Investigating gene signatures associated with immunity in colon adenocarcinoma to predict the immunotherapy effectiveness using NFM and WGCNA algorithms.

Colon adenocarcinoma (COAD), a frequently encountered and highly lethal malignancy of the digestive system, has been the focus of intensive research regarding its prognosis. The intricate immune microenvironment plays a pivotal role in the pathological progression of COAD; nevertheless, the underlying molecular mechanisms remain incompletely understood. This study aims to explore the immune gene expression patterns in COAD, construct a robust prognostic model, and delve into the molecular mechanisms and potential therapeutic targets for COAD liver metastasis, thereby providing critical support for individualized treatment strategies and prognostic evaluation. Initially, we curated a comprehensive dataset by screening 2600 immune-related genes (IRGs) from the ImmPort and InnateDB databases, successfully obtaining a rich data resource. Subsequently, the COAD patient cohort was classified using the non-negative matrix factorization (NMF) algorithm, enabling accurate categorization. Continuing on, utilizing the weighted gene co-expression network analysis (WGCNA) method, we analyzed the top 5000 genes with the smallest p-values among the differentially expressed genes (DEGs) between immune subtypes. Through this rigorous screening process, we identified the gene modules with the strongest correlation to the COAD subpopulation, and the intersection of genes in these modules with DEGs (COAD vs COAD vs Normal colon tissue) is referred to as Differentially Expressed Immune Genes Associated with COAD (DEIGRC). Employing diverse bioinformatics methodologies, we successfully developed a prognostic model (DPM) consisting of six genes derived from the DEIGRC, which was further validated across multiple independent datasets. Not only does this predictive model accurately forecast the prognosis of COAD patients, but it also provides valuable insights for formulating personalized treatment regimens. Within the constructed DPM, we observed a downregulation of CALB2 expression levels in COAD tissues, whereas NOXA1, KDF1, LARS2, GSR, and TIMP1 exhibited upregulated expression levels. These genes likely play indispensable roles in the initiation and progression of COAD and thus represent potential therapeutic targets for patient management. Furthermore, our investigation into the molecular mechanisms and therapeutic targets for COAD liver metastasis revealed associations with relevant processes such as fat digestion and absorption, cancer gene protein polysaccharides, and nitrogen metabolism. Consequently, genes including CAV1, ANXA1, CPS1, EDNRA, and GC emerge as promising candidates as therapeutic targets for COAD liver metastasis, thereby providing crucial insights for future clinical practices and drug development. In summary, this study uncovers the immune gene expression patterns in COAD, establishes a robust prognostic model, and elucidates the molecular mechanisms and potential therapeutic targets for COAD liver metastasis, thereby possessing significant theoretical and clinical implications. These findings are anticipated to offer substantial support for both the treatment and prognosis management of COAD patients.

Autophagy in Disease Onset and Progression.

Autophagy is a biological phenomenon whereby components of cells can self-degrade using autophagosomes. During this process, cells can clear dysfunctional organelles or unwanted elements. Autophagy can recycle unnecessary biomolecules into new components or sometimes, even destroy the cells themselves. This cellular process was first observed in 1962 by Keith R. Porter et al. Since then, autophagy has been studied for over 60 years, and much has been learned on the topic. Nevertheless, the process is still not fully understood. It has been proven, for example, that autophagy can be a positive force for maintaining good health by removing older or damaged cells. By contrast, autophagy is also involved in the onset and progression of various conditions caused by pathogenic infections. These diseases generally involve several important organs in the human body, including the liver, kidney, heart, and central nervous system. The regulation of the defects of autophagy defects may potentially be used to treat some diseases. This review comprehensively discusses recent research frontiers and topics of interest regarding autophagy-related diseases.

Explore the active ingredients and potential mechanisms of JianPi QingRe HuaYu Methods in the treatment of gastric inflammation-cancer transformation by network pharmacology and experimental validation.

