Search

BACKGROUND LIM domain proteins play crucial roles in tumors by interacting with diverse proteins. However, their roles in the course of colorectal mucosa-adenoma-carcinoma remain unclear. This study aimed to depict their dynamic expression profiles and elucidate their potential functions in this transition course. MATERIAL AND METHODS Differentially-expressed LIM proteins (DELGs) in paired adenomas, carcinomas, and mucosae were identified using the GEO dataset (GSE 117606) and validated by immunohistochemistry using our tissue microarray. Kaplan-Meier survival analysis, WGCNA, module-trait analysis, and KEGG enrichment were conducted. The correlation of DELGs expression levels with immune infiltration was assessed using the ESTIMATE package and TISCH database. The role of DELGs of interest was validated using cell proliferation, migration, and invasion assays. RESULTS Four DELGs were identified - LMO3, FHL1, NEBL, and TGFB1I1 - all of which were of significance in prognosis. Module-trait correlation and KEGG enrichment revealed their involvement in cancer-related signaling. Immunohistochemistry showed gradual downregulation of LMO3 but upregulation of NEBL in the mucosa-adenoma-carcinoma sequence. The opposite expression patterns were observed for FHL1 and TGFB1I1 in tumor epithelium and mesenchyme. High expression levels of the DELGs were correlated with increased infiltration of NK, NKT, and macrophages, except for NEBL. Importantly, LMO3 inhibited proliferation, migration, and invasion of colon epithelial cells. CONCLUSIONS This study identified 4 differentially-expressed LIM genes - LMO3, FHL1, TGFB1I1, and NEBL - and revealed they were involved in the mucosa-adenoma-carcinoma sequence via regulating cancer-related pathways, influencing epigenetic field, or affecting immune infiltration. Our findings provide new insights into the roles of LIM proteins in the course of mucosa-adenoma-carcinoma.

Extensive infiltration of tumor-associated macrophages was correlated poor prognosis in anaplastic thyroid cancer (ATC). However, the heterogeneity and characteristics of the ATC-associated macrophages (ATAMs) in ATC remain far from clear. We combined single-cell RNA-sequencing analysis and gene expression microarray datasets to assess the molecular signature of ATAMs. Compared with normal thyroid-associated macrophages (NTAMs), 778 differentially expressed genes (DEGs) significantly changed in ATAMs compared with NTAMs. These DEGs were correlated with oxidative phosphorylation (M2 phenotype) and phagocytosis (M1 phenotype). Moreover, ATAMs highly expressed pro-tumor genes associated with angiogenesis, fibrosis, metalloprotease activity, and metastasis. Notably, we identified one ATC-specific subset, IL2RA

Ferroptosis is an iron-dependent programmed cell death characterized by reactive oxygen species-induced lipid peroxide accumulation, which is different from cell apoptosis, pyroptosis, necrosis or autophagy. Ferroptosis plays an important role in the regulation of tumorigenesis and tumor development. Recent studies have shown that natural medicinal ingredients can induce ferroptosis in tumor cells through glutathione (GSH)/glutathione peroxidase 4 (GPx4) pathway, iron metabolism, lipid metabolism or other mechanisms. It has been reported that more than 30 natural medicinal ingredients can induce ferroptosis in tumor cells with multiple pathways and multiple targets. This article reviews the current research progress on the antitumor effects of natural medicinal ingredients through inducing cell ferroptosis.

OBJECTIVE: To investigate the molecular mechanism of resveratrol inhibiting the metastasis of liver cancer in vitro. METHODS: HepG2 and Huh7 cells were treated with different concentrations of resveratrol, and the cell viability was determined by CCK-8 assay to determine the optimal concentration of resveratrol for subsequent experiments. The expressions of miR-186-5p in liver cancer tissues and liver cancer cells were determined by quantitative real-time RT-PCR. The migration and invasion of HepG2 and Huh7 cells were detected by wound healing assay and Transwell assay, and the expression levels of epithelial-mesenchymal transition (EMT) related proteins were determined by Western blotting. RESULTS: Resveratrol with concentration of 6.25 μmol/L had no effect on the viability of HepG2 and Huh7 cells, so the concentration of resveratrol in subsequent experiments was 6.25 μmol/L. Resveratrol inhibited the wound healing and invasion of liver cancer cells; increased the expression of E-cadherin, and decreased the expression of vimentin and Twist1. The expression of miR-186-5p was significantly down-regulated in liver cancer tissues and cells compared with the adjacent tissues and normal liver cells (both P

Anaplastic thyroid carcinoma (ATC) is the most malignant tumor of endocrine system, which is an urgent medical problem to be solved. At present, immunotherapy studies on ATC mainly include cutting off the recruitment of tumor-associated macrophage (TAM), inducing the reprogramming of TAM and restoring its phagocytic function, targeting related immune checkpoints on T cells and natural killer cells, tumor vaccines based on oncolytic viruses and dendritic cells, and adoptive immunotherapy. Among them, immunotherapy strategies represented by targeted blocking of programmed death-1/programmed death ligand-1 at immune checkpoint have been preliminarily confirmed to benefit ATC patients, especially the combination of molecular targeted inhibitors and immunotherapy has shown excellent therapeutic effects. Due to the great heterogeneity of ATC, it is expected to provide more therapeutic strategies for patients of ATC by carrying out various immunotherapy studies including biological, immune and cellular therapies and exploring the therapeutic potential of the next generation of immune checkpoint inhibitors. This article reviews the potential immunotherapeutic targets of ATC and the progress of immunotherapy.

