Systematic prediction of key genes for ovarian cancer by co-expression network analysis

Ovarian cancer (OC) is the most lethal gynaecological malignancy, characterized by high recurrence and mortality. However, the mechanisms of its pathogenesis remain largely unknown, hindering the investigation of the functional roles. This study sought to identify key hub genes that may serve as biomarkers correlated with prognosis. Here, we conduct an integrated analysis using the weighted gene co-expression network analysis (WGCNA) to explore the clinically significant gene sets and identify candidate hub genes associated with OC clinical phenotypes. The gene expression profiles were obtained from the MERAV database. Validations of candidate hub genes were performed with RNASeqV2 data and the corresponding clinical information available from The Cancer Genome Atlas (TCGA) database. In addition, we examined the candidate genes in ovarian cancer cells. Totally, 19 modules were identified and 26 hub genes were extracted from the most significant module (R² = .53) in clinical stages. Through the validation of TCGA data, we found that five hub genes (COL1A1, DCN, LUM, POSTN and THBS2) predicted poor prognosis. Receiver operating characteristic (ROC) curves demonstrated that these five genes exhibited diagnostic efficiency for early-stage and advanced-stage cancer. The protein expression of these five genes in tumour tissues was significantly higher than that in normal tissues. Besides, the expression of COL1A1 was associated with the TAX resistance of tumours and could be affected by the autophagy level in OC cell line. In conclusion, our findings identified five genes could serve as biomarkers related to the prognosis of OC and may be helpful for revealing pathogenic mechanism and developing further research.     

MicroRNA-338 Inhibits Growth,Invasion and Metastasis of Gastric Cancer by Targeting NRP1 Expression

NRP1 as multifunctional non-tyrosine-kinase receptors play critical roles in tumor progression. MicroRNAs (miRNAs) are an important class of pervasive genes that are involved in a variety of biological functions, particularly cancer. It remains unclear whether miRNAs can regulate the expression of NRP1. The goal of this study was to identify miRNAs that could inhibit the growth, invasion and metastasis of gastric cancer by targeting NRP1 expression. We found that miR-338 expression was reduced in gastric cancer cell lines and in gastric cancer tissues. Moreover, we found that miR-338 inhibited gastric cancer cell migration, invasion, proliferation and promoted apoptosis by targeting NRP1 expression. As an upstream regulator of NRP1, miR-338 directly targets NRP1. The forced expression of miR-338 inhibited the phosphorylation of Erk1/2, P38 MAPK and Akt; however, the expression of phosphorylated Erk1/2, P38 MAPK and Akt was restored by the overexpression of NRP1. In AGS cells infected with miR-338 or transfected with SiNRP1, the protein levels of fibronectin, vimentin, N-cadherin and SNAIL were decreased, but the expression of E-cadherin was increased. The expression of mesenchymal markers in miR-338-expressing cells was restored to normal levels by the restoration of NRP1 expression. In vivo, miR-338 also decreased tumor growth and suppressed D-MVA by targeting NRP1. Therefore, we conclude that miR-338 acts as a novel tumor suppressor gene in gastric cancer. miR-338 can decrease migratory, invasive, proliferative and apoptotic behaviors, as well as gastric cancer EMT, by attenuating the expression of NRP1.     

Association of NDRG1 Gene Promoter Methylation with Reduced NDRG1 Expression in Gastric Cancer Cells and Tissue Specimens

NDRG1 (N-myc downstream-regulated gene 1) plays a role in cell differentiation and suppression of tumor metastasis. This study aims to determine the expression of NDRG1 mRNA and protein in gastric cancer cell lines and tissue specimens and then assess the possible cause of its aberrant expression. Six gastric cancer cell lines and 20 pairs of normal and gastric cancer tissue samples were used to assess NDRG1 expression using Real-time PCR and Western blot. High-resolution melting analysis (HRM) and methylation-specific PCR (MSP) were performed to detect gene mutation and methylation, respectively, in cell lines and tissues samples. Expression of NDRG1 mRNA and protein was downregulated in gastric cancer cell lines and tissues. Specifically, expression of NDRG1 mRNA and protein was lower in all six gastric cancer cell lines than that of normal gastric cells, while 15 out of 20 cases of gastric cancer tissues had the reduced levels of NDRG1 mRNA and protein. HRM data showed that there was no mutation in NDRG1 gene, but MSP data showed high levels of NDRG1 gene promoter methylation in the CpG islands in both cell lines and tissue samples. Moreover, treatment with the DNA methyltransferase inhibitor 5-Aza-2′-deoxycytidine upregulated NDRG1 expression in gastric cancer HGC27 cells, but not in the histone deacetylase inhibitor trichostatin A-treated HGC27 cells. In conclusion, this study has shown that expression of NDRG1 mRNA and protein was reduced in gastric cancer cell lines and tissues, which is due to methylation of NDRG1 gene promoter. Further study will unearth the clinical significance of the reduced NDRG1 protein in gastric cancer.     

