Venn diagrams in bioinformatics

Systems biology and in silico-based analysis of PCOS revealed the risk of metabolic disorders

Background

Polycystic ovarian syndrome (PCOS) is a common condition of hyperandrogenism, chronic ovulation, and polycystic ovaries in females during the reproduction and maturation of the ovum. Although PCOS has been associated with metabolic disorders, including type 2 diabetes (T2D), obesity (OBE), and cardiovascular disease (CVD), Causal connection and molecular features are still unknown.

Purpose

Therefore, we investigated the shared common differentially expressed genes (DEGs), pathways, and networks of associated proteins in PCOS and metabolic diseases with therapeutic intervention.

Methods

We have used a bioinformatics pipeline to analyze transcriptome data for the polycystic ovarian syndrome (PCOS), type 2 diabetes (T2D), obesity (OBE), and cardiovascular diseases (CVD) in female patients. Then we employed gene-disease association network, gene ontology (GO) and signaling pathway analysis, selection of hub genes from protein-protein interaction (PPI) network, molecular docking, and gold benchmarking approach to screen potential hub proteins.

Result

We discovered 2225 DEGs in PCOS patients relative to healthy controls and 34, 91, and 205 significant DEGs with T2D, Obesity, and CVD, respectively. Gene Ontology analysis revealed several significant shared and metabolic pathways from signaling pathway analysis. Furthermore, we identified ten potential hub proteins from PPI analysis that may serve as a therapeutic intervention in the future. Finally, we targeted one significant hub protein, IGF2R (PDB ID: 2V5O), out of ten hub proteins based on the Maximal clique centrality (MCC) algorithm and literature review for molecular docking study. Enzastaurin (-12.5), Kaempferol (-9.1), Quercetin (-9.0), and Coumestrol (-8.9) kcal/mol showed higher binding affinity in the molecular docking approach than 19 drug compounds. We have also found that the selected four compounds displayed favorable ADMET properties compared to the native ligand.

Conclusion

Our in-silico research findings identified a shared molecular etiology between PCOS and metabolic diseases that may suggest new therapeutic targets and warrants future experimental validation of the key targets.

Hsa_circ_0015278 Regulates FLT3-ITD AML Progression via Ferroptosis-Related Genes

AML with the FLT3-ITD mutation seriously threatens human health. The mechanism by which circRNAs regulate the pathogenesis of FLT3-ITD mutant-type AML through ferroptosis-related genes (FerRGs) remains unclear. Differentially expressed circRNAs and mRNAs were identified from multiple integrated data sources. The target miRNAs and mRNAs of the circRNAs were predicted using various databases. The PPI network, ceRNA regulatory network, GO, and KEGG enrichment analyses were performed. The "survival" and the "pROC" R packages were used for K-M and ROC analysis, respectively. GSEA, immune infiltration analysis, and clinical subgroup analysis were performed. Finally, circRNAs were validated by Sanger sequencing and qRT-PCR. In our study, 77 DECircs-1 and 690 DECircs-2 were identified. Subsequently, 11 co-up-regulated DECircs were obtained by intersecting DECircs-1 and DECircs-2. The target miRNAs of the circRNAs were screened by CircInteractome, circbank, and circAtlas. Utilizing TargetScan, ENCORI, and miRWalk, the target mRNAs of the miRNAs were uncovered. Ultimately, 73 FerRGs were obtained, and the ceRNA regulatory network was constructed. Furthermore, MAPK3 and CD44 were significantly associated with prognosis. qRT-PCR results confirmed that has_circ_0015278 was significantly overexpressed in FLT3-ITD mutant-type AML. In summary, we constructed the hsa_circ_0015278/miRNAs/FerRGs signaling axis, which provides new insight into the pathogenesis and therapeutic targets of AML with FLT3-ITD mutation.

Bariatric Surgery Associates with Nonalcoholic Steatohepatitis/Hepatocellular Carcinoma Amelioration via SPP1 Suppression

Nonalcoholic steatohepatitis (NASH) is one of the most common chronic liver diseases worldwide and no effective drugs or treatments have been approved for disease management. Recently, bariatric surgery (BS) is considered to be a novel disease-modifying therapy for NASH and liver metabolic diseases, according to clinical follow-up studies. Despite the revealment of physiopathological alterations, underlying mechanisms and key factors remain indeterminate. This study included multiple bulk RNA-sequencing datasets to investigate transcriptome variation in one-year follow-up BS and diet management (Diet) NASH patients' liver biopsies. Liver functions, fibrosis, and carcinogenesis were predicted in liver samples via hallmark-based function enrichment analysis. Key factors generated from multi-dataset comparison were further assessed with hepatocellular carcinoma (HCC) progression and prognosis. BS leads to active gene expression alterations in NASH liver in comparison to diet management (Diet). Both approaches reduce cell stress and immune response, whereas BS contributes to higher metabolic levels and lower apoptosis levels. The macrophage infiltration, adipose accumulation, and fibroblast activation were revealed to be lower in post-BS NASH livers, further demonstrating positive correlations mutually. Seven key genes (MNDA, ALOX5AP, PECAM1, SPP1, CD86, FGF21, CSTA) were screened out as potential macrophage-associated and carcinogenetic factors suppressed by BS. SPP1 was identified as a crucial factor participating in BS intervened NASH-HCC progression. This study determined that BS exerts potentially superior protective functions in NASH livers compared to diet management. SPP1 may serve as a novel factor to study the functionalities of BS on NASH patients.

