Persistent dysregulation of genes in the development of endometriosis

Abstract

Background: Endometriosis is a chronic condition that affects women of child-bearing age. Since the etiology and pathogenesis of endometriosis have not been fully elucidated, it is important to investigate the mechanisms that lead to the deterioration of endometriosis.

Methods: In this study, the transcriptome data of patients with normal, mild, and severe endometriosis were examined using the GSE51981 dataset obtained from the Gene Expression Omnibus database. Short Time Series Expression Miner (STEM) was used to screen the genes with continuous expression disorder in the development process, and the core genes were identified by constructing a protein-protein interaction network. The molecular mechanisms of endometriosis were examined using enrichment analysis. Finally, the transcription factors that regulate the core genes were predicted and the comprehensive mechanisms involved in the development of endometriosis were examined.

Results: A total of 3,472 differentially expressed genes were identified from the normal, mild, and severe endometriosis samples. These were allocated into 12 modules and HRAS, HSP90AA1, TGFB1, TP53, and UBC were selected as the core genes. Enrichment analysis showed that the genes in modules 6, 7, and 9 were significantly related to oxygen levels, metallic processes, and hormone levels, respectively. Transcription factor prediction analysis showed that TP53 regulates HRAS to participate in immune related signaling pathways. Drug prediction analysis identified 792 drugs that interact with the targeted core genes.

Conclusions: This study explored the molecular mechanisms involved in the development of endometriosis and identified potential biomarkers of endometriosis. This data may provide novel targets and research directions for the diagnosis and treatment of endometriosis.

Keywords: Endometriosis; Short Time Series Expression Miner (STEM); enrichment analysis; modules; protein-protein interaction network (PPI network).

Figure 1

Dysregulated genes that are continuously expressed in endometriosis from normal to mild, and from mild to severe. (A) Principal component analysis for samples of normal, mild, and severe endometriosis. (B) A Manhattan map of the differentially expressed genes for the three groups. (C) The common differentially expressed genes between mild-normal and severe-mild endometriosis. (D) Genes are organized into different clusters based on expression pattern using STEM. Line plots and box plots are used to show fold changes (log₂FC) and absolute expression levels (log₂FPKM), respectively. (E) Line plots and heatmap of different gene clusters. var, variance; PC, principal component; FPKM, fragments per kilobase million; STEM, Short Time Series Expression Miner; FC, fold change.

Figure 2

The PPI network of the continuously expressed maladjusted genes. (A) PPI networks of the continuously expressed maladjusted genes. (B) The differentially expressed genes of the two groups are displayed in the modules. (C) A heatmap of the differentially expressed genes in modules. (D) The results of correlation analysis between modules and phenotypes. (E) The expression trend of the core genes in the process of endometriosis. (F) The AUC value of the core genes in the different endometriosis processes. AUC, area under the curve; DEG, differentially expressed gene; FC, fold change; PPI, protein-protein interaction.

Figure 3

Evaluation of core genes. (A) Decision curve analysis for detectable mild endometriosis risk. (B) Decision curve analysis for detectable severe endometriosis risk. (C) Sample in different stages of the menstrual cycle of endometriosis. (D) Differentially expressed genes between early-secretory and proliferation and between mid-secretory and early-secretory. Red is upregulation and blue is downregulation. Genes with the largest fold change are labeled. (E) The expression of core genes in different stages of the menstrual cycle. FC, fold change.

Figure 4

The biological function and signaling pathways associated with the persistent maladjustment genes. (A) The biological processes associated with the dysfunctional genes. (B) The KEGG pathways associated with the dysfunctional genes. (C) The signaling pathways showing an upward trend in normal, mild, and severe endometriosis according to the GSVA results. (D) The signaling pathways with a downward trend in normal, mild, and severe endometriosis according to the GSVA results. KEGG, Kyoto Encyclopedia of Gene and Genome; GSVA, Gene Set Variation Analysis; GO, Gene Ontology; FDR, false discovery rate.

Figure 5

Transcription regulators of the core genes. (A) Transcription regulators that show a high correlation with the core genes. (B) Regulatory factors that regulate the network of core genes involved in signaling pathways. TF, transcription factor.

Figure 6

Immune levels in endometriosis. (A) Differential levels of immune cells between mild endometriosis and normal samples. Red is upregulation and blue is downregulation in mild endometriosis. (B) Differential levels of immune cells between severe and mild endometriosis samples. Red is upregulation and blue is downregulation in severe endometriosis. Gray lines represent no statistical significance. (C) Correlations between immune cells and core genes in mild endometriosis. (D) Correlations between immune cells and core genes in severe endometriosis. *, P<0.05, **, P<0.01. Tem, effector memory T cell; Tgd, gamma delta T cell; aDC, activated dendritic cell; TFH, follicular helper T cell; NK, natural killer; DC, dendritic cell; pDC, plasmacytoid dendritic cell; iDC, immature dendritic cell; TReg, regulatory T cell; Tcm, central memory T cell; FC, fold change.