NPS-2143 inhibit glioma progression by suppressing autophagy through mediating AKT-mTOR pathway.

Gliomas are the most common tumours in the central nervous system. In the present study, we aimed to find a promising anti-glioma compound and investigate the underlying molecular mechanism. Glioma cells were subjected to the 50 candidate compounds at a final concentration of 10 µM for 72 h, and CCK-8 was used to evaluate their cytotoxicity. NPS-2143, an antagonist of calcium-sensing receptor (CASR), was selected for further study due to its potent cytotoxicity to glioma cells. Our results showed that NPS-2143 could inhibit the proliferation of glioma cells and induce G1 phase cell cycle arrest. Meanwhile, NPS-2143 could induce glioma cell apoptosis by increasing the caspase-3/6/9 activity. NPS-2143 impaired the immigration and invasion ability of glioma cells by regulating the epithelial-mesenchymal transition process. Mechanically, NPS-2143 could inhibit autophagy by mediating the AKT-mTOR pathway. Bioinformatic analysis showed that the prognosis of glioma patients with low expression of CASR mRNA was better than those with high expression of CASR mRNA. Gene set enrichment analysis showed that CASR was associated with cell adhesion molecules and lysosomes in glioma. The nude mice xenograft model showed NPS-2143 could suppress glioma growth in vivo. In conclusion, NPS-2143 can suppress the glioma progression by inhibiting autophagy.

Identification of molecular targets and small drug candidates for Huntington's disease via bioinformatics and a network-based screening approach.

Huntington's disease (HD) is a gradually severe neurodegenerative ailment characterised by an increase of a specific trinucleotide repeat sequence (cytosine-adenine-guanine, CAG). It is passed down as a dominant characteristic that worsens over time, creating a significant risk. Despite being monogenetic, the underlying mechanisms as well as biomarkers remain poorly understood. Furthermore, early detection of HD is challenging, and the available diagnostic procedures have low precision and accuracy. The research was conducted to provide knowledge of the biomarkers, pathways and therapeutic targets involved in the molecular processes of HD using informatic based analysis and applying network-based systems biology approaches. The gene expression profile datasets GSE97100 and GSE74201 relevant to HD were studied. As a consequence, 46 differentially expressed genes (DEGs) were identified. 10 hub genes (TPM1, EIF2S3, CCN2, ACTN1, ACTG2, CCN1, CSRP1, EIF1AX, BEX2 and TCEAL5) were further differentiated in the protein-protein interaction (PPI) network. These hub genes were typically down-regulated. Additionally, DEGs-transcription factors (TFs) connections (e.g. GATA2, YY1 and FOXC1), DEG-microRNA (miRNA) interactions (e.g. hsa-miR-124-3p and has-miR-26b-5p) were also comprehensively forecast. Additionally, related gene ontology concepts (e.g. sequence-specific DNA binding and TF activity) connected to DEGs in HD were identified using gene set enrichment analysis (GSEA). Finally, in silico drug design was employed to find candidate drugs for the treatment HD, and while the possible modest therapeutic compounds (e.g. cortistatin A, 13,16-Epoxy-25-hydroxy-17-cheilanthen-19,25-olide, Hecogenin) against HD were expected. Consequently, the results from this study may give researchers useful resources for the experimental validation of Huntington's diagnosis and therapeutic approaches.

Loss of chromosome Y in regulatory T cells.

