Regulation Of MAP Kinase Activity Research Articles

Effects of repeated alcohol abstinence on within-subject prefrontal cortical gene expression in rhesus macaques.

Male rhesus monkeys (n = 24) had a biopsy of prefrontal cortical area 46 prior to chronic ethanol self-administration (n = 17) or caloric control (n = 7). Fourteen months of daily self-administration (water vs. 4% alcohol, 22h access/day termed "open-access") was followed by two cycles of prolonged abstinence (5weeks) each followed by 3months of open-access alcohol and a final abstinence followed by necropsy. At necropsy, a biopsy of Area 46, contralateral to the original biopsy, was obtained. Gene expression data (RNA-Seq) were collected comparing biopsy/necropsy samples. Monkeys were categorized by drinking status during the final post-abstinent drinking phase as light (LD), binge (BD), heavy (HD) and very heavy (VHD drinkers). Comparing pre-ethanol to post-abstinent biopsies, four animals that converted from HD to VHD status had significant ontology enrichments in downregulated genes (necropsy minus biopsy n = 286) that included immune response (FDR < 9 × 10-7) and plasma membrane changes (FDR < 1 × 10-7). Genes in the immune response category included IL16 and 18, CCR1, B2M, TLR3, 6 and 7, SP2 and CX3CR1. Upregulated genes (N = 388) were particularly enriched in genes associated with the negative regulation of MAP kinase activity (FDR < 3 × 10-5), including DUSP 1, 4, 5, 6 and 18, SPRY 2, 3, and 4, SPRED2, BMP4 and RGS2. Overall, these data illustrate the power of the NHP model and the within-subject design of genomic changes due to alcohol and suggest new targets for treating severe escalated drinking following repeated alcohol abstinence attempts.

Network visualization of genes involved in skeletal muscle myogenesis in livestock animals

BackgroundMuscle growth post-birth relies on muscle fiber number and size. Myofibre number, metabolic and contractile capacities are established pre-birth during prenatal myogenesis. The aim of this study was to identify genes involved in skeletal muscle development in cattle, sheep, and pigs - livestock.ResultsThe cattle analysis showed significant differences in 5043 genes during the 135–280 dpc period. In sheep, 444 genes differed significantly during the 70–120 dpc period. Pigs had 905 significantly different genes for the 63–91 dpc period.The biological processes and KEGG pathway enrichment results in each species individually indicated that DEGs in cattle were significantly enriched in regulation of cell proliferation, cell division, focal adhesion, ECM-receptor interaction, and signaling pathways (PI3K-Akt, PPAR, MAPK, AMPK, Ras, Rap1); in sheep - positive regulation of fibroblast proliferation, negative regulation of endothelial cell proliferation, focal adhesion, ECM-receptor interaction, insulin resistance, and signaling pathways (PI3K-Akt, HIF-1, prolactin, Rap1, PPAR); in pigs - regulation of striated muscle tissue development, collagen fibril organization, positive regulation of insulin secretion, focal adhesion, ECM-receptor interaction, and signaling pathways (PPAR, FoxO, HIF-1, AMPK). Among the DEGs common for studied animal species, 45 common genes were identified. Based on these, a protein-protein interaction network was created and three significant modules critical for skeletal muscle myogenesis were found, with the most significant module A containing four recognized hub genes - EGFR, VEGFA, CDH1, and CAV1. Using the miRWALK and TF2DNA databases, miRNAs (bta-miR-2374 and bta-miR-744) and transcription factors (CEBPB, KLF15, RELA, ZNF143, ZBTB48, and REST) associated with hub genes were detected. Analysis of GO term and KEGG pathways showed that such processes are related to myogenesis and associated with module A: positive regulation of MAP kinase activity, vascular endothelial growth factor receptor, insulin-like growth factor binding, focal adhesion, and signaling pathways (PI3K-Akt, HIF-1, Rap1, Ras, MAPK).ConclusionsThe identified genes, common to the prenatal developmental period of skeletal muscle in livestock, are critical for later muscle development, including its growth by hypertrophy. They regulate valuable economic characteristics. Enhancing and breeding animals according to the recognized genes seems essential for breeders to achieve superior gains in high-quality muscle mass.

180 Differences in Gene Expression in Granulosa Cells Harvested from Fertile and Sub-Fertile Beef Heifers

Abstract Infertility in beef replacement heifers is one of the leading contributors to economic losses in the cow-calf sector of the beef production industry. Successful reproduction is complex, involving multiple tissues and biological systems. This complexity makes identifying the leading causes of subfertility difficult. One potential source of fertility issues is poor oocyte health. As developing oocytes are dependent on granulosa cells (GCs) and physically coupled with GCs, we hypothesized that the gene expression profile would be different between the GCs from fertile heifers and those from sub-fertile heifers. The objective of this study was to identify differences in gene expression in GCs collected from beef heifers of differing fertility status, either fertile or sub-fertile. To gather this information, Angus-Simmental crossbred heifers underwent an estrus synchronization and fixed-time artificial insemination (AI) protocol (7-Day CO-synch + CIDR). At 41 days post-AI, heifers were pregnancy checked through ultrasound and palpation. Heifers pregnant to AI were classified as fertile (n = 8). Any heifers that remained non-pregnant following AI were exposed to bulls of proven fertility for 61 days. Bull-exposed heifers were evaluated for pregnancy 34 days after the bulls were removed. The non-pregnant heifers following both AI and natural service were classified as sub-fertile (n = 5). Pregnancies were terminated in fertile heifers, and heifers from both groups were allowed to resume normal cyclicity before GCs being harvested. RNA was extracted from GCs and quality was checked for each sample. Total RNA from GCs of 13 heifers was subjected to the library preparation and sequencing on the Nova-Seq platform. Through the application of DESeq2, 79 genes were identified as significantly differentially expressed genes (DEGs) with P-value &amp;lt; 0.05 and absolute (log2 fold change) &amp;gt; 0.5 including DNER, HOXD10, CD52, CXCL12, and HOXD11. DEGs, along with co-expressed genes, were over-represented in pathways associated with the regulation of MAP kinase activity, regulation of serine/threonine kinase activity, MHC protein binding, and plasma membrane signaling receptor complex. Through the pursuit of knowledge regarding the function of top DEGs, increased sample size, and more diverse sample collection time points, we may improve our understanding of the causation of heifer fertility issues. Improving our knowledge of heifer infertility has the potential to develop therapeutic options, and in turn, increase the efficiency and sustainability of cow-calf production systems.