BACKGROUND: JianPi QingRe HuaYu Methods (JQH) have been long used to treat chronic atrophic gastritis (CAG) and precancerous lesions of gastric cancer (PLGC). However, whether JQH can inhibit the transformation of gastritis to gastric cancer (GC) remains unclear. METHODS: Herein, we first retrieved the active ingredients and targets of JQH from the TCMSP database and the targets related to the gastric inflammation-cancer transformation from public databases. Differentially expressed genes (DEGs) related to gastric inflammation-cancer transformation were identified from the Gene Expression Omnibus (GEO) database. Then, we obtained the potential therapeutic targets of JQH in treating gastric inflammation-cancer transformation by intersecting drugs and disease targets. The Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and protein-protein interaction (PPI) analyses of the potential therapeutic targets were conducted using R software. Next, we conducted molecular docking and in vitro experiments to validate our results. RESULTS: We obtained 214 potential therapeutic targets of JQH by intersecting drugs and disease targets. We found that the potential mechanisms of JQH in treating gastric inflammation-cancer transformation might be related to JAK-STAT, Wnt, p53 and VEGF signaling pathways. The molecular docking indicated that quercetin, as the main active ingredient of JQH, might inhibit gastric inflammation-cancer transformation by binding with specific receptors. Our experimental results showed that quercetin inhibited cells proliferation (P < 0.001), promoted cell apoptosis (P < 0.001), reduced the secretion of pro-inflammatory cytokines (P < 0.001) and promoted the secretion of anti-inflammatory cytokines (P < 0.001) in MNNG-induced GES-1 cells. Furthermore, quercetin inhibited cells proliferation (P < 0.001) and reduced mRNA and protein level of markers of PLGC (P < 0.001) in CDCA-induced GES-1 cells. CONCLUSION: These results provide the material basis and regulatory mechanisms of JQH in treating gastric inflammation-cancer transformation.

AGAP2-AS1 promotes the assembly of m6A methyltransferases and activation of the IL6/STAT3 pathway by binding with WTAP in the carcinogenesis of gastric cancer.

Owing to the lack of biomarkers for early diagnosis, gastric cancer (GC) is often associated with a poor prognosis. Thus, there is an urgent need to identify early molecular targets in GC. Dysregulated long noncoding RNAs (lncRNAs) have been evaluated by integrated bioinformatics analysis; and we investigate their specific role and potential mechanism via N6-methyladenosine (m6A) methylation modification in the carcinogenesis and progression of GC. In this study, we report upregulation of lncRNA AGAP2-AS1, activated by a gain of H3K4Me3, in GC tissues and cells. AGAP2-AS1 was linked to adverse prognosis in patients with GC. Functionally, AGAP2-AS1 knockdown inhibited cell proliferation and migration of GC cells. Mechanistically, AGAP2-AS1 bound WT1-associated protein (WTAP) to promote the formation of the WTAP/methyltransferase-like 3 (METTL3)/METTL14 m6A methyltransferase complex. AGAP2-AS1 stabilized signal transducer and activator of transcription 3 (STAT3) mRNA in an m6A-dependent manner and, thus, activated the interleukin 6 (IL6)/STAT3 pathway. Importantly, activation of the AGAP2-AS1/WTAP/STAT3 pathways promoted cell proliferation and migration in GC. Collectively, the present findings revealed a novel regulatory relationship between lncRNA and m6A modification. Furthermore, targeting the AGAP2-AS1/WTAP/STAT3 axis may be a promising strategy for the inhibition of inflammation-mediated carcinogenesis and progression in GC.

Identification of berberine as a potential therapeutic strategy for kidney clear cell carcinoma and COVID-19 based on analysis of large-scale datasets.

Background: Regarding the global coronavirus disease 2019 (COVID)-19 pandemic, kidney clear cell carcinoma (KIRC) has acquired a higher infection probability and may induce fatal complications and death following COVID-19 infection. However, effective treatment strategies remain unavailable. Berberine exhibits significant antiviral and antitumour effects. Thus, this study aimed to provide a promising and reliable therapeutic strategy for clinical decision-making by exploring the therapeutic mechanism of berberine against KIRC/COVID-19. Methods: Based on large-scale data analysis, the target genes, clinical risk, and immune and pharmacological mechanisms of berberine against KIRC/COVID-19 were systematically investigated. Results: In total, 1,038 and 12,992 differentially expressed genes (DEGs) of COVID-19 and KIRC, respectively, were verified from Gene Expression Omnibus and The Cancer Genome Atlas databases, respectively, and 489 berberine target genes were obtained from official websites. After intersecting, 26 genes were considered potential berberine therapeutic targets for KIRC/COVID-19. Berberine mechanism of action against KIRC/COVID-19 was revealed by protein-protein interaction, gene ontology, and Kyoto Encyclopedia of Genes and Genomes with terms including protein interaction, cell proliferation, viral carcinogenesis, and the PI3K/Akt signalling pathway. In COVID-19 patients, ACOX1, LRRK2, MMP8, SLC1A3, CPT1A, H2AC11, H4C8, and SLC1A3 were closely related to disease severity, and the general survival of KIRC patients was closely related to ACOX1, APP, CPT1A, PLK1, and TYMS. Additionally, the risk signature accurately and sensitively depicted the overall survival and patient survival status for KIRC. Numerous neutrophils were enriched in the immune system of COVID-19 patients, and the lives of KIRC patients were endangered due to significant immune cell infiltration. Molecular docking studies indicated that berberine binds strongly to target proteins. Conclusion: This study demonstrated berberine as a potential treatment option in pharmacological, immunological, and clinical practice. Moreover, its therapeutic effects may provide potential and reliable treatment options for patients with KIRC/COVID-19.