BACKGROUND: Mosaic loss of chromosome Y (LOY) in leukocytes is the most prevalent somatic aneuploidy in aging humans. Men with LOY have increased risks of all-cause mortality and the major causes of death, including many forms of cancer. It has been suggested that the association between LOY and disease risk depends on what type of leukocyte is affected with Y loss, with prostate cancer patients showing higher levels of LOY in CD4 + T lymphocytes. In previous studies, Y loss has however been observed at relatively low levels in this cell type. This motivated us to investigate whether specific subsets of CD4 + T lymphocytes are particularly affected by LOY. Publicly available, T lymphocyte enriched, single-cell RNA sequencing datasets from patients with liver, lung or colorectal cancer were used to study how LOY affects different subtypes of T lymphocyte. To validate the observations from the public data, we also generated a single-cell RNA sequencing dataset comprised of 23 PBMC samples and 32 CD4 + T lymphocytes enriched samples. RESULTS: Regulatory T cells had significantly more LOY than any other studied T lymphocytes subtype. Furthermore, LOY in regulatory T cells increased the ratio of regulatory T cells compared with other T lymphocyte subtypes, indicating an effect of Y loss on lymphocyte differentiation. This was supported by developmental trajectory analysis of CD4 + T lymphocytes culminating in the regulatory T cells cluster most heavily affected by LOY. Finally, we identify dysregulation of 465 genes in regulatory T cells with Y loss, many involved in the immunosuppressive functions and development of regulatory T cells. CONCLUSIONS: Here, we show that regulatory T cells are particularly affected by Y loss, resulting in an increased fraction of regulatory T cells and dysregulated immune functions. Considering that regulatory T cells plays a critical role in the process of immunosuppression; this enrichment for regulatory T cells with LOY might contribute to the increased risk for cancer observed among men with Y loss in leukocytes.

Revealing the contribution of somatic gene mutations to shaping tumor immune microenvironment.

Interaction between tumor cells and immune cells determined highly heterogeneous microenvironments across patients, leading to substantial variation in clinical benefits from immunotherapy. Somatic gene mutations were found not only to elicit adaptive immunity but also to influence the composition of tumor immune microenvironment and various processes of antitumor immunity. However, due to an incomplete view of associations between gene mutations and immunophenotypes, how tumor cells shape the immune microenvironment and further determine the clinical benefit of immunotherapy is still unclear. To address this, we proposed a computational approach, inference of mutation effect on immunophenotype by integrated gene set enrichment analysis (MEIGSEA), for tracing back the genomic factor responsible for differences in immunophenotypes. MEIGSEA was demonstrated to accurately identify the previous confirmed immune-associated gene mutations, and systematic evaluation in simulation data further supported its performance. We used MEIGSEA to investigate the influence of driver gene mutations on the infiltration of 22 immune cell types across 19 cancers from The Cancer Genome Atlas. The top associated gene mutations with infiltration of CD8 T cells, such as CASP8, KRAS and EGFR, also showed extensive impact on other immune components; meanwhile, immune effector cells shared critical gene mutations that collaboratively contribute to shaping distinct tumor immune microenvironment. Furthermore, we highlighted the predictive capacity of gene mutations that are positively associated with CD8 T cells for the clinical benefit of immunotherapy. Taken together, we present a computational framework to help illustrate the potential of somatic gene mutations in shaping the tumor immune microenvironment.

Effect of ZIC2 on immune infiltration and ceRNA axis regulation in lung adenocarcinoma via bioinformatics and experimental studies.

OBJECTIVE: This study aimed to conclude the effect and mechanism of ZIC2 on immune infiltration in lung adenocarcinoma (LUAD). METHODS: Expression of ZIC2 in several kinds of normal tissues of TCGA data was analyzed and its correlation with the baseline characteristic of LUAD patients were analyzed. The immune infiltration analysis of LUAD patients was performed by CIBERSORT algorithm. The correlation analysis between ZIC2 and immune cell composition was performed. Additionally, the potential upstream regulatory mechanisms of ZIC2 were predicted to identify the possible miRNAs and lncRNAs that regulated ZIC2 in LUAD. In vitro and in vivo experiments were also conducted to confirm the potential effect of ZIC2 on cell proliferation and invasion ability of LUAD cells. RESULTS: ZIC2 expression was decreased in various normal tissues, but increased in multiple tumors, including LUAD, and correlated with the prognosis of LUAD patients. Enrichment by GO and KEGG suggested the possible association of ZIC2 with cell cycle and p53 signal pathway. ZIC2 expression was significantly correlated with T cells CD4 memory resting, Macrophages M1, and plasma cells, indicating that dysregulated ZIC2 expression in LUAD may directly influence immune infiltration. ZIC2 might be regulated by several different lncRNA-mediated ceRNA mechanisms. In vitro experiments validated the promotive effect of ZIC2 on cell viability and invasion ability of LUAD cells. In vivo experiments validated ZIC2 can accelerate tumor growth in nude mouse. CONCLUSION: ZIC2 regulated by different lncRNA-mediated ceRNA mechanisms may play a critical regulatory role in LUAD through mediating the composition of immune cells in tumor microenvironment.