Network pharmacology-based strategy to investigate the effect and mechanism of α-solanine against glioma

BackgroundAn anti-tumour activity has been demonstrated for α-solanine, a bioactive compound extracted from the traditional Chinese herb Solanum nigrum L. However, its efficacy in the treatment of gliomas and the underlying mechanisms remain unclear. The aim of this study was to investigate the inhibitory effects of α-solanine on glioma and elucidate its mechanisms and targets using network pharmacology, molecular docking, and molecular biology experiments.MethodsTraditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) was utilized to predict the potential targets of α-solanine. GeneCards was used to gather glioma-related targets, and the STRING online database was used to analyze protein–protein interaction (PPI) networks for the shared targets. Hub genes were identified from the resulting PPI network and further investigated using Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Additionally, prognostic and gene set enrichment analyses (GSEA) were carried out to identify potential therapeutic targets and their underlying mechanisms of action in relation to the prognosis of gliomas. In vitro experiments were conducted to verify the findings from the network pharmacology analysis.ResultsA total of 289 α-solanine targets and 1149 glioma-related targets were screened, of which 78 were common targets. 11 hub genes were obtained, including SRC, HRAS, HSP90AA1, IGF1, MAPK1, MAPK14, KDR, STAT1, JAK2, MAP2K1, and IGF1R. The GO and KEGG pathway analyses unveiled that α-solanine was strongly associated with several signaling pathways, including positive regulation of MAP kinase activity and PI3K-Akt. Moreover, α-solanine (10 µM and 15 µM) inhibited the proliferation and migration but promoted the apoptosis of glioma cells. Finally, STAT1 was identified as a potential mediator of the effect of α-solanine on glioma prognosis.Conclusionα-Solanine can inhibit the proliferation and migration of gliomas by regulating multiple targets and signalling pathways. These findings lay the foundation for the creation of innovative clinical anti-glioma agents.

Circulating neutrophils activated by cancer cells and M2 macrophages promote gastric cancer progression during PD-1 antibody-based immunotherapy.

Aims: To analyze the correlation between the neutrophil-to-lymphocyte ratio (NLR) and prognosis of advanced gastric cancer (AGC) patients treated by PD-1 antibody-based therapy and to delineate molecular characteristics of circulating neutrophils by single-cell RNA sequencing (scRNA-seq). Methods: The clinicopathological information of 45 AGC patients receiving PD-1 antibody-based regimens at the Department of Oncology, Ruijin Hospital, was reviewed. Treatment outcomes including objective response rate (ORR), progression-free survival (PFS), and overall survival (OS) were recorded. The correlation between NLR and efficacy of PD-1 antibody-based treatment was analyzed. Single-cell RNA sequencing (scRNA-seq) analysis was performed based on multisite biopsy samples from two AGC patients to explore the molecular characteristics of circulating neutrophils and their pro-tumor mechanisms. Tissue samples from 88 gastric cancer patients who underwent radial gastrectomy were collected for immunochemistry staining. Results: A high posttreatment NLR was associated with poor outcomes of AGC patients receiving PD-1 antibody-based regimens. scRNA-seq analysis showed that an increased number of circulating neutrophils were found in peripheral blood samples after treatment in which neutrophil cluster 1 (NE-1) was the major subcluster. NE-1 was featured with a neutrophil activation phenotype with the high expression of MMP9, S100A8, S100A9, PORK2, and TGF-β1. NE-1 displayed an intermediate state in pseudotime trajectory analysis with gene function enrichment found in neutrophil activation, leukocyte chemotaxis, and negative regulation of MAP kinase activity. Cellular interaction analysis showed that the chemokine signaling pathway is the major interactional pathway of NE-1 between subclusters of malignant epithelial cells (EP-4) and M2 macrophages (M2-1 and M2-2). In turn, the MAPK signaling pathway and Jak-STAT signaling pathway of EP-4, including IL1B/IL1RAP, OSM/OSMR, and TGFB1/TGFBR2 axes, were identified as interacting pathways between EP-4 and NE-1. The high expression of OSMR in tumor cells was closely correlated with lymph node metastasis of gastric cancer. Conclusion: The posttreatment NLR could be a poor prognostic marker of AGC patients treated with immune checkpoint inhibitors (ICIs). Subclusters of circulating neutrophils activated by tumor cells and M2 macrophages could participate in gastric cancer progression through signaling interactions with tumor cells.

