Differential expression analysis identifies a prognostically significant extracellular matrix-enriched gene signature in hyaluronan-positive clear cell renal cell carcinoma.

Hyaluronan (HA) accumulation in clear cell renal cell carcinoma (ccRCC) is associated with poor prognosis; however, its biology and role in tumorigenesis are unknown. RNA sequencing of 48 HA-positive and 48 HA-negative formalin-fixed paraffin-embedded (FFPE) samples was performed to identify differentially expressed genes (DEG). The DEGs were subjected to pathway and gene enrichment analyses. The Cancer Genome Atlas Kidney Renal Clear Cell Carcinoma (TCGA-KIRC) data and DEGs were used for the cluster analysis. In total, 129 DEGs were identified. HA-positive tumors exhibited enhanced expression of genes related to extracellular matrix (ECM) organization and ECM receptor interaction pathways. Gene set enrichment analysis showed that epithelial-mesenchymal transition-associated genes were highly enriched in the HA-positive phenotype. A protein-protein interaction network was constructed, and 17 hub genes were discovered. Heatmap analysis of TCGA-KIRC data identified two prognostic clusters corresponding to HA-positive and HA-negative phenotypes. These clusters were used to verify the expression levels and conduct survival analysis of the hub genes, 11 of which were linked to poor prognosis. These findings enhance our understanding of hyaluronan in ccRCC.

Identification and validation of a prognostic anoikis-related gene signature in papillary thyroid carcinoma by integrated analysis of single-cell and bulk RNA-sequencing.

Papillary thyroid carcinoma (PTC) prognosis may be deteriorated due to the metastases, and anoikis palys an essential role in the tumor metastasis. However, the potential effect of anoikis-related genes on the prognosis of PTC was unclear. The mRNA and clinical information were obtained from the cancer genome atlas database. Hub genes were identified and risk model was constructed using Cox regression analysis. Kaplan-Meier (K-M) curve was applied for the survival analysis. Immune infiltration and immune therapy response were calculated using CIBERSORT and TIDE. The identification of cell types and cell interaction was performed by Seurat, SingleR and CellChat packages. GO, KEGG, and GSVA were applied for the enrichment analysis. Protein-protein interaction network was constructed in STRING and Cytoscape. Drug sensitivity was assessed in GSCA. Based on bulk RNA data, we identified 4 anoikis-related risk signatures, which were oncogenes, and constructed a risk model. The enrichment analysis found high risk group was enriched in some immune-related pathways. High risk group had higher infiltration of Tregs, higher TIDE score and lower levels of monocytes and CD8 T cells. Based on scRNA data, we found that 4 hub genes were mainly expressed in monocytes and macrophages, and they interacted with T cells. Hub genes were significantly related to immune escape-related genes. Drug sensitivity analysis suggested that cyclin dependent kinase inhibitor 2A may be a better chemotherapy target. We constructed a risk model which could effectively and steadily predict the prognosis of PTC. We inferred that the immune escape may be involved in the development of PTC.

Research in revealing the effects on Cuscuta chinensis to diarrhea type irritable bowel syndrome based on network pharmacology and molecular docking potential mechanism.

To explore the potential mechanism in Cuscuta sinensis on diarrhea-type irritable bowel syndrome using network pharmacology and molecular docking techniques. First, the active components and related targets of Cuscuta were found setting oral utilization >30% and drug-like properties greater than or equal to 0.18 as filter information from TCMSP database. The targets of diarrheal irritable bowel syndrome were compiled by searching DrugBank, GeneCards, OMIM, PharmGkb, and TTD databases. The intersections of drugs and targets related to the disease were taken for gene ontology enrichment and Kyoto encyclopedia of genes and genomes enrichment analyses, to elucidate the potential molecular mechanisms and pathway information of Cuscuta sinensis for the treatment of diarrheal irritable bowel syndrome. The protein-protein interaction network was constructed by using the STRING database and visualized with Cytoscape_v3.10.0 software to find the protein-protein interaction network core At last, molecular docking was performed to validate the combination of active compounds with the core target. The target information of Cuscuta and diarrhea-type irritable bowel syndrome was compiled, which can be resulted in 11 active compounds such as quercetin, kaempferol, isorhamnetin, ß-sitosterol, and another 17 core targets such as TP53, IL6, AKT1, IL1B, TNF, EGFR, etc, whose Kyoto encyclopedia of genes and genomes was enriched in the pathways of lipids and atherosclerosis, chemical carcinogenesis-receptor activation, PI3K-Akt signaling pathway, and fluid shear stress and atherosclerosis, etc. Docking demonstrated that the core targets and the active compounds were able to be better combined. Cuscuta chinensis may exert preventive effects on diarrhea-type irritable bowel syndrome by reducing intestinal inflammation, protecting intestinal mucosa, and playing an important role in antioxidant response through multi-targets and multi-pathways.