Identification of gene signatures related to hypoxia and angiogenesis in pancreatic cancer to aid immunotherapy and prognosis.

Background: One of the most diverse tumors is pancreatic cancer (PC), which makes predicting the prognosis challenging. PC development is directly related to hypoxia, angiogenesis, and immunotherapy. It is still unclear how the three features are related. Methods: The Genotype-Tissue Expression (GTEx) and the Cancer Genome Atlas (TCGA) database were employed to obtain sequencing data for healthy pancreatic tissues and PC tissues, respectively. According to the constructed hypoxic prognostic model (HPM) and angiogenic prognostic model (APM), 4 subtypes of PC were identified. Hypoxia and angiogenesis prognostic model (HAPM) was established based on differentially expressed genes (DEGs) between high-angiogenesis/high-hypoxia (HH) and low-angiogenesis/low-hypoxia (LL) subgroups. Base on the median risk score, PC patients were separated into high-risk and low-risk groups, and clinical traits, prognosis, percentage of immune cell infiltration, PD-1 expression, and the fraction of T-cell depletion were compared between the groups. Finally, the predictive accuracy of the tumor immune dysfunction and rejection (TIDE) and tumor inflammatory signature (TIS) models, as well as HAPM, was compared. Result: We analyzed the mRNA sequencing data from 178 PC tissues and 171 normal pancreatic tissues to obtain 9527 DEGs. We discovered 200 genes linked with hypoxia and 36 genes involved with angiogenesis through the literature. We found the core genes related with hypoxia and angiogenesis in PC by intersecting the DEGs of the HH and LL subgroups with those of PC via WGCNA. IL-17 signaling pathway, ECM-receptor interactions, cytokine receptor interactions, etc. were all enriched in the Kyoto Encyclopedia of Genes and Genomes (KEGG) results of core genes. HAPM has good predictive efficiency, according to an evaluation of KM survival curves and ROC curves. The external dataset also validated the model's ability to anticipate outcomes. Patients in the high- and low-risk groups were compared for PD1 expression and T-cell exclusion scores, which suggested that the model might be used to forecast which PC patients might benefit from immunotherapy. Conclusions: The probable molecular processes connecting hypoxia and angiogenesis are described in this work, and a model is developed that may be utilized to forecast the prognosis for PC patients and the benefits of immunotherapy.