Uncovering mechanisms of Baojin Chenfei formula treatment for silicosis by inhibiting inflammation and fibrosis based on serum pharmacochemistry and network analysis

BackgroundBaojin Chenfei formula (BCF), a Chinese herbal formula, has significant effects on improving the clinical symptoms of patients with silicosis. However, its active compounds and the underlying mechanisms have not yet fully been elucidated. PurposeThis study aimed to explore the underlying mechanisms of BCF in treating silicosis. MethodsThe rat model of silicosis was developed via a single intratracheal instillation of SiO2 suspension to examine the therapeutic impacts of BCF on silicosis. Subsequently, the active compounds, targets, and mechanisms of BCF were analyzed based on serum pharmacochemistry and network analysis. Finally, the underlying mechanisms of representative compounds of BCF were validated in vitro experiments. ResultsBCF significantly alleviated SiO2-induced silicosis in rats, evidenced by improved lung function, decreased pathological injury, and reduced inflammatory response and fibrosis. 19 active compounds were identified from the rat serum samples after BCF gavage. Subsequently, 299 targets for these 19 compounds in BCF and 257 genes related to silicosis were collected. 26 overlapping targets, including AKT1, TNF, IL6, MAPK3, EGFR, and others, were obtained from the intersection of the 299 BCF-related targets and 257 silicosis-associated genes. These overlapping targets mainly corresponded to glycyrrhetic acid and paeoniflorin and were mainly associated with positive regulation of smooth muscle cell proliferation, positive regulation of MAP kinase activity, and inflammatory response. In vitro experiments also demonstrated that the representative compounds of BCF (glycyrrhetic acid and paeoniflorin) could suppress inflammatory response by the MAPK pathway, and also inhibited fibroblast activation by the EGFR-PI3K-AKT pathway. ConclusionActive compounds of BCF, such as glycyrrhetic acid and paeoniflorin, could suppress inflammatory response by the MAPK pathway and suppress fibroblast activation by the EGFR-PI3K-AKT pathway. These might be the mechanisms of BCF in treating silicosis.

Protein content of blood-derived extracellular vesicles: An approach to the pathophysiology of cerebral hemorrhage.

Introduction: Extracellular vesicles (EVs) participate in cell-to-cell paracrine signaling and can be biomarkers of the pathophysiological processes underlying disease. In intracerebral hemorrhage, the study of the number and molecular content of circulating EVs may help elucidate the biological mechanisms involved in damage and repair, contributing valuable information to the identification of new therapeutic targets. Methods: The objective of this study was to describe the number and protein content of blood-derived EVs following an intracerebral hemorrhage (ICH). For this purpose, an experimental ICH was induced in the striatum of Sprague-Dawley rats and EVs were isolated and characterized from blood at baseline, 24 h and 28 days. The protein content in the EVs was analyzed by mass spectrometric data-dependent acquisition; protein quantification was obtained by sequential window acquisition of all theoretical mass spectra data and compared at pre-defined time points. Results: Although no differences were found in the number of EVs, the proteomic study revealed that proteins related to the response to cellular damage such as deubiquitination, regulation of MAP kinase activity (UCHL1) and signal transduction (NDGR3), were up-expressed at 24 h compared to baseline; and that at 28 days, the protein expression profile was characterized by a higher content of the proteins involved in healing and repair processes such as cytoskeleton organization and response to growth factors (COR1B) and the regulation of autophagy (PI42B). Discussion: The protein content of circulating EVs at different time points following an ICH may reflect evolutionary changes in the pathophysiology of the disease.

Integrating Network Pharmacology Approaches to Decipher the Multi-Target Pharmacological Mechanism of Microbial Biosurfactants as Novel Green Antimicrobials against Listeriosis.

Listeria monocytogenes (L. monocytogenes) is a serious food-borne pathogen that can cause listeriosis, an illness caused by eating food contaminated with this pathogen. Currently, the treatment or prevention of listeriosis is a global challenge due to the resistance of bacteria against multiple commonly used antibiotics, thus necessitating the development of novel green antimicrobials. Scientists are increasingly interested in microbial surfactants, commonly known as "biosurfactants", due to their antimicrobial properties and eco-friendly nature, which make them an ideal candidate to combat a variety of bacterial infections. Therefore, the present study was designed to use a network pharmacology approach to uncover the active biosurfactants and their potential targets, as well as the signaling pathway(s) involved in listeriosis treatment. In the framework of this study, 15 biosurfactants were screened out for subsequent studies. Among 546 putative targets of biosurfactants and 244 targets of disease, 37 targets were identified as potential targets for treatment of L. monocytogenes infection, and these 37 targets were significantly enriched in a Gene Ontology (GO) analysis, which aims to identify those biological processes, cellular locations, and molecular functions that are impacted in the condition studied. The obtained results revealed several important biological processes, such as positive regulation of MAP kinase activity, protein kinase B signaling, ERK1 and ERK2 cascade, ERBB signaling pathway, positive regulation of protein serine/threonine kinase activity, and regulation of caveolin-mediated endocytosis. Several important KEGG pathways, such as the ERBBB signaling pathway, TH17 cell differentiation, HIF-1 signaling pathway, Yersinia infection, Shigellosis, and C-type lectin receptor signaling pathways, were identified. The protein-protein interaction analysis yielded 10 core targets (IL2, MAPK1, EGFR, PTPRC, TNF, ITGB1, IL1B, ERBB2, SRC, and mTOR). Molecular docking was used in the latter part of the study to verify the effectiveness of the active biosurfactants against the potential targets. Lastly, we found that a few highly active biosurfactants, namely lichenysin, iturin, surfactin, rhamnolipid, subtilisin, and polymyxin, had high binding affinities towards IL2, MAPK1, EGFR, PTPRC, TNF, ITGB1, IL1B, ERBB2, SRC, and mTOR, which may act as potential therapeutic targets for listeriosis. Overall, based on the integrated network pharmacology and docking analysis, we found that biosurfactants possess promising anti-listeriosis properties and explored the pharmacological mechanisms behind their effect, laying the groundwork for further research and development.