Hypoxia is widespread in solid tumors, such as NSCLC, and has become a very attractive target. On the basis of AZD9291 scaffold, novel hypoxia-targeted EGFR inhibitors without the acrylamide warhead but containing hypoxic reductive activation groups were described. Among them, compound JT21 exhibited impressive inhibitory activity (ICsub50/sub = 23 nM) against EGFRsupL858R/T790M/supand displayed about 21-fold inhibitory activity decrease against EGFRsupwt/sup. Under hypoxia, JT21 exhibited more significant proliferation inhibitory activities against H1975 cells (ICsub50/sub = 7.39 ± 2.20 nM) and HCC827 cells (ICsub50/sub = 5.88 ± 0.85 nM) than that of AZD9291, which was about 5 times more effective than normoxia activities. Meanwhile, the weak inhibition effects on A549 and BEAS-2B cells suggested JT21 might be a selective inhibitor for EGFR mutations with low toxicity. Furthermore, JT21 could induce apoptosis of H1975 cells under hypoxia and showed good bio-reductive property.

Background Metastatic prostate cancer (PCa) is a lethal tumor. However, the molecular mechanisms underlying PCa progression have not been fully elucidated. Methods Transcriptome expression profiling and clinical information on primary and metastatic PCa samples were obtained from TCGA. R software was used to screen the DEGs, and LASSO logistical regression method was utilized to identify the pivotal PCa metastasis-related DEGs. The transcriptional expression levels of the key genes were analyzed using the UALCAN database, and the corresponding protein expression were validated by Immunohistochemistry (IHC). Survival analysis of the key genes was performed using the GEPIA database. Wound healing assay and Transwell assay were conducted to determine whether knockdown of the key genes influence the migration and invasion abilities of PCa cells (22Rv1 and PC3). GSEA was performed to predict key genes-mediated signaling pathways for the development of PCa. Western blotting was used to evaluate the expression changes of E-cadherin, Twist1, and Vimentin in PCa cells with the key genes silencing. An in vivo mouse metastatic model for PCa was also generated to verify the important role of ISG15 and CST2 in PCa metastasis. Results A comparison between primary and metastatic PCa tissues was conducted, and 19 DEGs were screened. Among these, three key genes were identified that might be closely associated with PCa progression according to the LASSO logistical analysis, namely ISG15, DNAH8, and CST2. Further functional experiments revealed that knockdown of ISG15 and CST2 suppressed wound healing, migration, and invasion of PCa cells. To explore the molecular mechanism of ISG15 and CST2 in the development of PCa, GSEA was performed, and it was found that both genes play crucial roles in cell adhesion molecules, extracellular matrix-receptor interaction, and focal adhesion. Western blotting results exhibited that inhibiting ISG15 and CST2 led to increase the expression of E-cadherin and decrease the expression of Twist1 and Vimentin. Additionally, the metastatic in vivo study demonstrated that both PC3 and 22Rv1 cells expressing with luciferase-shISG15 and luciferase-shCST2 had significantly lower detectable bioluminescence than that in the control PCa cells. Conclusion ISG15 and CST2 may participate in PCa metastasis by regulating the epithelial-mesenchymal transition (EMT) signaling pathway. These findings may help to better understand the pathogenetic mechanisms governing PCa and provide promising therapeutic targets for metastatic PCa therapy.

Background: Gastric cancer is one of the most common fatal disease worldwide, but its mechanism and therapeutic targets are still unclear. In this study, we have analyzed the differences in gene modules and key pathways in gastric cancer patients, then elaborated the mechanism and effective treatment of gastric cancer with microarray data from the gene expression omnibus(GEO) database. Methods: GEO2R tools were used to identify differential expression genes (DEGs), String database was employed to construct a protein-protein interaction (PPI) network. We imported the PPI network into the Cytoscape software to find key nodes, and employed statistical approach of MCODE to cluster genes. After that the ClueGO was used to enrich and annotate the pathways of key modules. To investigate the relationship between the upstream regulator and hub genes, the transcriptional regulatory network was built based on TFCAT database. Results: 63 characteristic genes of gastric cancer are involved in regulation of ECM-receptor interaction, focal adhesion and protein digestion and absorption. SPARC, FN1, BGN and COL1A2 are four key nodes relating to tumor proliferation and metastasis, and their expression were strongly associated with poor survival (pConclusions: The present study defined the gene expression characteristics and transcriptional regulatory network that promote our understanding of the molecular mechanisms underlying the development of gastric cancer, and might provide new insights into targeted therapy and prognostic markers for the personalized treatment of gastric cancer.