Identification of ferroptosis‑associated genes in chronic kidney disease

Ferroptosis serves a pivotal role in developing chronic kidney disease (CKD). The present study aimed to detect and confirm the relevance of potential ferroptosis-related genes in CKD using bioinformatics and experimentation strategies. The original GSE15072 mRNA expression dataset was retrieved from the Gene Expression Omnibus database. Subsequently, the potential differentially expressed genes associated with ferroptosis of CKD were screened using R software. Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway enrichment analyses, correlation analysis and protein-protein interactions (PPI) were performed for differentially expressed ferroptosis-associated genes (DFGs). Lastly, the expression levels of the top nine DFGs were measured in the kidney tissue of Adriamycin-induced CKD rats and healthy controls via reverse transcription-quantitative (RT-q)PCR analysis. Overall, 49 DFGs among 21 patients with CKD and nine healthy controls were identified. GO and KEGG enrichment analyses demonstrated that these DFGs were primarily involved in 'ferroptosis' and 'mitophagy'. PPI findings indicated that these ferroptosis-associated genes interacted with one another. RT-qPCR of CKD tissue from the rat model revealed that STAT3, MAPK14, heat shock protein (HSP)A5, MTOR and solute carrier family 2 member 1 (SLC2A1) mRNA levels in CKD were upregulated. Overall, 49 potential ferroptosis-associated genes of CKD were identified via bioinformatics analyses. STAT3, MAPK14, HSPA5, MTOR and SLC2A1 may influence CKD onset by regulating ferroptosis. The present results add to the existing body of knowledge about CKD and may be useful in the treatment of CKD.

STXBP3 and GOT2 predict immunological activity in acute allograft rejection

Background

Acute allograft rejection (AR) following renal transplantation contributes to chronic rejection and allograft dysfunction. The current diagnosis of AR remains dependent on renal allograft biopsy which cannot immediately detect renal allograft injury in the presence of AR. In this study, sensitive biomarkers for AR diagnosis were investigated and developed to protect renal function.

Methods

We analyzed pre- and postoperative data from five databases combined with our own data to identify the key differently expressed genes (DEGs). Furthermore, we performed a bioinformatics analysis to determine the immune characteristics of DEGs. The expression of key DEGs was further confirmed using the real-time quantitative PCR (RT-qPCR), enzyme-linked immunosorbent assay (ELISA), and immunohistochemical (IHC) staining in patients with AR. ROC curves analysis was used to estimate the performance of key DEGs in the early diagnosis of AR.

Results

We identified glutamic-oxaloacetic transaminase 2 (GOT2) and syntaxin binding protein 3 (STXBP3) as key DEGs. The higher expression of STXBP3 and GOT2 in patients with AR was confirmed using RT-qPCR, ELISA, and IHC staining. ROC curve analysis also showed favorable values of STXBP3 and GOT2 for the diagnosis of early stage AR.

Conclusions

STXBP3 and GOT2 could reflect the immunological status of patients with AR and have strong potential for the diagnosis of early-stage AR.

Integrated analysis identified prognostic microRNAs in breast cancer

Background

MicroRNAs (miRNAs) play pivotal roles in the development and progression of breast cancer (BC). In this study, we attempted to identify miRNAs associated with BC prognosis and progression via integrated analysis.

Methods

We first screened 83 differentially expressed miRNAs (DEMs) in 1249 BC samples and 151 normal samples. We then validated their roles in expression and prognosis of BC, identified two survival-related DEMs, and established a risk model. The prediction efficiency was assessed in both the training and validation groups. Tissue and cell experiments were conducted to verify the regulatory effects of miR-127 in BC.

Results

The ROC curve indicated good prediction ability with 1-, 3-, and 5-year survival rates of 0.73, 0.72, and 0.72, respectively. Moreover, hsa-miR-127 was found to be an independent prognostic factor of BC. Functional analyses revealed that it is involved in various cancer pathways such as the PI3K-Akt and p53 pathways. miR-127 expression was down-regulated in both BC tissues and cell lines. The knockdown of miR-127 substantially increased, whereas overexpression decreased BC cell proliferation, invasion, and migration. This effect of miR-127 was consistent with its tumorigenic ability and tumor volume in nude mice.

Conclusions

These findings indicate that low expression of miR-127 contributes to BC migration, invasion, and tumorigenesis and that it can be a therapeutic target and prognostic biomarker for BC.

Exploring the active ingredients and pharmacological mechanisms of the oral intake formula Huoxiang Suling Shuanghua Decoction on influenza virus type A based on network pharmacology and experimental exploration

Objective

To investigate the active ingredients, underlying anti-influenza virus effects, and mechanisms of Huoxiang Suling Shuanghua Decoction (HSSD).

Materials and methods

The therapeutic effect of HSSD were confirmed through the survival rate experiment of H1N1-infected mice. Then, the HSSD solution and the ingredients absorbed into the blood after treatment with HSSD in rats were identified by UPLC/Q-TOF MS, while the main contents of ingredients were detected by high performance liquid chromatography (HPLC). Next, a systems pharmacology approach incorporating target prediction, gene ontology (GO) enrichment, kyoto encyclopedia of genes and genomes (KEGG) pathway analysis, and molecular docking were performed to screen out the active compounds and critical pathways of HSSD in treating influenza. According to prediction results, real-time quantitative polymerase chain reaction (RT-qPCR) and immunohistochemistry assay were used to detect the mRNA and protein expression levels of critical targets in H1N1-infected mice lungs.

Results

Huoxiang Suling Shuanghua Decoction improved the survival rate of H1N1-infected mice and prolonged the mice’s lifespan. Besides, HSSD exerts an antivirus effect by decreasing the levels of hemagglutinin (HA) and nucleoprotein (NP) to inhibit the replication and proliferation of H1N1, reducing the lung pathological state, inhibiting the cell apoptosis in the lung, and regulating the abnormal responses of peripheral blood, including GRA, LYM, white blood cell (WBC), PLT, and hemoglobin (HGB). Then, 87 compounds in the HSSD solution and 20 ingredients absorbed into the blood after treatment with HSSD were identified. Based on this, combined with the network analysis and previous research on antivirus, 16 compounds were screened out as the active components. Moreover, 16 potential targets were predicted by network pharmacology analysis. Next, molecular docking results showed stable binding modes between compounds and targets. Furthermore, experimental validation results indicated that HSSD regulates the contents of Immunoglobulin A (IgA), Immunoglobulin M (IgM), and Immunoglobulin G (IgG) in serum, modulating the levels of IFN-γ, IL-6, IL-10, MCP-1, MIP-1α, and IP-10 in the lung tissue, and significantly decreasing the mRNA and protein expressions of TLR4, CD14, MyD88, NF-κB p65, HIF1 α, VEGF, IL17A, and IL6 in the lung tissue.