The impact of different levels of wheat diets on hepatic oxidative stress, immune response, and lipid metabolism in Tibetan sheep (Ovis aries).

BACKGROUND: Compared with corn, wheat contains higher crude protein, amino acids concentration. However, wheat contains a mass of anti-nutritional factors, resulting in increased of the digesta viscosity and impaired the intestinal function in ruminant. OBJECTIVE: This study aimed to investigate the effects of substitution of different amounts of wheat for corn on hepatic metabolism in the Tibetan lamb. METHODS: Ninety Tibetan lambs (Body weight = 12.37 ± 0.92 kg) were randomly assigned to three groups: 0% wheat diet (Control), 10% wheat diet (Low group), and 15% wheat diet (High group). The feeding trial lasted for 130 d, including a 10 d adaption period. Hepatic gene expression profiling was performed via RNA sequencing after the conclusion of the feeding trials. RESULTS: Results showed that greater level of glutathione peroxidase levels in L group compared with those of the C and H groups (P < 0.05). The immune indexes, including interleukin-1ß (IL-1ß), immunoglobulin A (IgA), and IgM were also elevated in L group compared with the other groups (P < 0.05). Compared with H group, the hepatocytes were arranged radially, and hepatic plates anastomosed with each other to form a labyrinth-like structure in L group. Transcriptomic analysis showed 872 differentially expressed genes (DEG) between H and L group, of which 755 were down-regulated and 117 were up-regulated. Through Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, 32 pathways were significantly enriched (Q-value < 0.05), such as the cAMP signaling pathway, Th1 and Th2 cell differentiation, leukocyte transendothelial migration, platelet activation and adipocytokine signaling pathway. Additionally, the expression of comment DEGs were verified via quantitative reverse-transcription polymerase chain reaction. CONCLUSION: In summary, our findings suggest that wheat can be supplemented up to 10% in Tibetan sheep, contributing to improve the hepatic oxidative stress, immune response and lipid metabolism through regulating the expression of related genes.

Testing the Significance of Ranked Gene Sets in Genome-wide Transcriptome Profiling Data Using Weighted Rank Correlation Statistics.

Background: Popular gene set enrichment analysis approaches assumed that genes in the gene set contributed to the statistics equally. However, the genes in the transcription factors (TFs) derived gene sets, or gene sets constructed by TF targets identified by the ChIP-Seq experiment, have a rank attribute, as each of these genes have been assigned with a p-value which indicates the true or false possibilities of the ownerships of the genes belong to the gene sets. Objectives: Ignoring the rank information during the enrichment analysis will lead to improper statistical inference. We address this issue by developing of new method to test the significance of ranked gene sets in genome-wide transcriptome profiling data. Methods: A method was proposed by first creating ranked gene sets and gene lists and then applying weighted Kendall's tau rank correlation statistics to the test. After introducing top-down weights to the genes in the gene set, a new software called "Flaver" was developed. Results: Theoretical properties of the proposed method were established, and its differences over the GSEA approach were demonstrated when analyzing the transcriptome profiling data across 55 human tissues and 176 human cell-lines. The results indicated that the TFs identified by our method have higher tendency to be differentially expressed across the tissues analyzed than its competitors. It significantly outperforms the well-known gene set enrichment analyzing tools, GOStats (9%) and GSEA (17%), in analyzing well-documented human RNA transcriptome datasets. Conclusions: The method is outstanding in detecting gene sets of which the gene ranks were correlated with the expression levels of the genes in the transcriptome data.

AgeMeta: Quantitative Gene Expression Database of Mammalian Aging.

