A cross-study gene set enrichment analysis identifies critical pathways in endometriosis

Comparative Analysis of Shapley Values Enhances Transcriptomics Insights across Some Common Uterine Pathologies

Uterine pathologies pose a challenge to women's health on a global scale. Despite extensive research, the causes and origin of some of these common disorders are not well defined yet. This study presents a comprehensive analysis of transcriptome data from diverse datasets encompassing relevant uterine pathologies such as endometriosis, endometrial cancer and uterine leiomyomas. Leveraging the Comparative Analysis of Shapley values (CASh) technique, we demonstrate its efficacy in improving the outcomes of the classical differential expression analysis on transcriptomic data derived from microarray experiments. CASh integrates the microarray game algorithm with Bootstrap resampling, offering a robust statistical framework to mitigate the impact of potential outliers in the expression data. Our findings unveil novel insights into the molecular signatures underlying these gynecological disorders, highlighting CASh as a valuable tool for enhancing the precision of transcriptomics analyses in complex biological contexts. This research contributes to a deeper understanding of gene expression patterns and potential biomarkers associated with these pathologies, offering implications for future diagnostic and therapeutic strategies.

Transcriptomic analyses of ovarian clear-cell carcinoma with concurrent endometriosis

Introduction

Endometriosis, a benign inflammatory disease whereby endometrial-like tissue grows outside the uterus, is a risk factor for endometriosis-associated ovarian cancers. In particular, ovarian endometriomas, cystic lesions of deeply invasive endometriosis, are considered the precursor lesion for ovarian clear-cell carcinoma (OCCC).

Methods

To explore this transcriptomic landscape, OCCC from women with pathology-proven concurrent endometriosis (n = 4) were compared to benign endometriomas (n = 4) by bulk RNA and small-RNA sequencing.

Results

Analysis of protein-coding genes identified 2449 upregulated and 3131 downregulated protein-coding genes (DESeq2, P< 0.05, log2 fold-change > |1|) in OCCC with concurrent endometriosis compared to endometriomas. Gene set enrichment analysis showed upregulation of pathways involved in cell cycle regulation and DNA replication and downregulation of pathways involved in cytokine receptor signaling and matrisome. Comparison of pathway activation scores between the clinical samples and publicly-available datasets for OCCC cell lines revealed significant molecular similarities between OCCC with concurrent endometriosis and OVTOKO, OVISE, RMG1, OVMANA, TOV21G, IGROV1, and JHOC5 cell lines. Analysis of miRNAs revealed 64 upregulated and 61 downregulated mature miRNA molecules (DESeq2, P< 0.05, log2 fold-change > |1|). MiR-10a-5p represented over 21% of the miRNA molecules in OCCC with endometriosis and was significantly upregulated (NGS: log2fold change = 4.37, P = 2.43e-18; QPCR: 8.1-fold change, P< 0.05). Correlation between miR-10a expression level in OCCC cell lines and IC50 (50% inhibitory concentration) of carboplatin in vitro revealed a positive correlation (R2 = 0.93). MiR-10a overexpression in vitro resulted in a significant decrease in proliferation (n = 6; P< 0.05) compared to transfection with a non-targeting control miRNA. Similarly, the cell-cycle analysis revealed a significant shift in cells from S and G2 to G1 (n = 6; P< 0.0001). Bioinformatic analysis predicted that miR-10a-5p target genes that were downregulated in OCCC with endometriosis were involved in receptor signaling pathways, proliferation, and cell cycle progression. MiR-10a overexpression in vitro was correlated with decreased expression of predicted miR-10a target genes critical for proliferation, cell-cycle regulation, and cell survival including [SERPINE1 (3-fold downregulated; P< 0.05), CDK6 (2.4-fold downregulated; P< 0.05), and RAP2A (2-3-fold downregulated; P< 0.05)].

Discussion

These studies in OCCC suggest that miR-10a-5p is an impactful, potentially oncogenic molecule, which warrants further studies.

