 1454 Gene Ontology (GO) term gene sets. This model converts the gene expression profiles to the functionome consisting of 1454 quantified GO functions, and then, the key functions involving the malignant transformation of EOAC can be extracted by a series of filters. Our results demonstrate that the deregulated oxidoreductase activity, metabolism, hormone activity, inflammatory response, innate immune response and cell-cell signaling play the key roles in the malignant transformation of EAOC. These results provide the evidence supporting the specific molecular pathways involved in the malignant transformation of EAOC.

Keywords: Gene Ontology; data-driven analysis; endometriosis; function-based; microarray gene expression datasets; ovarian carcinoma.

Figure 1

Workflow of the gene set regularity model. The gene set regularity (GSR) index was computed by converting the gene expression ordering of gene elements in a gene set through the Gene Ontology (GO) term or canonical pathway databases. The genome-wide informativeness of the GSR index was assessed by the accuracy of pattern recognition, classification and prediction by machine learning using binary or multiclass classifications. Functionome analyses were carried out to investigate the pathogenesis of endometriosis (ES), clear cell carcinoma (CCC), endometrioid carcinoma (EC) and endometriosis associated ovarian carcinoma (EAOC) by statistical methods, hierarchical clustering and exploratory factor analysis.

Figure 2

Histograms of the gene set regularity indices for the three diseases and control groups. The figures show the distributions of gene set regularity (GSR) indices from the three diseases (orange) and control groups (blue). The control group for CCC and EC is identical.

Figure 3

Heatmaps and dendrogram for the three diseases. The dendrogram (left side of the heatmap) shows the relationship of the three diseases. When displayed on the heatmap, each of the three diseases computed through the Gene Ontology (GO) term gene sets show a distinct pattern, however, the patterns are more similar between CCC and EC.

Figure 4

The Gene Ontology tree of deregulated functions from exploratory factor analysis for endometriosis. The figure displays the screenshot of the full Gene Ontology (GO) tree for endometriosis (ES) (middle panel). After mapping to the GO tree, the similar or related GO terms are clustered together. Each cluster is circled (red), and the important deregulated GO terms (green boxes) in the cluster are magnified to view the details. Each cluster is labeled by the common parental GO term (orange rectangle).

Figure 5

The GO tree of deregulated functions from exploratory factor analysis for clear cell carcinoma. This figure displays the screenshot of the full GO tree for ovarian clear cell carcinoma (CCC) (middle panel). After mapping to the GO tree, the similar or related GO terms are clustered together. Each cluster is circled (red), and the important deregulated GO terms (green boxes) in the cluster were magnified to view the details. Each cluster is labeled by the common parental GO term (orange rectangle).

Figure 6

The GO tree of deregulated functions from exploratory factor analysis for endometrioid carcinoma. This figure displays the screenshot of the full Gene Ontology (GO) tree for ovarian endometrioid carcinoma (EC) (middle panel). After mapping to the GO tree, the similar or related GO terms are clustered together. Each cluster is circled (red), and the important deregulated GO terms (green boxes) in the cluster are magnified to view the details. Each cluster is labeled by the common parental GO term (orange rectangle).

Figure 7

Venn diagram of the deregulated GO term elements from exploratory factor analysis for the three diseases. The figure shows the results of the three diseases with the total factor elements for each disease. Their relationship is displayed on the Venn diagram to show the gene set numbers of all possible logical relations among the three diseases. The 35 commonly-deregulated GO terms among ES, CCC and EC are listed on the right side of the figure.

Figure 8

The 71 progressively-deregulated GO terms involving malignant transformation and their changes in GSR index and ranking from ES to CCC or EC. (A) The list of 71 progressively-deregulated GO terms whose GSR indices decreased and moved upward in rankings with the progression from ES to EAOC. (B) The GSR index levels of the 71 GO terms that decreased from ES to CCC or EC. (C) The ranking paths of the 71 GO terms changing from ES to CCC or EC. The coarse red line shows the paths for the average of the GSR indices (B) or rankings (C).

Figure 9

Possible contribution of the microenvironment in endometriosis to the development of EAOC. Endometriosis is an inflammatory condition arising from ectopic implantation of endometrial glands and stroma outside the uterine endometrium [29]. This microenvironment, especially the high concentration of free iron, which is derived from old menstrual blood accumulated in endometriosis (endometrioma), causes oxidative stress (ROS) and DNA damage [31,32]. Accumulation of DNA damage and inflammation/immune cytokines activated oncogenes [33,34]. Progressively reprogrammed metabolism and hormone changes over the years [35,36,37] eventually lead to the carcinogenesis of EAOC.