Transcriptome Profiling of Human Ulcerative Colitis Mucosa Reveals Altered Expression of Pathways Enriched in Genetic Susceptibility Loci

Human colonic mucosa altered by inflammation due to ulcerative colitis (UC) displays a drastically altered pattern of gene expression compared with healthy tissue. We aimed to understand the underlying molecular pathways influencing these differences by analyzing three publically-available, independently-generated microarray datasets of gene expression from endoscopic biopsies of the colon. Gene set enrichment analysis (GSEA) revealed that all three datasets share 87 gene sets upregulated in UC lesions and 8 gene sets downregulated (false discovery rate <0.05). The upregulated pathways were dominated by gene sets involved in immune function and signaling, as well as the control of mitosis. We applied pathway analysis to genotype data derived from genome-wide association studies (GWAS) of UC, consisting of 5,584 cases and 11,587 controls assembled from eight European-ancestry cohorts. The upregulated pathways derived from the gene expression data showed a highly significant overlap with pathways derived from the genotype data (33 of 56 gene sets, hypergeometric P = 1.49×10^–19). This study supports the hypothesis that heritable variation in gene expression as measured by GWAS signals can influence key pathways in the development of disease, and that comparison of genetic susceptibility loci with gene expression signatures can differentiate key drivers of inflammation from secondary effects on gene expression of the inflammatory process.     

Impact of Gene Dosage on Gene Expression,Biological Processes and Survival in Cervical Cancer: A Genome-Wide Follow-Up Study

We investigated the role of tumor copy number (CN)–altered genome (CN-AG) in the carcinogenesis of cervical cancer (CC), especially its effect on gene expression, biological processes, and patient survival. Fifty-nine human papillomavirus 16 (HPV16)-positive CCs were investigated with microarrays–31 for mapping CN-AG and 55 for global gene expression, with 27 CCs in common. Five-year survival was investigated in 55 patients. Deletions and amplifications >2.5 Mb were defined as CN alterations. The %CN-AG varied from 0 to 32.2% (mean = 8.1±8.9). Tumors were classified as low (mean = 0.5±0.6, n = 11), medium (mean = 5.4±2.4, n = 10), or high (mean = 19.2±6.6, n = 10) CN. The highest %CN-AG was found in 3q, which contributed an average of 55% of all CN alterations. Genome-wide, only 5.3% of CN-altered genes were deregulated directly by gene dosage. In contrast, the rate in fully duplicated 3q was twice as high. Amplification of 3q explained 23.2% of deregulated genes in whole tumors (r² = 0.232, p = 0.006; analysis of variance), including genes located in 3q and other chromosomes. A total of 862 genes were deregulated exclusively in high-CN tumors, but only 22.9% were CN altered. This suggests that the remaining genes are not deregulated directly by gene dosage, but by mechanisms induced in trans by CN-altered genes. Anaphase-promoting complex/cyclosome (APC/C)-dependent proteasome proteolysis, glycolysis, and apoptosis were upregulated, whereas cell adhesion and angiogenesis were downregulated exclusively in high-CN tumors. The high %CN-AG and upregulated gene expression profile of APC/C-dependent proteasome proteolysis were associated with poor patient survival (p<0.05, log-rank test). Along with glycolysis, they were linearly associated with FIGO stage (r>0.38, p<0.01, Spearman test). Therefore, inhibition of APC/C-dependent proteasome proteolysis and glycolysis could be useful for CC treatment. However, whether they are indispensable for tumor growth remains to be demonstrated.     