Shentao Ruangan formula promotes apoptosis via the E2F2-p53 pathway in hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) is a malignant tumor with high morbidity and mortality rates. E2F2 is an independent predictor of poor prognosis in HCC; however, The mechanism by which E2F2 promotes the progression of HCC remains unclear. The Shentao Ruangan (STR) formula exhibits antitumor efficacy against HCC; however, the underlying antitumor mechanisms remain unknown. PURPOSE: To explore the regulatory effect of E2F2 on the p53 signaling pathway and reveal the role and mechanism of STR in promoting cell apoptosis via the E2F2-p53 signaling pathway in HCC. METHODS: E2F2 overexpression or silencing by lentivirus in HepG2 cells were used to explore their influence on apoptosis and the p53 pathway. An H22 tumor-bearing mice model was used to determine the therapeutic efficacy of STR and its effects on the E2F2-p53 pathway. STR-mediated serum (STR-MS) was prepared, and its chemical constituents were identified using mass spectrometry. The effects of STR-MS on viability and apoptosis of HepG2 cells and the E2F2-p53 pathway were investigated and validated using rescue experiments. RESULTS: E2F2 overexpression significantly inhibited apoptosis and the p53 pathway in HepG2 cells, whereas E2F2-silenced HepG2 cells showed the reverse. This increased apoptosis was rescued by the addition of a p53 inhibitor (PFT-α) to E2F2-silenced HepG2 cells. In vivo, high doses of STR could remarkably inhibit the growth of xenografts, promote the apoptosis of hepatoma cells, downregulate E2F2, and activate the p53-dependent mitochondrial apoptotic pathway with good safety. In vitro, STR-MS exhibited similar effectiveness, and the best effect was achieved at 30% STR-MS concentration for 48 h. When 30% STR-MS was added to E2F2-overexpressing cells, the increased apoptosis and expression of key proteins in the p53-dependent mitochondrial apoptosis pathway were significantly rescued. CONCLUSION: Our findings demonstrate, for the first time, that E2F2 inhibits hepatoma cell apoptosis in a p53-dependent manner and that STR may promote apoptosis by regulating the E2F2-p53 pathway in HCC.

The Senescence-Related Signature Predicts Prognosis and Characterization of Tumor Microenvironment Infiltration in Pancreatic Cancer.

Background: Senescence is thought to be an imperative effect on the development of cancer. However, few studies pay an attention to the senescence-associated genes in pancreatic cancer (PC). The prognostic value of senescence-related genes (SRGs) and their involvement in tumor microenvironment (TME) in the PC remain obscure. The aim of this research was to investigate the prognostic role of senescence-associated genes and their affection in TME in PC. Methods: The transcriptome and clinical information of PC patients were obtained from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. Two SRG-mediated molecular clusters were comprehensively identified. In total, data from the 285 PC patients were randomly used to develop a senescence-associated gene signature in the training set and verified in the validation set. Immune microenvironment analysis pertained to senescence-related genes was performed. Results: A SRG_score including five senescence-associated genes was established to separate PC patients into two risk groups. High-risk patients had worse overall survival than low-risk patients. The result of the multivariate Cox regression analysis identified the risk score and stage as independent prognostic factors for PC patients. Receiver operating characteristic curve (ROC) analysis confirmed the credible predictive ability of the nomogram. The area under time-dependent ROC curve (AUC) reached 0.746 at 1 year, 0.781 at 3 years, and 0.868 at 5 years in the training set and 0.653 at 1 year, 0.755 at 3 years, and 0.785 at 5 years in the validation set. Moreover, the SRG_score was associated with TME, tumor mutation burden (TMB), and chemotherapeutic drug sensitivity. Conclusions: This study found that the novel SRG_score could be an independent prognostic target for PC patients. Senescence-associated genes had a vital impact on the immune microenvironment and the treatment of PC patients.

Potential therapeutic strategies for quercetin targeting critical pathological mechanisms associated with colon adenocarcinoma and COVID-19.

Patients with colon adenocarcinoma (COAD) are at a higher probability of infection with COVID-19 than healthy individuals. However, there is no globally accepted treatment protocol for patients with COAD/COVID-19. Quercetin has been found to have significant antitumor, antiviral and anti-inflammatory effects in several studies. Therefore, this study sought to evaluate the potential of quercetin as the agent for COAD/COVID-19 and to explore its mechanisms. We used bioinformatics algorithms to obtain COAD/COVID-19-related genes (CCRG) from COAD-related transcriptome data and COVID-related transcriptome sequencing data, and used these genes to construct a COAD prognostic model. We intersected the CCRG with the therapeutic target genes of quercetin and obtained a total of 105 genes (potential target genes of quercetin for the treatment of COAD/COVID-19). By constructing a protein-protein interaction (PPI) network, we ascertained FOS, NFKB1, NFKB1A, JUNB, and JUN as possible core target genes of quercetin for the treatment of COAD/COVID-19. Bioinformatic analysis of these 105 genes revealed that the mechanisms for quercetin the treatment of COAD/COVID-19 may be associated with oxidative stress, apoptosis, anti-inflammatory, immune, anti-viral and multiple pathways containing IL-17, TNF, HIF-1. In this study, we constructed a prognostic model of COAD/COVID19 patients by using CCRG and elucidated for the first time the potential target genes and molecular mechanisms of quercetin for the treatment of COAD/COVID-19, which may benefit the clinical treatment of COAD/COVID-19 patients. However, no clinical trials have yet been conducted to further validate the findings, but this will be the future direction of our research.

