Identification of key pathways and genes in endometrial cancer using bioinformatics analyses

Adipocytes Promote Endometrial Cancer Progression Through Activation of the SIRT1-HMMR Signaling Axis

Adipocyte is a predominant component of the omental adipose tissue that influences the tumor microenvironment and increases the risk of endometrial cancer progression (EC), however, little is known about the underlying mechanism. In this study, using a co-culture model, we found that the adipocyte-EC cell interaction promoted SIRT1 signaling in vitro and in vivo xenograft mice models. Furthermore, immunostaining of SIRT1 protein showed significantly higher expression of SIRT1 in endometrial cancer patients than in normal endometria. RNA sequencing analysis revealed HMMR (hyaluronan-mediated motility receptor), an oncogene, as a downstream effector of SIRT1 in adipocyte-associated EC. Transient knockdown and chromatin immunoprecipitation assays showed that SIRT1 inhibition impedes transcription of the HMMR gene via FOXM1, and reduced expression of HMMR in co-cultured EC cells blocks AURKA activation via TPX2, leading to cell cycle arrest. This is the first study to report the positive correlation between SIRT1 and HMMR in EC patient tumors and might be used as a potential biomarker in EC. Notably, SIRT1 regulates HMMR expression in a FOXM1-dependent manner, and interfering with SIRT1 may provide a promising strategy for the management of endometrial cancer.

BUB1, BUB1B, CCNA2, and CDCA8, along with miR-524-5p, as clinically relevant biomarkers for the diagnosis and treatment of endometrial carcinoma

BACKGROUND

Endometrial carcinoma (EC) is a malignant tumor of the female reproductive tract that has been associated with increased morbidity and mortality. This study aimed to identify biomarkers and potential therapeutic targets for EC.

METHODS

A publicly available transcriptome data set comprising 587 EC cases was subjected to a comprehensive bioinformatics analysis to identify candidate genes responsible for EC occurrence and development. Next, we used clinical samples and cell experiments for validation.

RESULTS

A total of 1,617 differentially expressed genes (DEGs) were identified. Analysis of patient survival outcomes revealed that BUB1, BUB1B, CCNA2, and CDCA8 were correlated with prognosis in patients with EC. Moreover, assessment of clinical samples confirmed that BUB1, BUB1B, CCNA2 and CDCA8 were strongly expressed in EC tissues. Additionally, bioinformatics and luciferase reporter assays confirmed that miR-524-5p can target and regulate these four genes. Overexpression of miR-524-5p significantly inhibited EC Ishikawa cells viability, migration and invasion. Inhibition of miR-524-5p showed the opposite results.

CONCLUSIONS

Expression of miR-524-5p reduced the migration and invasion of Ishikawa EC cells, and decreased BUB1, BUB1B, CCNA2, and CDCA8 expression. miR-524-5p, as well as BUB1, BUB1B, CCNA2, and CDCA8, may be clinically relevant biomarkers for the diagnosis and treatment of EC.

Ontologies and Knowledge Graphs in Oncology Research

The complexity of cancer research stems from leaning on several biomedical disciplines for relevant sources of data, many of which are complex in their own right. A holistic view of cancer—which is critical for precision medicine approaches—hinges on integrating a variety of heterogeneous data sources under a cohesive knowledge model, a role which biomedical ontologies can fill. This study reviews the application of ontologies and knowledge graphs in cancer research. In total, our review encompasses 141 published works, which we categorized under 14 hierarchical categories according to their usage of ontologies and knowledge graphs. We also review the most commonly used ontologies and newly developed ones. Our review highlights the growing traction of ontologies in biomedical research in general, and cancer research in particular. Ontologies enable data accessibility, interoperability and integration, support data analysis, facilitate data interpretation and data mining, and more recently, with the emergence of the knowledge graph paradigm, support the application of Artificial Intelligence methods to unlock new knowledge from a holistic view of the available large volumes of heterogeneous data.

Transgenic mice overexpressing the LH receptor in the female reproductive system spontaneously develop endometrial tumour masses

The receptor for the luteinizing hormone (LH-R) is aberrantly over expressed in cancers of the reproductive system. To uncover whether LH-R over expression has a causative role in cancer, we generated a transgenic (TG) mouse which overexpresses the human LH-R (hLH-R) in the female reproductive tract, under the control of the oviduct-specific glycoprotein (OGP) mouse promoter (mogp-1). The transgene was highly expressed in the uterus, ovary and liver, but only in the uterus morphological and molecular alterations (increased proliferation and trans-differentiation in the endometrial layer) were detected. A transcriptomic analysis on the uteri of young TG mice showed an up regulation of genes involved in cell cycle control and a down regulation of genes related to the immune system and the metabolism of xenobiotics. Aged TG females developed tumor masses in the uteri, which resembled an Endometrial Cancer (EC). Microarray and immunohistochemistry data indicated the deregulation of signaling pathways which are known to be altered in human ECs. The analysis of a cohort of 126 human ECs showed that LH-R overexpression is associated with early-stage tumors. Overall, our data led support to conclude that LH-R overexpression may directly contribute to trigger the neoplastic transformation of the endometrium.