Identification of Key Differentially Methylated/Expressed Genes and Pathways for Ovarian Endometriosis by Bioinformatics Analysis

The goal of this study was to identify genes that were differentially methylated and differentially expressed and their related signaling pathways in ovarian endometriosis tissue. First, the DNA methylation and gene expression profiles in the endometrial tissue of patients with ovarian endometriosis were studied using Illumina 450K methylation microarray analysis and the GSE141549 gene expression dataset. Second, differentially methylated and differentially expressed genes, herein referred to as differentially methylated/expressed genes, were identified and protein-protein interaction networks and functional analysis of these genes were determined. Third, qPCR and immunohistochemistry of patient samples was used to confirm the differential expression of a subset of differentially methylated/expressed genes. Finally, the GSE7305 dataset was used confirm the expression profile of differentially methylated/expressed genes and to determine the potential usefulness of these genes for diagnosis of endometriosis. A total of 37 hypermethylated low-expression genes and 66 hypomethylated high-expression genes were identified in ovarian endometriosis patients. Protein-protein interaction and functional analysis highlighted 8 hypermethylated low-expression genes (KRT19, KRT8, ESR1, PRL, SFN, IL20RA, IL2RB, and PAX8) and 4 hypomethylated high-expression genes (CYP11A1, NR5A1, ME1, and GSTM1). Significantly, both of these gene sets had a diagnostic value for patients with ovarian endometriosis. Signaling pathways that were identified included JAK-STAT (involving IL20RA and IL2RB), prolactin (involving PRL and ESR1), Staphylococcus aureus infection (involving KRT19), viral protein interaction with cytokine and cytokine receptor (involving IL20RA and IL2RB), cytokine-cytokine receptor interaction (involving IL20RA and IL2RB), and drug metabolism-cytochrome P450 (involving GSTM1). The differentially methylated/expressed genes and enriched signaling pathways identified in this study are likely to be associated with the process of ovarian endometriosis.

PAGER 2.0: an update to the pathway, annotated-list and gene-signature electronic repository for Human Network Biology

Integrative Gene-set, Network and Pathway Analysis (GNPA) is a powerful data analysis approach developed to help interpret high-throughput omics data. In PAGER 1.0, we demonstrated that researchers can gain unbiased and reproducible biological insights with the introduction of PAGs (Pathways, Annotated-lists and Gene-signatures) as the basic data representation elements. In PAGER 2.0, we improve the utility of integrative GNPA by significantly expanding the coverage of PAGs and PAG-to-PAG relationships in the database, defining a new metric to quantify PAG data qualities, and developing new software features to simplify online integrative GNPA. Specifically, we included 84 282 PAGs spanning 24 different data sources that cover human diseases, published gene-expression signatures, drug-gene, miRNA-gene interactions, pathways and tissue-specific gene expressions. We introduced a new normalized Cohesion Coefficient (nCoCo) score to assess the biological relevance of genes inside a PAG, and RP-score to rank genes and assign gene-specific weights inside a PAG. The companion web interface contains numerous features to help users query and navigate the database content. The database content can be freely downloaded and is compatible with third-party Gene Set Enrichment Analysis tools. We expect PAGER 2.0 to become a major resource in integrative GNPA. PAGER 2.0 is available at http://discovery.informatics.uab.edu/PAGER/.

Seminal Plasma Promotes Lesion Development in a Xenograft Model of Endometriosis

The factors that predispose one-tenth of reproductive-aged women to endometriosis are poorly understood. We determined that genetic deficiency in transforming growth factor β1 impairs endometriosis-like lesion growth in mice. Given that seminal plasma is an abundant source of transforming growth factor β, we evaluated the effect of exposure to seminal plasma on the growth of endometrial lesions. Human endometrial explants were exposed to seminal plasma or to control medium before transfer to Prkdc(scid)-mutant (severe combined immunodeficient) mice. Xenografts exposed to seminal plasma showed an eightfold increase in volume and a 4.3-fold increase in weight after 14 days. These increases were associated with increased proliferation of endometrial epithelial cells and enhanced survival and proliferation of human stromal cells compared with those in control lesions, in which human stromal cell persistence was negligible. Although the distribution of macrophages was altered, their number and activation status did not change in response to seminal plasma. Seminal plasma stimulated the production of a variety of cytokines in endometrial tissue, including growth-regulated oncogene, granulocyte macrophage colony-stimulating factor, and IL-1β. These data suggest that seminal plasma enhances the formation of endometriosis-like lesion via a direct effect on endometrial cell survival and proliferation, rather than via macrophage-mediated mechanisms. These findings raise the possibility that endometrial exposure to seminal plasma could contribute to endometriotic disease progression in women.