Conclusion

Huoxiang Suling Shuanghua Decoction exerts an anti-influenza effect by affecting the expressions of mRNA and protein including TLR4, CD14, MyD88, NF-kB p65, HIF-1α, VEGF, IL17A, IL6, and inhibiting the accumulation of inflammation. Our study provided experimental pieces of evidence about the practical application of HSSD in treating influenza.

Identification of a Fibroblast-Related Prognostic Model in Glioma Based on Bioinformatics Methods

Background: Glioma is the most common primary tumor of the central nervous system with a high lethality rate. This study aims to mine fibroblast-related genes with prognostic value and construct a corresponding prognostic model. Methods: A glioma-related TCGA (The Cancer Genome Atlas) cohort and a CGGA (Chinese Glioma Genome Atlas) cohort were incorporated into this study. Variance expression profiling was executed via the “limma” R package. The “clusterProfiler” R package was applied to perform a GO (Gene Ontology) analysis. The Kaplan–Meier (K–M) curve, LASSO regression analysis, and Cox analyses were implemented to determine the prognostic genes. A fibroblast-related risk model was created and affirmed by independent cohorts. We derived enriched pathways between the fibroblast-related high- and low-risk subgroups using gene set variation analysis (GSEA). The immune infiltration cell and the stromal cell were calculated using the microenvironment cell populations-counter (MCP-counter) method, and the immunotherapy response was assessed with the SubMap algorithm. The chemotherapy sensitivity was estimated using the “pRRophetic” R package. Results: A total of 93 differentially expressed fibroblast-related genes (DEFRGs) were uncovered in glioma. Seven prognostic genes were filtered out to create a fibroblast-related gene signature in the TCGA-glioma cohort training set. We then affirmed the fibroblast-related risk model via TCGA-glioma cohort and CGGA-glioma cohort testing sets. The Cox regression analysis proved that the fibroblast-related risk score was an independent prognostic predictor in prediction of the overall survival of glioma patients. The fibroblast-related gene signature revealed by the GSEA was applicable to the immune-relevant pathways. The MCP-counter algorithm results pointed to significant distinctions in the tumor microenvironment between fibroblast-related high- and low-risk subgroups. The SubMap analysis proved that the fibroblast-related risk score could predict the clinical sensitivity of immunotherapy. The chemotherapy sensitivity analysis indicated that low-risk patients were more sensitive to multiple chemotherapeutic drugs. Conclusion: Our study identified prognostic fibroblast-related genes and generated a novel risk signature that could evaluate the prognosis of glioma and offer a theoretical basis for clinical glioma therapy.

A novel therapeutic approach for IPF: Based on the "Autophagy - Apoptosis" balance regulation of Zukamu Granules in alveolar macrophages

ETHNOPHARMACOLOGICAL RELEVANCE

Zukamu Granules (ZKMG) is one of the representative Uygur patent drugs widely used in China, which is included in the National Essential Drugs List (2018 edition). As the first choice for common cold treatment in Uygur medicine theory, it has unique anti-inflammatory and antitussive efficacy.

AIM OF THE STUDY

According to the recent inflammatory hypothesis, the abnormal proliferation, autophagy and apoptosis process of lung cells especially alveolar macrophages (AMs) may play an important role in the progress of idiopathic pulmonary fibrosis (IPF). Therefore, we came up with a novel treatment approach for IPF by regulating the balance of AMs "autophagy - apoptosis", and took ZKMG as the sample drug for our research.

MATERIALS AND METHODS

Network pharmacology approach was conducted to predict the active components and intersected targets between ZKMG and inflammation. PPI network, GO and KEGG enrichment analysis were screened and analyzed to predict the anti-inflammatory mechanism of ZKMG. Biological experiment adopted from 128 rats, and hematoxylin-eosin staining, flow cytometry and RT-PCR were performed to examine the pathological morphology, HYP contents in lung tissue, AMs counting, AMs apoptosis, AMs phagocytosis rate, mRNA relative quantity determination of 3 key factors associated with AMs "autophagy - apoptosis" and mRNA relative quantity determination of AMs surface receptor signaling pathway.

RESULTS

The predicted results showed that the mechanism of ZKMG in anti-inflammatory was related to the response and elimination of inflammatory stimuli, the intervention of apoptosis and surface receptor signaling pathways of cells. The verification experiments showed that excessive apoptosis and insufficient autophagy of AMs always existed in the progression of IPF. ZKMG could inhibit AMs proliferation, significantly reduce AMs apoptosis rate, intervene the binding of the Bcl-2 to Beclin 1, inhibit the Caspase 3 activation, stimulate the enhancement of AMs phagocytosis, and inhibit the high expression of TLR4/MyD88/NF-κB surface receptor signaling pathway, which may partly retard the fibrosis process.

CONCLUSION

By inhibiting proliferation, enhancing phagocytosis, inhibiting the formation of Bcl-2 complex, and inhibiting the high expression of MYD88-dependent TLR4 signaling pathway, ZKMG can regulate the balance of AMs "autophagy - apoptosis" in the alveolitis stage to retard the fibrosis process partly. With a comprehensive strategy of "target prediction - experimental verification", we have demonstrated that inhibiting the apoptosis and promoting autophagy activity of AMs may suggest a new perspective for IPF treatment, which would provide reference for the subsequent development.

NOX4 has the potential to be a biomarker associated with colon cancer ferroptosis and immune infiltration based on bioinformatics analysis

Background

Colon cancer (CC) is a common tumor, but its pathogenesis is still not well understood. Competitive endogenous RNA (ceRNA) theory, ferroptosis and tumor immune infiltration may be the mechanisms of the development of cancer. The purpose of the study is to seek genes connected with both immunity and ferroptosis, and provide important molecular basis for early noninvasive diagnosis and immunotherapy of CC.