Gene expression profiling for mechanistic understanding of cellular aggregation in mammalian cell perfusion cultures

Aggregation of baby hamster kidney (BHK) cells cultivated in perfusion mode for manufacturing recombinant proteins was characterized. The potential impact of cultivation time on cell aggregation for an aggregating culture (cell line A) was studied by comparing expression profiles of 84 genes in the extracellular adhesion molecules (ECM) pathway by qRT‐PCR from 9 and 25 day shake flask samples and 80 and 94 day bioreactor samples. Significant up‐regulation of THBS2 (4.4‐ to 6.9‐fold) was seen in both the 25 day shake flask and 80 and 94 day bioreactor samples compared to the 9 day shake flask while NCAM1 was down‐regulated 5.1‐ to 8.9‐fold in the 80 and 94 day bioreactor samples. Subsequent comparisons were made between cell line A and a non‐aggregating culture (cell line B). A 65 day perfusion bioreactor sample from cell line B served as the control for 80 and 94 day samples from four different perfusion bioreactors for cell line A. Of the 84 genes in the ECM pathway, four (COL1A1, COL4A1, THBS2, and VCAN) were consistently up‐regulated in cell line A while two (NCAM1 and THBS1) were consistently down‐regulated. The magnitudes of differential gene expression were much higher when cell lines were compared (4.1‐ to 44.6‐fold) than when early and late cell line B samples were compared (4.4‐ to 6.9‐fold) indicating greater variability between aggregating and non‐aggregating cell lines. Based on the differential gene expression results, two mechanistic models were proposed for aggregation of BHK cells in perfusion cultures. Biotechnol. Bioeng. 2013; 110: 483–490. © 2012 Wiley Periodicals, Inc.     

ZIC1 is downregulated through promoter hypermethylation in gastric cancer

As one of major epigenetic changes responsible for tumor suppressor gene inactivation in the development of cancer, promoter hypermethylation was proposed as a marker to define novel tumor suppressor genes. In the current study we identified ZIC1 (Zic family member 1, odd-paired Drosophila homolog) as a novel tumor suppressor gene silenced through promoter hypermethylation in gastric cancer, the second leading cause of cancer death worldwide. In all of gastric cancer cells lines examined, ZIC1 expression was downregulated and such downregulation was accompanied with the hypermethylation of ZIC1 promoter. Demethylation treatment with 5-aza-2′-deoxycytidine (Aza) reversed ZIC1 downregulation, highlighting the importance of promoter methylation to ZIC1 downregulation in gastric cancer cells. Notably, ZIC1 expression was significantly downregulated in primary gastric carcinoma tissues in comparison with non-tumor adjacent gastric tissues (p < 0.01). Accordingly, promoter methylation of ZIC1 was frequently detected in primary gastric carcinoma tissues (94.6%, 35/37) but not normal gastric tissues, indicating that promoter hypermethylation mediated ZIC1 downregulation may play an important role in gastric carcinogenesis. Indeed, ectopic expression of ZIC1 led to the growth inhibition of gastric cancer cells through the induction of S-phase cell cycle arrest (p < 0.01). Our results revealed ZIC1 as a novel candidate tumor suppressor gene downregulated through promoter hypermethylation in gastric cancer.     

