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Background Exploration of the genes with abnormal expression during the development of breast cancer is essential to provide a deeper understanding of the mechanisms involved. Transcriptome sequencing and bioinformatics analysis of invasive ductal carcinoma and paracancerous tissues from the same patient were performed to identify the key genes and signaling pathways related to breast cancer development. Methods Samples of breast tumor tissue and paracancerous breast tissue were obtained from 6 patients. Sequencing used the Illumina HiSeq platform. All. Only perfectly matched clean reads were mapped to the reference genome database, further analyzed and annotated based on the reference genome information. Differentially expressed genes (DEGs) were identified using the DESeq R package (1.10.1) and DEGSeq R package (1.12.0). Using KOBAS software to execute the KEGG bioinformatics analyses, enriched signaling pathways of DEGs involved in the occurrence of breast cancer were determined. Subsequently, quantitative real time PCR was used to verify the accuracy of the expression profile of key DEGs from the RNA-seq result and to explore the expression patterns of novel cancer-related genes on 8 different clinical individuals. Results The transcriptomic sequencing results showed 937 DEGs, including 487 upregulated and 450 downregulated genes in the breast cancer specimens. Further quantitative gene expression analysis was performed and captured 252 DEGs (201 downregulated and 51 upregulated) that showed the same differential expression pattern in all libraries. Finally, 6 upregulated DEGs (CST2, DRP2, CLEC5A, SCD, KIAA1211, DTL) and 6 downregulated DEGs (STAC2, BTNL9, CA4, CD300LG, GPIHBP1 and PIGR), were confirmed in a quantitative real time PCR comparison of breast cancer and paracancerous breast tissues from 8 clinical specimens. KEGG analysis revealed various pathway changes, including 20 upregulated and 21 downregulated gene enrichment pathways. The extracellular matrix–receptor (ECM-receptor) interaction pathway was the most enriched pathway: all genes in this pathway were DEGs, including the THBS family, collagen and fibronectin. These DEGs and the ECM-receptor interaction pathway may perform important roles in breast cancer. Conclusion Several potential breast cancer-related genes and pathways were captured, including 7 novel upregulated genes and 76 novel downregulated genes that were not found in other studies. These genes are related to cell proliferation, movement and adhesion. They may be important for research into breast cancer mechanisms, particularly CST2 and CA4. A key signaling pathway, the ECM-receptor interaction signal pathway, was also identified as possibly involved in the development of breast cancer.

Endotoxins are toxic substances that widely exist in the environment and can enter the intestine with food and other substances. Intestinal epithelial cells are protected by a mucus layer that contains MUC2 as its main structural component. However, a detailed understanding of the mechanisms involved in the function of the mucus barrier in endotoxin penetration is lacking. Here, we established the most suitable proportion of Caco-2/HT-29 co-culture cells as a powerful tool to evaluate the intestinal mucus layer. Our findings significantly advance current knowledge as focal adhesion and ECM-receptor interaction were identified as the two most significantly implicated pathways in MUC2 small interfering RNA (siRNA)-transfected Caco-2/HT-29 co-culture cells after 24 h of LPS stimulation. When the mucus layer was not intact, LPS was found to damage the tight junctions of Caco-2/HT29 co-cultured cells. Furthermore, LPS was demonstrated to inhibit the integrin-mediated focal adhesion structure and damage the matrix network structure of the extracellular and actin microfilament skeletons. Ultimately, LPS inhibited the interactive communication between the extracellular matrix and the cytoskeleton for 24 h in the siMUC2 group compared with the LPS(+) and LPS(-) groups. Overall, we recognized the potential of MUC2 as a tool for barrier function in several intestinal bacterial diseases.

Urolithin A (UroA) can inhibit the growth of many human cancer cells, but it has not be reported if UroA inhibits nasopharyngeal carcinoma (NPC) cells. To explore the inhibitory effect of UroA on NPC and potential mechanism in vitro. RNA-sequencing-based mechanistic prediction was conducted by comparing KEGG enrichment of 40 μM UroA-treated for 24 h with untreated CNE2 cells. The untreated cells were selected as control. After NPC cells were treated with 20-60 μM UroA, proliferation, migration and invasion of were measured by colony formation, wound healing and transwell experiments. Apoptosis, mitochondrial membrane potential (MMP), reactive oxygen species (ROS) were measured by flow cytometry, Hoechst 33342, Rhodamine 123, JC-1 staining and ROS assay methods, respectively. Gene and protein expression were measured by RT-qPCR and Western blotting assay. RNA-sequencing and KEGG enrichment revealed UroA mainly altered the ECM receptor interaction pathway. UroA inhibited cells proliferation, epithelial-mesenchymal-transition pathway, migration and invasion with IC 50 values of 34.72 μM and 44.91 μM, induced apoptosis, MMP depolarization and increase ROS content at a concentration of 40 μM. UroA up-regulated E-cadherin, Bax/Bcl-2, c-caspase-3 and PARP proteins, while inhibiting COL4A1, MMP2, MMP9, N-cadherin, Vimentin and Snail proteins at 20-60 μM. Moreover, co-treatment of UroA (40 μM) and NAC (5 mM) could reverse the effect of UroA on apoptosis-related proteins. RNA-sequencing technology based on bioinformatic analyses may be applicable for studiying the mechanism of drugs for tumour treatment.

