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Zhang Z, Singh SP. A Study on the Analysis of Important Gene Networks and Pathways Involved in Progression of Endometriosis to Ovarian Endometrioma Cyst. Appl Biochem Biotechnol 2024; 196:4352-4365. [PMID: 37947944 DOI: 10.1007/s12010-023-04778-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/31/2023] [Indexed: 11/12/2023]
Abstract
Endometriosis (EM) is a gynecological condition known by the manifestation of endometrium alike soft tissue external to the usual place affecting up to 10% of all womenfolk in the reproductively active stage. However, the pathological process of endometriosis is not identified fully. The study aims to investigate the genes associated with the progression of endometriosis and its pathways using bioinformatics tools and techniques. The gene expression profile of three sets was retrieved, and bioinformatics data analysis was carried out for the microarray samples using GEO, DAVID, and STICH. Differently expressed genes (DEGs) refer to genes that exhibit significant changes in their expression levels between different conditions or groups, such as between different cell types, treatments, disease states, or developmental stages. DEG was determined based on a significant cutoff resulting in 298 unique elements based on the GEO Venn diagram map. DAVID (database for annotation, visualization, and integrated discovery) helps understand the biological significance of the data by identifying overrepresented biological terms, pathways, and functional annotations among a set of genes or proteins of interest. DAVID analysis revealed positively and negatively associated genes and followed by target proteins. DAVID is helpful for getting results of molecular mechanisms and pathways associated with DEGs. The gene expression studies showed that the m-RNA expression of all the genes was upregulated in the PA1 cell line. The present study identified five genes (COMT, CYP19A1, GALT, LTA, and STAR) from 298 unique DEGs using microarray data analysis, and 5 protein targets were also identified that were linked with EM. The study concludes that this information may provide a bridging gap in understanding the progression of endometriosis.
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Affiliation(s)
- Zhiqiang Zhang
- Department of Obstetrics and Gynecology, Shanxi Provincial People's Hospital, Taiyuan, 030012, China
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Castro-Martínez JA, Vargas E, Díaz-Beltrán L, Esteban FJ. Comparative Analysis of Shapley Values Enhances Transcriptomics Insights across Some Common Uterine Pathologies. Genes (Basel) 2024; 15:723. [PMID: 38927658 PMCID: PMC11203383 DOI: 10.3390/genes15060723] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2024] [Revised: 05/20/2024] [Accepted: 05/29/2024] [Indexed: 06/28/2024] Open
Abstract
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.
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Affiliation(s)
- José A. Castro-Martínez
- Systems Biology Unit, Department of Experimental Biology, Faculty of Experimental Sciences, University of Jaén, 23071 Jaén, Spain; (J.A.C.-M.); (E.V.); (L.D.-B.)
| | - Eva Vargas
- Systems Biology Unit, Department of Experimental Biology, Faculty of Experimental Sciences, University of Jaén, 23071 Jaén, Spain; (J.A.C.-M.); (E.V.); (L.D.-B.)
| | - Leticia Díaz-Beltrán
- Systems Biology Unit, Department of Experimental Biology, Faculty of Experimental Sciences, University of Jaén, 23071 Jaén, Spain; (J.A.C.-M.); (E.V.); (L.D.-B.)
- Clinical Research Unit, Department of Medical Oncology, University Hospital of Jaén, 23007 Jaén, Spain
| | - Francisco J. Esteban
- Systems Biology Unit, Department of Experimental Biology, Faculty of Experimental Sciences, University of Jaén, 23071 Jaén, Spain; (J.A.C.-M.); (E.V.); (L.D.-B.)
