Establishment of optimal regulatory network of colorectal cancer based on p42.3 protein

Objective: to establish regulatory network of colorectal cancer involving p42.3 protein and to provide theoretical evidence for deep functional exploration of p42.3 protein in the onset and development of colorectal cancer. Methods: with protein similarity algorithm, reference protein set of p42.3 cell apoptosis was built according to structural features of p42.3. GO and KEGG databases were used to establish regulatory network of tumor cell apoptosis involving p42.3; meanwhile, the largest possible working pathway that involves p42.3 protein was screened out based on Bayesian network theory. Besides, GO and KEGG were used to build regulatory network on early diagnosis gene markers for colorectal cancer including WWOX, K-ras, COX-2, p53, APC, DCC and PTEN, at the same time, a regulatory network of colorectal cancer cell apoptosis which involves p42.3 was established. Results: cell apoptotic regulatory network that p42.3 participates in primarily consists of Bcl-2 family genes and the largest possible pathway is p42.3 → FKBP → Bcl-2 centered as FKBP protein. Combined with colorectal cancer regulatory network that involves early diagnosis gene markers, it can be predicted that p42.3 is most likely to regulate the colorectal cancer cell apoptosis through FKBP → Bcl-2 → Bax → caspase-9 → caspase-3 pathway. Conclusion: the colorectal cancer apoptosis network based on p42.3 established in the study provides theoretical evidence for deep exploration of p42.3 regulatory mechanism and molecular targeting treatment of colorectal cancer.     

MiR-29a inhibits cell proliferation and induces cell cycle arrest through the downregulation of p42.3 in human gastric cancer

As a newly identified and characterized gene, p42.3 is associated with cell proliferation and tumorigenicity. The expression of p42.3 is upregulated in human gastric cancer (GC), but its underlying mechanisms of action are not well understood. MicroRNAs (miRNAs) are known to play vital regulatory roles in many cellular processes. Here we utilized bioinformatics and experimental approaches to investigate the regulatory relationship between miRNAs and the p42.3 gene. We showed that miR-29a could repress p42.3 expression at both the mRNA and protein levels via directly binding to its 3'UTR. Furthermore, an inverse relationship was observed between miR-29a and p42.3 expression in gastric cancer cell lines and GC tissue samples, especially in cases where p42.3 was downregulated. Taken together, we have elucidated previously unrecognized roles of miR-29a and indicated that miR-29a may function, at least partially, by targeting the p42.3 gene in human GC.     

Cancerous HLA class I expression and regulatory T cell infiltration in gastric cancer

Background

Since antitumor immune reactions between tumors and intratumoral immunocytes have been verified in several human tumors, immunological therapeutic strategies must be considered to obtain the proper efficacy of tumor shrinkage under these conditions. Human leukocyte antigen (HLA) class I expression in cancer cells and degree of infiltration of regulatory T cells (Tregs) in the stroma have been regarded as important markers of antitumor immune reactions in the context of independent immunological mechanisms. In the current study, we investigated HLA class I expression and Treg cells infiltration in gastric cancer and discussed the clinical implications of this combinatory analysis in gastric cancer.

Patients and methods

A total of 141 gastric cancer patients who received R0 gastrectomy at Kagoshima University Hospital were studied. Immunohistochemically, in 141 gastric cancer patients, HLA class I expression and Treg cell infiltration in cancerous tissue were evaluated using HLA class I (EMR8-5) and forkhead box p3 (FOXP3) monoclonal antibodies. The correlation between clinical factors and tumor-infiltrating Treg cells was analyzed.

Results

HLA class I expression was positively associated with depth of tumor invasion (P?r?=?0.04). A better postoperative outcome was associated with fewer numbers of Treg infiltration (P?=?0.034). A combination of HLA and Treg analysis may lead to a more accurate prediction of postoperative outcome (P?=?0.02).

Conclusions

Two different antitumor immunological markers, Treg infiltration and HLA class I expression, affected clinicopathological factors in gastric cancer by different mechanisms. Thus, an immunological combination of HLA class I expression and Treg cell infiltration may more accurately predict postoperative outcome. Immunological balance needs to be restored after evaluation of each immunological deficit in gastric cancer.     

