shinyGEO: a web-based application for analyzing gene expression omnibus datasets

Overexpression of cyclin F/CCNF as an independent prognostic factor for poor survival in clear cell renal cell carcinoma

Cyclin F (encoded by CCNF gene) has been reported to be implicated in the pathobiology of several human cancers. However, its potential clinical significance in clear cell renal cell carcinoma (ccRCC) remains unknown. The present study aimed to evaluate the potential significance of cyclin F, assessed by immunohistochemical (IHC) staining and molecular (bioinformatics) techniques, as a prognostic marker in ccRCC in relation to clinicopathological features and outcomes. IHC staining was performed using two independent ccRCC tissue array cohorts, herein called tissue macroarray (TMA)_1 and tissue microarray (TMA)_2, composed of 108 ccRCCs and 37 histologically normal tissues adjacent to the tumor (NAT) and 192 ccRCCs and 16 normal kidney samples, respectively. The mRNA expression data were obtained from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) public datasets, followed by bioinformatics analysis of biological mechanisms underlying prognosis. The relationship between immune cell infiltration level and CCNF expression in ccRCC was investigated using the Tumor Immune Estimation Resource 2.0 (TIMER2) and Gene Expression Profiling Interactive Analysis 2 (GEPIA2). Cyclin F expression was significantly elevated in ccRCC lesions compared to both NAT and normal renal tissues. Likewise, CCNF mRNA was markedly increased in ccRCCs relative to non-cancerous tissues. In all analyzed cohorts, tumors with features of more aggressive behavior were more likely to display cyclin F/CCNF-high expression than low. Furthermore, patients with high cyclin F/CCNF expression had shorter overall survival (OS) times than those with low expression. In addition, multivariable analysis revealed that cyclin F/CCNF-high expression was an independent prognostic factor for poor OS in ccRCC. Enrichment analysis for mechanistically relevant processes showed that CCNF and its highly correlated genes initiate the signaling pathways that eventually result in uncontrolled cell proliferation. CCNF expression was also correlated with immune cell infiltration and caused poor outcomes depending on the abundance of tumor-infiltrating immune cells in ccRCC. Our findings suggest that cyclin F/CCNF expression is likely to have an essential role in ccRCC pathobiology through regulating multiple oncogenic signaling pathways and affecting the tumor immune microenvironment and may serve as prognostic biomarker and promising therapeutic target in ccRCC.

Ubiquitin B, Ubiquitin C, and β-Catenin as Promising Diagnostic and Prognostic Tools in Prostate Cancer

Prostate cancer (PC) is a major global public health concern, imposing a significant burden on men and ranking as the second most prevalent malignancy. This study delves into the intricate world of ubiquitination processes and expression regulation, with a specific focus on understanding the roles of ubiquitin B (UBB), ubiquitin C (UBC), and β-Catenin in PC development. We thoroughly analyze the expression profiles of UBB, UBC, and β-Catenin, investigating their interactions and associations with clinical and histopathological data. These findings offer valuable insights into their potential as robust prognostic markers and their significance for patient survival. Our research uncovers the upregulation of UBB and UBC expression in PC tissues, and an even more pronounced expression in lymph node metastases, highlighting their pivotal roles in PC progression. Moreover, we identify a compelling correlation between high UBB and UBC levels and diminished overall survival in PC patients, emphasizing their clinical relevance. Additionally, we observe a significant reduction in membranous β-Catenin expression in PC tissues. Importantly, abnormal β-Catenin expression is strongly associated with shorter survival in PC patients and serves as a significant, independent prognostic factor for patient outcomes. Kaplan-Meier survival analysis indicates that patients with tumors characterized by simultaneous UBB and aberrant β-Catenin expression exhibit the poorest overall survival. These collective insights underline the clinical importance of evaluating UBB, UBC, and β-Catenin as combined prognostic markers in PC.

Molecular mapping of a core transcriptional signature of microglia-specific genes in schizophrenia

Besides playing a central role in neuroinflammation, microglia regulate synaptic development and is involved in plasticity. Converging lines of evidence suggest that these different processes play a critical role in schizophrenia. Furthermore, previous studies reported altered transcription of microglia genes in schizophrenia, while microglia itself seems to be involved in the etiopathology of the disease. However, the regional specificity of these brain transcriptional abnormalities remains unclear. Moreover, it is unknown whether brain and peripheral expression of microglia genes are related. Thus, we investigated the expression of a pre-registered list of 10 genes from a core signature of human microglia both at brain and peripheral levels. We included 9 independent Gene Expression Omnibus datasets (764 samples obtained from 266 individuals with schizophrenia and 237 healthy controls) from 8 different brain regions and 3 peripheral tissues. We report evidence of a widespread transcriptional alteration of microglia genes both in brain tissues (we observed a decreased expression in the cerebellum, associative striatum, hippocampus, and parietal cortex of individuals with schizophrenia compared with healthy controls) and whole blood (characterized by a mixed altered expression pattern). Our results suggest that brain underexpression of microglia genes may represent a candidate transcriptional signature for schizophrenia. Moreover, the dual brain-whole blood transcriptional alterations of microglia/macrophage genes identified support the model of schizophrenia as a whole-body disorder and lend weight to the use of blood samples as a potential source of biological peripheral biomarkers.

TidyGEO: preparing analysis-ready datasets from Gene Expression Omnibus

TidyGEO is a Web-based tool for downloading, tidying, and reformatting data series from Gene Expression Omnibus (GEO). As a freely accessible repository with data from over 6 million biological samples across more than 4000 organisms, GEO provides diverse opportunities for secondary research. Although scientists may find assay data relevant to a given research question, most analyses require sample-level annotations. In GEO, such annotations are stored alongside assay data in delimited, text-based files. However, the structure and semantics of the annotations vary widely from one series to another, and many annotations are not useful for analysis purposes. Thus, every GEO series must be tidied before it is analyzed. Manual approaches may be used, but these are error prone and take time away from other research tasks. Custom computer scripts can be written, but many scientists lack the computational expertise to create such scripts. To address these challenges, we created TidyGEO, which supports essential data-cleaning tasks for sample-level annotations, such as selecting informative columns, renaming columns, splitting or merging columns, standardizing data values, and filtering samples. Additionally, users can integrate annotations with assay data, restructure assay data, and generate code that enables others to reproduce these steps.