Somatic Mutations in T Cells in Patients with Hematological Diseases

Somatic mutations accumulate in cells during aging, and the mutation rate and spectrum vary between tissues. Mutation accumulation can be associated with inflammation: for example, myeloid driver gene mutations in hematopoietic stem cells (clonal hematopoiesis, CH), has been linked with atherosclerosis. Somatic mutations can also accumulate in T cells, where they are connected with immune dysregulation in large granular lymphocytic leukemia, characterized by autoimmunity and STAT3 mutations in T cells. However, the mutation spectrum in T cells in other hematological disorders is not yet fully discovered. We hypothesized that T cell lineage specific somatic mutations are associated with T cell clonality in various diseases involving the hematopoietic system. We systematically characterized the spectrum of somatic mutations in CD4+ and CD8+ T cells in altogether 207 samples from 95 patients with chronic graft-versus-host disease (cGVHD, number of patients: 40), myelodysplastic syndrome (MDS, n = 15), immune thrombocytopenia (n = 2), aplastic anemia (AA, n = 21, previously published), and immunodeficiency (n = 17, previously published). Age at sampling was similar between disease cohorts. DNA was extracted from bead separated CD4+ and CD8+ cells from peripheral blood or bone marrow samples. We applied a custom-made targeted NGS panel, consisting of 2533 immune-related genes. Variant calling was performed using Mutect2. In variant filtering, we used 42 healthy T cell and skin samples as panel of normals. To explore the association between somatic mutations and clonal T cell expansions, we performed TCRb deep sequencing from 148 matched patient samples. With mean sequencing depth of 382x, we identified 888 non-synonymous somatic variants in total. 784 (86%) of the variants were only found in either CD4+ or CD8+ fraction. 52 variants were shared between individual patient's CD4+ and CD8+ T cells, suggesting that they were acquired prior to T cell lineage differentiation. On the average, we observed 3.8 fraction-specific variants per sample. Mean variant allele frequency (VAF) was 4.5% and 12.7% for fraction-specific and shared variants, respectively. Variant types included missense (91%), nonsense (5.1%), splice-site (1.7%), frameshift (1.3%), and non-stop (0.2%) mutations. The most common mutational signatures were age-associated Signature 1 and defective DNA mismatch repair associated Signature 15. Immunodeficiency patients had lower number of fraction-specific variants compared to AA, MDS and cGVHD patients (p = 0.027). In all cohorts, CD8+ T cells had acquired more variants than CD4+ T cells (p = 0.00012; mean [median] for CD8: 4.4 [4] and CD4: 3.2 [2]). The highest fraction-specific VAF in each sample was associated with the largest T cell clone size in CD8+ but not in CD4+ samples (R = 0.59, p = 3.1e-09 and p = ns, respectively). In CD8+ T cells, age was associated with number of fraction-specific variants (R = 0.38, p = 1.1e-4) but not with the highest CD8-specific VAF (p = ns). Among the variants shared between individual patients' CD4+ and CD8+ T cells, we found mutations in DNMT3A (n = 3) and TET2 (n = 2) and ASXL1 (n = 1), the most recurrently mutated CH genes. In addition to shared mutations, in 12% of patients had fraction-specific myeloid driver gene mutations (e.g. DNMT3A, TET2, KRAS, NRAS) in CD4+ or CD8+ T cells. To identify pathways enriched for putative driver mutations, we performed analyses of fraction-specific T cell variants with OncodriveFM. The most significantly mutated gene ontology pathways included T cell co-stimulation, leukocyte migration, Ras protein signal transduction, and positive regulation of MAP kinase activity. In conclusion, T cell fraction-specific somatic mutations are common in patients with various hematological diseases, and they are enriched in pathways important for T cell function. CD8+ T cells accumulate more mutations than CD4+ T cells. In CD8+ T cells, the number of somatic mutations was associated with age, reflecting stochastic accumulation of mutations. Based on mutational signatures, somatic mutations in T cells are mainly result of endogenous mutational processes. In addition, mutational clone size CD8+ T cells was significantly associated with the largest TCR clone, suggesting that mutations have accumulated in expanded CD8+ T cell clones. Further studies are warranted to determine the functional effects of somatic mutations in T cells.

Investigations of nitazoxanide molecular targets and pathways for the treatment of hepatocellular carcinoma using network pharmacology and molecular docking.