Low ATM protein expression and depletion of p53 correlates with olaparib sensitivity in gastric cancer cell lines

Small-molecule inhibitors of poly (ADP-ribose) polymerase (PARP) have shown considerable promise in the treatment of homologous recombination (HR)-defective tumors, such as BRCA1- and BRCA2-deficient breast and ovarian cancers. We previously reported that mantle cell lymphoma cells with deficiency in ataxia telangiectasia mutated (ATM) are sensitive to PARP-1 inhibitors in vitro and in vivo. Here, we report that PARP inhibitors can potentially target ATM deficiency arising in a solid malignancy. We show that ATM protein expression varies between gastric cancer cell lines, with NUGC4 having significantly reduced protein levels. Significant correlation was found between ATM protein expression and sensitivity to the PARP inhibitor olaparib, with NUGC4 being the most sensitive. Moreover, reducing ATM kinase activity using a small-molecule inhibitor (KU55933) or shRNA-mediated depletion of ATM protein enhanced olaparib sensitivity in gastric cancer cell lines with depletion or inactivation of p53. Our results demonstrate that ATM is a potential predictive biomarker for PARP-1 inhibitor activity in gastric cancer harboring disruption of p53, and that combined inhibition of ATM and PARP-1 is a rational strategy for expanding the utility of PARP-1 inhibitors to gastric cancer with p53 disruption.     

Variation of human mucin gene expression in gastric cancer cell lines and gastric mucous cell primary cultures

Human gastric mucous cells - gastric cancer cell lines mucin gene expression - TNFalpha - RT-PCR immunocytochemistry Little is known on the expression pattern of mucin genes in human gastric cancer cell lines in relation to mucin expression in normal gastric epithelial cells. Thus, the aim of this study was to compare gastric cancer cell lines and non-transformed epithelial cells in their expression of the different mucin genes, in order to use these cells as models for physiological MUC expression in human stomach. Human gastric mucous cell primary cultures which were obtained from surgical specimen by collagenase/pronase treatment and a panel of six human gastric cancer cells were screened for mRNA expression of the mucin genes MUC1, MUC2, MUC5AC, MUC5B, and MUC6. Mucin gene expression was analyzed by semi-quantitative RT-PCR, and by Western blotting and immunocytochemistry. Primary cultured human gastric mucous cells retained the stomach-specific pattern of mRNA expression found in gastric mucosal biopsies (MUC1, MUC5AC, MUC6), whereas any gastric cancer cell line exhibited an aberrant mucin gene expression. Mucin gene expression showed large variations in levels and patterns from cell line to cell line, but MUC2 was aberrantly expressed in all cancer cells. Immunocytochemistry confirmed aberrant MUC2 protein expression in cancer cells. The expression of the secretory mucin genes MUC2 and MUC5AC varied in relation to the length of cultivation of the cancer cell lines. Treatment of the gastric cancer cells with TNFalpha resulted in an enhanced mRNA expression of MUC1, MUC2, and MUC5AC (2-fold increase within 3 hours; p <0.05). In contrast, immunocytochemistry disclosed a decrease in MUC2 and MUC5AC staining intensity. Our results indicate that primary cultured human gastric mucous cells provide a physiological in vitro system for investigations of gastric mucin gene regulation. In gastric cancer cells marked changes in the mucin gene expression pattern are found with coexpression of non-gastric type mucins. Gastric mucin gene expression may be regulated by proinflammatory cytokines which could have implications in gastritis.     

The impact of C-MYC gene expression on gastric cancer cell

The upregulation or mutation of C-MYC has been observed in gastric, colon, breast, and lung tumors and in Burkitt’s lymphoma. However, little is known about the role C-MYC plays in gastric adenocarcinoma. In the present study, we intended to investigate the influence of C-MYC on the growth, proliferation, apoptosis, invasion, and cell cycle of the gastric cancer cell line SGC7901 and the gastric cell line HFE145. C-MYC cDNA was subcloned into a constitutive vector PCDNA3.1 followed by transfection in normal gastric cell line HFE145 by using liposome. Then stable transfectants were selected and appraised. Specific inhibition of C-MYC was achieved using a vector-based siRNA system which was transfected in gastric cancer cell line SGC7901. The apoptosis and cell cycles of these clones were analyzed by using flow cytometric assay. The growth and proliferation were analyzed by cell growth curves and colony-forming assay, respectively. The invasion of these clones was analyzed by using cell migration assay. The C-MYC stable expression clones (HFE-Myc) and C-MYC RNAi cells (SGC-MR) were detected and compared with their control groups, respectively. HFE-Myc grew faster than HFE145 and HFE-PC (HFE145 transfected with PCDNA3.1 vector). SGC-MR1, 2 grew slower than SGC7901 and SGC-MS1, 2 (SGC7901 transfected with scrambled control duplexes). The cell counts of HFE-Myc in the third, fourth, fifth, sixth, and seventh days were significantly more than those of control groups (P < 0.05). Those of SGC-MR1, 2 in the fourth, fifth, sixth, and seventh days were significantly fewer than those of control groups (P < 0.05). Cell cycle analysis showed that proportions of HFE-Myc and SGC-MR cells in G0–G1 and G2–M were different significantly with their control groups, respectively (P < 0.05). The apoptosis rate of HFE-Myc was significantly higher than those of control groups (P < 0.05). Results of colony-forming assay showed that the colony formation rate of HFE-Myc was higher than those of control groups; otherwise, the rate of SGC-MR was lower than those of their control groups (P < 0.05). The results of cell migration assay showed that there were no significant differences between experimental groups and control groups (P > 0.05). In conclusion, C-MYC can promote the growth and proliferation of normal gastric cells, and knockdown of C-MYC can restrain the growth and proliferation of gastric cancer cells. It can induce cell apoptosis and help tumor cell maintain malignant phenotype. But it can have not a detectable influence on the ability of invasion of gastric cancer cells.     