AgeMeta is a database that provides systemic and quantitative description of mammalian aging at the level of gene expression. It encompasses transcriptomic changes with age across various tissues of humans, mice, and rats, based on a comprehensive meta-analysis of 122 publicly available gene expression datasets from 26 studies. AgeMeta provides an intuitive visual interface for quantification of aging-associated transcriptomics at the level of individual genes and functional groups of genes, allowing easy comparison among various species and tissues. Additionally, all the data in the database can be downloaded and analyzed independently. Overall, this work contributes to the understanding of the complex network of biological processes underlying mammalian aging and supports future advancements in this field. AgeMeta is freely available at: https://age-meta.com/.

Impact of Acute or Chronic Acidosis and Hypoxia on Gene Expression Patterns in Tumour Cells: Potential Functional Implications.

Tumours often exhibit pronounced hypoxia and hereby extracellular acidosis due to intensified glycolysis. Since metabolic parameters can modulate gene expression, the aim of the study was to analyse changes in gene expression patterns induced by acute (24 h) acidosis or hypoxia and also in tumour cells adapted to long-term acidosis (5 weeks). Three tumour cell lines (AT1 prostate carcinoma, MCF-7, and MDA-MB-231 breast carcinoma) were exposed to acidosis (pH 6.6) or hypoxia (pO2 1.5 mmHg) for 24 h. For long-term acidosis, AT1 tumour cells were continuously cultured at pH 6.6 for 5 weeks. Gene expression was examined by total RNA-sequencing and the functional significance was assessed by gene set enrichment analysis using the Gene Ontology database. Under short-term acidosis (24 h), AT1 and MCF-7 cells showed comparable changes. 714 genes were acidosis-dependently regulated in AT1 cells (275 up, 439 down), and 221 genes in MCF-7 cells (95 up, 126 down). MDA-MB-231 cells almost did not respond to low pH (13 regulated genes). Hypoxia affected MCF-7 cells the most (1498 regulated genes), whereas fewer genes were regulated in AT1 and MDA-MB-231 cells. Concerning the function of the regulated genes by short-term acidosis, RNA processing, cell cycle regulation, DNA synthesis, and mitochondrial function were negatively affected. Chronic acidosis showed a different picture. In AT1 cells, 1160 genes were differentially expressed (638 up, 522 down) when cells exposed to low pH for 5 weeks. The putatively acidosis-induced changes in functions included tissue structural development, RNA processing, and mitochondrial activity. This study shows that both acute and chronic acidosis of tumour cells lead to altered gene expression and thus affect cell function. Long-term acidosis leads to fundamentally different changes, indicating an adaptation process of the tumour cells.

Screening of hub genes for sepsis-induced myopathy by weighted gene co-expression network analysis and protein-protein interaction network construction.

Sepsis-induced myopathy is one of the serious complications of sepsis, which severely affects the respiratory and peripheral motor systems of patients, reduces their quality of life, and jeopardizes their lives, as evidenced by muscle atrophy, loss of strength, and impaired regeneration after injury. The pathogenesis of sepsis-induced myopathy is complex, mainly including cytokine action, enhances free radical production in muscle, increases muscle protein hydrolysis, and decreases skeletal muscle protein synthesis, etc. The above mechanisms have been demonstrated in existing studies. However, it is still unclear how the overall pattern of gene co-expression affects the pathological process of sepsis-induced myopathy. Therefore, we intend to identify hub genes and signaling pathways. Weighted gene co-expression network analysis was our main approach to study gene expression profiles: skeletal muscle transcriptome in ICU patients with sepsis-induced multi-organ failure (GSE13205). After data pre-processing, about 15,181 genes were used to identify 13 co-expression modules. Then, 16 genes (FEM1B, KLHDC3, GPX3, NIFK, GNL2, EBNA1BP2, PES1, FBP2, PFKP, BYSL, HEATR1, WDR75, TBL3, and WDR43) were selected as the hub genes including 3 up-regulated genes and 13 down-regulated genes. Then, Gene Set Enrichment Analysis was performed to show that the hub genes were closely associated with skeletal muscle dysfunction, necrotic and apoptotic skeletal myoblasts, and apoptosis in sepsis-induced myopathy. Overall, 16 candidate biomarkers were certified as reliable features for more in-depth exploration of sepsis-induced myopathy in basic and clinical studies.

