Identification of Gene Expression Changes from Colitis to CRC in the Mouse CAC Model

A connection between colorectal carcinogenesis and inflammation is well known, but the underlying molecular mechanisms have not been elucidated. Chemically induced colitis-associated cancer (CAC) is an outstanding mouse model for studying the link between inflammation and cancer. Additionally, the CAC model is used for examining novel diagnostic, prognostic, and predictive markers for use in clinical practice. Here, a CAC model was established in less than 100 days using azoxymethane (AOM) with dextran sulfate sodium salt (DSS) in BALB/c mice. We examined the mRNA expression profiles of three groups: control untreated mice (K), DSS-induced chronic colitis mice (D), and AOM/DSS-induced CAC (AD) mice. We identified 6301 differentially expressed genes (DEGs) among the three groups, including 93 persistently upregulated genes and 139 persistently downregulated genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses revealed that the most persistent DEGs were significantly enriched in metabolic or inflammatory components in the tumor microenvironment. Furthermore, several associated DEGs were identified as potential DEGs by protein-protein interaction (PPI) network analysis. We selected 14 key genes from the DEGs and potential DEGs for further quantitative real-time PCR (qPCR) verification. Six persistently upregulated, 3 persistently downregulated DEGs, and the other 3 genes showed results consistent with the microarray data. We demonstrated the regulation of 12 key genes specifically involved in Wnt signaling, cytokine and cytokine receptor interactions, homeostasis, and tumor-associated metabolism during colitis-associated CRC. Our results suggest that a close relationship between metabolic and inflammatory mediators of the tumor microenvironment is present in CAC.     

Identification and validation of key genes associated with non-small-cell lung cancer

Non-small-cell lung cancer (NSCLC) is one of the main causes of death induced by cancer globally. However, the molecular aberrations in NSCLC patients remain unclearly. In the present study, four messenger RNA microarray datasets (GSE18842, GSE40275, GSE43458, and GSE102287) were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) between NSCLC tissues and adjacent lung tissues were obtained from GEO2R and the overlapping DEGs were identified. Moreover, functional and pathway enrichment were performed by Funrich, while the protein–protein interaction (PPI) network construction were obtained from STRING and hub genes were visualized and identified by Cytoscape software. Furthermore, validation, overall survival (OS) and tumor staging analysis of selected hub genes were performed by GEPIA. A total of 367 DEGs (95 upregulated and 272 downregulated) were obtained through gene integration analysis. The PPI network consisted of 94 nodes and 1036 edges in the upregulated DEGs and 272 nodes and 464 edges in the downregulated DEGs, respectively. The PPI network identified 46 upregulated and 27 downregulated hub genes among the DEGs, and six (such as CENPE, NCAPH, MYH11, LRRK2, HSD17B6, and A2M) of that have not been identified to be associated with NSCLC so far. Moreover, the expression differences of the mentioned hub genes were consistent with that in lung adenocarcinoma and lung squamous cell carcinoma in the TCGA database. Further analysis showed that all the six hub genes were associated with tumor staging except MYH11, while only the upregulated DEG CENPE was associated with the worse OS of patients with NSCLC. In conclusion, the current study showed that CENPE, NCAPH, MYH11, LRRK2, HSD17B6, and A2M might be the key genes contributed to tumorigenesis or tumor progression in NSCLC, further functional study is needed to explore the involved mechanisms.     

The identification of candidate radio marker genes using a coexpression network analysis in gamma‐irradiated rice

Plant physiological and biochemical processes are significantly affected by gamma irradiation stress. In addition, gamma‐ray (GA) differentially affects gene expression across the whole genome. In this study, we identified radio marker genes (RMGs) responding only to GA stress compared with six abiotic stresses (chilling, cold, anoxia, heat, drought and salt) in rice. To analyze the expression patterns of differentially expressed genes (DEGs) in gamma‐irradiated rice plants against six abiotic stresses, we conducted a hierarchical clustering analysis by using a complete linkage algorithm. The up‐ and downregulated DEGs were observed against six abiotic stresses in three and four clusters among a total of 31 clusters, respectively. The common gene ontology functions of upregulated DEGs in clusters 9 and 19 are associated with oxidative stress. In a Pearson's correlation coefficient analysis, GA stress showed highly negative correlation with salt stress. On the basis of specific data about the upregulated DEGs, we identified the 40 candidate RMGs that are induced by gamma irradiation. These candidate RMGs, except two genes, were more highly induced in rice roots than in other tissues. In addition, we obtained other 38 root‐induced genes by using a coexpression network analysis of the specific upregulated candidate RMGs in an ARACNE algorithm. Among these genes, we selected 16 RMGs and 11 genes coexpressed with three RMGs to validate coexpression network results. RT‐PCR assay confirmed that these genes were highly upregulated in GA treatment. All 76 genes (38 root‐induced genes and 38 candidate RMGs) might be useful for the detection of GA sensitivity in rice roots.     