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Samare-Najaf M, Razavinasab SA, Samareh A, Jamali N. Omics-based novel strategies in the diagnosis of endometriosis. Crit Rev Clin Lab Sci 2024; 61:205-225. [PMID: 37878077 DOI: 10.1080/10408363.2023.2270736] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2023] [Accepted: 10/10/2023] [Indexed: 10/26/2023]
Abstract
Endometriosis, an enigmatic and chronic disorder, is considered a debilitating condition despite being benign. Globally, this gynecologic disorder affects up to 10% of females of reproductive age, impacting almost 190 million individuals. A variety of genetic and environmental factors are involved in endometriosis development, hence the pathophysiology and etiology of endometriosis remain unclear. The uncertainty of the etiology of the disease and its complexity along with nonspecific symptoms have led to misdiagnosis or lack of diagnosis of affected people. Biopsy and laparoscopy are referred to as the gold standard for endometriosis diagnosis. However, the invasiveness of the procedure, the unnecessary operation in disease-free women, and the dependence of the reliability of diagnosis on experience in this area are considered the most significant limitations. Therefore, continuous studies have attempted to offer a noninvasive and reliable approach. The recent advances in modern technologies have led to the generation of large-scale biological data sets, known as -omics data, resulting in the proceeding of the -omics century in biomedical sciences. Thereby, the present study critically reviews novel and noninvasive biomarkers that are based on -omics approaches from 2020 onward. The findings reveal that biomarkers identified based on genomics, epigenomics, transcriptomics, proteomics, and metabolomics are potentially able to diagnose endometriosis, predict prognosis, and stage patients, and potentially, in the near future, a multi-panel of these biomarkers will generate clinical benefits.
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Affiliation(s)
- Mohammad Samare-Najaf
- Blood Transfusion Research Center, High Institute for Research and Education in Transfusion Medicine, Kerman Regional Blood Transfusion Center, Kerman, Iran
- Biochemistry Department, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran
| | | | - Ali Samareh
- Department of Clinical Biochemistry, School of Medicine, Kerman University of Medical Sciences, Kerman, Iran
| | - Navid Jamali
- Department of Laboratory Sciences, Sirjan School of Medical Sciences, Sirjan, Iran
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Szymański M, Bonowicz K, Antosik P, Jerka D, Głowacka M, Soroka M, Steinbrink K, Kleszczyński K, Gagat M. Role of Cyclins and Cytoskeletal Proteins in Endometriosis: Insights into Pathophysiology. Cancers (Basel) 2024; 16:836. [PMID: 38398227 PMCID: PMC10886501 DOI: 10.3390/cancers16040836] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Revised: 01/21/2024] [Accepted: 02/16/2024] [Indexed: 02/25/2024] Open
Abstract
Endometriosis is a gynecological condition where endometrium-like tissue grows outside the uterus, posing challenges in understanding and treatment. This article delves into the deep cellular and molecular processes underlying endometriosis, with a focus on the crucial roles played by cyclins and cytoskeletal proteins in its pathogenesis, particularly in the context of Epithelial-Mesenchymal Transition (EMT). The investigation begins by examining the activities of cyclins, elucidating their diverse biological roles such as cell cycle control, proliferation, evasion of apoptosis, and angiogenesis among ectopic endometrial cells. A comprehensive analysis of cytoskeletal proteins follows, emphasizing their fundamental biological roles and their specific significance to endometriotic cell features. This review sheds light on the interconnected pathways through which cyclins and cytoskeletal proteins converge, contributing to the genesis and progression of endometriosis. Understanding these molecular complexities not only provides insight into the underlying causes of the disease but also holds promise for the development of specific therapeutic approaches, ushering in a new era in the management of this devastating disorder.
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Affiliation(s)
- Marcin Szymański
- Department of Histology and Embryology, Collegium Medicum in Bydgoszcz, Nicolaus Copernicus University in Torun, 85-092 Bydgoszcz, Poland; (M.S.); (K.B.); (D.J.)
| | - Klaudia Bonowicz
- Department of Histology and Embryology, Collegium Medicum in Bydgoszcz, Nicolaus Copernicus University in Torun, 85-092 Bydgoszcz, Poland; (M.S.); (K.B.); (D.J.)