Solid tumours hijack the histone variant network

Cancer is a complex disease characterized by loss of cellular homeostasis through genetic and epigenetic alterations. Emerging evidence highlights a role for histone variants and their dedicated chaperones in cancer initiation and progression. Histone variants are involved in processes as diverse as maintenance of genome integrity, nuclear architecture and cell identity. On a molecular level, histone variants add a layer of complexity to the dynamic regulation of transcription, DNA replication and repair, and mitotic chromosome segregation. Because these functions are critical to ensure normal proliferation and maintenance of cellular fate, cancer cells are defined by their capacity to subvert them. Hijacking histone variants and their chaperones is emerging as a common means to disrupt homeostasis across a wide range of cancers, particularly solid tumours. Here we discuss histone variants and histone chaperones as tumour-promoting or tumour-suppressive players in the pathogenesis of cancer.

Identification of key genes related to heart failure by analysis of expression profiles

Introduction

To elucidate the candidate biomarkers involved in the pathogenesis process of heart failure (HF) via analysis of differentially expressed genes (DEGs) of the dataset from the Gene Expression Omnibus (GEO).

Material and methods

The GSE76701 gene expression profiles regarding the HF and control subjects were respectively analysed. Briefly, DEGs were firstly identified and subjected to Cytoscape plug-in ClueGO + CluePedia and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. A protein-protein interaction (PPI) network was then built to analyse the interaction between DEGs, followed by the construction of an interaction network by combining with hub genes with the targeted miRNA genes of DEGs to identify the key molecules of HF. In addition, potential drugs targeting key DEGs were sought using the drug-gene interaction database (DGIdb), and a drug-mRNA-miRNA interaction network was also constructed.

Results

A total of 489 DEGs were verified between HF and control, which mainly enriched in type I interferon and leukocyte migration according to molecular function. Significantly increased levels of GAPDH, GALM1, MMP9, CCL5, and GNAL2 were found in the HF setting and were identified as the hub genes based on the PPI network. Furthermore, according to the drug-mRNA-miRNA network, FCGR2B, CCND1, and NF-κb, as well as corresponding miRNA-605-5p, miRNA-147a, and miRNA-671-5p were identified as the drug targets of HF.

Conclusions

The hub genes GAPDH, GALM1, MMP9, CCL5, and GNAL2 were significantly increased in HF. miRNA-605-5p, miRNA-147a, and miRNA-671-5p were predicted as the drug target-interacted gene-miRNA of HF.

MicroRNA as Epigenetic Modifiers in Endometrial Cancer: A Systematic Review

Simple Summary

Endometrial cancer (EC) is the 2nd most common gynecologic cancer worldwide. MicroRNAs (miRNAs) are small noncoding RNAs that contribute to epigenetic regulation. The objective of this systematic review is to summarize our current knowledge on the role of miRNAs in the epigenetic deregulation of tumor-related genes in EC. It includes all miRNAs reported to be involved in EC including their roles in DNA methylation and RNA-associated silencing. This systematic review should be useful for development of novel strategies to improve diagnosis and risk assessment as well as for new treatments aimed at miRNAs, their target genes or DNA methylation.

Abstract

The objective of this systematic review is to summarize our current knowledge on the influence of miRNAs in the epigenetic deregulation of tumor-related genes in endometrial cancer (EC). We conducted a literature search on the role of miRNAs in the epigenetic regulation of EC applying the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The following terms were used: microRNA, miRNA, miR, endometrial cancer, endometrium, epigenetic, epimutation, hypermethylation, lynch, deacetylase, DICER, novel biomarker, histone, chromatin. The miRNAs were classified and are presented according to their function (tumor suppressor or onco-miRNA), their targets (when known), their expression levels in EC tissue vs the normal surrounding tissue, and the degree of DNA methylation in miRNA loci and CpG sites. Data were collected from 201 articles, including 190 original articles, published between November 1, 2008 and September 30, 2020 identifying 313 different miRNAs implicated in epigenetic regulation of EC. Overall, we identified a total of 148 miRNAs with decreased expression in EC, 140 miRNAs with increased expression in EC, and 22 miRNAs with discordant expression levels. The literature implicated different epigenetic phenomena including altered miRNA expression levels (miR-182, -230), changes in the methylation of miRNA loci (miR-34b, -129-2, -130a/b, -152, -200b, -625) and increased/decreased methylation of target genes (miR-30d,-191). This work provides an overview of all miRNAs reported to be involved in epigenetic regulation in EC including DNA methylation and RNA-associated silencing. These findings may contribute to novel strategies in diagnosis, risk assessment, and treatments aimed at miRNAs, their target genes or DNA methylation.