Aims/Introduction The incidence of type 2 diabetes is increasing worldwide. Hepatic insulin resistance and liver lipid accumulation contributes to type 2 diabetes development. The aim of the present study was to investigate the key gene pathways and co‐expression networks in the livers of type 2 diabetes patients. Materials and Methods Dataset GSE15653 containing nine healthy individuals and nine type 2 diabetes patients was downloaded from the National Center for Biotechnology Information Gene Expression Omnibus database. Differentially expressed genes were obtained from the livers of type 2 diabetes patients, annotated pathway enrichment and protein–protein interaction network analysis. Next, functional modules and transcription factor networks were constructed. Gene co‐expression networks were analyzed by weighted correlation network analysis to identify key modules related to clinical traits, and the candidate key genes were validated in hepatic insulin resistance models in vitro. Results A total of 778 differentially expressed genes were filtered in the livers of type 2 diabetes patients, pathway enrichment analysis identified ke y pathways, such as the mitogen‐activated protein kinase signaling pathway, Hippo signaling pathway and hypoxia‐inducible factor‐1 signaling pathway, that were associated with type 2 diabetes. Several transcription factors of three functional modules identified from protein–protein interaction networks are likely to be implicated in type 2 diabetes. Furthermore, weighted correlation network analysis identified five modules that were shown to be highly correlated with type 2 diabetes and other clinical traits. Functional annotation showed that these modules were mainly enriched in pathways such as metabolic pathways, phosphoinositide 3‐kinase‐protein kinase B signaling pathway and natural killer cell‐mediated cytotoxicity. UBE2M and GPER were upregulated in L02 and HepG2 models, whereas P2RY11 only upregulated in L02 model, and UBE2N only downregulated in HepG2 model at a significant level. Conclusions These results would offer new insights into hepatic insulin resistance, type 2 diabetes pathogenesis, development and drug discovery.

Background Type 1 diabetes mellitus (T1DM) is an autoimmune disease caused by the immune destruction of islet β cells. Gene expression in peripheral blood mononuclear cells (PBMCs) could offer new disease and treatment markers in T1DM. The objective of this study was to explore the coexpression and dynamic molecular networks in PBMCs of T1DM patients. Methods Dataset GSE9006 contains PBMC samples of healthy volunteers, newly diagnosed T1DM patients, T1DM patients after insulin treatment, and newly diagnosed type 2 diabetes mellitus (T2DM) patients. Weighted correlation network analysis (WGCNA) was used to generate coexpression networks in T1DM and T2DM. Functional pathways in highly correlated modules of T1DM were enriched by gene set enrichment analysis (GSEA). We next filtered the differentially expressed genes (DEGs) and revealed their dynamic expression profiles in T1DM with or without insulin treatment. Furthermore, dynamic clusters and dynamic protein-protein interaction networks were identified. Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis was developed in dynamic clusters. Results WGCNA disclosed 12 distinct gene modules, and distinguished between correlated networks in T1DM and T2DM. Two modules were closely associated with T1DM. GSEA showed that the immune response and response to cytokines were enriched in the T1DM highly correlated module. Next, we screened 44 DEGs in newly diagnosed T1DM compared with healthy donors, and 71 DEGs in 1-month and 97 DEGs in 4-month insulin treatment groups compared with newly diagnosed T1DM. Dynamic expression profiles of DEGs indicated the potential targets for T1DM treatment. Moreover, four molecular dynamic clusters were analyzed in newly diagnosed and insulin-treated T1DM. Functional annotation showed that these clusters were mainly enriched in the IL-17 signaling pathway, nuclear factor-ϰB signaling pathway, and tumor necrosis factor signaling pathway. Conclusion The results indicate potential drug targets or clinical efficacy markers, as well as demonstrating the underlying molecular mechanisms of T1DM treatment.

To provide evidence for the better clinical use of traditional Chinese medicine preparations (TCMPs), comparison of the pharmacological mechanisms between TCMPs with similar therapeutic effect is necessary. However, methodology for dealing with this issue is still scarce. Danhong injection (DHI) and Naoxintong capsule (NXT) are representative TCMPs for ischemic stroke (IS) treatment, which are also frequently used in combination. Here they were employed as research objects to demonstrate the feasibility of systems pharmacology approach in elucidation of the independent and combined effect of TCMPs. By incorporating chemical screening, target prediction, and network construction, a feasible systems pharmacology model has been established to systematically uncover the underlying action mechanisms of DHI, NXT, or their pair in IS treatment. Systematic analysis of the created TCMP-Compound-Target-Disease network revealed that DHI and NXT shared common targets such as PTGS2, F2, ADRB1, IL6, ALDH2, and CCL2, which were involved in the vasomotor system regulation, blood-brain barrier disruption, redox imbalance, neurotrophin activity, and brain inflammation. In comparative mechanism study, the merged DHI/NXT-IS PPI network and pathway enrichment analysis indicated that DHI and NXT exerted the therapeutic effects mainly through immune system and VEGF signaling pathways. Meanwhile, they had their own unique pathways, e.g., calcium signaling pathway for DHI and gap junction for NXT. While for their synergistic mechanism, DHI and NXT participated in chemokine signaling pathway, T cell receptor signaling pathway, VEGF signaling pathway, gap junction, and so on. Our study provided an optimized strategy for dissecting the different and combined effect of TCMPs with similar actions.