- Faculty of Medicine, Collegium Medicum, Mazovian Academy in Płock, 08-110 Płock, Poland; (M.G.); (M.S.)
| | - Paulina Antosik
- Department of Clinical Pathomorphology, Collegium Medicum in Bydgoszcz, Nicolaus Copernicus University in Torun, 85-094 Bydgoszcz, Poland;
| | - Dominika Jerka
- Department of Histology and Embryology, Collegium Medicum in Bydgoszcz, Nicolaus Copernicus University in Torun, 85-092 Bydgoszcz, Poland; (M.S.); (K.B.); (D.J.)
| | - Mariola Głowacka
- Faculty of Medicine, Collegium Medicum, Mazovian Academy in Płock, 08-110 Płock, Poland; (M.G.); (M.S.)
| | - Małgorzata Soroka
- Faculty of Medicine, Collegium Medicum, Mazovian Academy in Płock, 08-110 Płock, Poland; (M.G.); (M.S.)
| | - Kerstin Steinbrink
- Department of Dermatology, University of Münster, Von-Esmarch-Str. 58, 48149 Münster, Germany; (K.S.); (K.K.)
| | - Konrad Kleszczyński
- Department of Dermatology, University of Münster, Von-Esmarch-Str. 58, 48149 Münster, Germany; (K.S.); (K.K.)
| | - Maciej Gagat
- Department of Histology and Embryology, Collegium Medicum in Bydgoszcz, Nicolaus Copernicus University in Torun, 85-092 Bydgoszcz, Poland; (M.S.); (K.B.); (D.J.)
- Faculty of Medicine, Collegium Medicum, Mazovian Academy in Płock, 08-110 Płock, Poland; (M.G.); (M.S.)
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Zhou D, Cao S, Xie H. Research on Predicting the Occurrence of Hepatocellular Carcinoma Based on Notch Signal-Related Genes Using Machine Learning Algorithms. THE TURKISH JOURNAL OF GASTROENTEROLOGY : THE OFFICIAL JOURNAL OF TURKISH SOCIETY OF GASTROENTEROLOGY 2023; 34:760-770. [PMID: 37051625 PMCID: PMC10441146 DOI: 10.5152/tjg.2023.22357] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Accepted: 07/12/2022] [Indexed: 04/14/2023]
Abstract
BACKGROUND/AIMS Hepatocellular carcinoma, a highly malignant tumor, is difficult to diagnose, treat, and predict the prognosis. Notch signaling pathway can affect hepatocellular carcinoma. We aimed to predict the occurrence of hepatocellular carcinoma based on Notch signal-related genes using machine learning algorithms. MATERIALS AND METHODS We downloaded hepatocellular carcinoma data from the Cancer Genome Atlas and Gene Expression Omnibus databases and used machine learning methods to screen the hub Notch signal-related genes. Machine learning classification was used to construct a prediction model for the classification and diagnosis of hepatocellular carcinoma cancer. Bioinformatics methods were applied to explore the expression of these hub genes in the hepatocellular carcinoma tumor immune microenvironment. RESULTS We identified 4 hub genes, namely, LAMA4, POLA2, RAD51, and TYMS, which were used as the final variables, and found that AdaBoostClassifie was the best algorithm for the classification and diagnosis model of hepatocellular carcinoma. The area under curve, accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and F1 score of this model in the training set were 0.976, 0.881, 0.877, 0.977, 0.996, 0.500, and 0.932; respectively. The area under curves were 0.934, 0.863, 0.881, 0.886, 0.981, 0.489, and 0.926. The area under curve in the external validation set was 0.934. Immune cell infiltration was related to the expression of 4 hub genes. Patients in the low-risk group of hepatocellular carcinoma were more likely to have an immune escape. CONCLUSION The Notch signaling pathway was closely related to the occurrence and development of hepatocellular carcinoma. The hepatocellular carcinoma classification and diagnosis model established based on this had a high degree of reliability and stability.