Identification of key candidate genes and pathways in multiple myeloma by integrated bioinformatics analysis

Multiple myeloma (MM) is a common hematologic malignancy for which the underlying molecular mechanisms remain largely unclear. This study aimed to elucidate key candidate genes and pathways in MM by integrated bioinformatics analysis. Expression profiles GSE6477 and GSE47552 were obtained from the Gene Expression Omnibus database, and differentially expressed genes (DEGs) with p < .05 and [logFC] > 1 were identified. Functional enrichment, protein–protein interaction network construction and survival analyses were then performed. First, 51 upregulated and 78 downregulated DEGs shared between the two GSE datasets were identified. Second, functional enrichment analysis showed that these DEGs are mainly involved in the B cell receptor signaling pathway, hematopoietic cell lineage, and NF-kappa B pathway. Moreover, interrelation analysis of immune system processes showed enrichment of the downregulated DEGs mainly in B cell differentiation, positive regulation of monocyte chemotaxis and positive regulation of T cell proliferation. Finally, the correlation between DEG expression and survival in MM was evaluated using the PrognoScan database. In conclusion, we identified key candidate genes that affect the outcomes of patients with MM, and these genes might serve as potential therapeutic targets.     

Transcriptome Profiling of Barley Cultivar Hua 30 MDEC in Response to <i>Agrobacterium</i> Infection

Agrobacterium-mediated transformation has been widely used in plants. However, the mechanism in plant cells’ response to Agrobacterium infection was very complex. The mechanism of the determinants in host cell remains obscure, especially in barley, which is recalcitrant for Agrobacterium-mediated transformation. In the present study, microspore-derived embryogenic calli (MDEC) from barley elite cultivar were employed as unique subjects to characterize the mechanisms during the Agrobacterium infection process. Hua 30 MDEC can be successfully infected by Agrobacterium. RNA-sequencing at different infection points (0, 2, 6, 12, 24 hpi) was performed. The average expressional intensity of the whole genomics increased from 0 to 2 hpi, and then decreased subsequently. More upregulated than downregulated differentially expressed genes (DEGs) were counted at the same time. GO enrichment analysis showed that protein modification was significantly overrepresented in upregulated DEGs. Chromosome-related biological processes, gene expression and cellular metabolic processes were significantly overrepresented in downregulated DEGs. KEGG analysis showed that plant defense responses, phenylpropanoid biosynthesis and biosynthesis of amino acids were significantly enriched across the infection time course. Nine DEGs related to defense responses were identified. All DEGs were upregulated from 2 to 24 hpi. We speculate that these genes are possibly related to Agrobacterium infection. These findings will provide deep insights into the molecular events occurring during the process of Agrobacterium-mediated transformation.     

Identification of differentially expressed genes in primary Sjögren's syndrome

Primary Sjögren's syndrome (pSS) is a chronic systemic autoimmune disease that affects exocrine glands. To study the molecular mechanism and identify crucial genes/pathways in pSS pathogenesis, the microarray-based whole-genome gene expression profiles from salivary glands of patients with pSS and non-sicca controls were retrieved. After normalization and subsequent batch effect adjustment, significance analysis of microarrays method was applied to five available datasets, and 379 differentially expressed genes (DEGs) were identified. The 300 upregulated DEGs were enriched in Gene Ontology terms of immune and inflammatory responses, including antigen processing and presentation, interferon-mediated signaling pathway, and chemotaxis. Previously reported pSS-associated genes, including HLA-DRA, TAP2, PRDM1, and IFI16, were found to be significantly upregulated. The downregulated DEGs were enriched in pathways of salivary secretion, carbohydrate digestion and absorption, and starch and sucrose metabolism, implying dysfunction of salivary glands during pathogenesis. Next, a protein-protein interaction network was constructed, and B2M, an upregulated DEG, was shown to be a hub, suggesting its potential involvement in pSS development. In summary, we found the activation of pSS-associated genes in pathogenesis, and provide clues for salivary glands dysfunction. Experimental investigation on the identified DEGs in this study will deepen our understanding on pSS.     

Transcriptome analysis of the response of silkworm to drastic changes in ambient temperature

Bombyx mori is a poikilothermic insect and is economically important for silk production. Drastic changes in the ambient temperature have a negative impact on sericulture. However, the reason as to why high temperature is associated with the occurrence of diseases in silkworm and the response of silkworm to low temperature remain unclear and were the focus of the present study. Dazao silkworm exposed to 13 °C (DZ-13), 25 °C (DZ-25), and 37 °C (DZ-37) were used for RNA-seq analysis. There were 478 and 194 upregulated differentially expressed genes (DEGs) in DZ-13 and DZ-37 while 49 and 273 downregulated DEGs in DZ-13 and DZ-37, respectively. Eight DEGs were co-upregulated, in which seven genes were for heat shock proteins (Hsps), implying that Hsps play important roles in the tolerance of silkworm to high and low temperature. Gene ontology analysis revealed that the developmental process was downregulated in DZ-13. All the DEGs in the oxidative phosphorylation and insulin signaling pathways were upregulated in DZ-13. Several cuticular proteins and ATP synthesis-related genes were upregulated in DZ-13, suggesting that thickening of the cuticle and increase in the ATPase expression would help silkworms to protect themselves from low temperature-induced stress. Several immune-related genes, such as BmRel and BmSerpin-2, were downregulated in DZ-37, revealing that the resistance of silkworm is decreased under high temperature shock resulting in susceptibility to pathogens. Thus, the increase in the thermo-tolerance of silkworm should be related to the enhancement in the pathogen resistance.