Identification and Analysis of DNA Methylation Inflammation-Related Key Genes in Intracerebral Hemorrhage.

Inflammation and DNA methylation have been reported to play key roles in intracerebral hemorrhage (ICH). This study aimed to investigate new diagnostic biomarkers associated with inflammation and DNA methylation using a comprehensive bioinformatics approaches. GSE179759 and GSE125512 were collected from the Gene Expression Omnibus database, and 3222 inflammation-related genes (IFRGs) were downloaded from the Molecular Signatures Database. Key differentially expressed methylation-regulated and inflammation-related genes (DE-MIRGs) were identified by overlapping methylation-regulated differentially expressed genes (MeDEGs) between patients with ICH and control samples, module genes from weighted correlation network analysis, and IFRGs. Functional annotation of DE-MIRGs was performed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). A protein-protein interaction (PPI) network was constructed to clarify the interrelationships between different DE-MIRGs. The key genes were categorized by least absolute shrinkage selection operator (LASSO) and support vector machine-recursive feature elimination (SVM-RFE), and gene set enrichment analysis (GSEA). A total of 22 DE-MIRGs were acquired from 451 MeDEGs, 3222 IFRGs, and 302 module genes, and were mainly enriched in the GO terms of wound healing, blood coagulation, and hemostasis; and the KEGG pathways of PI3K/Akt signaling, focal adhesion, and regulation of actin cytoskeleton. A PPI network with 22 nodes and 87 edges was constructed based on the 22 DE-MIRGs, 11 of which were selected for key gene selection. Two 2 key genes (SELP and S100A4) were identified using LASSO and SVM-RFE. Finally, SELP was mainly enriched in cell morphogenesis involved in differentiation, cytoplasmic translation, and actin binding of GO terms, and the KEGG pathway including endocytosis, focal adhesion, and platelet activation. S100A4 was mainly enriched in GO terms including mitochondrial inner membrane; mitochondrial respirasome and lysosomal membrane; and the KEGG pathway of oxidative phosphorylation, regulation of actin cytoskeleton, and chemical carcinogenesis-reactive oxygen species. Twenty-two DE-MIRGs-associated inflammation and DNA methylation were identified between patients with ICH and normal controls, and two key genes (SELP and S100A4) were identified and regarded as biomarkers for ICH, which could provide the research foundation for further investigation of the pathological mechanism of ICH.

Transcriptome Profiling Associated with CARD11 Overexpression in Colorectal Cancer Implicates a Potential Role for Tumor Immune Microenvironment and Cancer Pathways Modulation via NF-κB.

The immune system plays a critical role in inflammation by initiating responses to infections or tissue damage. The nuclear factor-κB (NF-κB) pathway plays a key role in inflammation and innate immunity, as well as other cellular activities. Dysregulation of this well-choreographed pathway has been implicated in various diseases, including cancer. CARD11 is a key molecule in the BCL10-MALT1 complex, which is involved in transducing the signal downstream of the NF-κB pathway. This study aims to elucidate how CARD11 overexpression exacerbates the prognosis of colorectal cancer (CRC). To identify the cellular pathways influenced by CARD11, transcriptomic analysis in both CRC cell lines and patients was carried out on CARD11- overexpressed HCT-116 and HT-29 CRC cell lines alongside empty vector-transfected cell lines. Furthermore, a comparison of transcriptomic data from adenoma and carcinoma CRC patients with low- (CARD11-) and high-(CARD11+) CARD11 expression was carried out. Whole transcriptomics and bioinformatics analysis results indicate that CARD11 appears to play a key role in CRC progression. Absolute GSEA (absGSEA) on HCT-116 transcriptomics data revealed that CARD11 overexpression promotes cell growth and tissue remodeling and enhances immune response. Key genes co-expressed with CARD11, such as EP300, KDM5A, HIF1A, NFKBIZ, and DUSP1, were identified as mediators of these processes. In the HT-29 cell line, CARD11 overexpression activated pathways involved in chemotaxis and extracellular matrix (ECM) organization, marked by IL1RN, MDK, SPP1, and chemokines like CXCL1, CXCL3, and CCL22, which were shown to contribute to the more invasive stage of CRC. In patient samples, adenoma patients exhibited increased expression of genes associated with the tumor immune microenvironment, such as IL6ST, collagen family members, and CRC transition markers, such as GLI3 and PIEZO2, in CARD11+ adenoma patients. Carcinoma patients showed a dramatic increase in the expression of MAPK8IP2 in CARD11+ carcinoma patients alongside other cancer-related genes, including EMB, EPHB6, and CPEB4.