Methods

We extracted messenger RNA (mRNA), microRNA (miRNA), and long noncoding RNA (lncRNA) data of CC from The Cancer Genome Atlas database (TCGA), identified the differentially expressed mRNA (DEmRNA), miRNA (DEmiRNA) and lncRNA (DElncRNA), then constructed a ceRNA network. Venn overlap analysis was used to identify genes associated with immunity and ferroptosis in ceRNA network. The expression and prognosis of target genes were analyzed via Gene Expression Profiling Interactive Analysis (GEPIA) and PrognoScan database, and we analysed the related functions and signaling pathways of target genes by enrichment analysis. The correlation between target genes and tumor immune infiltrating was explored by CIBERSORT and spearman correlation analysis. Finally, the expression of target genes was detected via quantitative reverse transcription-PCR (qRT-PCR) in CC and normal colon tissues.

Results

Results showed that there were 4 DElncRNA, 4 DEmiRNA and 126 DEmRNA in ceRNA network. NADPH oxidase 4 protein (NOX4) was a DEmRNA associated with immunity and ferroptosis in ceRNA network. NOX4 was highly expressed in CC and connected with unfavourable prognosis. NOX4 was obviously enriched in pathways connected with carcinogenesis and significantly correlated with six kinds of immune cells. Immune checkpoints and NOX4 spearman correlation analysis showed that the expression of NOX4 was positively related to programmed cell death protein 1 (PD-1)-PDCD1, programmed cell death-Ligand 1 (PD-L1)-CD274 and cytotoxic T-lymphocyte-associated protein 4 (CTLA4).

Conclusions

To conclude, our study suggests that NOX4 is associated with both ferroptosis and tumor immunity, and might be a biomarker associated with the carcinogenesis, prognosis of CC and a potential target of CC immunotherapy.

Bioinformatics analysis on differentially expressed genes between colorectal adenoma and colorectal adenocarcinoma

BACKGROUND

Colorectal adenoma (CRA) is the main cause of the progression of Colorectal adenocarcinoma (COAD). Therefore, it is very important to accurately reveal its developmental mechanism.

METHODS

Differential expression genes (DEGs) in three microarray datasets were screened using GEO and GEO2R. R packages were used for gene ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) path enrichment analysis. Hub genes screened by STRING, Cytoscape and CytoHubba were used. R was used for DEGs of hub genes, and Gene Expression Profiling Interactive Analysis (GEPIA2) database was used for prognostic Analysis. R-packet were used to analyze tumor pathology, tumour, lymph-nodes, and metastases (TNM) staging, enrichment, immune invasion and prognosis.

RESULTS

Among the 66 genes, including 36 up-regulated and 30 down-regulated genes. Survival analysis showed that COL1A1, COL5A2, COL5A1 and secreted protein acidic and rich in cysteine (SPARC) were associated with disease-free survival in patients. The four genes were related to tumor pathological stage, TNM stage and immune invasion. COL1A1 and COL5A2 were highly expressed in chromatin modification and cellular senescence. Low expression of COL5A1 and SPARC was significantly enriched in neutrophil degranulation and Wp VegfavegFR2 signaling pathways.

CONCLUSIONS

Obviously, these four key genes can serve as important targets for early diagnosis, treatment, immunity and prognosis of CRA to COAD.

Network pharmacology and molecular docking analysis reveal insights into the molecular mechanism of shiliao decoction in the treatment of cancer-associated malnutrition

Purpose

Shiliao Decoction (SLD) was developed for treatment and prevention of cancer-associated malnutrition (CAM) in China. In this study, we aim to discover SLD’s active compounds and demonstrate the mechanisms of SLD that combat CAM through network pharmacology and molecular docking techniques.

Methods

All components of SLD were retrieved from the pharmacology database of Traditional Chinese Medicine Systems Pharmacology (TCMSP). The GeneCards database and the Online Mendelian Inheritance in Man database (OMIM) were used to identify gene encoding target compounds, and Cytoscape was used to construct the drug compound–target network. The network of target protein-protein interactions (PPI) was constructed using the STRING database, while gene ontology (GO) functional terms and the Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathways associated with potential targets were analyzed using a program in R language (version 4.2.0). Core genes linked with survival and the tumor microenvironment were analyzed using the Kaplan–Meier plotter and TIMER 2.0 databases, respectively. Protein expression and transcriptome expression levels of core gene were viewed using the Human Protein Atlas (HPA) and the Cancer Genome Atlas (TCGA). A component-target-pathway (C-T-P) network was created using Cytoscape, and Autodock Vina software was used to verify the molecular docking of SLD components and key targets.

Results

The assembled compound–target network primarily contained 134 compounds and 147 targets of the SLD associated with JUN, TP53, MAPK3, MAPK1, MAPK14, STAT3, AKT1, HSP90AA1, FOS, and MYC, which were identified as core targets by the PPI network. KEGG pathway analysis revealed pathways involved in lipid and atherosclerosis, the PI3K/Akt signaling pathway, and immune-related pathways among others. JUN is expressed at different levels in normal and cancerous tissues, it is closely associated with the recruitment of different immune cells and has been shown to have a significant impact on prognosis. The C-T-P network suggests that the active component of SLD is capable of regulating target genes affecting these related pathways. Finally, the reliability of the core targets was evaluated using molecular docking technology.

Conclusion

This study revealed insights into SLD’s active components, potential targets, and possible molecular mechanisms, thereby demonstrating a potential method for examining the scientific basis and therapeutic mechanisms of TCM formulae.

Identification of Immune-Related Gene Signature in Stanford Type A Aortic Dissection

Background: Stanford type A aortic dissection (ATAAD) is a common life-threatening event in the aorta. Recently, immune disorder has been linked to the risk factors that cause ATAAD at the molecular level. However, the specific immune-related gene signature during the progression is unclear.

Methods: The GSE52093 and GSE98770 datasets related to ATAAD from the Gene Expression Omnibus (GEO) database were acquired. The immune gene expression levels were analyzed by single sample gene set enrichment analysis (ssGSEA). The correlations between gene networks and immune scores were determined by weighted gene correlation network analysis (WGCNA). The different immune subgroups were finally divided by consensus clustering. The differentially expressed genes (DEGs) were identified and subsequent functional enrichment analyses were conducted. The hub genes were identified by protein–protein interaction (PPI) network and functional similarities analyses. The immune cell infiltration proportion was determined by the CIBERSORT algorithm.