BackgroundColorectal carcinoma (CRC) often arises from benign adenoma after a stepwise accumulation of genetic alterations. Here, we profiled the dynamic landscapes of transcription factors (TFs) in the mucosa-adenoma-carcinoma progression sequence.MethodsThe transcriptome data of co-occurrent adenoma, carcinoma, and normal mucosa samples were obtained from GSE117606. Identification of differentially expressed TFs (DE-TFs) and subsequent function annotation were conducted in R software. Expression patterns of DE-TFs were clustered by Short Time-series Expression Miner software. Thereafter, modular co-expression analysis, Kaplan-Meier survival analysis, mutation profiling, and gene set enrichment analysis were conducted to investigate TF dynamics in colorectal tumorigenesis. Finally, tissue microarrays, including 51 tumors, 32 adenomas, and 53 normal tissues, were employed to examine the expression of significant candidates by immunohistochemistry staining.ResultsCompared to normal tissues, 20 (in adenoma samples) and 29 (in tumor samples) DE-TFs were identified. During the disease course, 28 expression patterns for DE-TFs and four co-expression modules were clustered. Notably, six DE-TFs, DACH1, GTF2IRD1, MEIS2, NR3C2, SOX9, and SPIB, were identified as having a dynamic signature along the colorectal adenoma-carcinoma sequence. The dynamic signature was of significance in GO enrichment, prognosis, and co-expression analysis. Among the 6-TF signature, the roles of GTF2IRD1, SPIB and NR3C2 in CRC progression are unclear. Immunohistochemistry validation showed that GTF2IRD1 enhanced significantly throughout the mucosa-adenoma-carcinoma sequence, while SPIB and NR3C2 kept decreasing in stroma during the disease course.ConclusionsOur study provided a dynamic 6-TF signature throughout the course of colorectal mucosa-adenoma-carcinoma. These findings deepened the understanding of colorectal cancer pathogenesis.

Ulcerative colitis (UC) is a chronic relapsing inflammatory bowel disease caused by an interaction of genetics, immune responses, and environmental factors. However, the precise pathogenesis of UC remains poorly understood. The aim of the present study was to explore the potential target genes implicated in UC and to elucidate its underlying pathogenic mechanism. Firstly, three UC-associated microarray datasets (GSE75214, GSE87466, and GSE92517) were obtained to screen the differentially expressed genes (DEGs). As a result, alcohol dehydrogenase 1C (ADH1C) was the most significantly downregulated DEG in UC. We confirmed that ADH1C was downregulated in colonic tissue taken from patients with UC and colitis mice. Moreover, ADH1C expression was also decreased in colonic cell lines (NCM460 and HT29) treated with mixed proinflammatory cytokines (TNF-α, IFN-γ, IL-1β). Interestingly, we found that overexpression of ADH1C could distinctly decrease the production of IL-6 and IL-8. To elucidate the molecular mechanism of ADH1C in UC, gene set enrichment analysis (GSEA) was performed and demonstrated that immune-related pathways were mainly enriched in the low ADH1C group. Further studies displayed that STAT1/NF-κB pathway was activated in colitis mice and inflammatory cell model. Importantly, overexpression of ADH1C could suppress the phosphorylation of STAT1 and IκB. Therefore, ADH1C might regulate inflammatory responses through STAT1/NF-κB pathway. In conclusion, ADH1C was downregulated during inflammation, and its increased expression could inhibit the activation of STAT1/NF-κB pathway, thereby alleviating the secretion of IL-6 and IL-8. These findings indicate that ADH1C may be a potential therapeutic target for UC therapy.

Acute type A aortic dissection (ATAAD) is a life-threatening disease. The understanding of its pathogenesis and treatment approaches remains unclear. In the present work, differentially expressed genes (DEGs) from two ATAAD datasets GSE52093 and GSE98770 were filtered. Transcription factor TEAD4 was predicted as a key modulator in protein-protein interaction (PPI) network. Weighted correlation network analysis (WGCNA) identified five modules in GSE52093 and four modules in GSE98770 were highly correlated with ATAAD. 71 consensus DEGs of highly correlated modules were defined and functionally annotated. L1000CDS2 was executed to predict drug for drug repositioning in ATAAD treatment. Eight compounds were filtered as potential drugs. Integrative analysis revealed the interaction network of five differentially expressed miRNA and 16 targeted DEGs. Finally, master DEGs were validated in human ATAAD samples and AD cell model in vitro. TIMP3 and SORBS1 were downregulated in ATAAD samples and AD cell model, while PRUNE2 only decreased in vitro. Calcium channel blocker and glucocorticoid receptor agonist might be potential drugs for ATAAD. The present study offers potential targets and underlying molecular mechanisms ATAAD pathogenesis, prevention and drug discovery.

BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is a chronic and progressive interstitial lung disease mainly caused by excessive proliferation of fibroblasts and activation of myofibroblasts. The cellular microenvironment is mainly composed of different types of cellular components and extracellular matrix (ECM), whose changes directly affect cellular heterogeneity, resulting in immensely complex cellular interactions. However, microenvironment study is mainly focused on the pathological process of tumors, and the microenvironment changes during IPF development remain unclear. METHODS: The current study intends to employ IPF-related single-cell sequencing and gene expression profile data to analyze the scores of different cell clusters in the IPF microenvironment, and exploit the underlying interaction between cells to illustrate the fundamental mechanism causing IPF. RESULTS: Our analysis revealed that the amount of endothelial cells was obviously decreased, and the amount of fibroblasts and myofibroblasts was increased during the development of IPF, suggesting a possible endothelial-mesenchymal transition (EndMT) process. Furthermore, we found that the hub genes obtained through IPF-related gene expression profile analysis may play a regulative role in the number and function of endothelial cells and fibroblasts/myofibroblasts during IPF. CONCLUSIONS: Our research represents a valuable analysis of the cellular microenvironment, and provides a novel mechanistic insight into the pathobiology of not only EndMT in IPF, but also other traumatic fibrotic disease disorders.