Gene Expression Reprogramming by Citrate Supplementation Reduces HepG2 Cell Migration and Invasion.

Citrate, which is obtained from oxaloacetate and acetyl-CoA by citrate synthase in mitochondria, plays a key role in both normal and cancer cell metabolism. In this work, we investigated the effect of 10 mM extracellular citrate supplementation on HepG2 cells. Gene expression reprogramming was evaluated by whole transcriptome analysis using gene set enrichment analysis (GSEA). The transcriptomic data were validated through analyzing changes in the mRNA levels of selected genes by qRT-PCR. Citrate-treated cells exhibited the statistically significant dysregulation of 3551 genes; 851 genes were upregulated and 822 genes were downregulated. GSEA identified 40 pathways affected by differentially expressed mRNAs. The most affected biological processes were related to lipid and RNA metabolism. Several genes of the cytochrome P450 family were upregulated in treated cells compared to controls, including the CYP3A5 gene, a tumor suppressor in hepatocellular carcinoma (HCC) that plays an important protective role in HCC metastasis. The citrate-induced dysregulation of cytochromes could both improve the effectiveness of chemotherapeutics used in combination and reduce the aggressiveness of tumors by diminishing cell migration and invasion.

Molecular Regulation of Porcine Skeletal Muscle Development: Insights from Research on CDC23 Expression and Function.

Cell division cycle 23 (CDC23) is a component of the tetratricopeptide repeat (TPR) subunit in the anaphase-promoting complex or cyclosome (APC/C) complex, which participates in the regulation of mitosis in eukaryotes. However, the regulatory model and mechanism by which the CDC23 gene regulates muscle production in pigs are largely unknown. In this study, we investigated the expression of CDC23 in pigs, and the results indicated that CDC23 is widely expressed in various tissues and organs. In vitro cell experiments have demonstrated that CDC23 promotes the proliferation of myoblasts, as well as significantly positively regulating the differentiation of skeletal muscle satellite cells. In addition, Gene Set Enrichment Analysis (GSEA) revealed a significant downregulation of the cell cycle pathway during the differentiation process of skeletal muscle satellite cells. The protein-protein interaction (PPI) network showed a high degree of interaction between genes related to the cell cycle pathway and CDC23. Subsequently, in differentiated myocytes induced after overexpression of CDC23, the level of CDC23 exhibited a significant negative correlation with the expression of key factors in the cell cycle pathway, suggesting that CDC23 may be involved in the inhibition of the cell cycle signaling pathway in order to promote the differentiation process. In summary, we preliminarily determined the function of CDC23 with the aim of providing new insights into molecular regulation during porcine skeletal muscle development.

ROGUE: an R Shiny app for RNA sequencing analysis and biomarker discovery.

BACKGROUND: The growing power and ever decreasing cost of RNA sequencing (RNA-Seq) technologies have resulted in an explosion of RNA-Seq data production. Comparing gene expression values within RNA-Seq datasets is relatively easy for many interdisciplinary biomedical researchers; however, user-friendly software applications increase the ability of biologists to efficiently explore available datasets. RESULTS: Here, we describe ROGUE (RNA-Seq Ontology Graphic User Environment, https://marisshiny. RESEARCH: chop.edu/ROGUE/ ), a user-friendly R Shiny application that allows a biologist to perform differentially expressed gene analysis, gene ontology and pathway enrichment analysis, potential biomarker identification, and advanced statistical analyses. We use ROGUE to identify potential biomarkers and show unique enriched pathways between various immune cells. CONCLUSIONS: User-friendly tools for the analysis of next generation sequencing data, such as ROGUE, will allow biologists to efficiently explore their datasets, discover expression patterns, and advance their research by allowing them to develop and test hypotheses.