Results: According to the ssGSEA results, the 13 ATAAD samples from the GEO database were divided into high- and low-immune subgroups according to the ssGSEA, WGCNA, and consensus clustering analysis results. Sixty-eight immune-related DEGs (IRDEGs) between the two subgroups were enriched in inflammatory-immune response biological processes, including leukocyte cell–cell adhesion, mononuclear cell migration, and myeloid leukocyte migration. Among these IRDEGs, 8 genes (CXCR4, LYN, CCL19, CCL3L3, SELL, F11R, DPP4, and VAV3) were identified as hub genes that represented immune-related signatures in ATAAD after the PPI and functional similarities analyses. The proportions of infiltrating CD8 T cells and M1 macrophages were significantly higher in ATAAD patients in the immune-high group than the immune-low group.

Conclusion: Eight immune-related genes were identified as hub genes representing potential biomarkers and therapeutic targets linked to the immune response in ATAAD patients.

Network Pharmacology and Molecular Docking-Based Strategy to Investigate the Multitarget Mechanisms of Shenqi Yizhi Granule on Alzheimer's Disease

Background

Traditional Chinese herbal medicine draws more attention to explore an effective therapeutic strategy for Alzheimer's disease (AD). Shenqi Yizhi granule (SQYG), a Chinese herbal recipe, has been applied to ameliorate cognitive impairment in mild-to-moderate AD patients. However, the overall molecular mechanism of SQYG in treating AD has not been clarified.

Objective

This study aimed to investigate the molecular mechanism of SQYG on AD using an integration strategy of network pharmacology and molecular docking.

Methods

The active compounds of SQYG and common targets between SQYG and AD were screened from databases. The herb-compound network, compound-target network, and protein-protein interaction network were constructed. The enrichment analysis of common targets and molecular docking were performed.

Results

816 compounds and 307 common targets between SQYG and AD were screened. KEGG analysis revealed that common targets were mainly enriched in lipid metabolism, metal ion metabolism, IL-17 signaling pathway, GABA receptor signaling, and neuroactive ligand-receptor interaction. Molecular docking analysis showed high binding affinity between ginsenoside Rg1 and Aβ _1-42, tanshinone IIA and BACE1, baicalin, and AchE.

Conclusions

The therapeutic mechanisms of SQYG on AD were associated with regulating lipid metabolism, metal ion metabolism, IL-17 signaling pathway, and GABA receptor signaling. Ginsenoside Rg1, tanshinone IIA, baicalin, astragaloside IV, and folic acid may play an important role in AD treatment.

Protocol for Increasing the Sensitivity of MS-Based Protein Detection in Human Chorionic Villi

An important step in the proteomic analysis of missing proteins is the use of a wide range of tissues, optimal extraction, and the processing of protein material in order to ensure the highest sensitivity in downstream protein detection. This work describes a purification protocol for identifying low-abundance proteins in human chorionic villi using the proposed “1DE-gel concentration” method. This involves the removal of SDS in a short electrophoresis run in a stacking gel without protein separation. Following the in-gel digestion of the obtained holistic single protein band, we used the peptide mixture for further LC–MS/MS analysis. Statistically significant results were derived from six datasets, containing three treatments, each from two tissue sources (elective or missed abortions). The 1DE-gel concentration increased the coverage of the chorionic villus proteome. Our approach allowed the identification of 15 low-abundance proteins, of which some had not been previously detected via the mass spectrometry of trophoblasts. In the post hoc data analysis, we found a dubious or uncertain protein (PSG7) encoded on human chromosome 19 according to neXtProt. A proteomic sample preparation workflow with the 1DE-gel concentration can be used as a prospective tool for uncovering the low-abundance part of the human proteome.

The macrophage-associated microRNA-4715-3p / Gasdermin D axis potentially indicates fibrosis progression in nonalcoholic fatty liver disease: evidence from transcriptome and biological data

Nonalcoholic fatty liver disease (NAFLD) is highly possible to progress to cirrhosis, malignancy, and liver failure through fibrogenesis. The enormous potential of pathogenetic and therapeutic targets in NAFLD has been revealed. This study aimed to explore novel factors potentially indicating or mediating NAFLD progression. Multiple bulk and single-cell RNA sequencing datasets were used, in which landscapes of cell populations were clarified to characterize immune cell infiltration. Significantly high infiltration of macrophages (MPs) was discovered during NAFLD progression. Samples in bulk NASH datasets were regrouped by MP level. Highly differentially expressed genes (DEGs) were identified in the Ctrl vs. NASH comparison, low MP vs. high MP comparison, and the weighted gene co-expression network analysis (WGCNA) clusters. Eight hub genes were identified as promising targets by protein–protein interaction analysis and validated in fibrosis progression, microRNA (miR)–protein interactions were predicted, and the hub genes were verified in a free fatty acid (FFA)-induced macrophage injury model. The results showed that Gasdermin D (GSDMD) was upregulated with fibrosis progression in NAFLD and was associated with macrophage infiltration. In addition, a potential regulator (miR-4715-3p) was correlated with GSDMD. The miR-4715-3p/GSDMD axis potentially modulates macrophage-associated immunity and indicates fibrosis progression in NAFLD.