Uncovering the molecular mechanism of Mume Fructus in treatment of Sjögren's syndrome.

BACKGROUND: Modern medicine has no cure for the xerostomia caused by the early onset of Sjögren's syndrome. Mume Fructus is a common Chinese herbal medicine used to relieve xerostomia. However, the molecular mechanisms of the effects of Mume Fructus are unknown. In this study, network pharmacology and molecular docking were used to investigate the mechanisms of action of Mume Fructus on Sjögren's syndrome. MATERIALS AND METHOD: The Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform database was used to identify the active components and targets of Mume Fructus, and the UniProt database was used to identify the genes encoding these targets. SS-related targets were also identified from the GeneCards and OMIM databases. By finding the intersection of the targets of the compounds and the targets of Sjögren's syndrome, the predicted targets of Mume Fructus in the treatment of Sjögren's syndrome were obtained. Further investigation of the active compounds and their targets was carried out by constructing a network of "medicine-candidate compound-target-disease" using Cytoscape 3.7.2, the Protein-Protein Interaction network using the STRING database and Cytoscape 3.7.2, and key targets were identified by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis on R software. Finally, molecular docking was used to verify the affinity of the candidate compounds to the key targets. RESULTS: Quercetin, beta-sitosterol, and kaempferol in Mume Fructus interact with AKT1, IL-6, IL-1B, JUN, CASP3, and MAPK8. These results suggest that Mume Fructus exerts its therapeutic effects on the peripheral gland injury of Sjögren's syndrome and its secondary cardiovascular disease and tumorigenesis through anti-inflammatory, anti-oxidant, and anti-tumor pathways. CONCLUSION: With network pharmacology, this study systematically identified the main active components, targets, and specific mechanisms of the therapeutic effects of Mume Fructus on Sjögren's syndrome, providing both a theoretical basis and research direction for further investigations on Mume Fructus.

Analysing the Cyanobacterial PipX Interaction Network Using NanoBiT Complementation in Synechococcus elongatus PCC7942.

The conserved cyanobacterial protein PipX is part of a complex interaction network with regulators involved in essential processes that include metabolic homeostasis and ribosome assembly. Because PipX interactions depend on the relative levels of their different partners and of the effector molecules binding to them, in vivo studies are required to understand the physiological significance and contribution of environmental factors to the regulation of PipX complexes. Here, we have used the NanoBiT complementation system to analyse the regulation of complex formation in Synechococcus elongatus PCC 7942 between PipX and each of its two best-characterized partners, PII and NtcA. Our results confirm previous in vitro analyses on the regulation of PipX-PII and PipX-NtcA complexes by 2-oxoglutarate and on the regulation of PipX-PII by the ATP/ADP ratio, showing the disruption of PipX-NtcA complexes due to increased levels of ADP-bound PII in Synechococcus elongatus. The demonstration of a positive role of PII on PipX-NtcA complexes during their initial response to nitrogen starvation or the impact of a PipX point mutation on the activity of PipX-PII and PipX-NtcA reporters are further indications of the sensitivity of the system. This study reveals additional regulatory complexities in the PipX interaction network, opening a path for future research on cyanobacteria.

Hypothesis: evidence that the PRS gene products of Saccharomyces cerevisiae support both PRPP synthesis and maintenance of cell wall integrity.