Background Unlike papillary thyroid cancer (PTC), anaplastic thyroid carcinoma (ATC) is extremely aggressive and rapidly lethal without effective therapies. However, the differences of master regulators and regulatory networks between PTC and ATC remain unclear. Methods: Three representative datasets comprising 32 ATC, 69 PTC, and 78 normal thyroid tissue samples were combined to form a large dataset. Differentially expressed genes (DEGs) were identified and enriched by limma package and gene set enrichment analysis, respectively. Subsequently, protein–protein interaction network and transcription factors (TFs) regulatory network were constructed to identify gene modules and master regulators. Further, master regulators were validated by RT-PCR and western blot. Finally, Kaplan-Meier plotter was applied to evaluate their prognostic values. Results: A total of 560 DEGs were identified as ATC-specific malignant signature. The regulatory network analysis showed that nine master regulators were significantly correlated with three gene modules and potentially regulated the expression of DEGs in three gene modules, respectively. Furthermore, CREB3L1, FOSL2, E2F1 and CAT were significantly associated with overall survival of thyroid cancer patients. FOXM1, FOSL2, MYBL2, AVEN and E2F1 were unfavorable factors of recurrence-free survival (RFS), while CAT was a favorable factor of RFS. RT-PCR and western blot confirmed that six TFs were obviously up-regulated in ATC tissues/cell line as compared with PTC and normal thyroid tissues/cell lines, respectively. In addition, 19 ATC-specific kinases were identified to illustrate the potential post-translational modification. Conclusions: Our findings provide a comprehensive insight into malignant mechanism of ATC, which may indicate their value in the future investigation of ATC.

Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest solid tumors. The rapid progression of PDAC results in an advanced stage of patients when diagnosed. However, the dynamic molecular mechanism underlying PDAC progression remains far from clear.The microarray GSE62165 containing PDAC staging samples was obtained from Gene Expression Omnibus and the differentially expressed genes (DEGs) between normal tissue and PDAC of different stages were profiled using R software, respectively. The software program Short Time-series Expression Miner was applied to cluster, compare, and visualize gene expression differences between PDAC stages. Then, function annotation and pathway enrichment of DEGs were conducted by Database for Annotation Visualization and Integrated Discovery. Further, the Cytoscape plugin DyNetViewer was applied to construct the dynamic protein-protein interaction networks and to analyze different topological variation of nodes and clusters over time. The phosphosite markers of stage-specific protein kinases were predicted by PhosphoSitePlus database. Moreover, survival analysis of candidate genes and pathways was performed by Kaplan-Meier plotter. Finally, candidate genes were validated by immunohistochemistry in PDAC tissues.Compared with normal tissues, the total DEGs number for each PDAC stage were 994 (stage I), 967 (stage IIa), 965 (stage IIb), 1027 (stage III), 925 (stage IV), respectively. The stage-course gene expression analysis showed that 30 distinct expressional models were clustered. Kyoto Encyclopedia of Genes and Genomes analysis indicated that the up-regulated DEGs were commonly enriched in five fundamental pathways throughout five stages, including pathways in cancer, small cell lung cancer, ECM-receptor interaction, amoebiasis, focal adhesion. Except for amoebiasis, these pathways were associated with poor PDAC overall survival. Meanwhile, LAMA3, LAMB3, LAMC2, COL4A1 and FN1 were commonly shared by these five pathways and were unfavorable factors for prognosis. Furthermore, by constructing the stage-course dynamic protein interaction network, 45 functional molecular modules and 19 nodes were identified as featured regulators for all PDAC stages, among which the collagen family and integrins were considered as two main regulators for facilitating aggressive progression. Additionally, the clinical relevance analysis suggested that the stage IV featured nodes MLF1IP and ITGB4 were significantly correlated with shorter overall survival. Moreover, 15 stage-specific protein kinases were identified from the dynamic network and CHEK1 was particularly activated at stage IV. Experimental validation showed that MLF1IP, LAMA3 and LAMB3 were progressively increased from tumor initiation to progression.Our study provided a view for a better understanding of the dynamic landscape of molecular interaction networks during PDAC progression and offered potential targets for therapeutic intervention.

To identify the time dependent profiles of gene expression and featured co-expression network modules in peripheral blood of rats after middle cerebral artery occlusion (MCAO).Microarray GSE119121 from GEO database was analyzed by R language to identify the significantly changed genes in peripheral blood at different time points (0, 1, 2, 3, 6 and 24 h) after MCAO. Gene expression patterns at different time courses were screened by STEM tools. Then, function annotation and pathway enrichment of differentially expressed genes (DEGs) were performed using the Gene Ontology (GO) database and the Kyoto Gene and Genomic Encyclopedia (KEGG) database. Depending on CEMiTool package, gene expression profile matrix was inputted into R to construct the co-expression networks and to analyze modules, and enrichment analysis was conducted to evaluate the correlation between the modules and different time points.Comparing with gene at 0 h, the numbers of DEGs in peripheral blood at different time points after MCAO were 163 (1 h), 502 (2 h), 527 (3 h), 550 (6 h), and 75 (24 h), respectively. Moreover, a total of 38 gene expression patterns were enriched, and pattern 65 and pattern 34 were specifically up-regulated or down-regulated at 2-6 h.Our study has identified the featured genes and dynamic co-expression network modules in peripheral blood after acute ischemic stroke, which provides a potential basis for judging the onset time of ischemic stroke.