Identifying the shared genes and KEGG pathways of Resolvin D1-targeted network and osteoarthritis using bioinformatics

Osteoarthritis (OA) is a common chronic degenerative disease characterized by the loss of articular cartilage, which causes loss of joint function and reduce quality of life. Resolvin D1 (RvD1) has shown interesting anti-inflammatory effects; however, the mechanism of action of RvD1 in OA remains unclear. The aim of this study was to investigate the potential mechanism of RvD1 in OA by bioinformatics and partial in vitro mechanisms. Here, 106 shared differentially expressed genes (DEGs) were identified based on the GSE82107, GSE55235, GSE55457 dataset; 700 DEGs were identified based on GSE169077. Enrichment analyses of these genes were then successively conducted. RvD1-targeted genes and KEGG pathways are identified by STITCH. 27 shared KEGG pathways were identified among RvD1-targeted pathways and OA. Furthermore, cell apoptosis assay, western blotting, real-time fluorescent quantitative PCR (qRT-PCR), enzyme linked immunosorbent assay (ELISA) were used to confirm the expression levels of the key genes of shared Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways between RvD1-targeted and OA in IL-1β treated rat knee chondrocytes. The results showed that RvD1-targeted pathways and the expression of nuclear p65, p53, and p-JNK were inhibited in the RvD1 group compared with the IL-1β group. Thus, the findings indicate that RvD1 may inhibit the development of OA through NF/kB, p53, MAPK/JNK, PI3K-AKT signaling pathways, and act as a treatment for OA.

MicroRNA-642b-3p functions as an oncomiR in gastric cancer by down-regulating the CUB and sushi multiple domains protein 1/smad axis

Aberrant expression of microRNAs (miRNAs or miRs) has been involved in the progression of gastric cancer (GC). Our analysis of GC-related gene expression profiles identified the significantly up-regulated miR-642b-3p expression, which has been reported as a mediator in various cancers but rarely mentioned in researches on GC. Herein, this study intends to investigate the role of miR-642b-3p in GC development. Bioinformatics analysis was conducted to predict the downstream target gene of miR-642b-3p. Expression patterns of miR-642b-3p and CUB and sushi multiple domains protein 1 (CSMD1) in GC tissues and cell lines was then determined. Immunofluorescence, wound healing and Transwell invasion assays were performed to observe the malignant behaviors of GC cells with altered expression of miR-642b-3p and CSMD1. Nude mice with xenograft tumors were developed for in vivo validation. miR-642b-3p expression was increased in GC tissues and cell lines. miR-642b-3p targeted CSMD1 and reduced the expression of CSMD1, thereby inhibiting the activation of Smad signaling pathway. By this mechanism, the epithelial–mesenchymal transition (EMT), invasive and migratory potentials of GC cells were repressed. Meanwhile, in vivo data verified that miR-642b-3p enhanced the tumor growth of GC cells, which was associated with blockade of CSMD1-dependent activation of the Smad signaling pathway. Overall, miR-642b-3p acts as an oncomiR promoting tumor development in GC through suppressing CSMD1 expression and inactivating the Smad signaling pathway, which may enable the development of new therapeutic strategies for treatment of GC.

A Risk Model Based on Immune-Related Genes Predicts Prognosis and Characterizes the Immune Landscape in Esophageal Cancer

Aberrant immune gene expression has been shown to have close correlations with the occurrence and progression of esophageal cancer (EC). We aimed to generate a prognostic signature based on immune-related genes (IRGs) capable of predicting prognosis, immune checkpoint gene (ICG) expressions, and half-inhibitory concentration (IC₅₀) for chemotherapy agents for EC patients. Transcriptome, clinical, and mutation data on tumorous and paratumorous tissues from EC patients were collected from The Cancer Genome Atlas (TCGA) database. Then, we performed differential analysis to identify IRGs differentially expressed in EC. Their biofunctions and related pathways were explored using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. These gene expression profiling data were merged with survival information and subjected to univariate Cox regression to select prognostic genes, which were then included in a Lasso-Cox model for signature generation (risk score calculation). Patients were divided into the high- and low-risk groups using the median risk score as a cutoff. The accuracy of the signature in overall survival prediction was assessed, so were its performances in predicting ICG expressions and IC₅₀ for chemotherapy and targeted therapy agents and immune cell landscape characterization. Fifteen prognostic IRGs were identified, seven of which were optimal for risk score calculation. As expected, high-risk patients had worse overall survival than low-risk individuals. Significant differences were found in tumor staging, immune cell infiltration degree, frequency of tumor mutations, tumor mutation burden (TMB), and immune checkpoint gene expressions between high- vs. low-risk patients. Further, high-risk patients exhibited high predicted IC₅₀ for paclitaxel, cisplatin, doxorubicin, and erlotinib compared to low-risk patients. The seven-IRG-based signature can independently and accurately predict overall survival and tumor progression, characterize the tumor immune microenvironment (TIME) and estimate ICG expressions and IC₅₀ for antitumor therapies. It shows the potential of guiding personalized treatment for EC patients.

Identification of the Shared Gene Signatures and Biological Mechanism in Type 2 Diabetes and Pancreatic Cancer

Background

The relationship between pancreatic cancer (PC) and type 2 diabetes mellitus (T2DM) has long been widely recognized, but the interaction mechanisms are still unknown. This study was aimed to investigate the shared gene signatures and molecular processes between PC and T2DM.

Methods

The Gene Expression Omnibus (GEO) database was used to retrieve the RNA sequence and patient information of PC and T2DM. Weighted gene co-expression network analysis (WGCNA) was performed to discover a co-expression network associated with PC and T2DM. Enrichment analysis of shared genes present in PC and T2DM was performed by ClueGO software. These results were validated in the other four cohorts based on differential gene analysis. The predictive significance of S100A6 in PC was evaluated using univariate and multivariate Cox analyses, as well as Kaplan-Meier plots. The biological process of S100A6 enrichment in PC was detected using Gene Set Enrichment Analysis (GSEA). The involvement of S100A6 in the tumor immune microenvironment (TIME) was assessed by CIBERSORT. In vitro assays were used to further confirm the function of S100A6 in PC.

Results

WGCNA recognized three major modules for T2DM and two major modules for PC. There were 44 shared genes identified for PC and T2DM, and Gene Ontology (GO) analysis showed that regulation of endodermal cell fate specification was primarily enriched. In addition, a key shared gene S100A6 was derived in the validation tests. S100A6 was shown to be highly expressed in PC compared to non-tumor tissues. PC patients with high S100A6 expression had worse overall survival (OS) than those with low expression. GSEA revealed that S100A6 is involved in cancer-related pathways and glycometabolism-related pathways. There is a strong relationship between S100A6 and TIME. In vitro functional assays showed that S100A6 helped to induce the PC cells' proliferation and migration. We also proposed a diagram of common mechanisms of PC and T2DM.