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Affiliation(s)
- Dingzhong Zhou
- Department of Interventional Vascular Surgery, Affiliated Hospital (Clinical College) of Xiangnan University, Chenzhou, P. R. China
- Key Laboratory of Medical Imaging and Artifical Intelligence of Hunan Province, Chenzhou, P. R. China
| | - Sujuan Cao
- Department of Oncology, Affiliated Hospital (Clinical College) of Xiangnan University, Chenzhou, P. R. China
| | - Hui Xie
- Key Laboratory of Medical Imaging and Artifical Intelligence of Hunan Province, Chenzhou, P. R. China
- Department of Radiation Oncology, Affiliated Hospital (Clinical College) of Xiangnan University, Chenzhou, P. R. China
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Wang Z, Liu J, Li M, Lian L, Cui X, Ng TW, Zhu M. Integrated bioinformatics analysis uncovers characteristic genes and molecular subtyping system for endometriosis. Front Pharmacol 2022; 13:932526. [PMID: 36059959 PMCID: PMC9428290 DOI: 10.3389/fphar.2022.932526] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Accepted: 06/27/2022] [Indexed: 11/13/2022] Open
Abstract
Objective: Endometriosis is a chronic inflammatory estrogen-dependent disease with the growth of endometrial tissues outside the uterine cavity. Nevertheless, the etiology of endometriosis is still unclear. Integrated bioinformatics analysis was implemented to reveal the molecular mechanisms underlying this disease.Methods: A total of four gene expression datasets (GSE7305, GSE11691, GSE23339, and GSE25628) were retrieved from the GEO, which were merged into a meta-dataset, followed by the removal of batch effects via the sva package. Weighted gene co-expression network analysis (WGCNA) was implemented, and endometriosis-related genes were screened under normal and endometriosis conditions. Thereafter, characteristic genes were determined via Lasso analysis. The diagnostic performance was estimated via receiver operating characteristic curves, and epigenetic and post-transcriptional modifications were analyzed. Small molecular compounds were predicted. Unsupervised clustering analysis was conducted via non-negative matrix factorization algorithm. The enriched pathways were analyzed via gene set enrichment analysis or GSVA. Immune features were evaluated according to immune-checkpoints, HLA, receptors, chemokines, and immune cells.Results: In total, four characteristic genes (BGN, AQP1, ELMO1, and DDR2) were determined for endometriosis, all of which exhibited the favorable efficacy in diagnosing endometriosis. Their aberrant levels were modulated by epigenetic and post-transcriptional modifications. In total, 51 potential drugs were predicted against endometriosis. The characteristic genes exhibited remarkable associations with immunological function. Three subtypes were classified across endometriosis, with different mechanisms and immune features.Conclusion: Our study reveals the characteristic genes and novel molecular subtyping of endometriosis, contributing to the early diagnosis and intervention in endometriosis.
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Affiliation(s)
| | | | | | | | - Xiaojie Cui
- *Correspondence: Maoshu Zhu, Tai-Wei Ng, ; Xiaojie Cui,
| | - Tai-Wei Ng
- *Correspondence: Maoshu Zhu, Tai-Wei Ng, ; Xiaojie Cui,
| | - Maoshu Zhu
- *Correspondence: Maoshu Zhu, Tai-Wei Ng, ; Xiaojie Cui,
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ASPN Is a Potential Biomarker and Associated with Immune Infiltration in Endometriosis. Genes (Basel) 2022; 13:genes13081352. [PMID: 36011263 PMCID: PMC9407481 DOI: 10.3390/genes13081352] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2022] [Revised: 07/20/2022] [Accepted: 07/25/2022] [Indexed: 11/16/2022] Open
Abstract
Objective: Endometriosis is a benign gynecological disease characterized by distant metastasis. Previous studies have discovered abnormal numbers and function of immune cells in endometriotic lesions. We aimed to find potential biomarkers of endometriosis and to explore the relationship between ASPN and the immune microenvironment of endometriosis. Methods: We obtained the GSE141549 and GSE7305 datasets containing endometriosis and normal endometrial samples from the Gene Expression Omnibus database (GEO). In the GSE141549 dataset, differentially expressed genes (DEGs) were found. The Least Absolute Shrinkage and Selection Operator (Lasso) regression and generalized linear models (GLMs) were used to screen new biomarkers. The expression levels and diagnostic utility of biomarkers were assessed in GSE7305, and biomarker expression levels were further validated using qRT-PCR and western blot. We identified DEGs between high and low expression groups of key biomarkers. Enrichment analysis was carried out to discover the target gene’s biological function. We analyzed the relationship between key biomarker expression and patient clinical features. Finally, the immune cells