Aldehyde Dehydrogenase Genes as Prospective Actionable Targets in Acute Myeloid Leukemia

It has been previously shown that the aldehyde dehydrogenase (ALDH) family member ALDH1A1 has a significant association with acute myeloid leukemia (AML) patient risk group classification and that AML cells lacking ALDH1A1 expression can be readily killed via chemotherapy. In the past, however, a redundancy between the activities of subgroup members of the ALDH family has hampered the search for conclusive evidence to address the role of specific ALDH genes. Here, we describe the bioinformatics evaluation of all nineteen member genes of the ALDH family as prospective actionable targets for the development of methods aimed to improve AML treatment. We implicate ALDH1A1 in the development of recurrent AML, and we show that from the nineteen members of the ALDH family, ALDH1A1 and ALDH2 have the strongest association with AML patient risk group classification. Furthermore, we discover that the sum of the expression values for RNA from the genes, ALDH1A1 and ALDH2, has a stronger association with AML patient risk group classification and survival than either one gene alone does. In conclusion, we identify ALDH1A1 and ALDH2 as prospective actionable targets for the treatment of AML in high-risk patients. Substances that inhibit both enzymatic activities constitute potentially effective pharmaceutics.

Decorin suppresses tumor lymphangiogenesis: A mechanism to curtail cancer progression

The complex interplay between malignant cells and the cellular and molecular components of the tumor stroma is a key aspect of cancer growth and development. These tumor-host interactions are often affected by soluble bioactive molecules such as proteoglycans. Decorin, an archetypical small leucine-rich proteoglycan primarily expressed by stromal cells, affects cancer growth in its soluble form by interacting with several receptor tyrosine kinases (RTK). Overall, decorin leads to a context-dependent and protracted cessation of oncogenic RTK activity by attenuating their ability to drive a pro-survival program and to sustain a pro-angiogenic network. Through an unbiased transcriptomic analysis using deep RNAseq, we discovered that decorin downregulated a cluster of tumor-associated genes involved in lymphatic vessel development when systemically delivered to mice harboring breast carcinoma allografts. We found that Lyve1 and Podoplanin, two established markers of lymphatic vessels, were markedly suppressed at both the mRNA and protein levels and this suppression correlated with a significant reduction in tumor lymphatic vessels. We further discovered that soluble decorin, but not its homologous proteoglycan biglycan, inhibited lymphatic vessel sprouting in an ex vivo 3D model of lymphangiogenesis. Mechanistically, we found that decorin interacted with VEGFR3, the main lymphatic RTK, and its activity was required for the decorin-mediated block of lymphangiogenesis. Finally, we discovered that Lyve1 was in part degraded via decorin-evoked autophagy in a nutrient- and energy-independent manner. These findings implicate decorin as a new biological factor with anti-lymphangiogenic activity and provide a potential therapeutic agent for curtailing breast cancer growth and metastasis.

Cyclic-AMP response element binding protein (CREB) and microRNA miR-29b regulate renalase gene expression under catecholamine excess conditions

AIMS

Renalase, a key mediator of cross-talk between kidneys and sympathetic nervous system, exerts protective roles in various cardiovascular/renal disease states. However, molecular mechanisms underpinning renalase gene expression remain incompletely understood. Here, we sought to identify the key molecular regulators of renalase under basal/catecholamine-excess conditions.

MATERIALS AND METHODS

Identification of the core promoter domain of renalase was carried out by promoter-reporter assays in N2a/HEK-293/H9c2 cells. Computational analysis of the renalase core promoter domain, over-expression of cyclic-AMP-response-element-binding-protein (CREB)/dominant negative mutant of CREB, ChIP assays were performed to determine the role of CREB in transcription regulation. Role of the miR-29b-mediated-suppression of renalase was validated in-vivo by using locked-nucleic-acid-inhibitors of miR-29. qRT-PCR and Western-blot analyses measured the expression of renalase, CREB, miR-29b and normalization controls in cell lysates/ tissue samples under basal/epinephrine-treated conditions.

KEY FINDINGS

CREB, a downstream effector in epinephrine signaling, activated renalase expression via its binding to the renalase-promoter. Physiological doses of epinephrine and isoproteronol enhanced renalase-promoter activity and endogenous renalase protein level while propranolol diminished the promoter activity and endogenous renalase protein level indicating a potential role of beta-adrenergic receptor in renalase gene regulation. Multiple animal models (acute exercise, genetically hypertensive/stroke-prone mice/rat) displayed directionally-concordant expression of CREB and renalase. Administration of miR-29b inhibitor in mice upregulated endogenous renalase expression. Moreover, epinephrine treatment down-regulated miR-29b promoter-activity/transcript levels.

SIGNIFICANCE

This study provides evidence for renalase gene regulation by concomitant transcriptional activation via CREB and post-transcriptional attenuation via miR-29b under excess epinephrine conditions. These findings have implications for disease states with dysregulated catecholamines.

A critical review of datasets and computational suites for improving cancer theranostics and biomarker discovery

Cancer has been constantly evolving and so is the research pertaining to cancer diagnosis and therapeutic regimens. Early detection and specific therapeutics are the key features of modern cancer therapy. These requirements can only be fulfilled with the integration of diverse high-throughput technologies. Integration of advanced omics methodology involving genomics, epigenomics, proteomics, and transcriptomics provide a clear understanding of multi-faceted cancer. In the past few years, tremendous high-throughput data have been generated from cancer genomics and epigenomic analyses, which on further methodological analyses can yield better biological insights. The major epigenetic alterations reported in cancer are DNA methylation levels, histone post-translational modifications, and epi-miRNA regulating the oncogenes and tumor suppressor genes. While the genomic analyses like gene expression profiling, cancer gene prediction, and genome annotation divulge the genetic alterations in oncogenes or tumor suppressor genes. Also, systems biology approach using biological networks is being extensively used to identify novel cancer biomarkers. Therefore, integration of these multi-dimensional approaches will help to identify potential diagnostic and therapeutic biomarkers. Here, we reviewed the critical databases and tools dedicated to various epigenomic and genomic alterations in cancer. The review further focuses on the multi-omics resources available for further validating the identified cancer biomarkers. We also highlighted the tools for cancer biomarker discovery using a systems biology approach utilizing genomic and epigenomic data. Biomarkers predicted using such integrative approaches are shown to be more clinically relevant.

DRPPM-EASY: A Web-Based Framework for Integrative Analysis of Multi-Omics Cancer Datasets

High-throughput transcriptomic and proteomic analyses are now routinely applied to study cancer biology. However, complex omics integration remains challenging and often time-consuming. Here, we developed DRPPM-EASY, an R Shiny framework for integrative multi-omics analysis. We applied our application to analyze RNA-seq data generated from a USP7 knockdown in T-cell acute lymphoblastic leukemia (T-ALL) cell line, which identified upregulated expression of a TAL1-associated proliferative signature in T-cell acute lymphoblastic leukemia cell lines. Next, we performed proteomic profiling of the USP7 knockdown samples. Through DRPPM-EASY-Integration, we performed a concurrent analysis of the transcriptome and proteome and identified consistent disruption of the protein degradation machinery and spliceosome in samples with USP7 silencing. To further illustrate the utility of the R Shiny framework, we developed DRPPM-EASY-CCLE, a Shiny extension preloaded with the Cancer Cell Line Encyclopedia (CCLE) data. The DRPPM-EASY-CCLE app facilitates the sample querying and phenotype assignment by incorporating meta information, such as genetic mutation, metastasis status, sex, and collection site. As proof of concept, we verified the expression of TP53 associated DNA damage signature in TP53 mutated ovary cancer cells. Altogether, our open-source application provides an easy-to-use framework for omics exploration and discovery.