The gene products of PRS1-PRS5 in Saccharomyces cerevisiae are responsible for the production of PRPP (5-phospho-D-ribosyl-α-1-pyrophosphate). However, it has been demonstrated that they are also involved in the cell wall integrity (CWI) signalling pathway as shown by protein-protein interactions (PPIs) with, for example Slt2, the MAP kinase of the CWI pathway. The following databases: SGD, BioGRID and Hit Predict, which collate PPIs from various research papers, have been scrutinized for evidence of PPIs between Prs1-Prs5 and components of the CWI pathway. The level of certainty in PPIs was verified by interaction scores available in the Hit Predict database revealing that well-documented interactions correspond with higher interaction scores and can be graded as high confidence interactions based on a score > 0.28, an annotation score ≥ 0.5 and a method-based high confidence score level of ≥ 0.485. Each of the Prs1-Prs5 polypeptides shows some degree of interaction with the CWI pathway. However, Prs5 has a vital role in the expression of FKS2 and Rlm1, previously only documented by reporter assay studies. This report emphasizes the importance of investigating interactions using more than one approach since every method has its limitations and the use of different methods, as described herein, provides complementary experimental and statistical data, thereby corroborating PPIs. Since the experimental data described so far are consistent with a link between PRPP synthetase and the CWI pathway, our aim was to demonstrate that these data are also supported by high-throughput bioinformatic analyses promoting our hypothesis that two of the five PRS-encoding genes contain information required for the maintenance of CWI by combining data from our targeted approach with relevant, unbiased data from high-throughput analyses.

Transcriptomic analysis revealed potential regulatory biomarkers and repurposable drugs for breast cancer treatment.

Breast cancer (BC) is the most widespread cancer worldwide. Over 2 million new cases of BC were identified in 2020 alone. Despite previous studies, the lack of specific biomarkers and signaling pathways implicated in BC impedes the development of potential therapeutic strategies. We employed several RNAseq datasets to extract differentially expressed genes (DEGs) based on the intersection of all datasets, followed by protein-protein interaction network construction. Using the shared DEGs, we also identified significant gene ontology (GO) and KEGG pathways to understand the signaling pathways involved in BC development. A molecular docking simulation was performed to explore potential interactions between proteins and drugs. The intersection of the four datasets resulted in 146 DEGs common, including AURKB, PLK1, TTK, UBE2C, CDCA8, KIF15, and CDC45 that are significant hub-proteins associated with breastcancer development. These genes are crucial in complement activation, mitotic cytokinesis, aging, and cancer development. We identified key microRNAs (i.e., hsa-miR-16-5p, hsa-miR-1-3p, hsa-miR-147a, hsa-miR-195-5p, and hsa-miR-155-5p) that are associated with aggressive tumor behavior and poor clinical outcomes in BC. Notable transcription factors (TFs) were FOXC1, GATA2, FOXL1, ZNF24 and NR2F6. These biomarkers are involved in regulating cancer cell proliferation, invasion, and migration. Finally, molecular docking suggested Hesperidin, 2-amino-isoxazolopyridines, and NMS-P715 as potential lead compounds against BC progression. We believe that these findings will provide important insight into the BC progression as well as potential biomarkers and drug candidates for therapeutic development.

On the mechanism of wogonin against acute monocytic leukemia using network pharmacology and experimental validation.

Wogonin is a natural flavone compound from the plant Scutellaria baicalensis, which has a variety of pharmacological activities such as anti-cancer, anti-virus, anti-inflammatory, and immune regulation. However, the potential mechanism of wogonin remains unknown. This study was to confirm the molecular mechanism of wogonin for acute monocytic leukemia treatment, known as AML-M5. The potential action targets between wogonin and acute monocytic leukemia were predicted from databases. The compound-target-pathway network and protein-protein interaction network (PPI) were constructed. The enrichment analysis of related targets and molecular docking were performed. The network pharmacological results of wogonin for AML-M5 treatment were verified using the THP-1 cell line. 71 target genes of wogonin associated with AML-M5 were found. The key genes TP53, SRC, AKT1, RELA, HSP90AA1, JUN, PIK3R1, and CCND1 were preliminarily found to be the potential central targets of wogonin for AML-M5 treatment. The PPI network analysis, GO analysis and KEGG pathway enrichment analysis demonstrated that the PI3K/AKT signaling pathway was the significant pathway in the wogonin for AML-M5 treatment. The antiproliferative effects of wogonin on THP-1 cells of AML-M5 presented a dose-dependent and time-dependent manner, inducing apoptosis, blocking the cell cycle at the G2/M phase, decreasing the expressions of CCND1, CDK2, and CyclinA2 mRNA, as well as AKT and p-AKT proteins. The mechanisms of wogonin on AML-M5 treatment may be associated with inhibiting cell proliferation and regulating the cell cycle via the PI3K/AKT signaling pathway.

Exploring the mechanism of Jinlida granules against type 2 diabetes mellitus by an integrative pharmacology strategy.