that infiltrate endometriosis were assessed using the Microenvironment Cell Population-Counter (MCP-counter), and the correlation of biomarker expression with immune cell infiltration and immune checkpoints genes was studied. Results: There were a total of 38 DEGs discovered. Two machine learning techniques were used to identify 10 genes. Six biomarkers (SCG2, ASPN, SLIT2, GEM, EGR1, and FOS) had good diagnostic efficiency (AUC > 0.7) by internal and external validation. We excluded previously reported related genes (SLIT2, EGR1, and FOS). ASPN was the most significantly differentially expressed biomarker between normal and ectopic endometrial tissues, as verified by qPCR. The western blot assay revealed a significant upregulation of ASPN expression in endometriotic tissues. The investigation for DEGs in the ASPN high- and low-expression groups revealed that the DEGs were particularly enriched in extracellular matrix tissue, vascular smooth muscle contraction, cytokine interactions, the calcium signaling pathway, and the chemokine signaling pathway. High ASPN expression was related to r-AFS stage (p = 0.006), age (p = 0.03), and lesion location (p < 0.001). Univariate and multivariate logistic regression analysis showed that ASPN expression was an independent influencing factor in patients with endometriosis. Immune cell infiltration analysis revealed a significant increase in T-cell, B-cell, and fibroblast infiltration in endometriosis lesions; cytotoxic lymphocyte, NK-cell, and endothelial cell infiltration were reduced. Additionally, the percentage of T cells, B cells, fibroblasts, and endothelial cells was favorably connected with ASPN expression, while the percentage of cytotoxic lymphocytes and NK cells was negatively correlated. Immune checkpoint gene (CTLA4, LAG3, CD27, CD40, and ICOS) expression and ASPN expression were positively associated. Conclusions: Increased expression of ASPN is associated with immune infiltration in endometriosis, and ASPN can be used as a diagnostic biomarker as well as a potential immunotherapeutic target in endometriosis.
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Chen S, Chai X, Wu X. Bioinformatical analysis of the key differentially expressed genes and associations with immune cell infiltration in development of endometriosis. BMC Genom Data 2022; 23:20. [PMID: 35303800 PMCID: PMC8932180 DOI: 10.1186/s12863-022-01036-y] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2021] [Accepted: 03/02/2022] [Indexed: 12/11/2022] Open
Abstract
Background This study explored the key genes related to immune cell infiltration in endometriosis. Results The Gene Expression Omnibus (GEO) datasets (GSE7305, GSE7307, and GSE11691), containing a total of 37 endometriosis and 42 normal tissues, were retrieved and analyzed to determine the differentially expressed genes (DEGs). Gene ontology (GO) annotations and Kyoto Encyclopedia of Genes (KEGG) analysis were performed to identify the pathways that were significantly enriched. The xCell software was used to analyze immune cell infiltration and correlation analyses were performed to uncover the relationship between key genes and immune cells. The analysis identified 1031 DEGs (581 upregulated and 450 downregulated DEGs), while GO analysis revealed altered extracellular matrix organization, collagen-containing extracellular matrix, and glycosaminoglycan binding and KEGG enrichment showed genes related to metabolic pathways, pathways in cancer, phosphatidylinositol 3-kinase-protein kinase B (PI3K-Akt) signaling, proteoglycans in cancer, and the mitogen-activated protein kinase (MAPK) signaling pathway. Furthermore, the protein–protein interaction network revealed 10 hub genes, i.e., IL6, FN1, CDH1, CXCL8, IGF1, CDK1, PTPRC, CCNB1, MKI67, and ESR1. The xCell analysis identified immune cells with significant changes in all three datasets, including CD4+ and CD8+ T cells, CD8+ Tem, eosinophils, monocytes, Th1 cells, memory B-cells, activated dendritic cells (aDCs), and plasmacytoid dendritic cells (pDCs). These 10 hub genes were significantly associated with at least three types of immune cells. Conclusions Aberrant gene expression was related to abnormal infiltration of different immune cells in endometriosis and was associated with endometriosis development by affecting the tissue microenvironment and growth of ectopic endometrial cells.
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Affiliation(s)
- Shengnan Chen
- Department of Obstetrics and Gynecology, The Second Xiangya Hospital of Central South University, Changsha, 410011, China
| | - Xiaoshan Chai
- Department of Obstetrics and Gynecology, The Second Xiangya Hospital of Central South University, Changsha, 410011, China
| | - Xianqing Wu
- Department of Obstetrics and Gynecology, The Second Xiangya Hospital of Central South University, Changsha, 410011, China.
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