Lipid-related protein NECTIN2 is an important marker in the progression of carotid atherosclerosis: An intersection of clinical and basic studies

Background:

The nectin cell adhesion molecule 2 (NECTIN2) protein is a cell adhesion molecule involved in lipid metabolism. We aimed to explore the potential role of NECTIN2 in carotid atherosclerosis (CA).

Materials and Methods:

Patients who underwent carotid endarterectomy (CEA) at the First Affiliated Hospital of Zhengzhou University were enrolled in this study. APOE-/- rats fed western or normal diet were used to model early pathological changes in CA. The relationship between patients’ lipid indices and plaque severity was assessed using ordinal regression analysis. Mendelian randomisation (MR) analysis was used to determine the causal links between low-density lipoprotein cholesterol (LDL-C) and atherosclerosis. After matching analysis of the single-cell transcriptome and microarray data of carotid plaques, NECTIN2 was identified as a key factor affecting CA. The importance of NECTIN2 was further verified by immunofluorescence staining of CEA and APOE-/- rat specimens.

Results:

A total of 108 patients were included. The traditional lipid indices did not correlate significantly with the plaque severity (P > 0.05). NECTIN2 provided a strong causal link between LDL-C level and CA (MR effect size >0). Deep-sequencing data illustrated that NECTIN2 expression was cell specific. In early-stage CA, NECTIN2 expression was increased in endothelial cells; however, in advanced-stage CA, NECTIN2 was overexpressed in macrophages located in fibrous caps. APOE-/- rat carotid artery and human carotid plaques modelled the entire atherosclerotic process, showing an upregulation of NECTIN2 expression in CA.

Conclusions:

Lipid-related protein NECTIN2 is a potential marker in CA progression and can potentially be a new therapeutic target for clinical prevention.

FaDA: A web application for regular laboratory data analyses

Web-based data analysis and visualization tools are mostly designed for specific purposes, such as the analysis of data from whole transcriptome RNA sequencing or single-cell RNA sequencing. However, generic tools designed for the analysis of common laboratory data for noncomputational scientists are also needed. The importance of such web-based tools is emphasized by the continuing increases in the sample capacity of conventional laboratory tools such as quantitative PCR, flow cytometry or ELISA instruments. We present a web-based application FaDA, developed with the R Shiny package that provides users with the ability to perform statistical group comparisons, including parametric and nonparametric tests, with multiple testing corrections suitable for most standard wet-laboratory analyses. FaDA provides data visualizations such as heatmaps, principal component analysis (PCA) plots, correlograms and receiver operating curves (ROCs). Calculations are performed through the R language. The FaDA application provides a free and intuitive interface that allows biologists without bioinformatic skill to easily and quickly perform common laboratory data analyses. The application is freely accessible at https://shiny-bird.univ-nantes.fr/app/Fada.

Polymorphic estrogen receptor binding site causes Cd2-dependent sex bias in the susceptibility to autoimmune diseases

Complex autoimmune diseases are sexually dimorphic. An interplay between predisposing genetics and sex-related factors probably controls the sex discrepancy in the immune response, but the underlying mechanisms are unclear. Here we positionally identify a polymorphic estrogen receptor binding site that regulates Cd2 expression, leading to female-specific differences in T cell-dependent mouse models of autoimmunity. Female mice with reduced Cd2 expression have impaired autoreactive T cell responses. T cells lacking Cd2 costimulation upregulate inhibitory Lag-3. These findings help explain sexual dimorphism in human autoimmunity, as we find that CD2 polymorphisms are associated with rheumatoid arthritis and 17-β-estradiol-regulation of CD2 is conserved in human T cells. Hormonal regulation of CD2 might have implications for CD2-targeted therapy, as anti-Cd2 treatment more potently affects T cells in female mice. These results demonstrate the relevance of sex-genotype interactions, providing strong evidence for CD2 as a sex-sensitive predisposing factor in autoimmunity.

LAG-3 Blockade with Relatlimab (BMS-986016) Restores Anti-Leukemic Responses in Chronic Lymphocytic Leukemia

The inclusion of monoclonal antibodies targeting immune checkpoints such PD-1/PD-L1 or CTLA-4 has revolutionized the landscape of anti-cancer therapy. However, PD-1 and CTLA-4 blockade failed to achieve clinical benefit in CLL, thus attention has been focused on emerging checkpoints in this malignancy. LAG-3 is an immune checkpoint receptor that negatively regulates T cell-mediated responses by inducing an hyporesponsive state, thus promoting tumor escape. Patients with chronic lymphocytic leukemia (CLL) develop a profound immune suppression that leads to lessened immunosurveillance and increased risk of developing a secondary neoplasia. In the study herein, we report the profound dysregulation of LAG-3 on leukemic cells in CLL. Likewise, natural killer (NK) and T cells showed increased LAG-3 expression, hence suggesting a role for this checkpoint in CLL-associated immunosuppression. High LAG-3 expression, as well as high levels of soluble LAG-3 (sLAG-3), correlated with adverse cytogenetics and poor outcome in patients with CLL, highlighting the clinical relevance of this immune checkpoint. Treatment of peripheral blood mononuclear cells (PBMCs) from patients with CLL with relatlimab, a new anti-LAG-3 blocking antibody currently evaluated in numerous clinical trials, depleted leukemic cells and restored NK cell- and T cell-mediated responses. Moreover, combination of LAG-3 with the immunomodulatory drug (IMiD) lenalidomide significantly increased IL-2 production by T cells and antibody-dependent cytotoxicity (ADCC) mediated by NK cells. Altogether, these data provide new insights into the potential anti-leukemic effects of relatlimab, currently in clinical trials in CLL, and provides the rationale to further investigate its combination with IMiDs for the management of hematological malignancies.

BTLA/HVEM Axis Induces NK Cell Immunosuppression and Poor Outcome in Chronic Lymphocytic Leukemia

Simple Summary

Chronic lymphocytic leukemia (CLL) represents the most frequent B cell malignancy in Western countries and still remains as an incurable disease. Despite recent advances in targeted therapies including ibrutinib, idelalisib or venetoclax, resistance mechanisms have been described and patients develop a progressive immunosuppression. Since immune checkpoint blockade has demonstrated to reinvigorate T and NK cell-mediated anti-tumor responses, the aim of this work was to elucidate whether this immunosuppression relies, at least in part, in BTLA/HVEM axis in patients with CLL. Our results demonstrate that BTLA and HVEM expression is deeply dysregulated on leukemic and NK cells and correlates with poor outcome. Moreover, soluble BTLA levels correlated with adverse cytogenetics and shorter time to treatment. BTLA blockade restored, at least in part, NK cell-mediated responses in patients with CLL. Altogether, our results provide the rationale to further investigate the role of BTLA/HVEM axis in the pathogenesis of CLL.