When 3D genome technology meets viral infection, including SARS-CoV-2.

Mammalian chromosomes undergo varying degrees of compression to form three-dimensional genome structures. These three-dimensional structures undergo dynamic and precise chromatin interactions to achieve precise spatial and temporal regulation of gene expression. Most eukaryotic DNA viruses can invade their genomes into the nucleus. However, it is still poorly understood how the viral genome is precisely positioned after entering the host cell nucleus to find the most suitable location and whether it can specifically interact with the host genome to hijack the host transcriptional factories or even integrate into the host genome to complete its transcription and replication rapidly. Chromosome conformation capture technology can reveal long-range chromatin interactions between different chromosomal sites in the nucleus, potentially providing a reference for viral DNA-host chromatin interactions. This review summarized the research progress on the three-dimensional interaction between virus and host genome and the impact of virus integration into the host genome on gene transcription regulation, aiming to provide new insights into chromatin interaction and viral gene transcription regulation, laying the foundation for the treatment of infectious diseases.

Identification of core genes associated with the anti-atherosclerotic effects of Salvianolic acid B and immune cell infiltration characteristics using bioinformatics analysis.

BACKGROUND: Atherosclerosis (AS) is the greatest contributor to pathogenesis of atherosclerotic cardiovascular disease (ASCVD), which is associated with increased mortality and reduced quality of life. Early intervention to mitigate AS is key to prevention of ASCVD. Salvianolic acid B (Sal B) is mainly extracted from root and rhizome of Salvia Miltiorrhiza Bunge, and exerts anti-atherosclerotic effect. The purpose of this study was to screen for anti-AS targets of Sal B and to characterize immune cell infiltration in AS. METHODS: We identified targets of Sal B using SEA ( http://sea.bkslab.org/ ) and SIB ( https://www.sib.swiss/ ) databases. GSE28829 and GSE43292 datasets were obtained from Gene Expression Omnibus database. We identified differentially expressed genes (DEGs) and performed enrichment analysis. Weighted gene co-expression network analysis (WGCNA) was used to determine the most relevant module associated with atherosclerotic plaque stability. Intersecting candidate genes were evaluated by generating receiver operating characteristic (ROC) curves and molecular docking. Then, immune cell types were identified using CIBERSOFT and single-sample gene set enrichment analysis (ssGSEA), the relationship between candidate genes and immune cell infiltration was evaluated. Finally, a network-based approach to explore the candidate genes relationship with microRNAs (miRNAs) and Transcription factors (TFs). RESULTS: MMP9 and MMP12 were been selected as candidate genes from 64 Sal B-related genes, 81 DEGs and turquoise module with 220 genes. ROC curve results showed that MMP9 (AUC = 0.815, P<0.001) and MMP12 (AUC = 0.763, P<0.001) were positively associated with advanced atherosclerotic plaques. The results of immune infiltration showed that B cells naive, B cells memory, Plasma cells, T cells CD8, T cells CD4 memory resting, T cells CD4 memory activated, T cells regulatory (Tregs), T cells gamma delta, NK cells activated, Monocytes, and Macrophages M0 may be involved in development of AS, and the candidate genes MMP9 and MMP12 were associated with these immune cells to different degrees. What' s more, miR-34a-5p and FOXC1, JUN maybe the most important miRNA and TFs. CONCLUSION: The anti-AS effects of Sal B may be related to MMP9 and MMP12 and associated with immune cell infiltration, which is expected to be used in the early intervention of AS.

Puerarin: A Potential Therapeutic for SARS-CoV-2 and Hantavirus Co-Infection.

Patients with Hantavirus-caused epidemic hemorrhagic fever (EHF) are at risk of contracting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, there is currently no validated EHF/SARS-CoV-2 strategy. Several studies have recently shown Puerarin, a natural product, has potent antiviral properties. The goal of present study was to determine the mechanism of puerarin in patients with EHF/COVID-19. We use network pharmacology and bioinformatics to investigate the possible pharmacological targets, bioactivities, and molecular mechanisms of puerarin in the treatment of patients with EHF/SARS-CoV-2. The study investigated the pathogenesis of COVID-19 and EHF and the signaling pathway impacted by puerarin. 68 common genes linked to puerarin and EHF/SARS-CoV-2 were discovered during the investigation. By using protein-protein interaction (PPI) network, we identified RELA, JUN, NF-B1, NF-B2, and FOS as potential therapeutic targets. The bioactivity and signaling pathways of puerarin have also been demonstrated in the treatment of EHF and COVID-19. According to present study, puerarin could reduce excessive immune responses and inflammation through the NF-B, TNF, and HIF-1 signaling pathways. This study explored the potential therapeutic targets and mechanisms of Puerarin in the treatment of EHF/COVID-19.