Integrative Analysis Reveals Regulatory Programs in Endometriosis

Endometriosis is a common gynecological disease found in approximately 10% of reproductive-age women. Gene expression analysis has been performed to explore alterations in gene expression associated with endometriosis; however, the underlying transcription factors (TFs) governing such expression changes have not been investigated in a systematic way. In this study, we propose a method to integrate gene expression with TF binding data and protein-protein interactions to construct an integrated regulatory network (IRN) for endometriosis. The IRN has shown that the most regulated gene in endometriosis is RUNX1, which is targeted by 14 of 26 TFs also involved in endometriosis. Using 2 published cohorts, GSE7305 (Hover, n = 20) and GSE7307 (Roth, n = 36) from the Gene Expression Omnibus database, we identified a network of TFs, which bind to target genes that are differentially expressed in endometriosis. Enrichment analysis based on the hypergeometric distribution allowed us to predict the TFs involved in endometriosis (n = 40). This included known TFs such as androgen receptor (AR) and critical factors in the pathology of endometriosis, estrogen receptor α, and estrogen receptor β. We also identified several new ones from which we selected FOXA2 and TFAP2C, and their regulation was confirmed by quantitative real-time polymerase chain reaction and immunohistochemistry (IHC). Further, our analysis revealed that the function of AR and p53 in endometriosis is regulated by posttranscriptional changes and not by differential gene expression. Our integrative analysis provides new insights into the regulatory programs involved in endometriosis.

Gene set enrichment analysis of pathways and transcription factors associated with diabetic retinopathy using a microarray dataset

Diabetic retinopathy (DR) is a serious microvascular complication of diabetes, which causes visual disability and blindness. Several studies have used gene expression profiling of DR to identify the key genes involved in this process; however, few studies have focused on the associated pathways and transcription factors (TFs), or on the co-expression patterns at the multiple pathways level. In this study, we employed a microarray dataset from the public database library of the Gene Expression Omnibus (GEO) associated with DR and applied gene set enrichment analysis (GSEA) to this dataset and performed candidate TF selection. As a result, 10 upregulated pathways, including the type I diabetes mellitus and peroxisome proliferator-activated receptor (PPAR) signaling pathways, as well as 59 downregulated pathways, including the ErbB signaling pathway and the mammalian target of rapamycin (mTOR) signaling pathway, were identified as DR‑related pathways. The majority of these pathways have been previously identified, but some were novel. Finally, co-expression networks of related pathways were constructed using the significant core genes and TFs, such as PPARγ and SMAD4. The results of our study may enhance our understanding of the molecular mechanisms associated DR at the genome-wide level.

Comprehensive identification of essential pathways and transcription factors related to epilepsy by gene set enrichment analysis on microarray datasets

Epilepsy is a common chronic neurological disorder characterized by seizures or convulsions, and is known to affect patients with primary brain tumors. The etiology of epilepsy is superficially thought to be multifactorial; however, the genetic factors which may be involved in the pathogenesis of seizures have not yet been elucidated, particularly at the pathway level. In the present study, in order to systematically investigate the gene regulatory networks involved in epilepsy, we employed a microarray dataset from the public database library of Gene Expression Omnibus (GEO) associated with tumor-induced epileptogenesis and applied gene set enrichment analysis (GSEA) on these data sets and performed candidate transcription factor (TF) selection. As a result, 68 upregulated pathways, including the extracellular matrix (ECM)-receptor interaction (P=0.004) and peroxisome proliferator-activated receptor (PPAR) signaling pathways (P=0.045), as well as 4 downregulated pathways, including the GnRH signaling pathway (P=0.029) and gap junction (P=0.034) were identified as epileptogenesis-related pathways. The majority of these pathways identified have been previously reported and our results were in accordance with those reports. However, some of these pathways identified were novel. Finally, co-expression networks of the related pathways were constructed with the significant core genes and TFs, such as PPAR-γ and phosphatidylethanolamine-binding protein. The results of our study may contribute to the improved understanding of the molecular mechanisms of epileptogenesis on a genome-wide level.