Abstract

Chronic lymphocytic leukemia (CLL) is characterized by progressive immunosuppression and diminished cancer immunosurveillance. Immune checkpoint blockade (ICB)-based therapies, a major breakthrough against cancer, have emerged as a powerful tool to reinvigorate antitumor responses. Herein, we analyzed the role of the novel inhibitory checkpoint BTLA and its ligand, HVEM, in the regulation of leukemic and natural killer (NK) cells in CLL. Flow cytometry analyses showed that BTLA expression is upregulated on leukemic cells and NK cells from patients with CLL, whereas HVEM is downregulated only in leukemic cells, especially in patients with advanced Rai-Binet stage. In silico analysis revealed that increased HVEM, but not BTLA, mRNA expression in leukemic cells correlated with diminished overall survival. Further, soluble BTLA (sBTLA) was found to be increased in the sera of patients with CLL and highly correlated with poor prognostic markers and shorter time to treatment. BTLA blockade with an anti-BTLA monoclonal antibody depleted leukemic cells and boosted NK cell-mediated responses ex vivo by increasing their IFN-γ production, cytotoxic capability, and antibody-dependent cytotoxicity (ADCC). In agreement with an inhibitory role of BTLA in NK cells, surface BTLA expression on NK cells was associated with poor outcome in patients with CLL. Overall, this study is the first to bring to light a role of BTLA/HVEM in the suppression of NK cell-mediated immune responses in CLL and its impact on patient’s prognosis, suggesting that BTLA/HVEM axis may be a potential therapeutic target in this disease.

TANK-Binding Kinase 1 (TBK1) Serves as a Potential Target for Hepatocellular Carcinoma by Enhancing Tumor Immune Infiltration

Background

Numerous cancer types present the aberrant TANK-binding kinase 1 (TBK1) expression, which plays an important role in driving inflammation and innate immunity. However, the prognostic role of TBK1 and its relationship with immune cell infiltration in hepatocellular carcinoma (HCC) remain unclear.

Methods

The expression and prognostic value of TBK1 was analyzed by Tumor Immune Estimation Resource (TIMER), Kaplan-Meier plotter and Gene Expression Profiling Interactive Analysis (GEPIA), Clinical Proteomic Tumor Analysis Consortium (CPTAC) and further confirmed in the present cohort of patients with HCC. The association between TBK1 and HCC immune infiltrates, and its potential mechanism were investigated via analyses of the Tumor Immune Estimation Resource, tumor-immune system interactions database (TISIDB), CIBERSORT, STRING, and Metascape. The effect of TBK1 on immune infiltrates and the therapeutic value of targeting TBK1 were further investigated in a HCC mouse model by treatment with a TBK1 antagonist.

Results

The level of TBK1 expression in HCC was higher than that measured in normal tissues, and associated with poorer overall survival (GEPIA: hazard ratio [HR]=1.80, P=0.038; Kaplan-Meier plotter: HR=1.87, P<0.001; CPTAC: HR=2.23, P=0.007; Our cohort: HR=2.92, P=0.002). In addition, high TBK1 expression was found in HCC with advanced TNM stage and identified as an independent poor prognostic factor for overall survival among patients with HCC. In terms of immune infiltration, tumor tissues from HCC patients with high TBK1 expression had a low proportion of CD8+ T cells, and TBK1 expression did not show prognostic value in HCC patients with enriched CD8+ T cells. Furthermore, TBK1 expression was positively correlated with the markers of T cell exhaustion and immunosuppressive cells in the HCC microenvironment. Mechanistically, the promotion of HCC immunosuppression by TBK1 was involved in the regulation of inflammatory cytokines. In vivo experiments revealed that treatment with a TBK1 antagonist delayed HCC growth by increasing the number of tumor-infiltrating CD8+ T cells.

Conclusions

The up-regulated expression of TBK1 may be useful in predicting poor prognosis of patients with HCC. In addition, TBK1, which promotes the HCC immunosuppressive microenvironment, may be a potential immunotherapeutic target for patients with HCC.

Widespread transcriptional disruption of the microRNA biogenesis machinery in brain and peripheral tissues of individuals with schizophrenia

In schizophrenia, altered transcription in brain and peripheral tissues may be due to altered expression of the microRNA biogenesis machinery genes. In this study, we explore the expression of these genes both at the cerebral and peripheral levels. We used shinyGEO application to analyze gene expression from ten Gene Expression Omnibus datasets, in order to perform differential expression analyses for eight genes encoding the microRNA biogenesis machinery. First, we compared expression of the candidate genes between control subjects and individuals with schizophrenia in postmortem cerebral samples from seven different brain regions. Then, we compared the expression of the candidate genes between control subjects and individuals with schizophrenia in three peripheral tissues. In brain and peripheral tissues of individuals with schizophrenia, we report distinct altered expression patterns of the microRNA biogenesis machinery genes. In the dorsolateral prefrontal cortex, associative striatum and cerebellum of individuals with schizophrenia, we observed an overexpression pattern of some candidate genes suggesting a heightened miRNA production in these brain regions. Additionally, mixed transcriptional abnormalities were identified in the hippocampus. Moreover, in the blood and olfactory epithelium of individuals with schizophrenia, we observed distinct aberrant transcription patterns of the candidate genes. Remarkably, in individuals with schizophrenia, we report DICER1 overexpression in the dorsolateral prefrontal cortex, hippocampus and cerebellum as well as a congruent DICER1 upregulation in the blood compartment suggesting that it may represent a peripheral marker. Transcriptional disruption of the miRNA biogenesis machinery may contribute to schizophrenia pathogenesis both in brain and peripheral tissues.

Integrated Microarray to Identify the Hub miRNAs and Constructed miRNA-mRNA Network in Neuroblastoma Via Bioinformatics Analysis

Neuroblastomas (NB) are childhood malignant tumors originating in the sympathetic nervous system. MicroRNAs (miRNAs) play an essential regulatory role in tumorigenesis and development. In this study, NB miRNA and mRNA expression profile data in the Gene Expression Omnibus database were used to screen for differentially expressed miRNAs (DEMs) and genes (DEGs). We used the miRTarBase and miRSystem databases to predict the target genes of the DEMs, and we selected target genes that overlapped with the DEGs as candidate genes for further study. Annotations, visualization, and the DAVID database were used to perform Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis on the candidate genes. Additionally, the protein-protein interaction (PPI) network and miRNA-mRNA regulatory network were constructed and visualized using the STRING database and Cytoscape, and the hub modules were analyzed for function and pathway enrichment using the DAVID database and BiNGO plug-in. 107 DEMs and 1139 DEGs were identified from the miRNA and mRNA chips, respectively. 4390 overlapping target genes were identified using the two databases, and 405 candidate genes which intersected with the DEGs were selected. These candidate genes were enriched in 363 GO terms and 24 KEGG pathways. By constructing a PPI network and a miRNA-mRNA regulatory network, three hub miRNAs (hsa-miR-30e-5p, hsa-miR-15a, and hsa-miR-16) were identified. The target genes of the hub miRNAs were significantly enriched in the following pathways: microRNAs in cancer, the PI3K-Akt signaling pathway, pathways in cancer, the p53 signaling pathway, and the cell cycle. In summary, our results have identified candidate genes and pathways related to the underlying molecular mechanism of NB. These findings provide a new perspective for NB research and treatment.