Interplay between gene expression noise and regulatory network architecture

Complex regulatory networks orchestrate most cellular processes in biological systems. Genes in such networks are subject to expression noise, resulting in isogenic cell populations exhibiting cell-to-cell variation in protein levels. Increasing evidence suggests that cells have evolved regulatory strategies to limit, tolerate or amplify expression noise. In this context, fundamental questions arise: how can the architecture of gene regulatory networks generate, make use of or be constrained by expression noise? Here, we discuss the interplay between expression noise and gene regulatory network at different levels of organization, ranging from a single regulatory interaction to entire regulatory networks. We then consider how this interplay impacts a variety of phenomena, such as pathogenicity, disease, adaptation to changing environments, differential cell-fate outcome and incomplete or partial penetrance effects. Finally, we highlight recent technological developments that permit measurements at the single-cell level, and discuss directions for future research.     

Integrating heterogeneous gene expression data for gene regulatory network modelling

Gene regulatory networks (GRNs) are complex biological systems that have a large impact on protein levels, so that discovering network interactions is a major objective of systems biology. Quantitative GRN models have been inferred, to date, from time series measurements of gene expression, but at small scale, and with limited application to real data. Time series experiments are typically short (number of time points of the order of ten), whereas regulatory networks can be very large (containing hundreds of genes). This creates an under-determination problem, which negatively influences the results of any inferential algorithm. Presented here is an integrative approach to model inference, which has not been previously discussed to the authors' knowledge. Multiple heterogeneous expression time series are used to infer the same model, and results are shown to be more robust to noise and parameter perturbation. Additionally, a wavelet analysis shows that these models display limited noise over-fitting within the individual datasets.     

Differential gene expression and network analysis in head and neck squamous cell carcinoma

Molecular and Cellular Biochemistry - Head and neck squamous cell carcinoma (HNSCC) is a prevalent malignancy with a poor prognosis, whose biomarkers have not been studied in great detail. We have...     

Finding gene regulatory network candidates using the gene expression knowledge base

Background

Network-based approaches for the analysis of large-scale genomics data have become well established. Biological networks provide a knowledge scaffold against which the patterns and dynamics of ‘omics’ data can be interpreted. The background information required for the construction of such networks is often dispersed across a multitude of knowledge bases in a variety of formats. The seamless integration of this information is one of the main challenges in bioinformatics. The Semantic Web offers powerful technologies for the assembly of integrated knowledge bases that are computationally comprehensible, thereby providing a potentially powerful resource for constructing biological networks and network-based analysis.

Results

We have developed the Gene eXpression Knowledge Base (GeXKB), a semantic web technology based resource that contains integrated knowledge about gene expression regulation. To affirm the utility of GeXKB we demonstrate how this resource can be exploited for the identification of candidate regulatory network proteins. We present four use cases that were designed from a biological perspective in order to find candidate members relevant for the gastrin hormone signaling network model. We show how a combination of specific query definitions and additional selection criteria derived from gene expression data and prior knowledge concerning candidate proteins can be used to retrieve a set of proteins that constitute valid candidates for regulatory network extensions.

Conclusions

Semantic web technologies provide the means for processing and integrating various heterogeneous information sources. The GeXKB offers biologists such an integrated knowledge resource, allowing them to address complex biological questions pertaining to gene expression. This work illustrates how GeXKB can be used in combination with gene expression results and literature information to identify new potential candidates that may be considered for extending a gene regulatory network.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-014-0386-y) contains supplementary material, which is available to authorized users.     