Identification and Expression Analysis of Cytokinin Metabolic Genes in Soybean under Normal and Drought Conditions in Relation to Cytokinin Levels

Cytokinins (CKs) mediate cellular responses to drought stress and targeted control of CK metabolism can be used to develop drought-tolerant plants. Aiming to manipulate CK levels to improve drought tolerance of soybean cultivars through genetic engineering of CK metabolic genes, we surveyed the soybean genome and identified 14 CK biosynthetic (isopentenyltransferase, GmIPT) and 17 CK degradative (CK dehydrogenase, GmCKX) genes. Comparative analyses of GmIPTs and GmCKXs with Arabidopsis counterparts revealed their similar architecture. The average numbers of abiotic stress-inducible cis-elements per promoter were 0.4 and 1.2 for GmIPT and GmCKX genes, respectively, suggesting that upregulation of GmCKXs, thereby reduction of CK levels, maybe the major events under abiotic stresses. Indeed, the expression of 12 GmCKX genes was upregulated by dehydration in R2 roots. Overall, the expressions of soybean CK metabolic genes in various tissues at various stages were highly responsive to drought. CK contents in various organs at the reproductive (R2) stage were also determined under well-watered and drought stress conditions. Although tRNA-type GmIPT genes were highly expressed in soybean, cis-zeatin and its derivatives were found at low concentrations. Moreover, reduction of total CK content in R2 leaves under drought was attributable to the decrease in dihydrozeatin levels, suggesting a role of this molecule in regulating soybean's responses to drought stress. Our systematic analysis of the GmIPT and GmCKX families has provided an insight into CK metabolism in soybean under drought stress and a solid foundation for in-depth characterization and future development of improved drought-tolerant soybean cultivars by manipulation of CK levels via biotechnological approach.     

Identification of Highly Methylated Genes across Various Types of B-Cell Non-Hodgkin Lymphoma

Epigenetic alterations of gene expression are important in the development of cancer. In this study, we identified genes which are epigenetically altered in major lymphoma types. We used DNA microarray technology to assess changes in gene expression after treatment of 11 lymphoma cell lines with epigenetic drugs. We identified 233 genes with upregulated expression in treated cell lines and with downregulated expression in B-cell lymphoma patient samples (n = 480) when compared to normal B cells (n = 5). The top 30 genes were further analyzed by methylation specific PCR (MSP) in 18 lymphoma cell lines. Seven of the genes were methylated in more than 70% of the cell lines and were further subjected to quantitative MSP in 37 B-cell lymphoma patient samples (diffuse large B-cell lymphoma (activated B-cell like and germinal center B-cell like subtypes), follicular lymphoma and Burkitt`s lymphoma) and normal B lymphocytes from 10 healthy donors. The promoters of DSP, FZD8, KCNH2, and PPP1R14A were methylated in 28%, 67%, 22%, and 78% of the 36 tumor samples, respectively, but not in control samples. Validation using a second series of healthy donor controls (n = 42; normal B cells, peripheral blood mononuclear cells, bone marrow, tonsils and follicular hyperplasia) and fresh-frozen lymphoma biopsies (n = 25), confirmed the results. The DNA methylation biomarker panel consisting of DSP, FZD8, KCNH2, and PPP1R14A was positive in 89% (54/61) of all lymphomas. Receiver operating characteristic analysis to determine the discriminative power between lymphoma and healthy control samples showed a c-statistic of 0.96, indicating a possible role for the biomarker panel in monitoring of lymphoma patients.     

Host Gene Expression Profiling and In Vivo Cytokine Studies to Characterize the Role of Linezolid and Vancomycin in Methicillin-Resistant Staphylococcus aureus (MRSA) Murine Sepsis Model

Linezolid (L), a potent antibiotic for Methicillin Resistant Staphylococcus aureus (MRSA), inhibits bacterial protein synthesis. By contrast, vancomycin (V) is a cell wall active agent. Here, we used a murine sepsis model to test the hypothesis that L treatment is associated with differences in bacterial and host characteristics as compared to V. Mice were injected with S. aureus USA300, and then intravenously treated with 25 mg/kg of either L or V at 2 hours post infection (hpi). In vivo alpha-hemolysin production was reduced in both L and V-treated mice compared to untreated mice but the reduction did not reach the statistical significance [P = 0.12 for L; P = 0.70 for V). PVL was significantly reduced in L-treated mice compared to untreated mice (P = 0.02). However the reduction of in vivo PVL did not reach the statistical significance in V- treated mice compared to untreated mice (P = 0.27). Both antibiotics significantly reduced IL-1β production [P = 0.001 for L; P = 0.006 for V]. IL-6 was significantly reduced with L but not V antibiotic treatment [P<0.001 for L; P = 0.11 for V]. Neither treatment significantly reduced production of TNF-α. Whole-blood gene expression profiling showed no significant effect of L and V on uninfected mice. In S. aureus-infected mice, L altered the expression of a greater number of genes than V (95 vs. 42; P = 0.001). Pathway analysis for the differentially expressed genes identified toll-like receptor signaling pathway to be common to each S. aureus-infected comparison. Expression of immunomodulatory genes like Cxcl9, Cxcl10, Il1r2, Cd14 and Nfkbia was different among the treatment groups. Glycerolipid metabolism pathway was uniquely associated with L treatment in S. aureus infection. This study demonstrates that, as compared to V, treatment with L is associated with reduced levels of toxin production, differences in host inflammatory response, and distinct host gene expression characteristics in MRSA sepsis.     