Lu Li,1,* Zongfu Pan,2,* Si Yang,1 Wenya Shan,1 Yanyan Yang1 1Department of Pharmacy, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang, People’s Republic of China; 2Department of Pharmacy, Zhejiang Cancer Hospital, Hangzhou, Zhejiang, People’s Republic of China *These authors contributed equally to this work Purpose: The number of people with type 2 diabetes (T2D) is growing rapidly worldwide. Islet β-cell dysfunction and failure are the main causes of T2D pathological processes. The aim of this study was to elucidate the underlying pathways and coexpression networks in T2D islets. Materials and methods: We analyzed the differentially expressed genes (DEGs) in the data set GSE41762, which contained 57 nondiabetic and 20 diabetic samples, and developed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. Protein–protein interaction (PPI) network, the modules from the PPI network, and the gene annotation enrichment of modules were analyzed as well. Moreover, a weighted correlation network analysis (WGCNA) was applied to screen critical gene modules and coexpression networks and explore the biological significance. Results: We filtered 957 DEGs in T2D islets. Then GO and KEGG analyses identified that key pathways like inflammatory response, type B pancreatic cell differentiation, and calcium ion-dependent exocytosis were involved in human T2D. Three significant modules were filtered from the PPI network. Ribosome biogenesis, extrinsic apoptotic signaling pathway, and membrane depolarization during action potential were associated with the modules, respectively. Furthermore, coexpression network analysis by WGCNA identified 13 distinct gene modules of T2D islets and revealed four modules, which were strongly correlated with T2D and T2D biomarker hemoglobin A1c (HbA1c). Functional annotation showed that these modules mainly enriched KEGG pathways such as NF-kappa B signaling pathway, tumor necrosis factor signaling pathway, cyclic adenosine monophosphate signaling pathway, and peroxisome proliferators-activated receptor signaling pathway. Conclusion: The results provide potential gene pathways and underlying molecular mechanisms for the prevention, diagnosis, and treatment of T2D. Keywords: type 2 diabetes, islet β cell, bioinformatics analysis, differentially expressed genes, WGCNA

Non-small-cell lung cancer (NSCLC) is an extremely debilitating respiratory malignancy. However, the pathogenesis of NSCLC has not been fully clarified. The main objective of our study was to identify potential microRNAs (miRNAs) and their regulatory mechanism in NSCLC. Using a systematic review, two NSCLC-associated miRNA data sets (GSE102286 and GSE56036) were obtained from Gene Expression Omnibus, and the differentially expressed miRNAs (DE-miRNAs) were accessed by GEO2R. Survival analysis of candidate DE-miRNAs was conducted using the Kaplan-Meier plotter database. To further illustrate the roles of DE-miRNAs in NSCLC, their potential target genes were predicted by miRNet and were annotated by the Database for Annotation, Visualization and Integrated Discovery (DAVID) program. Moreover, the protein-protein interaction (PPI) and miRNA-hub gene regulatory network were established using the STRING database and Cytoscape software. The function of DE-miRNAs in NSCLC cells was evaluated by transwell assay. Compared with normal tissues, a total of eight DE-miRNAs was commonly changed in two data sets. The survival analysis showed that six miRNAs (miR-21-5p, miR-31-5p, miR-708-5p, miR-30a-5p, miR-451a, and miR-126-3p) were significantly correlated with overall survival. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis indicated that target genes of upregulated miRNAs were enriched in pathways in cancer, microRNAs in cancer and proteoglycans in cancer, while the target genes of downregulated miRNAs were mainly associated with pathways in cancer, the PI3K-Akt signaling pathway and HTLV-I infection. Based on the miRNA-hub gene network and expression analysis, PTEN, EGFR, STAT3, RHOA, VEGFA, TP53, CTNNB1, and KRAS were identified as potential target genes. Furthermore, all six miRNAs exhibited significant effects on NSCLC cell invasion. These findings indicate that six DE-miRNAs and their target genes may play important roles in the pathogenesis of NSCLC, which will provide novel information for NSCLC treatments.

Background Type 1 diabetes mellitus (T1DM) is an autoimmune disease caused by the immune destruction of islet β cells. Gene expression in peripheral blood mononuclear cells (PBMCs) could offer new disease and treatment markers in T1DM. The objective of this study was to explore the coexpression and dynamic molecular networks in PBMCs of T1DM patients. Methods Dataset GSE9006 contains PBMC samples of healthy volunteers, newly diagnosed T1DM patients, T1DM patients after insulin treatment, and newly diagnosed type 2 diabetes mellitus (T2DM) patients. Weighted correlation network analysis (WGCNA) was used to generate coexpression networks in T1DM and T2DM. Functional pathways in highly correlated modules of T1DM were enriched by gene set enrichment analysis (GSEA). We next filtered the differentially expressed genes (DEGs) and revealed their dynamic expression profiles in T1DM with or without insulin treatment. Furthermore, dynamic clusters and dynamic protein–protein interaction networks were identified. Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis was developed in dynamic clusters. Results WGCNA disclosed 12 distinct gene modules, and distinguished between correlated networks in T1DM and T2DM. Two modules were closely associated with T1DM. GSEA showed that the immune response and response to cytokines were enriched in the T1DM highly correlated module. Next, we screened 44 DEGs in newly diagnosed T1DM compared with healthy donors, and 71 DEGs in 1-month and 97 DEGs in 4-month insulin treatment groups compared with newly diagnosed T1DM. Dynamic expression profiles of DEGs indicated the potential targets for T1DM treatment. Moreover, four molecular dynamic clusters were analyzed in newly diagnosed and insulin-treated T1DM. Functional annotation showed that these clusters were mainly enriched in the IL-17 signaling pathway, nuclear factor-ϰB signaling pathway, and tumor necrosis factor signaling pathway. Conclusion The results indicate potential drug targets or clinical efficacy markers, as well as demonstrating the underlying molecular mechanisms of T1DM treatment.