Insulin Resistance and Endometrial Cancer: Emerging Role for microRNA

Endometrial cancer (EC) remains one of the most common cancers of the female reproductive system. Epidemiological and clinical data implicate insulin resistance (IR) and its accompanying hyperinsulinemia as key factors in the development of EC. MicroRNAs (miRNAs) are short molecules of non-coding endogenous RNA that function as post-transcriptional regulators. Accumulating evidence has shown that the miRNA expression pattern is also likely to be associated with EC risk factors. The aim of this work was the verification of the relationships between IR, EC, and miRNA, and, as based on the literature data, elucidation of miRNA's potential utility for EC prevention in IR patients. The pathways affected in IR relate to the insulin receptors, insulin-like growth factors and their receptors, insulin-like growth factor binding proteins, sex hormone-binding globulin, and estrogens. Herein, we present and discuss arguments for miRNAs as a plausible molecular link between IR and EC development. Specifically, our careful literature search indicated that dysregulation of at least 13 miRNAs has been ascribed to both conditions. We conclude that there is a reasonable possibility for miRNAs to become a predictive factor of future EC in IR patients.

Identification of early stage recurrence endometrial cancer biomarkers using bioinformatics tools

Endometrial cancer (EC) is the sixth most common cancer in women worldwide. Early diagnosis is critical in recurrent EC management. The present study aimed to identify biomarkers of EC early recurrence using a workflow that combined text and data mining databases (DisGeNET, Gene Expression Omnibus), a prioritization algorithm to select a set of putative candidates (ToppGene), protein-protein interaction network analyses (Search Tool for the Retrieval of Interacting Genes, cytoHubba), association analysis of selected genes with clinicopathological parameters, and survival analysis (Kaplan-Meier and Cox proportional hazard ratio analyses) using a The Cancer Genome Atlas cohort. A total of 10 genes were identified, among which the targeting protein for Xklp2 (TPX2) was the most promising independent prognostic biomarker in stage I EC. TPX2 expression (mRNA and protein) was higher (P<0.0001 and P<0.001, respectively) in ETS variant transcription factor 5-overexpressing Hec1a and Ishikawa cells, a previously reported cell model of aggressive stage I EC. In EC biopsies, TPX2 mRNA expression levels were higher (P<0.05) in high grade tumors (grade 3) compared with grade 1–2 tumors (P<0.05), in tumors with deep myometrial invasion (>50% compared with <50%; P<0.01), and in intermediate-high recurrence risk tumors compared with low-risk tumors (P<0.05). Further validation studies in larger and independent EC cohorts will contribute to confirm the prognostic value of TPX2.

Identification of Potential Crucial Genes Associated With the Pathogenesis and Prognosis of Endometrial Cancer

Background and Objective

Endometrial cancer (EC) is a common gynecological malignancy worldwide. Despite advances in the development of strategies for treating EC, prognosis of the disease remains unsatisfactory, especially for advanced EC. The aim of this study was to identify novel genes that can be used as potential biomarkers for identifying the prognosis of EC and to construct a novel risk stratification using these genes.

Methods and Results

An mRNA sequencing dataset, corresponding survival data and expression profiling of an array of EC patients were obtained from The Cancer Genome Atlas and Gene Expression Omnibus, respectively. Common differentially expressed genes (DEGs) were identified based on sequencing and expression as given in the profiling dataset. Pathway enrichment analysis of the DEGs was performed using the Database for Annotation, Visualization, and Integrated Discovery. The protein-protein interaction network was established using the string online database in order to identify hub genes. Univariate and multivariable Cox regression analyses were used to screen prognostic DEGs and to construct a prognostic signature. Survival analysis based on the prognostic signature was performed on TCGA EC dataset. A total of 255 common DEGs were found and 11 hub genes (TOP2A, CDK1, CCNB1, CCNB2, AURKA, PCNA, CCNA2, BIRC5, NDC80, CDC20, and BUB1BA) that may be closely related to the pathogenesis of EC were identified. A panel of 7 DEG signatures consisting of PHLDA2, GGH, ESPL1, FAM184A, KIAA1644, ESPL1, and TRPM4 were constructed. The signature performed well for prognosis prediction (p < 0.001) and time-dependent receiver-operating characteristic (ROC) analysis displayed an area under the curve (AUC) of 0.797, 0.734, 0.729, and 0.647 for 1, 3, 5, and 10-year overall survival (OS) prediction, respectively.

Conclusion

This study identified potential genes that may be involved in the pathophysiology of EC and constructed a novel gene expression signature for EC risk stratification and prognosis prediction.