Jinlida granule (JLD) is a Traditional Chinese Medicine (TCM) formula used for the treatment of type 2 diabetes mellitus (T2DM). However, the mechanism of JLD treatment for T2DM is not fully revealed. In this study, we explored the mechanism of JLD against T2DM by an integrative pharmacology strategy. Active components and corresponding targets were retrieved from Traditional Chinese Medicine System Pharmacology (TCMSP), SwissADME and Bioinformatics Analysis Tool for Molecular Mechanisms of Traditional Chinese Medicine Database (BATMAN-TCM) database. T2DM-related targets were obtained from Drugbank and Genecards databases. The protein-protein interaction (PPI) network was constructed and analyzed with STRING (Search Toll for the Retrieval of Interacting Genes/proteins) and Cytoscape to get the key targets. Then, Gene Ontology (GO) and Kyoto Encyclopedia of Gene and Genomes (KEGG) enrichment analyses were performed with the Database for Annotation, Visualization and Integrated Discovery (DAVID). Lastly, the binding capacities and reliability between potential active components and the targets were verified with molecular docking and molecular dynamics simulation. In total, 185 active components and 337 targets of JLD were obtained. 317 targets overlapped with T2DM-related targets. RAC-alpha serine/threonine-protein kinase (AKT1), tumor necrosis factor (TNF), interleukin-6 (IL-6), cellular tumor antigen p53 (TP53), prostaglandin G/H synthase 2 (PTGS2), Caspase-3 (CASP3) and signal transducer and activator of transcription 3 (STAT3) were identified as seven key targets by the topological analysis of the PPI network. GO and KEGG enrichment analyses showed that the effects were primarily associated with gene expression, signal transduction, apoptosis and inflammation. The pathways were mainly enriched in PI3K-AKT signaling pathway and AGE-RAGE signaling pathway in diabetic complications. Molecular docking and molecular dynamics simulation verified the good binding affinity between the key components and targets. The predicted results may provide a theoretical basis for drug screening of JLD and a new insight for the therapeutic effect of JLD on T2DM.

[Auxiliary diagnosis and prognosis evaluation of KIF4A, RAD51AP1 and CDKN3 in esophageal cancer].

To investigate the expression of mRNA in esophageal cancer (ESCA) tissues and its potential and diagnostic and prognostic value by high-throughput sequencing data. Using the Cancer Genome Atlas Program (TCGA) database in USA by integrative bioinformatics analysis methods, the gene expression profiles and clinical data of 173 patients with ECSA were collected. The mRNA expression levels in ESCA tissue and para-cancerous tissue samples were analyzed using DESeq2, edgeR and limma to screen the differentially expressed genes (DEGs). DEGs-related protein network diagrams were drawn. GO and KEGG function enrichment analysis were performed and the hub genes were screened and the survival analysis of hub genes was analyzed. Genes related to the prognosis of ESCA were selected and their prognostic value in ESCA was analyzed. Finally, the receiver operating characteristic curve was drawn to evaluate its diagnostic value. The results showed that using TCGA cancer data, a total of 620 up-regulated DEGs and 668 down-regulated DEGs with significant differential expression between ESCA and para-cancerous tissues were screened. DEGs were mainly involved in receptor complexes, ubiquitin ligase complexes, etc., playing GTPase activity, phospholipid binding, and other molecular functions, and participating in the regulation of intracellular substance transport, small molecule metabolism, and other biological processes. Protein functional enrichment analysis showed that these proteins were mainly enriched in the IL-17 signaling pathway, TNF signaling pathway, Toll-like receptor signaling pathway, Epstein-Barr virus infection, neutrophil extracellular trap formation, and other pathways involved in the formation and development process of ESCA. Survival analysis showed that the overall survival rate of ESCA patients with high expression of KIF4A, RAD51AP1, and CDKN3 was significantly shortened, and the difference was statistically significant (P<0.05). Furthermore, the areas under the curve (AUC) of KIF4A, RAD51AP1, and CDKN3 for diagnosing esophageal cancer were 0.956, 0.951 and 0.979, respectively, with sensitivities and specificities both exceeding 80%. Additionally, ROC results of the combined diagnostic model of these three genes showed an AUC of 0.979, with sensitivities and specificities of 0.914 and 1, respectively. This indicates that KIF4A, RAD51AP1 and CDKN3 have individual or combined auxiliary diagnostic value for ESCA. In conclusion, KIF4A, RAD51AP1 and CDKN3 have high diagnostic efficiency for ESCA, and their increased expression is closely related to the prognosis, suggesting that these three genes could be used as auxiliary diagnostic and prognostic factors for ESCA.