Nitazoxanide has been investigated for colorectal cancer and breast cancer. However, its molecular targets and pathways have not yet been explored for hepatocellular carcinoma (HCC) treatment. Utilizing a network pharmacology approach, nitazoxanide’s potential targets and molecular pathways for HCC treatment were investigated. HCC targets were extracted from the GeneCards database. Potential targets of nitazoxanide were predicted using Swiss Target Prediction and Super Pred. Intersecting targets were analyzed with VENNY online tool. Using Cytoscape, a protein-protein interaction (PPI), cluster, and core targets-pathways networks were constructed. Using the Database for Annotation, Visualization and Integrated Discovery (DAVID), gene ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted. The nitazoxanide was molecularly docked with anti-HCC core targets by employing Auto Dock Vina. A total of 168 potential targets of nitazoxanide, 13,415 HCC-related targets, and 153 intersecting targets were identified. The top eight anti-HCC core targets were identified: SRC, EGFR, CASP3, MMP9, mTOR, HIF1A, ERBB2, and PPARG. GO enrichment analysis showed that nitazoxanide might have anti-HCC effects by affecting gene targets involved in multiple biological processes (BP) (protein phosphorylation, transmembrane receptor protein tyrosine kinase (RTKs) signaling pathway, positive regulation of MAP kinase activity, etc.). KEGG pathways and core targets-pathways network analysis indicated that pathways in cancer and proteoglycans in cancer are two key pathways that significantly contribute to the anti-HCC effects of nitazoxanide. Results of molecular docking demonstrated the potential for active interaction between the top eight anti-HCC core targets and nitazoxanide. Our research offers a theoretical basis for the notion that nitazoxanide may have distinct therapeutic effects in HCC, and the identified pharmacological targets and pathways might function as biomarkers for HCC therapy.

Comprehensive Landscape of Immune Infiltration and Aberrant Pathway Activation in Ischemic Stroke.

Ischemic stroke (IS) is a multifactorial disease caused by the interaction of multiple environmental and genetic risk factors, and it is the most common cause of disability. The immune microenvironment and inflammatory response participate in the whole process of IS occurrence and development. Therefore, the rational use of relevant markers or characteristic pathways in the immune microenvironment will become one of the important therapeutic strategies for the treatment of IS. We collected peripheral blood samples from 10 patients diagnosed with IS at the First Affiliated Hospital of Gannan Medical University and First Affiliated Hospital, Jinan" University, and from 10 normal people. The GSE16561 dataset was downloaded from the Gene Expression Omnibus (GEO) database. xCell, gene set enrichment analysis (GSEA), single-sample GSEA (ssGSEA) and immune-related gene analysis were used to evaluate the differences in the immune microenvironment and characteristic pathways between the IS and control groups of the two datasets. xCell analysis showed that the IS-24h group had significantly reduced central memory CD8+ T cell, effector memory CD8+ T cell, B cell and Th1 cell scores and significantly increased M1 macrophage and macrophage scores. GSEA showed that the IS-24h group had significantly increased inflammation-related pathway activity(myeloid leukocyte activation, positive regulation of tumor necrosis factor biosynthetic process, myeloid leukocyte migration and leukocyte chemotaxis), platelet-related pathway activity(platelet activation, signaling and aggregation; protein polymerization; platelet degranulation; cell-cell contact zone) and pathology-related pathway activity (ERBB signaling pathway, positive regulation of ERK1 and ERK2 cascade, vascular endothelial growth factor receptor signaling pathway, and regulation of MAP kinase activity). Immune-related signature analysis showed that the macrophage signature, antigen presentation-related signature, cytotoxicity-related signature, B cell-related signature and inflammation-related signature were significantly lower in the IS-24h group than in the control group. In this study, we found that there were significant differences in the immune microenvironment between the peripheral blood of IS patients and control patients, as shown by the IS group having significantly reduced CD8+ Tcm, CD8+ Tem, B cell and Th1 cell scores and significantly increased macrophage and M1 macrophage scores. Additionally, inflammation-related, pathological, and platelet-related pathway activities were significantly higher in the IS group than in the control group.

Screening and identification of potential biomarkers and therapeutic drugs in melanoma via integrated bioinformatics analysis.

Melanoma is a highly aggressive malignant skin tumor with a high rate of metastasis and mortality. In this study, a comprehensive bioinformatics analysis was used to clarify the hub genes and potential drugs. Download the GSE3189, GSE22301, and GSE35388 microarray datasets from the Gene Expression Omnibus (GEO), which contains a total of 33 normal samples and 67 melanoma samples. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) approach analyze DEGs based on the DAVID. Use STRING to construct protein-protein interaction network, and use MCODE and cytoHubba plug-ins in Cytoscape to perform module analysis and identified hub genes. Use Gene Expression Profile Interactive Analysis (GEPIA) to assess the prognosis of genes in tumors. Finally, use the Drug-Gene Interaction Database (DGIdb) to screen targeted drugs related to hub genes. A total of 140 overlapping DEGs were identified from the three microarray datasets, including 59 up-regulated DEGs and 81 down-regulated DEGs. GO enrichment analysis showed that these DEGs are mainly involved in the biological process such as positive regulation of gene expression, positive regulation of cell proliferation, positive regulation of MAP kinase activity, cell migration, and negative regulation of the apoptotic process. The cellular components are concentrated in the membrane, dendritic spine, the perinuclear region of cytoplasm, extracellular exosome, and membrane raft. Molecular functions include protein homodimerization activity, calmodulin-binding, transcription factor binding, protein binding, and cytoskeletal protein binding. KEGG pathway analysis shows that these DEGs are mainly related to protein digestion and absorption, PPAR signaling pathway, signaling pathways regulating stem cells' pluripotency, and Retinol metabolism. The 23 most closely related DEGs were identified from the PPI network and combined with the GEPIA prognostic analysis, CDH3, ESRP1, FGF2, GBP2, KCNN4, KIT, SEMA4D, and ZEB1 were selected as hub genes, which are considered to be associated with poor prognosis of melanoma closely related. Besides, ten related drugs that may have therapeutic effects on melanoma were also screened. These newly discovered genes and drugs provide new ideas for further research on melanoma.