Altered Expression of Fibrosis Genes in Capsules of Failed Ahmed Glaucoma Valve Implants

Purpose

Ahmed glaucoma valve (AGV) implant is an aqueous shunt device used to control intraocular pressure in glaucoma. Implant failure results from impervious encapsulation of the shunt plate causing increased hydraulic resistance and raised intraocular pressure. We hypothesized that deregulation of fibrosis pathway contributes to capsular resistance. We tested this by studying fibrosis related gene expression in failed AGV implants.

Methods

Differential gene expression was examined in failed AGV capsules and compared to normal control tenon. Following total RNA extraction, 84 key genes in fibrosis pathway were examined by real-time PCR using RT² Profiler PCR Array. Relative gene expression was calculated using ΔΔC_t method. Gene specific TaqMan assays were used to validate select genes with ≥2 fold differential expression in the array expression profile.

Results

We observed differential expression in several genes in the fibrosis pathway. Almost half (39/84) of examined genes showed ≥2 fold differential expression in majority of capsules examined on the array. TaqMan assays for select genes including CCN2 (CTGF), THBS1, SERPINE1, THBS2, COL3A1, MMP3, and IL1A in an increased validation sample set showed significant changes in expression (p value from <0.001 to 0.022) at a high frequency in concurrence with our array results.

Conclusions

Pathway-focused analyses identified candidate genes with altered expression providing molecular evidence for deregulation of the fibrosis pathway in AGV failure.     

CAPN2 acts as an indicator of hepatitis B virus to induce hepatic fibrosis

This study is aimed to investigate whether calpain 2 (CAPN2) serves as an indicator of the hepatitis B virus (HBV) to induce hepatic fibrosis. Differentially-expressed genes (DEGs) in HBV-induced hepatic fibrosis and normal liver tissues were analyzed, and signal pathway which was analyzed by the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis using DEGs. Next, the gene-related network map was constructed using the Search Tool for the Retrieval of Interacting Genes. Moreover, CAPN2 protein expression, level of hepatic fibrosis, CAPN2 messenger RNA level, and protein levels of CAPN2, a-SAM, COL3A1, COL1A1, and MAPK1 were determined using Immunohistochemistry (IHC), hematoxylin and eosin, RT-qPCR, and western blot (WB), respectively. There were 420 DEGs screened in HBV-induced hepatic fibrosis and normal liver tissues, among which, 373 were significantly upregulated and 47 were obviously downregulated. KEGG analysis showed that the upregulated DEGs were mainly concentrated in extracellular matrix-receptor interaction, protein digestion, and absorption signaling pathways. The network diagram analysis showed that the DEGs, such as CAPN2, ITGAV, and CCR2, play the key role in the DEG network map, and CAPN2 related to hepatic fibrosis via MAPK1. The increased CAPN2 expression and obvious hepatic fibrosis was displayed in the HBV-induced hepatic fibrosis tissues. In addition, HBV could induce CAPN2 expression, and the interference of CAPN2 could inhibit the expression of hepatic fibrosis markers, including a-SAM, COL3A1, COL1A1, and MAPK1. CAPN2 is regarded as a biomarker of hepatic fibrosis induced by HBV.     

Bioinformatics analysis identifies COL1A1, THBS2 and SPP1 as potential predictors of patient prognosis and immunotherapy response in gastric cancer

Background: The present study aimed to use bioinformatics tools to explore pivotal genes associated with the occurrence of gastric cancer (GC) and assess their prognostic significance, and link with clinicopathological parameters. We also investigated the predictive role of COL1A1, THBS2, and SPP1 in immunotherapy.Materials and methods: We identified differential genes (DEGs) that were up- and down-regulated in the three datasets ({"type":"entrez-geo","attrs":{"text":"GSE26942","term_id":"26942"}}GSE26942, {"type":"entrez-geo","attrs":{"text":"GSE13911","term_id":"13911"}}GSE13911, and {"type":"entrez-geo","attrs":{"text":"GSE118916","term_id":"118916"}}GSE118916) and created protein–protein interaction (PPI) networks from the overlapping DEGs. We then investigated the potential functions of the hub genes in cancer prognosis using PPI networks, and explored the influence of such genes in the immune environment.Results: Overall, 268 overlapping DEGs were identified, of which 230 were up-regulated and 38 were down-regulated. CytoHubba selected the top ten hub genes, which included SPP1, TIMP1, SERPINE1, MMP3, COL1A1, BGN, THBS2, CDH2, CXCL8, and THY1. With the exception of SPP1, survival analysis using the Kaplan–Meier database showed that the levels of expression of these genes were associated with overall survival. Genes in the most dominant module explored by MCODE, COL1A1, THBS2, and SPP1, were primarily enriched for two KEGG pathways. Further analysis showed that all three genes could influence clinicopathological parameters and immune microenvironment, and there was a significant correlation between COL1A1, THBS2, SPP1, and PD-L1 expression, thus indicating a potential predictive role for GC response to immunotherapy.Conclusion: ECM–receptor interactions and focal adhesion pathways are of great significance in the progression of GC. COL1A1, THBS2, and SPP1 may help predict immunotherapy response in GC patients.     