Gene Expression Signatures That Predict Outcome of Tamoxifen-Treated Estrogen Receptor-Positive,High-Risk,Primary Breast Cancer Patients: A DBCG Study

Background

Tamoxifen significantly improves outcome for estrogen receptor-positive (ER+) breast cancer, but the 15-year recurrence rate remains 30%. The aim of this study was to identify gene profiles that accurately predicted the outcome of ER+ breast cancer patients who received adjuvant Tamoxifen mono-therapy.

Methodology/Principal Findings

Post-menopausal breast cancer patients diagnosed no later than 2002, being ER+ as defined by >1% IHC staining and having a frozen tumor sample with >50% tumor content were included. Tumor samples from 108 patients treated with adjuvant Tamoxifen were analyzed for the expression of 59 genes using quantitative-PCR. End-point was clinically verified recurrence to distant organs or ipsilateral breast. Gene profiles were identified using a model building procedure based on conditional logistic regression and leave-one-out cross-validation, followed by a non-parametric bootstrap (1000x re-sampling). The optimal profiles were further examined in 5 previously-reported datasets containing similar patient populations that were either treated with Tamoxifen or left untreated (n = 623). Three gene signatures were identified, the strongest being a 2-gene combination of BCL2-CDKN1A, exhibiting an accuracy of 75% for prediction of outcome. Independent examination using 4 previously-reported microarray datasets of Tamoxifen-treated patient samples (n = 503) confirmed the potential of BCL2-CDKN1A. The predictive value was further determined by comparing the ability of the genes to predict recurrence in an additional, previously-published, cohort consisting of Tamoxifen-treated (n = 58, p = 0.015) and untreated patients (n = 62, p = 0.25).

Conclusions/Significance

A novel gene expression signature predictive of outcome of Tamoxifen-treated patients was identified. The validation suggests that BCL2-CDKN1A exhibit promising predictive potential.     

12 Survival-related differentially expressed genes based on the TARGET-osteosarcoma database

The Therapeutically Applicable Research to Generate Effective Treatments (TARGET) project aims to determine molecular changes that drive childhood cancers, including osteosarcoma. The main purpose of the program is to use the open-source database to develop novel, effective, and less toxic therapies. We downloaded TARGET-OS RNA-Sequencing data through R studio and merged the mRNA expression of genes with clinical information (vital status, survival time and gender). Further, we analyzed differential gene expressions between dead and alive patients based on TARGET-OS project. By this study, we found 5758 differentially expressed genes between deceased and alive patients with a false discovery rate below 0.05; 4469 genes were upregulated in deceased patients compared to alive, whereas 1289 genes were downregulated. The survival-related genes were obtained using Kaplan–Meier survival analysis and Cox univariate regression (KM < 0.05 and Cox P-value < 0.05). Out of 5758 differentially expressed genes, only 217 have been associated with overall survival. Eight survival-related downregulated genes (ERCC4, CLUAP1, CTNNBIP1, GCA, RAB40C, SIRPA, USP11, and TCN2) and four survival-related upregulated genes (MUC1, COL13A1, JAG2 and KAZALD1) were selected for further analysis as potential independent prognostic candidate genes. This study may help to discover novel prognostic markers and potential therapeutic targets for osteosarcoma.