Role of CENPF and NDC80 in the rehabilitation nursing of hepatocellular carcinoma and cirrhosis: An observational study.

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors globally and often develops on the foundation of chronic liver disease or cirrhosis. Cirrhosis is a clinically prevalent chronic progressive liver disease characterized by diffuse liver damage resulting from long-term or repeated actions of 1 or more etiological factors. However, the impact of CENPF and nuclear division cycle 80 (NDC80) genes on rehabilitation nursing of HCC and cirrhosis remains unclear. HCC and cirrhosis datasets GSE63898 and GSE89377 profile files were downloaded from the gene expression omnibus database generated on platforms GPL13667 and GPL6947, respectively. Differentially expressed genes (DEGs) screening, weighted gene co-expression network analysis (WGCNA), construction and analysis of protein-protein interaction (PPI) networks, functional enrichment analysis, gene set enrichment analysis (GSEA), survival analysis, immune infiltration analysis, and comparative toxicogenomics database (CTD) analysis were conducted. Gene expression heatmaps were plotted. miRNAs regulating central DEGs were selected through TargetScan. A total of 626 DEGs were identified. According to gene ontology (GO) analysis, they were primarily enriched in small molecule metabolic processes, drug metabolic processes, binding of identical proteins, and lipid metabolic processes. Kyoto Encyclopedia of Gene and Genome (KEGG) analysis results indicated that the target genes were mainly enriched in metabolic pathways, phagosomes, glycine, serine, and threonine metabolism. The construction and analysis of the PPI network revealed 3 core genes (NDC80, CENPF, RRM2). Gene expression heatmaps showed that core genes (CENPF, NDC80) were highly expressed in HCC and cirrhosis samples. CTD analysis found that 2 genes (CENPF and NDC80) were associated with liver, jaundice, ascites, fever, dyspepsia, and hepatic encephalopathy. CENPF and NDC80 are highly expressed in HCC and cirrhosis, and CENPF and NDC80 might be the biomarkers of rehabilitation nursing of HCC and cirrhosis.

MYC and NCAPG2 as molecular targets of colorectal cancer and gastric cancer in nursing.

Colorectal cancer is a common malignant tumor in intestinal tract, the early symptoms are not obvious. Gastric cancer is a malignant tumor originating from the gastric mucosal epithelium. However, the role of MYC and non-SMC condensin II complex subunit G2 (NCAPG2) in colorectal cancer and gastric cancer remains unclear. The colorectal cancer datasets GSE49355 and gastric cancer datasets GSE19826 were downloaded from gene expression omnibus database. Differentially expressed genes (DEGs) were screened and weighted gene co-expression network analysis (WGCNA) was performed. Functional enrichment analysis, gene set enrichment analysis (GSEA) and immune infiltration analysis was performed. Construction and analysis of protein-protein interactions (PPI) network. Survival analysis and comparative toxicogenomics database (CTD) were performed. A heat map of gene expression was drawn. A total of 751 DEGs were obtained. According to the gene ontology (GO) analysis, in Biological process (BP) analysis, they are mainly enriched in cell differentiation, cartilage development, and skeletal development. In cellular component (CC) analysis, they are mainly enriched in the cytoskeleton of muscle cells and actin filaments. In molecular function (MF) analysis, they are mainly concentrated in Rho GTPase binding, DNA binding, and fibronectin binding. In Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis, they are mainly enriched in the MAPK signaling pathway, apoptosis, and cancer pathways. The soft threshold power for WGCNA analysis was set to 9, resulting in the generation of 40 modules. Ultimately, 2 core genes (MYC and NCAPG2) were identified. The heatmap of core gene expression showed high expression of MYC and NCAPG2 in colorectal cancer tissue samples and low expression in normal tissue samples, while they were core molecules in gastric cancer. Survival analysis indicated that MYC and NCAPG2 were risk factors, showing an upregulation trend with increasing risk scores. CTD analysis revealed associations of MYC and NCAPG2 with colorectal cancer, gastric cancer, inflammation, and immune system diseases. MYC and NCAPG2 are highly expressed in colorectal cancer. The higher the expression of MYC and NCAPG2, the worse the prognosis. MYC and NCAPG2 are core molecules in gastric cancer.

Integration of multi-omics data for survival prediction of lung adenocarcinoma.