Puerarin: A Potential Therapeutic for Colon Adenocarcinoma (COAD) Patients Suffering From SARS-CoV-2 Infection.

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.

Exploration of the Shared Gene and Molecular Mechanisms Between Endometriosis and Recurrent Pregnancy Loss.

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.

Identification of Bioactive Compounds and Potential Mechanisms of Kuntai Capsule in the Treatment of Polycystic Ovary Syndrome by Integrating Network Pharmacology and Bioinformatics.

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.

Identification of Potential Molecular Mechanism Related to Infertile Endometriosis.

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.

Immune Cell Infiltration Landscape of Ovarian Cancer to Identify Prognosis and Immunotherapy-Related Genes to Aid Immunotherapy.

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.

Protective effect of Qingre Huoxue decoction against myocardial infarction via PI3K/Akt autophagy pathway based on UPLC-MS, network pharmacology, and in vivo evidence.

CONTEXT: Qingre Huoxue (QRHX) decoction, a traditional Chinese medicine, has been widely used to prevent and treat myocardial infarction (MI). OBJECTIVE: This study elucidates the possible mechanisms of QRHX in preventing or treating MI in a rat model. MATERIALS AND METHODS: The chemical constituents of QRHX were identified by UPLC-MS. Sprague-Dawley rats were randomly divided into the Sham (normal saline), Model (normal saline), QRHX-L, QRHX-M and QRHX-H group (n = 10 per group). QRHX decoction was administered by gavage to the rats for 14 days (5, 10 and 20 g/kg/day). The left anterior descending ligation method was performed to develop MI in Model and QRHX groups, and the same surgical procedures excluding ligation sutures were performed for the sham group. Finally, we evaluated cardiac function, myocardial fibrosis degree, serum inflammatory factors, autophagy levels and verified the signalling pathways in vivo. RESULTS: A total of 68 active components of QRHX corresponding to 223 active targets were obtained and 2558 MI-related disease targets were collected. After integration, 123 QRHX anti-MI targets were obtained, and 70 signalling pathways, such as PI3K/Akt, were identified by enrichment analysis. In vivo experiments suggest that QRHX could reduce the degree of myocardial fibrosis, downregulate serum inflammatory factors, and promote autophagy in MI rats. DISCUSSION AND CONCLUSIONS: QRHX plays a protective role in the myocardium by mediating PI3K/Akt signalling pathway to activate autophagy and inhibiting inflammatory factor expression. These findings provide a scientific basis for further research and validation of QRHX as a potential therapeutic for MI.

Molecular subtypes based on DNA methylation predict prognosis in lung squamous cell carcinoma.

BACKGROUND: Due to tumor heterogeneity, the diagnosis, treatment, and prognosis of patients with lung squamous cell carcinoma (LUSC) are difficult. DNA methylation is an important regulator of gene expression, which may help the diagnosis and therapy of patients with LUSC. METHODS: In this study, we collected the clinical information of LUSC patients in the Cancer Genome Atlas (TCGA) database and the relevant methylated sequences of the University of California Santa Cruz (UCSC) database to construct methylated subtypes and performed prognostic analysis. RESULTS: Nine hundred sixty-five potential independent prognosis methylation sites were finally identified and the genes were identified. Based on consensus clustering analysis, seven subtypes were identified by using 965 CpG sites and corresponding survival curves were plotted. The prognostic analysis model was constructed according to the methylation sites' information of the subtype with the best prognosis. Internal and external verifications were used to evaluate the prediction model. CONCLUSIONS: Models based on differences in DNA methylation levels may help to classify the molecular subtypes of LUSC patients, and provide more individualized treatment recommendations and prognostic assessments for different clinical subtypes. GNAS, FZD2, FZD10 are the core three genes that may be related to the prognosis of LUSC patients.