PATH-SURVEYOR: pathway level survival enquiry for immuno-oncology and drug repurposing.

Pathway-level survival analysis offers the opportunity to examine molecular pathways and immune signatures that influence patient outcomes. However, available survival analysis algorithms are limited in pathway-level function and lack a streamlined analytical process. Here we present a comprehensive pathway-level survival analysis suite, PATH-SURVEYOR, which includes a Shiny user interface with extensive features for systematic exploration of pathways and covariates in a Cox proportional-hazard model. Moreover, our framework offers an integrative strategy for performing Hazard Ratio ranked Gene Set Enrichment Analysis and pathway clustering. As an example, we applied our tool in a combined cohort of melanoma patients treated with checkpoint inhibition (ICI) and identified several immune populations and biomarkers predictive of ICI efficacy. We also analyzed gene expression data of pediatric acute myeloid leukemia (AML) and performed an inverse association of drug targets with the patient's clinical endpoint. Our analysis derived several drug targets in high-risk KMT2A-fusion-positive patients, which were then validated in AML cell lines in the Genomics of Drug Sensitivity database. Altogether, the tool offers a comprehensive suite for pathway-level survival analysis and a user interface for exploring drug targets, molecular features, and immune populations at different resolutions.

Transcriptomic Establishment of Pig Macrophage Polarization Signatures.

Macrophages are the foremost controllers of innate and acquired immunity, playing important roles in tissue homeostasis, vasculogenesis, and congenital metabolism. In vitro macrophages are crucial models for understanding the regulatory mechanism of immune responses and the diagnosis or treatment of a variety of diseases. Pigs are the most important agricultural animals and valuable animal models for preclinical studies, but there is no unified method for porcine macrophage isolation and differentiation at present; no systematic study has compared porcine macrophages obtained by different methods. In the current study, we obtained two M1 macrophages (M1_IFNγ + LPS, and M1_GM-CSF) and two M2 macrophages (M2_IL4 + IL10, and M2_M-CSF), and compared the transcriptomic profiles between and within macrophage phenotypes. We observed the transcriptional differences either between or within phenotypes. Porcine M1 and M2 macrophages have consistent gene signatures with human and mouse macrophage phenotypes, respectively. Moreover, we performed GSEA analysis to attribute the prognostic value of our macrophage signatures in discriminating various pathogen infections. Our study provided a framework to guide the interrogation of macrophage phenotypes in the context of health and disease. The approach described here could be used to propose new biomarkers for diagnosis in diverse clinical settings including porcine reproductive and respiratory syndrome virus (PRRSV), African swine fever virus (ASFV), Toxoplasma gondii (T. gondii), porcine circovirus type 2 (PCV2), Haemophilus parasuis serovar 4 (HPS4), Mycoplasma hyopneumoniae (Mhp), Streptococcus suis serotype 2 (SS2), and LPS from Salmonella enterica serotype minnesota Re 595.

TRIP 13-dependent pathways promote the development of gastric cancer.

TRIP13 is highly expressed in various human tumors and promotes tumorigenesis. We aimed to explore the biological effect of TRIP13 on gastric cancer. The RNA sequence data were retrieved from TCGA to evaluate TRIP13 mRNA expression in gastric cancer. Paired formalin-fixed paraffin-embedded blocks were further analyzed to verify the relationship between TRIP13 expression and carcinogenic status. The functions of TRIP13 on the proliferation of gastric malignancy were investigated by MTT, flow cytometry, colony formation experiment, and nude mouse tumor formation experiment. Finally, microarray analysis of TRIP13-related pathways was performed to identify the potential underlying mechanism of TRIP13 in gastric cancer. TRIP13 was found to have high expression in tumor samples. TRIP13 expression status was significantly subjective to tumor-node-metastasis (TNM) staging and poor survival. The downregulation of TRIP13 promoted apoptosis and inhibited tumor growth. TRIP13-dependent JAK/STAT and NF-κB signaling cascade were found as two key pathways in the carcinogenesis of GC. In conclusion, TRIP13 participates in the carcinogenesis of stomach cancer, and its overexpression in the cancerous tissues dovetail with advanced stage and survival. Moreover, TRIP13 functions as an upstream regulator of the JAK/STAT and p53 signaling pathways, which play critical roles in developing various malignancies.