[Bioinformatic screening of key genes controlling the development and progression of lung cancer]

BACKGROUND AND OBJECTIVE

Lung cancer is the most common cancer in the world. The gene expression profiling of lung cancer has been extensively investigated. However, only a few studies have identified the possible pathways and significant genes related to lung cancer. The aim of this study is to explore the large number of lung cancer-related microarray datasets and identify the crucial genes that can benefit the understanding of the progression and development of this disease.

METHODS

To identify the genes that effected lung cancer at the mRNA level, gene set enrichment analysis was used to analyze six selected gene expression datasets.

RESULTS

Among the six gene expression datasets, 3 up-regulated and 26 down-regulated pathways were found by gene set enrichment analysis. We found 11 significant genes with P < 0.05 from the results of tight junction meta-analysis of the six data sets.

CONCLUSIONS

The tight junction pathway plays an important role in the study of the occurrence and development of lung cancer. Significant genes within the pathways will be further discussed in future studies.

Genome-wide expressions in autologous eutopic and ectopic endometrium of fertile women with endometriosis

BACKGROUND

In order to obtain a lead of the pathophysiology of endometriosis, genome-wide expressional analyses of eutopic and ectopic endometrium have earlier been reported, however, the effects of stages of severity and phases of menstrual cycle on expressional profiles have not been examined. The effect of genetic heterogeneity and fertility history on transcriptional activity was also not considered. In the present study, a genome-wide expression analysis of autologous, paired eutopic and ectopic endometrial samples obtained from fertile women (n=18) suffering from moderate (stage 3; n=8) or severe (stage 4; n=10) ovarian endometriosis during proliferative (n=13) and secretory (n=5) phases of menstrual cycle was performed.

METHODS

Individual pure RNA samples were subjected to Agilent's Whole Human Genome 44K microarray experiments. Microarray data were validated (P<0.01) by estimating transcript copy numbers by performing real time RT-PCR of seven (7) arbitrarily selected genes in all samples. The data obtained were subjected to differential expression (DE) and differential co-expression (DC) analyses followed by networks and enrichment analysis, and gene set enrichment analysis (GSEA). The reproducibility of prediction based on GSEA implementation of DC results was assessed by examining the relative expressions of twenty eight (28) selected genes in RNA samples obtained from fresh pool of eutopic and ectopic samples from confirmed ovarian endometriosis patients with stages 3 and 4 (n=4/each) during proliferative and secretory (n=4/each) phases.

RESULTS

Higher clustering effect of pairing (cluster distance, cd=0.1) in samples from same individuals on expressional arrays among eutopic and ectopic samples was observed as compared to that of clinical stages of severity (cd=0.5) and phases of menstrual cycle (cd=0.6). Post hoc analysis revealed anomaly in the expressional profiles of several genes associated with immunological, neuracrine and endocrine functions and gynecological cancers however with no overt oncogenic potential in endometriotic tissue. Dys-regulation of three (CLOCK, ESR1, and MYC) major transcription factors appeared to be significant causative factors in the pathogenesis of ovarian endometriosis. A novel cohort of twenty-eight (28) genes representing potential marker for ovarian endometriosis in fertile women was discovered.

CONCLUSIONS

Dysfunctional expression of immuno-neuro-endocrine behaviour in endometrium appeared critical to endometriosis. Although no overt oncogenic potential was evident, several genes associated with gynecological cancers were observed to be high in the expressional profiles in endometriotic tissue.

A Comparative Study of Mouse Hepatic and Intestinal Gene Expression Profiles under PPARα Knockout by Gene Set Enrichment Analysis