Mining miRNAs' Expressions in Glioma Based on GEO Database and Their Effects on Biological Functions

PURPOSE

To mine miR expression in glioma based on the Gene Expression Omnibus (GEO) database and to explore its effects on biological functions.

METHODS

Differentially expressed miRs in glioma-related chips were found out based on the GEO database. Fifty patients with glioma treated in our hospital from February 2012 to July 2013 (observation group, OG) and a further 50 healthy people undergoing physical examinations (control group, CG) were enrolled. miR-873-5p expression in serum and in U87, T98G, U251, LN-229, and HEK-293T cells was tested by qRT-PCR. T98G and U251 cells were transfected with miR-873-5p-mimics and miR-NC sequences. The expression in the two cells was also tested by qRT-PCR. The proliferation, invasion, and apoptosis of the transfected cells were, respectively, tested by MTT assay, Transwell, and flow cytometry. The patients were followed up for 5 years to observe their survival.

RESULTS

miR-873-5p expression in OG was remarkably higher than that in CG (p < 0.001). miR-873-5p was closely correlated with the tumor diameter, lymph node metastasis, and TNM staging of the patients (p < 0.05). According to the plotted receiver operating characteristic (ROC) curves, the areas under the curves (AUCs) of miR-873-5p for diagnosing the disease, tumor diameter, lymph node metastasis, and TNM staging were 0.842, 0.706, 0.865, and 0.793, respectively. The 5-year and recurrence-free survival rates in the low expression group were lower than those in the high expression group. According to multivariate Cox regression analysis, tumor diameter, lymph node metastasis, and miR-873-5p were independent prognostic factors for the disease. After transfection, compared with those in the miR-NC group, T98G and U251 cells in the miR-873-5p-mimic group had remarkably higher miR-873-5p expression (p < 0.05), remarkably lower proliferation and invasion rates (p < 0.05), and a remarkably higher apoptotic rate (p < 0.05).

CONCLUSIONS

miR-873-5p can inhibit glioma cells to proliferate and invade, and promote their apoptosis, so it is expected to become a potential diagnostic index and therapeutic target for glioma.

Identification of potential specific biomarkers and key signaling pathways between osteogenic and adipogenic differentiation of hBMSCs for osteoporosis therapy

Background

The differentiation of bone mesenchymal stem cells (BMSCs) into adipogenesis (AD) rather than osteogenesis (OS) is an important pathological feature of osteoporosis. Illuminating the detailed mechanisms of the differentiation of BMSCs into OS and AD would contribute to the interpretation of osteoporosis pathology.

Methods

To identify the regulated mechanism in lineage commitment of the BMSCs into OS and AD in the early stages, the gene expression profiles with temporal series were downloaded to reveal the distinct fates when BMSCs adopt a committed lineage. For both OS and AD lineages, the profiles of days 2–4 were compared with day 0 to screen the differentially expressed genes (DEGs), respectively. Next, the functional enrichment analysis was utilized to find out the biological function, and protein-protein interaction network to predict the central genes. Finally, experiments were performed to verify our finding.

Results

FoxO signaling pathway with central genes like FoxO3, IL6, and CAT is the crucial mechanism of OS, while Rap1 signaling pathway of VEGFA and FGF2 enrichment is more significant for AD. Besides, PI3K-Akt signaling pathway might serve as the latent mechanism about the initiation of differentiation of BMSCs into multiple lineages.

Conclusion

Above hub genes and early-responder signaling pathways control osteogenic and adipogenic fates of BMSCs, which maybe mechanistic models clarifying the changes of bone metabolism in the clinical progress of osteoporosis. The findings provide a crucial reference for the prevention and therapy of osteoporosis.

High-dimensionality Data Analysis of Pharmacological Systems Associated with Complex Diseases

It is widely accepted that molecular reductionist views of highly complex human physiologic activity, e.g., the aging process, as well as therapeutic drug efficacy are largely oversimplifications. Currently some of the most effective appreciation of biologic disease and drug response complexity is achieved using high-dimensionality (H-D) data streams from transcriptomic, proteomic, metabolomics, or epigenomic pipelines. Multiple H-D data sets are now common and freely accessible for complex diseases such as metabolic syndrome, cardiovascular disease, and neurodegenerative conditions such as Alzheimer's disease. Over the last decade our ability to interrogate these high-dimensionality data streams has been profoundly enhanced through the development and implementation of highly effective bioinformatic platforms. Employing these computational approaches to understand the complexity of age-related diseases provides a facile mechanism to then synergize this pathologic appreciation with a similar level of understanding of therapeutic-mediated signaling. For informative pathology and drug-based analytics that are able to generate meaningful therapeutic insight across diverse data streams, novel informatics processes such as latent semantic indexing and topological data analyses will likely be important. Elucidation of H-D molecular disease signatures from diverse data streams will likely generate and refine new therapeutic strategies that will be designed with a cognizance of a realistic appreciation of the complexity of human age-related disease and drug effects. We contend that informatic platforms should be synergistic with more advanced chemical/drug and phenotypic cellular/tissue-based analytical predictive models to assist in either de novo drug prioritization or effective repurposing for the intervention of aging-related diseases. SIGNIFICANCE STATEMENT: All diseases, as well as pharmacological mechanisms, are far more complex than previously thought a decade ago. With the advent of commonplace access to technologies that produce large volumes of high-dimensionality data (e.g., transcriptomics, proteomics, metabolomics), it is now imperative that effective tools to appreciate this highly nuanced data are developed. Being able to appreciate the subtleties of high-dimensionality data will allow molecular pharmacologists to develop the most effective multidimensional therapeutics with effectively engineered efficacy profiles.

Automated Hypothesis Generation to Identify Signals Relevant in the Development of Mammalian Cell and Tissue Bioprocesses, With Validation in a Retinal Culture System

We have developed an accessible software tool (receptoR) to predict potentially active signaling pathways in one or more cell type(s) of interest from publicly available transcriptome data. As proof-of-concept, we applied it to mouse photoreceptors, yielding the previously untested hypothesis that activin signaling pathways are active in these cells. Expression of the type 2 activin receptor (Acvr2a) was experimentally confirmed by both RT-qPCR and immunochemistry, and activation of this signaling pathway with recombinant activin A significantly enhanced the survival of magnetically sorted photoreceptors in culture. Taken together, we demonstrate that our approach can be easily used to mine publicly available transcriptome data and generate hypotheses around receptor expression that can be used to identify novel signaling pathways in specific cell types of interest. We anticipate that receptoR (available at https://www.ucalgary.ca/ungrinlab/receptoR) will enable more efficient use of limited research resources.