Apoptosis pathways and osteoporosis: An approach to genomic analysis.

BACKGROUND: Osteoporosis is a disease of the bone system that causes a decrease in skeletal density and degrades skeletal tissue. Decreased bone quality, so that bones are easily broken, damaged and fractured, is an important public health problem. Previous studies have shown that the maintenance of adult bone mass is not only due to changes in bone marrow and bone cells. By regulating apoptosis, they change the lifespan of each individual. This study influences understanding of the function of apoptosis in the pathogenesis of osteoporosis and the importance of controlling the mechanisms of osteoporosis. METHODS: On the National Institute of Biotechnology Information website, Gene Expression Omnibus (GEO) microarray data and GSE551495 GEO profiles were collected. The gene set enrichment analysis tool was used to confirm the enrichment of genetic sets in relation to the gene set. The collection of C2 gene sets is compiled from the KEGG (https://www.gsea-msigdb.org/gsea/msigdb/human/search.jsp and https://www.kegg.jp/kegg/) online database and REACTOME (https://www.gsea-msigdb.org/gsea/msigdb/human/search.jsp and https://reactome.org/) pathway analysis. The Search Tool for the Retrieval of Interaction Genes (STRING) website was used to construct and select proteins and genes. The comparative toxicological genomic database (CTD) tools can be used to predict the relationship between apoptosis, osteoporosis-related genes and interactions between central genes and osteoporosis. RESULTS: These results generally expand our understanding of the path of apoptosis in osteoporosis. We have discovered genes CASP9, CASP8, CASP3, BAX and TP53 associated with osteoporosis. In activation of KEGG apoptosis and REACTOME, caspase activation through the extrinsic apoptotic signaling pathway is characterized by the identification of a subcollection of C2. Other STRINGs show the formation of protein networks and central gene selection, and CTD can accurately predict the relationship between these apoptosis pathways and central genes. CONCLUSIONS: Our research has highlighted the importance of the osteoporosis pathway associated with osteoporosis apoptosis with several analytical approaches. These results have broadened our understanding of the pathways of osteoporosis apoptosis. It is particularly possible to predict the sensitivity and vulnerability to osteoporosis.

A prognostic model based on regulatory T-cell-related genes in gastric cancer: Systematic construction and validation.

Human gastrointestinal tumours have been shown to contain massive numbers of tumour infiltrating regulatory T cells (Tregs), the presence of which are closely related to tumour immunity. This study was designed to develop new Treg-related prognostic biomarkers to monitor the prognosis of patients with gastric cancer (GC). Treg-related prognostic genes were screened from Treg-related differentially expressed genes in GC patients by using Cox regression analysis, based on which a prognostic model was constructed. Then, combined with RiskScore, survival curve, survival status assessment and ROC analysis, these genes were used to verify the accuracy of the model, whose independent prognostic ability was also evaluated. Six Treg-related prognostic genes (CHRDL1, APOC3, NPTX1, TREML4, MCEMP1, GH2) in GC were identified, and a 6-gene Treg-related prognostic model was constructed. Survival analysis revealed that patients had a higher survival rate in the low-risk group. Combining clinicopathological features, we performed univariate and multivariate regression analyses, with results establishing that the RiskScore was an independent prognostic factor. Predicted 1-, 3- and 5-year survival rates of GC patients had a good fit with the actual survival rates according to nomogram results. In addition patients in the low-risk group had higher tumour mutational burden (TMB) values. Gene Set Enrichment Analysis (GSEA) demonstrated that genes in the high-risk group were significantly enriched in pathways related to immune inflammation, tumour proliferation and migration. In general, we constructed a 6-gene Treg-associated GC prognostic model with good prediction accuracy, where RiskScore could act as an independent prognostic factor. This model is expected to provide a reference for clinicians to estimate the prognosis of GC patients.