Network Pharmacology-Based Strategy for Predicting Therapy Targets of Traditional Chinese Medicine Xihuang Pill on Liver Cancer.

Objective To investigate the potential therapy targets and pharmacological mechanism of traditional Chinese medicine (TCM) Xihuang pill in liver cancer based on network pharmacology. Methods Drug ingredients-target network was constructed based on the target sets of Xihuang pill and liver cancer. The overlapping genes between Xihuang pill targets and liver cancer-related molecular targets were investigated using comparative analysis. Moreover, the PPI network and module was constructed based on overlapping genes and hub nodes, respectively, followed by the pathway enrichment analysis. Results A drug ingredients-target network was established with 1184 nodes and 11035 interactions. Moreover, a total of 106 overlapping genes were revealed between drug targets and liver cancer molecular targets. Furthermore, a PPI network and 4 modules were further investigated based on overlapping genes, respectively. These hub nodes such as VEGFA and EGFR were mainly enriched in GO functions including positive regulation of MAP kinase activity, activation of protein kinase activity, regulation of MAP kinase activity, and pathways like proteoglycans in cancer, bladder cancer, and estrogen signaling. Conclusion VEGFA and EGFR might be potential therapy targets of Xihuang pill in liver cancer. Furthermore, the effect of Xihuang pill on liver cancer might be realized by targeting VEGFA and EGFR in pathways like proteoglycans in cancer and estrogen signaling.

Identification of key miRNAs in papillary thyroid carcinoma based on data mining and bioinformatics methods.

MicroRNAs (miRNAs) are a class of short (approximately 22 nucleotides), non-coding and endogenous RNA molecules that play pivotal roles in the occurrence and development of cancer. The present study aimed to investigate key miRNAs involved in papillary thyroid carcinoma (PTC). Two independent datasets (GSE73182 and GSE113629) were obtained from the GEO database. The differentially expressed miRNAs (DEmiRNAs) between PTC tissues and normal thyroid tissues were analyzed by GEO2R with the Limma R package. Key miRNAs in PTC were identified by the VennDiagram R package. The targets of the key miRNAs were predicted by miRWalk and were functionally enriched by clusterProfiler R package. Five miRNAs including hsa-miR-146b-5p, hsa-miR-15a-5p, hsa-miR-21-5p, hsa-miR-221-3p and hsa-miR-222-3p were identified as key miRNAs in PTC. The expression levels of these key miRNAs were upregulated in PTC. This finding was also confirmed in the other dataset. Target prediction of miRNAs indicated that hsa-miR-146b-5p, hsa-miR-15a-5p, hsa-miR-21-5p, hsa-miR-221-3p and hsa-miR-222-3p exhibited 2, 41, 3, 14 and 8 target genes, respectively. Enrichment analysis indicated that these key miRNAs were mainly involved in nine biological processes, such as regulation of MAP kinase activity, JNK cascade signaling and regulation of protein serine/threonine kinase activity) and in 28 pathways, including the mitogen associated protein kinase, the sphingolipid, ErbB, Ras and the C-type lectin receptor signaling pathways. In conclusion, the present study identified several key miRNAs in PTC, which serve as potential targets for PTC diagnosis and treatment.

GoSTAG: gene ontology subtrees to tag and annotate genes within a set

BackgroundOver-representation analysis (ORA) detects enrichment of genes within biological categories. Gene Ontology (GO) domains are commonly used for gene/gene-product annotation. When ORA is employed, often times there are hundreds of statistically significant GO terms per gene set. Comparing enriched categories between a large number of analyses and identifying the term within the GO hierarchy with the most connections is challenging. Furthermore, ascertaining biological themes representative of the samples can be highly subjective from the interpretation of the enriched categories.ResultsWe developed goSTAG for utilizing GO Subtrees to Tag and Annotate Genes that are part of a set. Given gene lists from microarray, RNA sequencing (RNA-Seq) or other genomic high-throughput technologies, goSTAG performs GO enrichment analysis and clusters the GO terms based on the p-values from the significance tests. GO subtrees are constructed for each cluster, and the term that has the most paths to the root within the subtree is used to tag and annotate the cluster as the biological theme. We tested goSTAG on a microarray gene expression data set of samples acquired from the bone marrow of rats exposed to cancer therapeutic drugs to determine whether the combination or the order of administration influenced bone marrow toxicity at the level of gene expression. Several clusters were labeled with GO biological processes (BPs) from the subtrees that are indicative of some of the prominent pathways modulated in bone marrow from animals treated with an oxaliplatin/topotecan combination. In particular, negative regulation of MAP kinase activity was the biological theme exclusively in the cluster associated with enrichment at 6 h after treatment with oxaliplatin followed by control. However, nucleoside triphosphate catabolic process was the GO BP labeled exclusively at 6 h after treatment with topotecan followed by control.ConclusionsgoSTAG converts gene lists from genomic analyses into biological themes by enriching biological categories and constructing GO subtrees from over-represented terms in the clusters. The terms with the most paths to the root in the subtree are used to represent the biological themes. goSTAG is developed in R as a Bioconductor package and is available at https://bioconductor.org/packages/goSTAG

Deciphering transcriptome profiles of peripheral blood mononuclear cells in response to PRRSV vaccination in pigs.