DSCAM-AS1-Driven Proliferation of Breast Cancer Cells Involves Regulation of Alternative Exon Splicing and 3'-End Usage

DSCAM-AS1 is a cancer-related long noncoding RNA with higher expression levels in Luminal A, B, and HER2-positive Breast Carcinoma (BC), where its expression is strongly dependent on Estrogen Receptor Alpha (ERα). DSCAM-AS1 expression is analyzed in 30 public datasets and, additionally, by qRT-PCR in tumors from 93 BC patients, to uncover correlations with clinical data. Moreover, the effect of DSCAM-AS1 knockdown on gene expression and alternative splicing is studied by RNA-Seq in MCF-7 cells. We confirm DSCAM-AS1 overexpression in high grade Luminal A, B, and HER2+ BCs and find a significant correlation with disease relapse. In total, 908 genes are regulated by DSCAM-AS1-silencing, primarily involved in the cell cycle and inflammatory response. Noteworthily, the analysis of alternative splicing and isoform regulation reveals 2085 splicing events regulated by DSCAM-AS1, enriched in alternative polyadenylation sites, 3′UTR (untranslated region) shortening and exon skipping events. Finally, the DSCAM-AS1-interacting splicing factor heterogeneous nuclear ribonucleoprotein L (hnRNPL) is predicted as the most enriched RBP for exon skipping and 3′UTR events. The relevance of DSCAM-AS1 overexpression in BC is confirmed by clinical data and further enhanced by its possible involvement in the regulation of RNA processing, which is emerging as one of the most important dysfunctions in cancer.

Comprehensive analysis of the SLC16A gene family in pancreatic cancer via integrated bioinformatics

SLC16A family members play crucial roles in tumorigenesis and tumor progression. However, the exact role of distinct members in the SLC16A family in human pancreatic cancer remains unclear. Integrated bioinformatics analysis for the identification of therapeutic targets for certain cancers based on transcriptomics, proteomics and high-throughput sequencing could help us obtain novel information and understand potential underlying molecular mechanisms. In the present study, we investigated SLC16A family members in pancreatic cancer through accumulated data from GEO (Gene Expression Omnibus), TCGA (The Cancer Genome Atlas) and other available databases. The expression profile, clinical application significance and prognostic value of the SLC16A family for patients with pancreatic cancer were explored. SLC16A1, SLC16A3 and SLC16A13 exhibited biomarker potential for prognosis, and we further identified their related genes and regulatory networks, revealing core molecular pathways that require further investigation for pancreatic cancer.

Galectin-1 Overexpression Activates the FAK/PI3K/AKT/mTOR Pathway and Is Correlated with Upper Urinary Urothelial Carcinoma Progression and Survival

Galectin-1 (GAL1) is a β-galactoside-binding protein involved in multiple aspects of tumorigenesis. However, the biological role of GAL1 in upper tract urothelial carcinoma (UTUC) has not been entirely understood. Herein, we investigated the oncological effects of GAL1 expression in tumor specimens and identified related gene alterations through molecular analysis of GAL1. Clinical parameter data and tumor specimens were collected from 86 patients with pT3N0M0 UTUC who had undergone radical nephroureterectomy. We analyzed the difference in survival by using Kaplan-Meier analyses and Cox proportional regression models and in GAL1 expression by using immunohistochemical (IHC) methods. Public genomic data from the Cancer Genome Atlas (TCGA) and GSE32894 data sets were analyzed for comparison. Using four urothelial carcinoma (UC) cell lines (BFTC-909, T24, RT4, and J82) as in vitro models, we evaluated the functions of GAL1 in UC cell growth, invasiveness, and migration and its role in downstream signaling pathways. The study population was classified into two groups, GAL1-high (n = 35) and GAL1-low (GAL1 n = 51), according to IHC interpretation. Univariate analysis revealed that high GAL1 expression was significantly associated with poor recurrence-free survival (RFS; p = 0.028) and low cancer-specific survival (CSS; p = 0.025). Multivariate analysis revealed that GAL1-high was an independent predictive factor for RFS (hazard ratio (HR) 2.43; 95% confidence interval (CI) 1.17-5.05, p = 0.018) and CSS (HR 4.04; 95% CI 1.25-13.03, p = 0.019). In vitro studies revealed that GAL1 knockdown significantly reduced migration and invasiveness in UTUC (BFTC-909) and bladder cancer cells (T24). GAL1 knockdown significantly reduced protein levels of matrix metalloproteinase-2 (MMP-2) and MMP-9, which increased tissue inhibitor of metalloproteinase-1 (TIMP-1) and promoted epithelial-mesenchymal transition (EMT). Through gene expression microarray analysis of GAL1 vector and GAL1-KD cells, we identified multiple significant signaling pathways including p53, Forkhead box O (FOXO), and phosphoinositide 3-kinase/protein kinase B (PI3K/AKT). We validated microarray results through immunoblotting, thus proving that downregulation of GAL1 reduced focal adhesion kinase (FAK), p-PI3K, p-AKT, and p-mTOR expression. We concluded that GAL1 expression was highly related to oncological survival in patients with locally advanced UTUC. GAL1 promoted UC invasion and metastasis by activating the FAK/PI3K/AKT/mTOR pathway.

Preoperative plasma fatty acid metabolites inform risk of prostate cancer progression and may be used for personalized patient stratification

Background

Little is known about the relationship between the metabolite profile of plasma from pre-operative prostate cancer (PCa) patients and the risk of PCa progression. In this study we investigated the association between pre-operative plasma metabolites and risk of biochemical-, local- and metastatic-recurrence, with the aim of improving patient stratification.

Methods

We conducted a case-control study within a cohort of PCa patients recruited between 1996 and 2015. The age-matched primary cases (n = 33) were stratified in low risk, high risk without progression and high risk with progression as defined by the National Comprehensive Cancer Network. These samples were compared to metastatic (n = 9) and healthy controls (n = 10). The pre-operative plasma from primary cases and the plasma from metastatic patients and controls were assessed with untargeted metabolomics by LC-MS. The association between risk of progression and metabolite abundance was calculated using multivariate Cox proportional-hazard regression and the relationship between metabolites and outcome was calculated using median cut-off normalized values of metabolite abundance by Log-Rank test using the Kaplan Meier method.

