Context. Kuntai capsule (KTC), a proprietary Chinese medicine, have been used for the treatment of polycystic ovary syndrome (PCOS). Objective. This study elucidates the potential therapeutic targets and molecular mechanisms of KTC in the treatment of PCOS. Materials and Methods. Using the Traditional Chinese Medicine System Pharmacology Database and Analysis Platform (TCMSP), the active ingredients and potential targets of KTC were obtained. The Gene Expression Omnibus (GEO) database was used to find differentially expressed genes (DEGs) related to PCOS. Search the CTD, DisGeNet, genecards, NCBI, OMIM, and PharmGKB databases for therapeutic targets related to PCOS. The intersection of potential targets, DEGs, and therapeutic targets was submitted to perform bioinformatics analysis by R language. Finally, the analyses’ core targets and their corresponding active ingredients were molecularly docked. Results. 88 potential therapeutic targets of KTC for PCOS were discovered by intersecting the potential targets, DEGs, and therapeutic targets. According to bioinformatics analysis, the mechanisms of KTC treatment for PCOS could be linked to IL‐17 signaling route, p53 signaling pathway, HIF‐1 signaling pathway, etc. The minimal binding energies of the 5 core targets and their corresponding ingredients were all less than ‐6.5. Further research found that quercetin may replace KTC in the treatment of PCOS. Discussion and Conclusions. We explored the active ingredients and molecular mechanisms of KTC in the treatment of PCOS and found that quercetin may be the core ingredient of KTC in the treatment of PCOS.

Objectives: In this research, we aim to explore the bioinformatic mechanism of infertile endometriosis in order to identify new treatment targets and molecular mechanism. Methods: The Gene Expression Omnibus (GEO) database was used to download MRNA sequencing data from infertile endometriosis patients. The “limma” package in R software was used to find differentially expressed genes (DEGs). Weighted gene co-expression network analysis (WGCNA) was used to classify genes into modules, further obtained the correlation coefficient between the modules and infertility endometriosis. The intersection genes of the most disease-related modular genes and DEGs are called gene set 1. To clarify the molecular mechanisms and potential therapeutic targets for infertile endometriosis, we used Gene Ontology (GO), Kyoto Gene and Genome Encyclopedia (KEGG) enrichment, Protein-Protein Interaction (PPI) networks, and Gene Set Enrichment Analysis (GSEA) on these intersecting genes. We identified lncRNAs and miRNAs linked with infertility and created competing endogenous RNAs (ceRNA) regulation networks using the Human MicroRNA Disease Database (HMDD), mirTarBase database, and LncRNA Disease database. Results: Firstly, WGCNA enrichment analysis was used to examine the infertile endometriosis dataset GSE120103, and we discovered that the Meorangered1 module was the most significantly related with infertile endometriosis. The intersection genes were mostly enriched in the metabolism of different amino acids, the cGMP-PKG signaling pathway, and the cAMP signaling pathway according to KEGG enrichment analysis. The Meorangered1 module genes and DEGs were then subjected to bioinformatic analysis. The hub genes in the PPI network were performed KEGG enrichment analysis, and the results were consistent with the intersection gene analysis. Finally, we used the database to identify 13 miRNAs and two lncRNAs linked to infertility in order to create the ceRNA regulatory network linked to infertile endometriosis. Conclusion: In this study, we used a bioinformatics approach for the first time to identify amino acid metabolism as a possible major cause of infertility in patients with endometriosis and to provide potential targets for the diagnosis and treatment of these patients.

Ovarian cancer (OC) is the second leading cause of death in gynecological cancer. Multiple study have shown that the efficacy of tumor immunotherapy is related to tumor immune cell infiltration (ICI). However, so far, the Immune infiltration landscape of tumor microenvironment (TME) in OC has not been elucidated. In this study, We organized the transcriptome data of OC in the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, evaluated the patient’s TME information, and constructed the ICI scores to predict the clinical benefits of patients undergoing immunotherapy. Immune-related genes were further used to construct the prognostic model. After clustering analysis of ICI genes, we found that patients in ICI gene cluster C had the best prognosis, and their tumor microenvironment had the highest proportion of macrophage M1 and T cell follicular helper cells. This result was consistent with that of multivariate cox (multi-cox) analysis. The prognostic model constructed by immune-related genes had good predictive performance. By estimating Tumor mutation burden (TMB), we also found that there were multiple genes with statistically different mutation frequencies in the high and low ICI score groups. The model based on the ICI score may help to screen out patients who would benefit from immunotherapy. The immune-related genes screened may be used as biomarkers and therapeutic targets.