Identification of genes with correlated patterns of variations in DNA copy number and gene expression level in gastric cancer

To identify DNA copy number changes that had a direct influence on mRNA expression in gastric cancer, cDNA microarray-based comparative genomic hybridization (aCGH) and gene expression profiling were performed using 17 K cDNA microarrays. A set of 158 genes showing Pearson correlation coefficients over 0.6 between DNA copy number changes and mRNA expression level variations was selected. In an independent gene expression profiling of 60 tissue samples, the 158 genes were able to distinguish most of the normal and tumor tissues in an unsupervised hierarchical clustering, suggesting that the differential expression patterns displayed by this specific group of genes are most likely based on the gene copy number changes. Furthermore, 43 statistically significant (P<0.01) genes were selected that correctly distinguished all of the tissue samples. The copy number changes detected by aCGH can be verified by fluorescence in situ hybridization and real-time polymerase chain reaction. The selected genes include those that were previously identified as being tumor suppressors or deleted in various tumors, including GATA binding protein 4 (GATA4), monoamine oxidase A (MAOA), cyclin C (CCNC), and oncogenes including malignant fibrous histiocytoma amplified sequence 1 (MFHAS1/MASL1), high mobility group AT-hook 2 (HMGA2), PPAR binding protein (PPARBP), growth factor receptor-bound protein 7 (GRB7), and TBC1 (tre-2, BUB2, cdc16) domain family, member 1 (TBC1D1).     

Variation in gene expression patterns in human gastric cancers

Gastric cancer is the world's second most common cause of cancer death. We analyzed gene expression patterns in 90 primary gastric cancers, 14 metastatic gastric cancers, and 22 nonneoplastic gastric tissues, using cDNA microarrays representing approximately 30,300 genes. Gastric cancers were distinguished from nonneoplastic gastric tissues by characteristic differences in their gene expression patterns. We found a diversity of gene expression patterns in gastric cancer, reflecting variation in intrinsic properties of tumor and normal cells and variation in the cellular composition of these complex tissues. We identified several genes whose expression levels were significantly correlated with patient survival. The variations in gene expression patterns among cancers in different patients suggest differences in pathogenetic pathways and potential therapeutic strategies.     

Comparative expression analysis of four breast cancer subtypes versus matched normal tissue from the same patients

Gene expression studies have been widely used in an effort to identify signatures that can predict clinical progression of cancer. In this study we focused instead on identifying gene expression differences between breast tumors and adjacent normal tissue, and between different subtypes of tumor classified by clinical marker status. We have collected a set of 20 breast cancer tissues, matched with the adjacent pathologically normal tissue from the same patient. The cancer samples representing each subtype of breast cancer identified by estrogen receptor ER(+/-) and Her2(+/-) status and divided into four subgroups (ER+/Her2+, ER+/Her2-, ER-/Her2+, and ER-/Her2-) were hybridized on Affymetrix HG-133 Plus 2.0 microarrays. By comparing cancer samples with their matched normal controls we have identified 3537 overall differentially expressed genes using data analysis methods from Bioconductor. When we looked at the genes in common of the four subgroups, we found 151 regulated genes, some of them encoding known targets for breast cancer treatment. Unique genes in the four subgroups instead suggested gene regulation dependent on the ER/Her2 markers selection. In conclusion, the results indicate that microarray studies using robust analysis of matched tumor and normal samples from the same patients can be used to identify genes differentially expressed in breast cancer tumor subtypes even when small numbers of samples are considered and can further elucidate molecular features of breast cancer.