Results

Medium-chain acylcarnitines (C6-C12) were positively associated with the risk of PSA progression (p = 0.036, median cut-off) while long-chain acylcarnitines (C14-C16) were inversely associated with local (p = 0.034) and bone progression (p = 0.0033). In primary cases, medium-chain acylcarnitines were positively associated with suberic acid, which also correlated with the risk of PSA progression (p = 0.032, Log-Rank test). In the metastatic samples, this effect was consistent for hexanoylcarnitine, L.octanoylcarnitine and decanoylcarnitine. Medium-chain acylcarnitines and suberic acid displayed the same inverse association with tryptophan, while indoleacetic acid, a breakdown product of tryptophan metabolism was strongly associated with PSA (p = 0.0081, Log-Rank test) and lymph node progression (p = 0.025, Log-Rank test). These data were consistent with the increased expression of indoleamine 2,3 dioxygenase (IDO1) in metastatic versus primary samples (p = 0.014). Finally, functional experiments revealed a synergistic effect of long chain fatty acids in combination with dihydrotestosterone administration on the transcription of androgen responsive genes.

Conclusions

This study strengthens the emerging link between fatty acid metabolism and PCa progression and suggests that measuring levels of medium- and long-chain acylcarnitines in pre-operative patient plasma may provide a basis for improving patient stratification.

Available Software for Meta-analyses of Genome-wide Expression Studies

Advances in transcriptomic methods have led to a large number of published Genome-Wide Expression Studies (GWES), in humans and model organisms. For several years, GWES involved the use of microarray platforms to compare genome-expression data for two or more groups of samples of interest. Meta-analysis of GWES is a powerful approach for the identification of differentially expressed genes in biological topics or diseases of interest, combining information from multiple primary studies. In this article, the main features of available software for carrying out meta-analysis of GWES have been reviewed and seven packages from the Bioconductor platform and five packages from the CRAN platform have been described. In addition, nine previously described programs and four online programs are reviewed. Finally, advantages and disadvantages of these available programs and proposed key points for future developments have been discussed.

NT5E/CD73 as Correlative Factor of Patient Survival and Natural Killer Cell Infiltration in Glioblastoma

CD73, a cell-surface protein encoded by the gene NT5E, is overexpressed in glioblastoma (GBM), where it contributes to the tumor’s pathophysiology via the generation of immunosuppressive adenosine. Adenosinergic signaling, in turn, drives immunosuppression of natural killer (NK) cells through metabolic and functional reprogramming. The correlation of CD73 with patient survival in relation to GBM pathology and the intratumoral infiltration of NK cells has not been comprehensively studied before. Here, we present an analysis of the prognostic relevance of CD73 in GBM based on transcriptional gene expression from patient data from The Cancer Genome Atlas (TCGA) database. Utilizing bioinformatics data mining tools, we explore the relationship between GBM prognosis, NT5E expression, and intratumoral presence of NK cells. Our analysis demonstrates that CD73 is a negative prognostic factor for GBM and that presence of NK cells may associate with improved prognosis. Moreover, the interplay between expression of NT5E and specific NK genes hints to potential functional effects of CD73 on NK cell activation.

Identification of crucial genes based on expression profiles of hepatocellular carcinomas by bioinformatics analysis

Hepatocellular carcinoma (HCC) is one of the most heterogeneous malignant cancers with no effective targets and treatments. However, the molecular pathogenesis of HCC remains largely uncertain. The aims of our study were to find crucial genes involved in HCC through multidimensional methods and revealed potential molecular mechanisms. Here, we reported the gene expression profile GSE121248 findings from 70 HCC and 37 adjacent normal tissues, all of which had chronic hepatitis B virus (HBV) infection, we were seeking to identify the dysregulated pathways, crucial genes and therapeutic targets implicated in HBV-associated HCC. We found 164 differentially expressed genes (DEGs) (92 downregulated genes and 72 upregulated genes). Gene ontology (GO) analysis of DEGs revealed significant functional enrichment of mitotic nuclear division, cell division, and the epoxygenase P450 pathway. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that the DEGs were mainly enriched in metabolism, cell cycle regulation and the p53 signaling pathway. The Mcode plugin was calculated to construct a module complex of DEGs, and the module was mainly enriched in cell cycle checkpoints, RHO GTPase effectors and cytochrome P450. Considering a weak contribution of each gene, gene set enrichment analysis (GSEA) was performed, revealing results consistent with those described above. Six crucial proteins were selected based on the degree of centrality, including NDC80, ESR1, ZWINT, NCAPG, ENO3 and CENPF. Real-time quantitative PCR analysis validated the six crucial genes had the same expression trend as predicted. Furthermore, the methylation data of The Cancer Genome Atlas (TCGA) with HCC showed that mRNA expression of crucial genes was negatively correlated with methylation levels of their promoter region. The overall survival reflected that high expression of NDC80, CENPF, ZWINT, and NCAPG significantly predicted poor prognosis, whereas ESR1 high expression exhibited a favorable prognosis. The identification of the crucial genes and pathways would contribute to the development of novel molecular targets and biomarker-driven treatments for HCC.

miR-221-5p regulates proliferation and migration in human prostate cancer cells and reduces tumor growth in vivo

Background

Despite latest advances in prostate cancer (PCa) therapy, PCa remains the third-leading cause of cancer-related death in European men. Dysregulation of microRNAs (miRNAs), small non-coding RNA molecules with gene expression regulatory function, has been reported in all types of epithelial and haematological cancers. In particular, miR-221-5p alterations have been reported in PCa.

Methods

miRNA expression data was retrieved from a comprehensive publicly available dataset of 218 PCa patients (GSE21036) and miR-221-5p expression levels were analysed. The functional role of miR-221-5p was characterised in androgen- dependent and androgen- independent PCa cell line models (C4–2 and PC-3M-Pro4 cells) by miR-221-5p overexpression and knock-down experiments. The metastatic potential of highly aggressive PC-3M-Pro4 cells overexpressing miR-221-5p was determined by studying extravasation in a zebrafish model. Finally, the effect of miR-221-5p overexpression on the growth of PC-3M-Pro4luc2 cells in vivo was studied by orthotopic implantation in male Balb/cByJ nude mice and assessment of tumor growth.

Results

Analysis of microRNA expression dataset for human primary and metastatic PCa samples and control normal adjacent benign prostate revealed miR-221-5p to be significantly downregulated in PCa compared to normal prostate tissue and in metastasis compared to primary PCa. Our in vitro data suggest that miR-221-5p overexpression reduced PCa cell proliferation and colony formation. Furthermore, miR-221-5p overexpression dramatically reduced migration of PCa cells, which was associated with differential expression of selected EMT markers. The functional changes of miR-221-5p overexpression were reversible by the loss of miR-221-5p levels, indicating that the tumor suppressive effects were specific to miR-221-5p. Additionally, miR-221-5p overexpression significantly reduced PC-3M-Pro4 cell extravasation and metastasis formation in a zebrafish model and decreased tumor burden in an orthotopic mouse model of PCa.