Conclusions

This study firstly revealed that the regulation of endodermal cell fate specification may be common pathogenesis of PC and T2DM and identified S100A6 as a possible biomarker and therapeutic target for PC and T2DM patients.

Construction and Verification of a Combined Hypoxia and Immune Index for Clear Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) is one of the most aggressive malignancies in humans. Hypoxia-related genes are now recognized as a reflection of poor prognosis in cancer patients with cancer. Meanwhile, immune-related genes play an important role in the occurrence and progression of ccRCC. Nevertheless, reliable prognostic indicators based on hypoxia and immune status have not been well established in ccRCC. The aims of this study were to develop a new gene signature model using bioinformatics and open databases and to validate its prognostic value in ccRCC. The data used for the model structure can be accessed from The Cancer Genome Atlas database. Univariate, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analyses were used to identify the hypoxia- and immune-related genes associated with prognostic risk, which were used to develop a characteristic model of prognostic risk. Kaplan-Meier and receiver-operating characteristic curve analyses were performed as well as independent prognostic factor analyses and correlation analyses of clinical characteristics in both the training and validation cohorts. In addition, differences in tumor immune cell infiltrates were compared between the high and low risk groups. Overall, 30 hypoxia- and immune-related genes were identified, and five hypoxia- and immune-related genes (EPO, PLAUR, TEK, TGFA, TGFB1) were ultimately selected. Survival analysis showed that the high-risk score on the hypoxia- and immune-related gene signature was significantly associated with adverse survival outcomes. Furthermore, clinical ccRCC samples from our medical center were used to validate the differential expression of the five genes in tumor tissue compared to normal tissue through quantitative real-time polymerase chain reaction (qRT-PCR). However, more clinical trials are needed to confirm these results, and future experimental studies must verify the potential mechanism behind the predictive value of the hypoxia- and immune-related gene signature.

An Improved Fusion Paired Group Lasso Structured Sparse Canonical Correlation Analysis Based on Brain Imaging Genetics to Identify Biomarkers of Alzheimer’s Disease

Brain imaging genetics can demonstrate the complicated relationship between genetic factors and the structure or function of the humankind brain. Therefore, it has become an important research topic and attracted more and more attention from scholars. The structured sparse canonical correlation analysis (SCCA) model has been widely used to identify the association between brain image data and genetic data in imaging genetics. To investigate the intricate genetic basis of cerebrum imaging phenotypes, a great deal of other standard SCCA methods combining different interested structed have now appeared. For example, some models use group lasso penalty, and some use the fused lasso or the graph/network guided fused lasso for feature selection. However, prior knowledge may not be completely available and the group lasso methods have limited capabilities in practical applications. The graph/network guided approaches can use sample correlation to define constraints, thereby overcoming this problem. Unfortunately, this also has certain limitations. The graph/network conducted methods are susceptible to the sign of the sample correlation of the data, which will affect the stability of the model. To improve the efficiency and stability of SCCA, a sparse canonical correlation analysis model with GraphNet regularization (FGLGNSCCA) is proposed in this manuscript. Based on the FGLSCCA model, the GraphNet regularization penalty is imposed in our study and an optimization algorithm is presented to optimize the model. The structural Magnetic Resonance Imaging (sMRI) and gene expression data are used in this study to find the genotype and characteristics of brain regions associated with Alzheimer’s disease (AD). Experiment results shown that the new FGLGNSCCA model proposed in this manuscript is superior or equivalent to traditional methods in both artificially synthesized neuroimaging genetics data or actual neuroimaging genetics data. It can select essential features more powerfully compared with other multivariate methods and identify significant canonical correlation coefficients as well as captures more significant typical weight patterns which demonstrated its excellent ability in finding biologically important imaging genetic relations.

Bioinformatics and In Silico Findings Uncover Bio-Targets of Calycosin Against Heart Failure and Diabetes Mellitus

BACKGROUND

Heart failure (HF) and diabetes mellitus (DM) are life-threatening diseases. However, existing clinical drugs to treat HF complicated with DM are relatively limited. In this study, we performed a viable bioinformatics strategy combining network pharmacology and molecular docking to identify potential anti-HF and -DM targets and therapeutic mechanisms of calycosin, a functional phytoestrogen.

METHODS

Web-based databases were used to collect candidate genes/targets of calycosin and HF/DM and then identify the hub bio-targets of calycosin against HF/DM. Using the online-available database, all functional processes and signaling pathways of calycosin against HF/DM were screened and identified before further visualization.

RESULTS

All potential bio-targets of calycosin and HF/DM were collected, and 20 hub targets of calycosin against HF/DM were identified. Interestingly, molecular docking findings indicated that mitogen-activated protein kinase-1 (MAPK1), β-arrestin 1 (ARRB1), and homologue-1 (ABL1) may be potent pharmacological targets of calycosin against HF/DM. In addition, all primary molecular functions of calycosin against HF/DM were identified, including regulating protein binding, ubiquitination, and the metabolic process. Furthermore, the top molecular pathways of calycosin against HF/DM were revealed, including cardiomyocyte and chemokine signaling pathways.

CONCLUSION

Our bioinformatics analysis uncovered the network targets and therapeutic mechanisms of calycosin against HF/DM. For the first time, the current in silico findings revealed that the identified hub targets may be used to screen and treat HF/DM.

Prediction of the Molecular Mechanisms Underlying Erlong Zuoci Treatment of Age-Related Hearing Loss via Network Pharmacology-Based Analyses Combined with Experimental Validation

Background: The traditional Chinese medicine formula ErLong ZuoCi (ELZC) has been extensively used to treat age-related hearing loss (ARHL) in clinical practice in China for centuries. However, the underlying molecular mechanisms are still poorly understood.

Objective: Combine network pharmacology with experimental validation to explore the potential molecular mechanisms underlying ELZC with a systematic viewpoint.