BackgroundPorcine reproductive and respiratory syndrome (PRRS) is one of the most economically important viral diseases affecting swine industry worldwide. Despite routine farm vaccination, effective control strategies for PRRS remained elusive which underscores the need for in-depth studies to gain insight into the host immune response to vaccines. The current study aimed to investigate transcriptional responses to PRRS Virus (PRRSV) vaccine in the peripheral blood mononuclear cells (PBMCs) within 3 days following vaccination in German Landrace pigs.ResultsTranscriptome profiling of PBMCs from PRRSV vaccinated and age-matched unvaccinated pigs at right before (0 h), and at 6, 24 and 72 h after PRRSV vaccination was performed using the Affymetrix gene chip porcine gene 1.0 st array. Comparison of PBMCs transcriptome profiles between vaccinated and unvaccinated pigs revealed a distinct host innate immune transcriptional response to PRRSV vaccine. There was a significant temporal variation in transcriptional responses of PRRSV vaccine in PBMCs accounting 542, 2,263 and 357 differentially expressed genes (DEGs) at 6, 24 and 72 h post vaccination, respectively compared to the time point before vaccination (controls). Gene ontology analysis revealed the involvement of these DEGs in various biological process including innate immune response, signal transduction, positive regulation of MAP kinase activity, TRIF-dependent toll-like receptor signaling pathway, T cell differentiation and apoptosis. Immune response specific pathways such as cytokine-cytokine receptor interaction, chemokine signaling pathway, signal transduction, JAK-STAT pathway and regulation, TRAF6 mediated induction of NF-kB and MAPK, the NLRP3 inflammasome, endocytosis and interferon signaling were under regulation during the early stage of PRRSV vaccination. Network enrichment analysis revealed APP, TRAF6, PIN1, FOS, CTNNB1, TNFAIP3, TIP1, CDKN1, SIRT1, ESR1 and HDAC5 as the highly interconnected hubs of the functional network of PRRSV vaccine induced transcriptome changes in PBMCs.ConclusionsThis study showed that a massive gene expression change occurred in PBMCs following PRRSV vaccination in German Landrace pigs. Within first 3 days of vaccine exposure, the highest transcript abundance was observed at 24 h after vaccination compared to that of control. Results of this study suggest that APP, TRAF6, PIN1, FOS, CDKN1A and TNFAIP3 could be considered as potential candidate genes for PRRSV vaccine responsiveness.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-016-2849-1) contains supplementary material, which is available to authorized users.

Abstract 2778: Interaction of Microsatellite Instability (MSI) and tumor for Differential DNA Methylation in Colorectal carcinoma

Abstract Introduction: Colorectal Cancer (CRC) is one of the most common malignancies worldwide. The role of MSI and KRAS somatic mutation in tumor tissue is well known in CRC. In genome-wide scale, we explored whether differential methylation is associated with MSI status. Methods: We carried out a genome-wide methylation assay (Illumina 450K) for a total of 250 paired samples from 125 CRC patients (m = 72, f = 53) at different stages (stage1:25, stage II: 33 and stageIII: 67). Of them 101 had left-sided (descending colon to rectum) CRC and 30 had MSI, and 34 had somatic mutation in KRAS (rs112445441). Results: MSI was more frequent in the right-sided tumor (54% vs. 17%, p = 0.003). Frequency of KRAS mutation was not different between right and left-sided CRC (29% vs. 27%). Among the patients with microsatellite stable (MSS) CRC (n = 95), paired comparison of methylation data between tumor and corresponding normal tissue revealed a total of 1641 tumor-specific differentially methylated loci (DML) covering 686 genes that were significant at FDR 0.001 and the magnitude of difference (delta beta) was at least 20%; Similar analysis in patients with MSI (n = 30) revealed 6209 tumor-specific DML covering 2316 genes. This suggested that MSI is associated with methylation change in much larger number of genes. We could not find any methylation signature from normal colon tissue that could predict MSI or KRAS mutation in the corresponding tumor tissue. However, we identified 413 genes to be differentially methylated in tumor tissue compared to corresponding normal tissue only in presence of MSI, irrespective of KRAS mutation status, tumor staging, and location of tumor. These are “MSI-associated tumor-specific genes”. Among these, 19 DML covering17 genes showed delta-beta &amp;gt;30%. The list was enriched in genes associated with biologically relevant GO-terms like, “negative regulation of cell proliferation”, “regulation of MAP kinase activity”, “regulation of biological process” etc. We also identified 240 genes differentially methylated in tumor tissue compared to corresponding normal tissue irrespective of MSI status, KRAS mutation, tumor staging, and location of tumor. These are “general tumor-specific genes”. Among these loci, 87 DML (49 genes) showed delta-beta &amp;gt;30%. Conclusions: Our study shows evidence of association between MSI and DNA methylation in the pathogenesis of CRC. Citation Format: Muhammad G. Kibriya, Mohammed Kamal, Mustafizur Rahman, Shantanu Roy, Maruf Raza, Rupash Paul, Habibul Ahsan, Zahidul Haq, Farzana Jasmine. Interaction of Microsatellite Instability (MSI) and tumor for Differential DNA Methylation in Colorectal carcinoma. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 2778.