Photoreceptor cells are highly susceptible to oxidative-stress-induced damage due to their high metabolic rate. Oxidative stress plays a key role in driving pathological events in several different ocular diseases, which lead to retinal degeneration and ultimately blindness. A growing number of studies have been performed to understand downstream events caused by ROS induced oxidative stress in photoreceptor cells; however, the underlying mechanisms of ROS toxicity are not fully understood. To shed light on ROS induced downstream pathological events, we employed a tandem mass tag (TMT) labelling-based quantitative mass-spectrometric approach to determine proteome changes in 661W photoreceptor cells following oxidative stress induction via the application of different concentrations of H2O2 at different time points. Overall, 5920 proteins were identified and quantified, and 450 differentially expressed proteins (DEPs) were identified, which were altered in a dose and time dependent manner in all treatment groups compared to the control group. These proteins were involved in several biological pathways, including spliceosome and ribosome response, activated glutathione metabolism, decreased ECM-receptor interaction, oxidative phosphorylation, abnormally regulated lysosome, apoptosis, and ribosome biogenesis. Our results highlighted ECM receptor interaction, oxidative phosphorylation and spliceosome pathways as the major targets of oxidative stress that might mediate vascular dysfunction and cellular senescence.

The present study was aimed to explore possible key genes and bioprocess affected by age during fracture healing. GSE589, GSE592 and GSE1371 were downloaded from gene expression omnibus database. The time-series genes of three age levels rats were firstly identified with hclust function in R. Then functional and pathway enrichment analysis for selected time-series genes were performed. Finally, the VennDiagram package of R language was used to screen overlapping n time-series genes. The expression changes of time-series genes in the rats of three age levels were classified into two types: one was higher expressed at 0 day, decreased at 3 day to 2 week, and increased from 4 to 6 week; the other was the opposite. Functional and pathways enrichment analysis showed that 12 time-series genes of adult and old rats were significantly involved in ECM-receptor interaction pathway. The expression changes of 11 genes were consistent with time axis, 10 genes were up-regulated at 3 days after fracture, and increased slowly in 6 week, while Itga2b was down-regulated. The functions of 106 overlapping genes were all associated with growth and development of bone after fracture. The key genes in ECM-receptor interaction pathway including Spp1, Ibsp, Tnn and Col3a1 have been reported to be related to fracture in literatures. The difference during fracture healing in three age levels rats is mainly related to age. The Spp1, Ibsp, Tnn and Col3a1 are possible potential age-related genes and ECM-receptor interaction pathway is the potential age-related process during fracture healing.

•  Introduction •  Atherosclerosis ‐ overview ‐  General remarks ‐  Early atherosclerosis ‐  Exogenous and/or infectious activators ‐  Endogenous activators ‐  Later phases of atherosclerosis •  Innate and inflammatory pathways in atherogenesis •  Innate receptors ‐  PAMP and DAMP ‐  Pentraxins ‐  NOD‐like proteins/receptors (NLRs) ‐  toll‐like receptors (TLRs) ‐  Knockout of pattern recognition molecules reduces atherosclerosis •  Innate cytokines ‐  The innate cytokines interleukin‐1 (IL‐1) and tumor necrosis factor‐α (TNF‐α) ‐  TNF−/− ApoE−/− mice are less atherosclerotic ‐  IL‐1−/− ApoE−/− mice are less atherosclerotic ‐  Monocyte chemoattractant protein‐1 and fractalkine ‐  IL‐6 activates innate pathways and is produced by cardiovascular cells ‐  Functions of IL‐6 important for atherogenesis ‐  Role of trans‐signalling in cardiovascular inflammation ‐  Animal experiments suggest a role for the IL‐6 system in atherosclerosis •  Cytokine‐mediated interaction of vessel wall cells and leucocytes ‐  Endothelial cell (EC)‐monocyte interaction ‐  Smooth muscle cell (SMC)‐EC interaction ‐  SMC‐monocyte and SMC‐T cell interaction •  Summary and conclusion •  Future perspectives ‐  Which initiator(s) starts atherogenesis? ‐  Is there more than one starting point? ‐  What are the specific roles of the various cytokines in the vessel wall? ‐  Are treatments addressing different phases of atherogenesis of advantage? ‐  What about prevention? ‐  What are the expectations? Inflammation is a central element of atherogenesis. Innate pathways contribute to vascular inflammation. However, the initial molecular process(es) starting atherogenesis remain elusive. The various risk factors, represented by particular compounds (activators), may cause altered cellular functions in the endothelium (e.g. vascular endothelial cell activation or ‐dysfunction), in invading cells (e.g. inflammatory mediator production) or in local vessel wall cells (e.g. inflammatory mediators, migration), thereby triggering the innate inflammatory process. The cellular components of innate immunology include granulocytes, natural killer cells and monocytes. Among the molecular innate constituents are innate molecules, such as the toll‐like receptors or innate cytokines. Interleukin‐1 (IL‐1) and IL‐6 are among the innate cytokines. Cytokines are potent activators of a great number of cellular functions relevant to maintain or commove homeostasis of the vessel wall. Within the vessel wall, vascular smooth muscle cells (SMCs) can significantly contribute to the cytokine‐dependent inflammatory network by: (i) production of cytokines, (ii) response to cytokines and (iii) cytokine‐mediated interaction with invading leucocytes. The cytokines IL‐1 and IL‐6 are involved in SMC‐leucocyte interaction. The IL‐6 effects are proposed to be mediated by trans‐signalling. Dysregulated cellular functions resulting from dysregulated cytokine production may be the cause of cell accumulation, subsequent low‐density lipoprotein accumulation and deposition of extracellular matrix (ECM). The deposition of ECM, increased accumulation of leucocytes and altered levels of inflammatory mediators may constitute an ‘innate‐immunovascular‐memory’ resulting in an ever‐growing response to anew invasion. Thus, SMC‐fostered inflammation, promoted by invading innate cells, may be a potent component for development and acceleration of atherosclerosis.

This chapter contains sections titled: Introduction The extracellular matrix (ECM) and the airway smooth muscle (ASM) ASM and integrins The ASM cell and inflammation The ASM cell and infection References