Methods: The chemical components of ELZC were collected from the Traditional Chinese Medicine System Pharmacology database, and their possible target proteins were predicted using the SwissTargetPrediction database. The putative ARHL-related target proteins were identified from the database: GeneCards and OMIM. We constructed the drug-target network as well as drug-disease specific protein-protein interaction networks and performed clustering and topological property analyses. Functional annotation and signaling pathways were performed by gene ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis. Finally, in vitro experiments were also performed to validate ELZC’s key target proteins and treatment effects on ARHL.

Results: In total, 63 chemical compounds from ELZC and 365 putative ARHL-related targets were identified, and 1860 ARHL-related targets were collected from the OMIM and GeneCards. A total of 145 shared targets of ELZC and ARHL were acquired by Venn diagram analysis. Functional enrichment analysis suggested that ELZC might exert its pharmacological effects in multiple biological processes, such as cell proliferation, apoptosis, inflammatory response, and synaptic connections, and the potential targets might be associated with AKT, ERK, and STAT3, as well as other proteins. In vitro experiments revealed that ELZC pretreatment could decrease senescence-associated β-galactosidase activity in hydrogen peroxide-induced auditory hair cells, eliminate DNA damage, and reduce cellular senescence protein p21 and p53. Finally, Western blot analysis confirmed that ELZC could upregulate the predicted target ERK phosphorylation.

Conclusion: We provide an integrative network pharmacology approach, in combination with in vitro experiments to explore the underlying molecular mechanisms governing ELZC treatment of ARHL. The protective effects of ELZC against ARHL were predicted to be associated with cellular senescence, inflammatory response, and synaptic connections which might be linked to various pathways such as JNK/STAT3 and ERK cascade signaling pathways. As a prosperous possibility, our experimental data suggest phosphorylation ERK is essential for ELZC to prevent degeneration of cochlear.

Two types of immune infiltrating cells and six hub genes can predict the occurrence of myasthenia gravis in patients with thymoma

Thymoma is the most common primary mass in anterior mediastinum. Although associated with low malignancy, it is often accompanied by myasthenia gravis resulting in poor prognosis. Due to the dual factors of tumor immune tolerance and autoimmune reaction, it is urgent to understand the immune status of MG with thymoma. In this study, RNA sequencing data were obtained from the TCGA and GEO cohorts to identify differentially expressed messenger RNAs and infiltrated immune cells. A total of 121 samples in TCGA and 43 samples in GEO were screened out. The infiltrated immune cells were identified by CIBERSORT, in which Tfh cells and activated DC cells were abnormal in thymoma patients. The differently expressed genes were performed by package LIMMA. The functional characteristics of differently expression genes were analyzed by GO and KEGG; one GO and seven KEGG pathways were both found in both TCGA and GEO cohorts. Meanwhile, 27 common differently expressed genes were obtained and were displayed by a Venn diagram. The TRRUST was used to screen the hub genes for the common 27 different genes and 6 genes were found. Then, PPI networks were constructed. Subsequently, the relationship between SCNAs of common genes and related immune cells tested by TIMER. Kaplan–Meier plots, ROC curve and Cox’s expression model for immune infiltration and hub genes were also tested. In conclusion, we found that two types of immune infiltrated cells and six hub genes can predict the occurrence of myasthenia gravis in thymoma patients.

hsa_circ_0060975 is highly expressed and predicts a poor prognosis in gastric cancer

Gastric cancer (GC) is the fifth most common cancer and GC has a high mortality rate worldwide. Circular (circ) RNAs serve an important role in cancer. The present study aimed to investigate the expression level of hsa_circ_0060975 in gastric cancer (GC) and to determine the clinical pathological significance of hsa_circ_0060975 in patients with GC. Reverse transcription-quantitative PCR was used to detect expression level of hsa_circ_0060975 in 192 GC and adjacent non-cancerous gastric tissues, in GC cell lines (MKN-45, HGC27 and AGS) and a human gastric epithelium cell line (GES-1), as well as in plasma samples from 126 patients with GC and 92 healthy volunteers. All plasma and tissue samples of were obtained from The First Affiliated Hospital of Anhui Medical University (Hefei, China). The relationship between hsa_circ_0060975 expression and clinical pathological factors was analyzed using the χ² test. The diagnostic value of hsa_circ_0060975 was analyzed using the receiver operating characteristic curve (ROC curve), while the Kaplan-Meier method was used to analyze the relationship of hsa_circ_0060975 expression with the survival of patients with GC as determined by log-rank tests. Univariate and multivariate Cox regression analyses were used to identify the prognostic factors, including hsa_circ_0060975 expression and clinical pathological factors. In addition, the potential function of hsa_circ_0060975 was evaluated via bioinformatics analysis. The expression level of hsa_circ_0060975 was higher in GC tissues compared with adjacent non-cancerous gastric tissues, GC cell lines compared with GES-1 and plasma samples from patients with GC compared with plasma samples from healthy volunteers. In addition, higher hsa_circ_0060975 expression was associated with histological grade, pathological stage and tumor (T) classification in GC tissues and plasma samples (P<0.05). The area under the ROC curves of hsa_circ_0060975, the combination with hsa_circ_0060975 and carcinoembryonic antigen (CEA) or CEA alone were 0.804 (sensitivity, 0.746; specificity, 0.783; P<0.001); 0.931 (sensitivity, 0.937; specificity, 0.870; P<0.001) and 0.924 (sensitivity, 0.937; sspecificity, 0.804; P<0.001) respectively. The Kaplan-Meier survival analysis revealed that the overall survival (OS) and disease-free survival (DFS) time of patients with higher hsa_circ_0060975 expression were shorter compared with those in patients with lower hsa_circ_0060975 expression. Univariate and multivariate Cox regression analyses in OS and DFS time determined that the expression level of hsa_circ_0060975, histological grade and pathological stage were independent prognostic factors for patients with GC. In addition, the bioinformatics analysis results suggested that the abnormal expression of hsa_circ_0060975 may serve an important role in tumorigenesis. Hence, hsa_circ_0060975 expression may be an independent prognostic factor for patients with GC and may be a potential marker for biological malignancy.