Genomic convergence and network analysis approach to identify candidate genes in Alzheimer's disease

BackgroundAlzheimer’s disease (AD) is one of the leading genetically complex and heterogeneous disorder that is influenced by both genetic and environmental factors. The underlying risk factors remain largely unclear for this heterogeneous disorder. In recent years, high throughput methodologies, such as genome-wide linkage analysis (GWL), genome-wide association (GWA) studies, and genome-wide expression profiling (GWE), have led to the identification of several candidate genes associated with AD. However, due to lack of consistency within their findings, an integrative approach is warranted. Here, we have designed a rank based gene prioritization approach involving convergent analysis of multi-dimensional data and protein-protein interaction (PPI) network modelling.ResultsOur approach employs integration of three different AD datasets- GWL,GWA and GWE to identify overlapping candidate genes ranked using a novel cumulative rank score (SR) based method followed by prioritization using clusters derived from PPI network. SR for each gene is calculated by addition of rank assigned to individual gene based on either p value or score in three datasets. This analysis yielded 108 plausible AD genes. Network modelling by creating PPI using proteins encoded by these genes and their direct interactors resulted in a layered network of 640 proteins. Clustering of these proteins further helped us in identifying 6 significant clusters with 7 proteins (EGFR, ACTB, CDC2, IRAK1, APOE, ABCA1 and AMPH) forming the central hub nodes. Functional annotation of 108 genes revealed their role in several biological activities such as neurogenesis, regulation of MAP kinase activity, response to calcium ion, endocytosis paralleling the AD specific attributes. Finally, 3 potential biochemical biomarkers were found from the overlap of 108 AD proteins with proteins from CSF and plasma proteome. EGFR and ACTB were found to be the two most significant AD risk genes.ConclusionsWith the assumption that common genetic signals obtained from different methodological platforms might serve as robust AD risk markers than candidates identified using single dimension approach, here we demonstrated an integrated genomic convergence approach for disease candidate gene prioritization from heterogeneous data sources linked to AD.Electronic supplementary materialThe online version of this article (doi:10.1186/1471-2164-15-199) contains supplementary material, which is available to authorized users.

Changes in Gene Expression Profiles in Patients with 5q- Syndrome Caused by Lenalidomide Treatment

Abstract 5023A direct effects of lenalidomide on gene expression in 5q- patients was studied using HumanRef-8 v2 Expression BeadChips (Illumina). Expression profiles of 6 patients (before treatment and at the time of the first erytroid response) and 6 healthy controls were investigated from CD14+ monocytes of peripheral blood. Differentially expressed genes were identified by Significance Analysis of Microarrays (SAM). Simultaneously, selected genes (TNF, JUN, IL1) were monitored in the course of treatment using Real-Time PCR with Taqman Gene Expression Assays.A comparison of gene expression levels before and during lenalidomide treatment revealed 97 differentially expressed genes (FC >2; p<0.05) related to following biological processes: immune response (16 genes), inflammatory response (11 genes), response to bacteria (8 genes), anti-apoptosis (7 genes), regulation of MAP kinase activity (5 genes), oxygen transport (4 genes), and regulation of cell proliferation (11 genes). An overexpression of a number of cytokines (e.g. TNF, IL8, IL1B, CCL3L, CXCL2, and TNFAIP3) was detected in patients before treatment, after lenalidomide administration expression of the majority of the up-regulated cytokine genes decreased to the control baseline level. Detected overproduction of the cytokines in 5q- syndrome may lead to an increased apoptosis of hematopoietic progenitor cells and together with excessive oxidative stress may contribute to the damage the hematopoietic niche. In the same manner, untreated patients showed suppressed expression of two genes (CXCR4, CRTAP) which play an important role in the stem cell niche. After treatment, we detected increased expression of these genes. Both the observations might explain favorable effects of lenalidomide on the bone marrow stroma defect seen in 5q- syndrome. On the other hand, a substantial increase of the ARPC1B gene (an activator and a substrate of Aurora A) expression was detected after lenalidomide treatment. Since overexpression of Aurora A leads to polyploidy and chromosomal instability, ARPC1B might play a role in the disease progression observed in some patients treated with lenalidomide.To conclude, described changes in genes expression may contribute to identification of the pathways affected by lenalidomide and to the explanation of some effects of this drug that have not been fully understood yet.Supported by grants NS/9634 MZCR, UHKT2005 00023736, MSM0021620808 and COST EUGESMA Disclosures:No relevant conflicts of interest to declare.

Differential regulation of MAP kinase activation by a novel splice variant of human MAP kinase phosphatase-2

MAP kinase phosphatase-2 (MKP-2) is a member of the family of dual specificity phosphatases that functions to inactivate the ERK and JNK MAP kinase signalling pathways. Here, we identify a novel human MKP-2 variant (MKP-2-S) lacking the MAP kinase binding site but retaining the phosphatase catalytic domain. Endogenous MKP-2-S transcripts and proteins were found in PC3 prostate and MDA-MB-231 breast cancer cells and also human prostate biopsies. Cellular transfection of MKP-2-S gave rise to a nuclear protein of 33kDa which displayed phosphatase activity comparable to the formerly described long form of MKP-2 (MKP-2-L). Due to its lack of a kinase interacting motif (KIM), MKP-2-S did not bind to JNK or ERK; MKP-2-L bound ERK and to a lesser extent JNK. Protein turnover of adenoviral expressed MKP-2-S was accelerated relative to MKP-2-L, with a greater susceptibility to proteosomal-mediated degradation. MKP-2-S retained its ability to deactivate JNK in a similar manner as MKP-2-L and was an effective inhibitor of LPS-stimulated COX-2 induction. However, unlike MKP-2-L, MKP-2-S was unable to reverse serum-induced ERK activation or significantly inhibit endothelial cell proliferation. These findings reveal the occurrence of a novel splice variant of MKP-2 which is unable to bind ERK and may be significant in the dysregulation of MAP kinase activity in certain disease states, particularly in breast and prostate cancers.