Endometriosis (EMs) is a common benign gynecological disease in women of childbearing age, which usually causes pelvic pain, secondary dysmenorrhea, and infertility. EMs has been linked to recurrent pregnancy loss (RPL) in epidemiological data. The relationship of both, however, remains unknown. The purpose of this study is to explore the underlying pathological mechanisms between EMs and RPL. We searched Gene Expression Omnibus (GEO) database to obtain omics data of EMs and RPL. Co-expression modules for EMs and RPL were investigated by using weighted gene co-expression network analysis (WGCNA). The intersections of gene modules with the strong correlation to EMs or RPL obtained by WGCNA analysis were considered as shared genes. MicroRNAs (miRNAs) and their corresponding target genes linked to EMs and RPL were found though the Human MicroRNA Disease Database (HMDD) and the miRTarbase database. Finally, we constructed miRNAs-mRNAs regulatory networks associated with the two disorders by using the intersection of previously obtained target genes and shared genes. We discovered as significant modules for EMs and RPL, respectively, by WGCNA. The energy metabolism might be the common pathogenic mechanism of EMs and RPL, according to the findings of a Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. We discovered several target genes that might be linked to these two disorders, as well as the potential mechanisms. RAB8B, GNAQ, H2AFZ, SUGT1, and LEO1 could be therapeutic candidates for RPL and EMs. The PI3K-Akt signaling pathway and platelet activation were potentially involved in the mechanisms of EM-induced RPL. Our findings for the first time revealed the underlying pathological mechanisms of EM-induced RPL and identified several useful biomarkers and potential therapeutic targets.

Patients with colonic adenocarcinoma (COAD) are at relatively high risk of SARS-CoV-2 infection. However, there is a lack of medical strategies to treat COVID-19/COAD comorbidity. Puerarin, a natural product, is a known antiviral, antitumor, and immunomodulatory effect. Therefore, we hypothesised that puerarin could be used to treat COVID-19/COAD patients. Based on network pharmacology and bioinformatics analysis, the potential targets and pharmacological mechanisms of puerarin in COVID-19/COAD were identified. By intersecting therapeutic target genes for puerarin, COVID-19-related genes and COAD-related genes, 42 target genes of puerarin that could potentially treat COVID-19/COAD comorbidity were obtained. By using the 42 potential target genes to construct the protein-protein interaction (PPI) network, we obtained five core target genes, namely RELA, BCL2, JUN, FOS, and MAPK1. The results of bioinformatics analysis revealed that puerarin could be able to treat COVID-19/COAD comorbidity through apoptosis, antiviral, antioxidant, NF-κB signaling pathway, MAPK signaling pathway, IL-17 signaling pathway, TNF signaling pathway, and HIF-1 signaling pathway etc. This study found that puerarin has the potential to treat COVID-19/COAD patients and that the therapeutic target genes obtained in the study may provide clues for the treatment of COVID19/COAD comorbidity.

Background: Angiogenesis is indispensable for the sustained survival and progression of both embryonic development and tumorigenesis. This intricate process is tightly regulated by a multitude of pro‐angiogenic genes. The presence of gene modules facilitating angiogenesis has been substantiated in both embryonic development and the context of tumor proliferation. However, it remains unresolved whether the pro‐angiogenic gene modules expressed during embryonic development also exist in tumors. Methods: This study performed a pan‐cancer single‐cell RNA sequencing (scRNA‐seq) analysis on samples from 332 patients across seven cancer types: thyroid carcinoma, lung cancer, breast cancer, hepatocellular carcinoma, colorectal cancer, ovarian carcinoma, and prostate adenocarcinoma. Data processing was carried out using the Seurat R package, with rigorous quality control to filter high‐quality cells and mitigate batch effects across datasets. We used principal component analysis (PCA), shared nearest neighbor graph‐based clustering, and Uniform Manifold Approximation and Projection (UMAP) to visualize cell types and identify distinct cell clusters. Myeloid cell subpopulations were further analyzed for the expression of embryonic pro‐angiogenic gene modules (EPGM) and tumor pro‐angiogenic gene modules (TPGM). Results: The analysis identified nine major cell types within the tumor microenvironment, with myeloid cells consistently exhibiting elevated expression of both tumor pro‐angiogenic gene modules (TPGM) and EPGM across all tumor types. In particular, myeloid cells, including macrophages and monocytes, showed high EPGM expression, indicating an active role of embryonic pro‐angiogenesis pathways in tumors. A subset analysis revealed 20 distinct myeloid subtypes with varying EPGM and TPGM expression across different cancers. Treatment and disease stage influenced these gene expressions, with certain subtypes, such as HSPAhi/STAT1+ macrophages in breast cancer, displaying reduced pro‐angiogenic gene activity post‐treatment. Conclusion: This study provides evidence that tumors may exploit EPGM to enhance vascularization and support sustained growth, as evidenced by the elevated EPGM expression in tumor‐associated myeloid cells. The consistent presence of EPGM in TAMs across multiple cancer types suggests a conserved mechanism wherein tumors harness embryonic angiogenic pathways to facilitate their progression. Distinct EPGM expression patterns in specific myeloid cell subsets indicate potential therapeutic targets, particularly in cases where EPGM activation contributes to resistance against anti‐angiogenic therapies. These findings shed new light on the molecular mechanisms underlying tumor angiogenesis and highlight the prognostic relevance of EPGM expression in cancer, underscoring its potential as a biomarker for clinical applications.