Systematic analysis of multigene predictors in gastric cancer exploiting gene expression signature

Gastric cancer (GC) is the second most common cause of cancer death worldwide but could be more curable if diagnosed at an earlier stage. At present, the capability to predict the efficaciousness of molecular diagnosis for GC for each patient remains elusive. The purpose of this study was to identify tumor biomarkers through systems analysis of multigene predictors exploiting the available data resource. In this study, we investigated the top 10% overexpressed genes in GC from five data sets of the Oncomine platform, with 265 GC samples versus 174 normal gastric mucosa samples. Sixteen candidate genes were identified as predictors of GC, of which 14 genes were verified through the comparison of expression levels in specimens from normal (chronic gastritis, 21 samples) and GC groups (38 samples). In addition, unique molecular portraits of diffuse adenocarcinoma (DA), intestinal adenocarcinoma (IA), and mixed adenocarcinoma (MA) were studied through Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis, where DA showed higher extracellular matrix alteration while IA and MA showed higher cell-cycle alteration than other types. We also found that the elevated expressions of genes during GC progression were independent of gene mutations, and high core-binding factor subunit β expression is correlated with a high overall survival rate in GC patients. Our research may provide an efficient clinical diagnosis of GC at an early stage with high accuracy and thus help improve the overall survival rate through early therapeutic interventions.     

Ad-IL-24对SGC-7901胃癌细胞生长抑制的体外实验

旨在研究携带人IL-24基因的腺病毒表达载体(Ad-IL-24)对SGC-7901人胃癌细胞的生长抑制作用并分析其分子机制。以不同MOI(感染复数)的Ad空载体腺病毒感染SGC-7901人胃癌细胞,筛选出最佳感染剂量;Ad-IL-24以最佳感染剂量感染SGC-7901胃癌细胞,RT-PCR法和Western blotting法检测腺病毒介导的IL-24基因在SGC-7901胃癌细胞中的转录;MTT法检测Ad-IL-24对SGC-7901胃癌细胞的生长抑制作用,流式细胞仪检测其诱导SGC-7901人胃癌细胞凋亡和细胞周期改变的效应,Hoechst33258染色荧光显微镜检测其诱导胃癌细胞凋亡的核形态改变;RT-PCR半定量法进一步检测SGC-7901胃癌细胞中凋亡相关基因的转录。结果显示,100MOI为感染SGC-7901胃癌细胞的腺病毒最佳感染剂量;Ad-IL-24能成功介导IL-24基因在SGC-7901胃癌细胞中转录性表达;Ad-IL-24感染SGC-7901胃癌细胞后,能明显抑制胃癌细胞生长和诱导凋亡;Ad-IL-24能显著上调SGC-7901胃癌细胞中bax、caspase-3和p53的表达和下调bc...     

Microarray analysis of piceatannol-induced changes in gene expression in human gastric cancer cells

Piceatannol, isolated from the roots of Rheum undulatum, prevented oxygen radical formation and inhibited lipid peroxidation; the effective concentrations were 25 M for a radical scavenging assay and 2.1 M for a microsome assay. Using cDNA microarray analysis to determine which genes were modulated by piceatannol, 33 genes were up-regulated while 157 genes were down-regulated in the human gastric cancer cell line.     

人p17.3基因及其推导蛋白的结构和功能分析

用生物信息学技术研究人类神经元蛋白p17.3的基因结构、染色体定位、组织表达特征及其推导蛋白的理化特性、空间结构和功能等。以高通量基因组序列(HTGS)数据库及SAGE文库为基础对p17.3基因进行染色体定位及组织表达谱分析。通过DAS和TMpred等程序预测其蛋白质结构及功能。利用PDB程序模拟其三维空间结构。研究表明p17.3基因定位于人类染色体Xp11.2-3,在多种组织中广谱表达,但在前列腺表达量最高。其编码蛋白含有一个PEST区域、一个线粒体靶向序列和一个潜在“跨膜螺旋”结构。p17.3基因可能是一个参与神经元发育调控的基因。     

cAMP-dependent protein phosphorylation and its regulatory role in the cell

Literary data are reviewed on the role of the cAMP-dependent phosphorylation of proteins in the regulation of cell metabolism, membrane permeability, and muscle contraction. It is suggested that a low cAMP level in the tumor and other actively proliferating cells may be associated with a raised exit of cAMP from cells into the surrounding medium because of the increased phosphorylation of the membrane proteins of these cells.