Anaplastic thyroid carcinoma (ATC) is one of the most aggressive and rapidly lethal tumors. However, limited advances have been made to prolong the survival and to reduce the mortality over the last decades. Therefore, identifying the master regulators underlying ATC progression is desperately needed. In our present study, three datasets including GSE33630, GSE29265, and GSE65144 were retrieved from Gene Expression Omnibus with a total of 32 ATC samples and 78 normal thyroid tissues. A total of 1804 consistently changed differentially expressed genes (DEGs) were identified from three datasets. KEGG pathways enrichment suggested that upregulated DEGs were mainly enriched in ECM-receptor interaction, cell cycle, PI3K-Akt signaling pathway, focal adhesion, and p53 signaling pathway. Furthermore, key gene modules in PPI network were identified by Cytoscape plugin MCODE and they were mainly associated with DNA replication, cell cycle process, collagen fibril organization, and regulation of leukocyte migration. Additionally, TOP2A, CDK1, CCNB1, VEGFA, BIRC5, MAPK1, CCNA2, MAD2L1, CDC20, and BUB1 were identified as hub genes of the PPI network. Interestingly, module analysis showed that 8 out of 10 hub genes participated in Module 1 network and more than 70% genes of Module 2 consisted of collagen family members. Notably, transcription factors (TFs) regulatory network analysis indicated that E2F7, FOXM1, and NFYB were master regulators of Module 1, while CREB3L1 was the master regulator of Module 2. Experimental validation showed that CREB3L1, E2F7, and FOXM1 were significantly upregulated in ATC tissue and cell line when compared with normal thyroid group. In conclusion, the TFs regulatory network provided a more detail molecular mechanism underlying ATC occurrence and progression. TFs including E2F7, FOXM1, CREB3L1, and NFYB were likely to be master regulators of ATC progression, suggesting their potential role as molecular therapeutic targets in ATC treatment.

Objectives. Many patients with papillary thyroid cancer (PTC) have a high recurrence risk and poor prognosis, and the main obstacle to the clinical diagnosis and treatment of PTC is lack of effective predictive molecular markers. The purpose of this study was to investigate the clinicopathological and prognostic implications of WW domain binding protein 5 (WBP5) expression in PTC. Materials and Methods. Immunohistochemistry of WBP5 was performed using tissue microarrays of 131 patients with PTC who underwent surgery during January 2006 and January 2010 in the Zhejiang Cancer Hospital. Statistical analyses were conducted to evaluate the association between WBP5 expression and the clinicopathological features and to analyze the disease-free survival (DFS) and prognostic factors. Results and Conclusion. The positive expression rate of WBP5 in PTC and the adjacent normal tissues was 42.75% (56/131) and 45.45% (10/22), respectively. WBP5 expression was significantly correlated with bilaterality, capsule invasion, and N-stage, and it was a favorable factor of DFS. Moreover, patients with a high WBP5 expression exhibited reduced risk of disease recurrence compared with that in patients with low WBP5 expression in the univariate analysis, whereas the multivariate analysis suggested that WBP5 was not an independent prognostic factor. Our results indicate that WBP5 might be a favorable prognosis indicator of PTC.

Background Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest solid tumors. The rapid progression of PDAC results in an advanced stage of patients when diagnosed. However, the dynamic molecular mechanism underlying PDAC progression remains far from clear. Methods The microarray GSE62165 containing PDAC staging samples was obtained from Gene Expression Omnibus and the differentially expressed genes (DEGs) between normal tissue and PDAC of different stages were profiled using R software, respectively. The software program Short Time-series Expression Miner was applied to cluster, compare, and visualize gene expression differences between PDAC stages. Then, function annotation and pathway enrichment of DEGs were conducted by Database for Annotation Visualization and Integrated Discovery. Further, the Cytoscape plugin DyNetViewer was applied to construct the dynamic protein–protein interaction networks and to analyze different topological variation of nodes and clusters over time. The phosphosite markers of stage-specific protein kinases were predicted by PhosphoSitePlus database. Moreover, survival analysis of candidate genes and pathways was performed by Kaplan–Meier plotter. Finally, candidate genes were validated by immunohistochemistry in PDAC tissues. Results Compared with normal tissues, the total DEGs number for each PDAC stage were 994 (stage I), 967 (stage IIa), 965 (stage IIb), 1027 (stage III), 925 (stage IV), respectively. The stage-course gene expression analysis showed that 30 distinct expressional models were clustered. Kyoto Encyclopedia of Genes and Genomes analysis indicated that the up-regulated DEGs were commonly enriched in five fundamental pathways throughout five stages, including pathways in cancer, small cell lung cancer, ECM-receptor interaction, amoebiasis, focal adhesion. Except for amoebiasis, these pathways were associated with poor PDAC overall survival. Meanwhile, LAMA3, LAMB3, LAMC2, COL4A1 and FN1 were commonly shared by these five pathways and were unfavorable factors for prognosis. Furthermore, by constructing the stage-course dynamic protein interaction network, 45 functional molecular modules and 19 nodes were identified as featured regulators for all PDAC stages, among which the collagen family and integrins were considered as two main regulators for facilitating aggressive progression. Additionally, the clinical relevance analysis suggested that the stage IV featured nodes MLF1IP and ITGB4 were significantly correlated with shorter overall survival. Moreover, 15 stage-specific protein kinases were identified from the dynamic network and CHEK1 was particularly activated at stage IV. Experimental validation showed that MLF1IP, LAMA3 and LAMB3 were progressively increased from tumor initiation to progression. Conclusions Our study provided a view for a better understanding of the dynamic landscape of molecular interaction networks during PDAC progression and offered potential targets for therapeutic intervention.