Conclusions

Together these data strongly support a tumor suppressive role of miR-221-5p in the context of PCa and its potential as therapeutic target.

Electronic supplementary material

The online version of this article (10.1186/s12885-019-5819-6) contains supplementary material, which is available to authorized users.

Mining data and metadata from the gene expression omnibus

Publicly available gene expression datasets deposited in the Gene Expression Omnibus (GEO) are growing at an accelerating rate. Such datasets hold great value for knowledge discovery, particularly when integrated. Although numerous software platforms and tools have been developed to enable reanalysis and integration of individual, or groups, of GEO datasets, large-scale reuse of those datasets is impeded by minimal requirements for standardized metadata both at the study and sample levels as well as uniform processing of the data across studies. Here, we review methodologies developed to facilitate the systematic curation and processing of publicly available gene expression datasets from GEO. We identify trends for advanced metadata curation and summarize approaches for reprocessing the data within the entire GEO repository.

BART: bioinformatics array research tool

Background

Microarray experiments comprise more than half of all series in the Gene Expression Omnibus (GEO). However, downloading and analyzing raw or semi-processed microarray data from GEO is not intuitive and requires manual error-prone analysis and a bioinformatics background. This is due to a lack of standardization in array platform fabrication as well as the lack of a simple interactive tool for clustering, plotting, differential expression testing, and testing for functional enrichment.

Results

We introduce the Bioinformatics Array Research Tool (BART), an R Shiny web application that automates the microarray download and analysis process across diverse microarray platforms. It provides an intuitive interface, automatically downloads and parses data from GEO, suggests groupings of samples for differential expression testing, performs batch effect correction, outputs quality control plots, converts probe IDs, generates full lists of differentially expressed genes, and performs functional enrichment analysis. We show that BART enables a more comprehensive analysis of a wider range of microarray datasets on GEO by comparing it to four leading online microarray analysis tools.

Conclusions

BART allows a scientist with no bioinformatics background to extract knowledge from their own microarray data or microarray experiments available from GEO. BART is functional on more microarray experiments and provides more comprehensive analyses than extant microarray analysis tools. BART is hosted on bart.salk.edu, includes a user tutorial, and is available for download from https://bitbucket.org/Luisa_amaral/bart.

ScanGEO: parallel mining of high-throughput gene expression data

Summary

Current options to mine publicly available gene expression data deposited in NCBI's gene expression omnibus (GEO), such as the GEO web portal and related applications, are optimized to reanalyze a single study, or search for a single gene, and therefore require manual intervention to reanalyze multiple studies for user-specified gene sets. ScanGEO is a simple, user-friendly Shiny web application designed to identify differentially expressed genes across all GEO studies matching user-specified criteria, for a flexible set of genes, visualize results and provide summary statistics and other reports using a single command.

Availability and implementation

The ScanGEO source code is written in R and implemented as a Shiny app that can be freely accessed at http://scangeo.dartmouth.edu/ScanGEO/. For users who would like to run a local instantiation of the app, the R source code is available under a GNU GPLv3 license at https://github.com/StantonLabDartmouth/AppScanGEO.

Contact

katja.koeppen@dartmouth.edu.

Supplementary information

Supplementary data are available at Bioinformatics online.

Curated compendium of human transcriptional biomarker data

One important use of genome-wide transcriptional profiles is to identify relationships between transcription levels and patient outcomes. These translational insights can guide the development of biomarkers for clinical application. Data from thousands of translational-biomarker studies have been deposited in public repositories, enabling reuse. However, data-reuse efforts require considerable time and expertise because transcriptional data are generated using heterogeneous profiling technologies, preprocessed using diverse normalization procedures, and annotated in non-standard ways. To address this problem, we curated 45 publicly available, translational-biomarker datasets from a variety of human diseases. To increase the data's utility, we reprocessed the raw expression data using a uniform computational pipeline, addressed quality-control problems, mapped the clinical annotations to a controlled vocabulary, and prepared consistently structured, analysis-ready data files. These data, along with scripts we used to prepare the data, are available in a public repository. We believe these data will be particularly useful to researchers seeking to perform benchmarking studies—for example, to compare and optimize machine-learning algorithms' ability to predict biomedical outcomes.

Identifying tumor promoting genomic alterations in tumor-associated fibroblasts via retrovirus-insertional mutagenesis

Tumor-associated fibroblasts (TAFs) are often essential for solid tumor growth. However, few genetic or epigenetic alterations have been found in TAFs during the progression of solid tumors. Employing a tumor-stromal cell co-injection model, we adapted here retroviral-insertional mutagenesis to stromal cells to identify novel tumor-associated genes in TAFs. We successfully identified 20 gene candidates that might modulate tumor growth if altered in TAFs at genomic level. To validate our finding, the function of one of the candidate genes, tubulin tyrosine ligase (Ttl), was further studied in TAFs from fibrosarcoma, colon, breast and hepatocarcinoma. We demonstrated that down-regulated TTL expression in TAFs indeed promoted tumor growth in mice. Interestingly, decreased expression of TTL in tumor stromal cells also correlated with poor outcome in human colon carcinoma. Thus, the co-injection model of tumor cells with retrovirus-modified fibroblasts proved a valid method to identify tumor-modulating genes in TAFs, allowing for a deeper insight into the role of the stroma for tumor development.

Genome-wide DNA methylation analysis in blood cells from patients with Werner syndrome

Background

Werner syndrome is a progeroid disorder characterized by premature age-related phenotypes. Although it is well established that autosomal recessive mutations in the WRN gene is responsible for Werner syndrome, the molecular alterations that lead to disease phenotype remain still unidentified.

Results

To address whether epigenetic changes can be associated with Werner syndrome phenotype, we analysed genome-wide DNA methylation profile using the Infinium MethylationEPIC BeadChip in the whole blood from three patients affected by Werner syndrome compared with three age- and sex-matched healthy controls. Hypermethylated probes were enriched in glycosphingolipid biosynthesis, FoxO signalling and insulin signalling pathways, while hypomethylated probes were enriched in PI3K-Akt signalling and focal adhesion pathways. Twenty-two out of 47 of the differentially methylated genes belonging to the enriched pathways resulted differentially expressed in a publicly available dataset on Werner syndrome fibroblasts. Interestingly, differentially methylated regions identified CERS1 and CERS3, two members of the ceramide synthase family. Moreover, we found differentially methylated probes within ITGA9 and ADAM12 genes, whose methylation is altered in systemic sclerosis, and within the PRDM8 gene, whose methylation is affected in dyskeratosis congenita and Down syndrome.

Conclusions

DNA methylation changes in the peripheral blood from Werner syndrome patients provide new insight in the pathogenesis of the disease, highlighting in some cases a functional correlation of gene expression and methylation status.

Electronic supplementary material

The online version of this article (doi:10.1186/s13148-017-0389-4) contains supplementary material, which is available to authorized users.