Gene expression profiling of PPARα has been used in several studies, but fewer studies went further to identify the tissue-specific pathways or genes involved in PPARα activation in genome-wide. Here, we employed and applied gene set enrichment analysis to two microarray datasets both PPARα related respectively in mouse liver and intestine. We suggested that the regulatory mechanism of PPARα activation by WY14643 in mouse small intestine is more complicated than in liver due to more involved pathways. Several pathways were cancer-related such as pancreatic cancer and small cell lung cancer, which indicated that PPARα may have an important role in prevention of cancer development. 12 PPARα dependent pathways and 4 PPARα independent pathways were identified highly common in both liver and intestine of mice. Most of them were metabolism related, such as fatty acid metabolism, tryptophan metabolism, pyruvate metabolism with regard to PPARα regulation but gluconeogenesis and propanoate metabolism independent of PPARα regulation. Keratan sulfate biosynthesis, the pathway of regulation of actin cytoskeleton, the pathways associated with prostate cancer and small cell lung cancer were not identified as hepatic PPARα independent but as WY14643 dependent ones in intestinal study. We also provided some novel hepatic tissue-specific marker genes.

Functional microRNA involved in endometriosis

Endometriosis is a common disease seen by gynecologists. Clinical features involve pelvic pain and unexplained infertility. Although endometriosis is pathologically characterized by endometrial tissue outside the normal uterine location, endometriosis is otherwise not easily explained. Endometriomas, endometriotic cysts of the ovary, typically cause pain and distortion of pelvic anatomy. To begin to understand the pathogenesis of endometriomas, we describe the first transcriptome-microRNAome analysis of endometriomas and eutopic endometrium using next-generation sequencing technology. Using this approach, we generated a total of more than 54 million independent small RNA reads from our 19 clinical samples. At the microRNA level, we found 10 microRNA that were up-regulated (miR-202, 193a-3p, 29c, 708, 509-3-5p, 574-3p, 193a-5p, 485-3p, 100, and 720) and 12 microRNA that were down-regulated (miR-504, 141, 429, 203, 10a, 200b, 873, 200c, 200a, 449b, 375, and 34c-5p) in endometriomas compared with endometrium. Using in silico prediction algorithms, we correlated these microRNA with their corresponding differentially expressed mRNA targets. To validate the functional roles of microRNA, we manipulated levels of miR-29c in an in vitro system of primary cultures of human endometrial stromal fibroblasts. Extracellular matrix genes that were potential targets of miR-29c in silico were significantly down-regulated using this biological in vitro system. In vitro functional studies using luciferase reporter constructs further confirmed that miR-29c directly affects specific extracellular matrix genes that are dysregulated in endometriomas. Thus, miR-29c and other abnormally regulated microRNA appear to play important roles in the pathophysiology of uterine function and dysfunction.

New insights into the pathophysiology of endometriosis: from chronic inflammation to danger signal

BACKGROUND

Various theories try to explain the development and progression of endometriosis, however, no single theory can explain all aspects of this disorder. Gene expression profiling studies might reveal factors that explain variability in disease development and progression, which can serve as specific biomarkers for endometriosis and novel drug development. We have recently showed that the upregulated genes were predominantly clustered in stress and detoxification, providing a mechanistic explanation for the oxidative stress and chronic inflammatory response in endometriosis.

OBJECTIVE

This review aims: (1) to analyse the published data, with the aim of identifying pathways consistently regulated by the endometriosis genotype and (2) to summarise the findings of specific genes, which are involved in the process of oxidative stress and inflammation.

METHODS

We identified gene array and proteomics studies whose data were accessible in PubMed.

RESULTS

A major finding is the increased expressions of several markers including heat shock protein, S100, fibronectin, and neutrophil elastase, which might be involved in the process of Toll-like receptor (TLR)-dependent sterile inflammation. The study reviews a convergence in the main pathogenic process, where the TLR-mediated inflammation occurs possibly through the endogenous ligands.

CONCLUSIONS

In conclusion, a circulus vitiosus of both the oxidative stress pathway and the TLR pathways is generated when the process becomes chronic (danger signal spiral).

Genetics and genomics of endometriosis

Endometriosis is a common cause of morbidity in women with an unknown etiology. Studies have demonstrated the familial nature of endometriosis and suggest that inheritance occurs in a polygenic/multifactorial fashion. Studies have attempted to define the gene or genes responsible for endometriosis through association or linkage studies with candidate genes or DNA mapping technology. A number of genomics studies have demonstrated significant alterations in gene expression in endometriosis. A more thorough understanding of the genetics and genomics of endometriosis will facilitate understanding the basic biology of the disease and open new inroads to diagnosis and treatment of this enigmatic condition.