To identify hub genes and key pathways associated with anaplastic thyroid carcinoma (ATC), and to explore possible intervention strategy.The differentially expressed genes (DEGs) in ATC were identified by Gene Expression Omnibus (GEO) combined with using R language; the pathway enrichment of DEGs were performed by using Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO). The protein-protein interaction (PPI) network of DEGs was constructed by STRING database and visualized by Cytoscape. Furthermore, the hub genes and key nodes were calculated by MCODE. Finally, the drug repurposing was performed by L1000CDSA total of 2087 DEGs were identified. The DEGs were clustered based on functions and pathways with significant enrichment analysis, among which PI3K-Akt signaling pathway, p53 signaling pathway, inflammatory response, extracellular matrix organization were significantly upregulated. The PPI network was constructed and the most significant three modules and nine genes were filtered. Twenty-two potential compounds were repurposed for ATC treatment.Using integrated bioinformatics analysis, we have identified hub genes and key pathways in ATC, and provide novel strategy for the treatment of ATC.

Additional file 1: Figures S1â S5. Featured clusters at different PDAC stages.

Oridonin, the major terpene found in Rabdosia rubescens, is widely used as a dietary supplement or therapeutic drug. However, the effects of oridonin on major CYP450s are still unclear. As oridonin can enhance the effect of other clinical drugs, in this study, we investigated the influence of oridonin on CYP450s mRNA expression and its impact on activities in human HepaRG cell to evaluate the safety by studying its potential drug interaction. HepaRG cells were cultured with series concentrations of oridonin (1, 5, 10, and 20 μmol/L), and the major CYP450s mRNA and protein expression, as well as enzyme activities were analyzed by real-time polymerase chain reaction, Western blot analysis and UPLC-MS/MS-based metabolite assay. In general, ordonin has induced effects on the major member of CYP450s mRNA and protein expression, as well as on the enzyme activity in human HepaRG cells, especially on CYP3A4 and CYP2C9. To our knowledge, this is the first systematic research about the inductive effects of oridonin on the major member of CYP450s in human cell line. These results may provide at least partly of the basis for potential drug-drug interactions and oridonin should be used with caution to avoid potential risk.

The aim of this study was to investigate the role of NEAT1 in hepatocellular carcinoma (HCC), and probe whether NEAT1 participate in the epithelial-mesenchymal transition (EMT) and metastasis regulated by HIF-2α. Expression of lncRNA NEAT1 was initially assessed in HCC tissues and in a series of HCC cell lines. The correlations between NEAT1 levels and HIF-2α were analyzed through plasmid vector construction. The potential underlying mechanisms of NEAT1 in HCC were performed through in vitro and in vivo functional assays. Expression of NEAT1, HIF-2α were significantly increased in HCC tissues and cell lines. Then, in vitro assays revealed that NEAT1 promotes EMT and metastasis by stimulating the inactivation of HIF-2α in HCC. An in vivo animal model also demonstrated the cancer promotion mechanism of NEAT1. In this study, we found that the NEAT1 was high expression in HCC. NEAT1 promotes tumor cell EMT, migration and invasion capacities by stimulating the activation of HIF-2α in HCC.

Long non-coding RNA nuclear-enriched abundant transcript 1 (NEAT1) plays an important role in the pathogenesis and development of several types of cancer. However, the functional mechanism of NEAT1 in hepatocellular carcinoma (HCC) remains unclear. NEAT1 and microRNA (miR)-129-5p expression in HCC tissues and cell lines was quantified by means of quantitative PCR. The effects of NEAT1 expression inhibition or upregulation in HCC cell lines were analyzed in terms of cell viability and apoptosis. Biological software was used to predict the binding sites of NEAT1 and miR-129-5p. The expression of the miR-129-5p target molecules valosin-containing protein (VCP) and IκB was detected using Western blotting. The effect of NEAT1 on tumor growth was observed in mouse models of transplanted hepatoma. In the present study, it was concluded that the expression of NEAT1 was significantly increased in the HCC tissues and cell lines. Meanwhile, after downregulating NEAT1 expression in HepG2/Huh7 cell lines, the cell viability was significantly lowered, whereas the corresponding rate of apoptosis was significantly increased. Additionally, it was found that the NEAT1 and miR-129-5p expression showed a negative correlation in HCC tissues. It was further proved that there was a certain negative regulatory mechanism between NEAT1 and miR-129-5p, which was related to the expression of VCP and IκB. The mouse model experiments confirmed that the interference with NEAT1 expression inhibited tumor growth. The study concluded that the overexpression of NEAT1 inhibited the expression of miR-129-5p by regulating VCP/IκB, thereby promoting the proliferation of HCC cells. This study provides new insights into the pathogenesis of HCC, as well as identifying new target genes for diagnosis and treatment. NEW & NOTEWORTHY The results provide strong evidence that upregulated NEAT1 promotes the proliferation of cancer cells in hepatocellular carcinoma (HCC) and this regulatory mechanism depends on the microRNA (miR)-129-5p-valosin-containing protein-IκB axis. The study also indicates that NEAT1 could be a potential therapeutic target for HCC.