BACKGROUND AND OBJECTIVE: The morbidity of lung adenocarcinoma (LUAD) has been increasing year by year and the prognosis is poor. This has prompted researchers to study the survival of LUAD patients to ensure that patients can be cured in time or survive after appropriate treatment. There is still no fully valid model that can be applied to clinical practice. METHODS: We introduced struc2vec-based multi-omics data integration (SBMOI), which could integrate gene expression, somatic mutations and clinical data to construct mutation gene vectors representing LUAD patient features. Based on the patient features, the random survival forest (RSF) model was used to predict the long- and short-term survival of LUAD patients. To further demonstrate the superiority of SBMOI, we simultaneously replaced scale-free gene co-expression network (FCN) with a protein-protein interaction (PPI) network and a significant co-expression network (SCN) to compare accuracy in predicting LUAD patient survival under the same conditions. RESULTS: Our results suggested that compared with SCN and PPI network, the FCN based SBMOI combined with RSF model had better performance in long- and short-term survival prediction tasks for LUAD patients. The AUC of 1-year, 5-year, and 10-year survival in the validation dataset were 0.791, 0.825, and 0.917, respectively. CONCLUSIONS: This study provided a powerful network-based method to multi-omics data integration. SBMOI combined with RSF successfully predicted long- and short-term survival of LUAD patients, especially with high accuracy on long-term survival. Besides, SBMOI algorithm has the potential to combine with other machine learning models to complete clustering or stratificational tasks, and being applied to other diseases.

Mining and exploration of rehabilitation nursing targets for colorectal cancer.

BACKGROUND: There are often subtle early symptoms of colorectal cancer, a common malignancy of the intestinal tract. However, it is not yet clear how MYC and NCAPG2 are involved in colorectal cancer. METHOD: We obtained colorectal cancer datasets GSE32323 and GSE113513 from the Gene Expression Omnibus (GEO). After downloading, we identified differentially expressed genes (DEGs) and performed Weighted Gene Co-expression Network Analysis (WGCNA). We then undertook functional enrichment assay, gene set enrichment assay (GSEA) and immune infiltration assay. Protein-protein interaction (PPI) network construction and analysis were undertaken. Survival analysis and Comparative Toxicogenomics Database (CTD) analysis were conducted. A gene expression heat map was generated. We used TargetScan to identify miRNAs that are regulators of DEGs. RESULTS: 1117 DEGs were identified. Their predominant enrichment in activities like the cellular phase of the cell cycle, in cell proliferation, in nuclear and cytoplasmic localisation and in binding to protein-containing complexes was revealed by Gene Ontology (GO). When the enrichment data from GSE32323 and GSE113513 colon cancer datasets were merged, the primary enriched DEGs were linked to the cell cycle, protein complex, cell cycle control, calcium signalling and P53 signalling pathways. In particular, MYC, MAD2L1, CENPF, UBE2C, NUF2 and NCAPG2 were identified as highly expressed in colorectal cancer samples. Comparative Toxicogenomics Database (CTD) demonstrated that the core genes were implicated in the following processes: colorectal neoplasia, tumour cell transformation, inflammation and necrosis. CONCLUSIONS: High MYC and NCAPG2 expression has been observed in colorectal cancer, and increased MYC and NCAPG2 expression correlates with worse prognosis.

Berberine alleviates neuroinflammation by downregulating NFκB/LCN2 pathway in sepsis-associated encephalopathy: network pharmacology, bioinformatics, and experimental validation.

BACKGROUND: Sepsis refers to a systemic inflammatory response caused by infection, involving multiple organs. Sepsis-associated encephalopathy (SAE), as one of the most common complications in patients with severe sepsis, refers to the diffuse brain dysfunction caused by sepsis without central nervous system infection. However, there is no clear diagnostic criteria and lack of specific diagnostic markers. METHODS: The main active ingredients of coptidis rhizoma(CR) were identified from TCMSP and SwissADME databases. SwissTargetPrediction and PharmMapper databases were used to obtain targets of CR. OMIM, DisGeNET and Genecards databases were used to explore targets of SAE. Limma differential analysis was used to identify the differential expressed genes(DEGs) in GSE167610 and GSE198861 datasets. WGCNA was used to identify feature module. GO and KEGG enrichment analysis were performed using Metascape, DAVID and STRING databases. The PPI network was constructed by STRING database and analyzed by Cytoscape software. AutoDock and PyMOL software were used for molecular docking and visualization. Cecal ligation and puncture(CLP) was used to construct a mouse model of SAE, and the core targets were verified in vivo experiments. RESULTS: 277 common targets were identified by taking the intersection of 4730 targets related to SAE and 509 targets of 9 main active ingredients of CR. 52 common DEGs were mined from GSE167610 and GSE198861 datasets. Among the 25,864 DEGs in GSE198861, LCN2 showed the most significant difference (logFC = 6.9). GO and KEGG enrichment analysis showed that these 52 DEGs were closely related to "inflammatory response" and "innate immunity". A network containing 38 genes was obtained by PPI analysis, among which LCN2 ranked the first in Degree value. Molecular docking results showed that berberine had a well binding affinity with LCN2. Animal experiments results showed that berberine could inhibit the high expression of LCN2,S100A9 and TGM2 induced by CLP in the hippocampus of mice, as well as the high expression of inflammatory factors (TNFα, IL-6 and IL-1ß). In addition, berberine might reduce inflammation and neuronal cell death by partially inhibiting NFκB/LCN2 pathway in the hippocampus of CLP models, thereby alleviating SAE. CONCLUSION: Overall, Berberine may exert anti-inflammatory effects through multi-ingredients, multi-targets and multi-pathways to partially rescue neuronal death and alleviate SAE.

Integrative analysis based on the cell cycle-related genes identifies TPX2 as a novel prognostic biomarker associated with tumor immunity in breast cancer.

BACKGROUND: This study aims to identify the essential cell cycle-related genes associated with prognosis in breast cancer (BRCA), and to verify the relationship between the central gene and immune infiltration, so as to provide detailed and comprehensive information for the treatment of BRCA. MATERIALS AND METHODS: Gene expression profiles (GSE10780, GSE21422, GSE61304) and the Cancer Genome Atlas (TCGA) BRCA data were used to identify differentially expressed genes (DEGs) and further functional enrichment analysis. STRING and Cytoscape were employed for the protein-protein interaction (PPI) network construction. TPX2 was viewed as the crucial prognostic gene by the Survival and Cox analysis. Furthermore, the connection between TPX2 expression and immune infiltrating cells and immune checkpoints in BRCA was also performed by the TIMER online database and R software. RESULTS: A total of 18 cell cycle-related DEGs were identified in this study. Subsequently, an intersection analysis based on TCGA-BRCA prognostic genes and the above DEGs identified three genes (TPX2, UBE2C, CCNE2) as crucial prognostic candidate biomarkers. Moreover, we also demonstrated that TPX2 is closely associated with immune infiltration in BRCA and a positive relation between TPX2 and PD-L1 expression was firstly detected. CONCLUSIONS: These results revealed that TPX2 is a potential prognostic biomarker and closely correlated with immune infiltration in BRCA, which could provide powerful and efficient strategies for breast cancer immunotherapy.

Proteomic and metabolomic insights into seed germination of Ferula assa-foetida.

Cold stratification is known to affect the speed of seed germination; however, its regulation at the molecular level in Ferula assa-foetida remains ambiguous. Here, we used cold stratification (4 °C in the dark) to induce germination in F. assa-foetida and adopted a proteomic and metabolomic approach to understand the molecular mechanism of germination. Compared to the control, we identified 209 non-redundant proteins and 96 metabolites in germinated F. assa-foetida seed. Results highlight the common and unique regulatory mechanisms like signaling cascade, reactivation of energy metabolism, activation of ROS scavenging system, DNA repair, gene expression cascade, cytoskeleton, and cell wall modulation in F. assa-foetida germination. A protein-protein interaction network identifies 18 hub protein species central to the interactome and could be a key player in F. assa-foetida germination. Further, the predominant metabolic pathways like glucosinolate biosynthesis, arginine and proline metabolism, cysteine and methionine metabolism, aminoacyl-tRNA biosynthesis, and carotenoid biosynthesis in germinating seed may indicate the regulation of carbon and nitrogen metabolism is prime essential to maintain the physiology of germinating seedlings. The findings of this study provide a better understanding of cold stratification-induced seed germination, which might be utilized for genetic modification and traditional breeding of Ferula assa-foetida. SIGNIFICANCE: Seed germination is the fundamental checkpoint for plant growth and development, which has ecological significance. Ferula assa-foetida L., commonly known as "asafoetida," is a medicinal and food crop with huge therapeutic potential. To date, our understanding of F. assa-foetida seed germination is rudimentary. Therefore, studying the molecular mechanism that governs dormancy decay and the onset of germination in F. assa-foetida is essential for understanding the basic principle of seed germination, which could offer to improve genetic modification and traditional breeding.

An integrated analysis of the anticarcinogenic role of forkhead box protein 1 in oesophageal squamous cell carcinoma.

Forkhead box protein 1 (FOXP1) serves as a tumour promoter or suppressor depending on different cancers, but its effect in oesophageal squamous cell carcinoma has not been fully elucidated. This study investigated the role of FOXP1 in oesophageal squamous cell carcinoma through bioinformatics analysis and experimental verification. We determined through public databases that FOXP1 expresses low in oesophageal squamous cell carcinoma compared with normal tissues, while high expression of FOXP1 indicates a better prognosis. We identified potential target genes regulated by FOXP1, and explored the potential biological processes and signalling pathways involved in FOXP1 in oesophageal squamous cell carcinoma through GO and KEGG enrichment, gene co-expression analysis, and protein interaction network construction. We also analysed the correlation between FOXP1 and tumour immune infiltration levels. We further validated the inhibitory effect of FOXP1 on the proliferation of oesophageal squamous cell carcinoma cells through CCK-8, colony formation and subcutaneous tumour formation assays. This study revealed the anticarcinogenic effect of FOXP1 in oesophageal squamous cell carcinoma, which may serve as a novel biological target for the treatment of tumour.

Identification of drug responsible glycogene signature in liver carcinoma from meta-analysis using RNA-seq data.

Glycans have attracted much attention in cancer therapeutic strategies, and cell surface proteins and lipids with glycans are known to be altered during the carcinogenic process. However, our understanding of how the glycogenes profile responds to drug stimulation remains incomplete. In this study, we search public databases for Sequence Read Archive data on drug-treated liver cancer cells, with the aim to comprehensively analyze the drug responses of glycogenes via bioinformatic meta-analysis. The study comprised 86 datasets, encompassing eight distinct liver cancer cell lines and 13 different drugs. Differentially expressed genes were quantified, and 399 glycogenes were identified. The glycogenes signature was then analyzed using bioinformatics methodologies. In the Protein-protein interaction network analysis, we identified drug-responsive glycogenes such as Beta-1,4-Galactosyltransferase 1, GDP-Mannose 4,6-Dehydratase, UDP-Glucose Ceramide Glucosyltransferase, and Solute Carrier Family 2 Member 4 as key glycan biomarkers. In the enrichment analysis using the pathway list of glycogenes, the results also demonstrated that drug stimulation resulted in alterations to glycopathway-related genes involved in several processes, namely O-Mannosylation, POMGNT2 Type, Capping, Heparan Sulfate Sulfation, and Glucuronidation pathways. These genes and pathways commonly exhibit variable expression across multiple liver cancer cells in response to the same drug, making them potential targets for new cancer therapies. In addition to their primary roles, drugs may also participate in the regulation of glycans. The insights from this study could pave the way for the development of liver cancer therapies that target the regulation of gene profiles involved in the biosynthesis of glycans.

Identification of core genes of craniopharyngioma angiogenesis based on single-cell nuclear transcriptome sequencing.

This study aimed to explore the core genes of craniopharyngioma angiogenesis for targeted vascular therapy based on single-cell nuclear transcriptome sequencing. For single-cell nuclear transcriptome sequencing, we collected six samples from the tumor center and adjacent hypothalamic tumor tissues from three patients with craniopharyngioma, as well as four normal brain tissues based on Gene Expression Omnibus. We screened genes with differential up-regulation between vascular endothelial cells of craniopharyngioma and those of normal brain tissues, performed GO and KEGG analysis, constructed the protein-protein interaction network, and selected key genes verified using immunofluorescence. After data cleaning and quality control, 623 craniopharyngioma endothelial cells and 439 healthy brain endothelial cells were obtained. Compared with normal brain endothelial cells, craniopharyngioma endothelial cells were screened for 394 differentially up-expressed genes (DEGs). GO and KEGG results showed that DEGs probably modulated endothelial cells, adherens junction, focal adhesion, migration, actin cytoskeleton, and invasion via the PI3K-AKT, Rap1, Ras, Wnt, and Hippo pathways. The core genes screened were CTNNB1, PTK2, ITGB1, STAT3, FYN, HIF1A, VCL, SMAD3, PECAM1, FOS, and CDH5. This study obtained possible anti-angiogenic genes in craniopharyngioma. Our results shed novel insights into molecular mechanisms and craniopharyngioma treatment.