Meta-analysis of archived DNA microarrays identifies genes regulated by hypoxia and involved in a metastatic phenotype in cancer cells

Flu-CED: A comparative transcriptomics database of influenza virus-infected human and animal models

BACKGROUND

The continuing emergence of influenza virus has highlighted the value of public databases and related bioinformatic analysis tools in investigating transcriptomic change caused by different influenza virus infections in human and animal models.

METHODS

We collected a large amount of transcriptome research data related to influenza virus-infected human and animal models in public databases (GEO and ArrayExpress), and extracted and integrated array and metadata. The gene expression matrix was generated through strictly quality control, balance, standardization, batch correction, and gene annotation. We then analyzed gene expression in different species, virus, cells/tissues or after antibody/vaccine treatment and imported sample metadata and gene expression datasets into the database.

RESULTS

Overall, maintaining careful processing and quality control, we collected 8064 samples from 103 independent datasets, and constructed a comparative transcriptomics database of influenza virus named the Flu-CED database (Influenza comparative expression database, https://flu.com-med.org.cn/). Using integrated and processed transcriptomic data, we established a user-friendly website for realizing the integration, online retrieval, visualization, and exploration of gene expression of influenza virus infection in different species and the biological functions involved in differential genes. Flu-CED can quickly query single and multi-gene expression profiles, combining different experimental conditions for comparative transcriptome analysis, identifying differentially expressed genes (DEGs) between comparison groups, and conveniently finding DEGs.

CONCLUSION

Flu-CED provides data resources and tools for analyzing gene expression in human and animal models infected with influenza virus that can deepen our understanding of the mechanisms underlying disease occurrence and development, and enable prediction of key genes or therapeutic targets that can be used for medical research.

Identifying global expression patterns and key regulators in epithelial to mesenchymal transition through multi-study integration

Background

Epithelial to mesenchymal transition (EMT) is the process by which stationary epithelial cells transdifferentiate to mesenchymal cells with increased motility. EMT is integral in early stages of development and wound healing. Studies have shown that EMT could be a critical early event in tumor metastasis that is involved in acquisition of migratory and invasive properties in multiple carcinomas.

Methods

In this study, we used 15 published gene expression microarray datasets from Gene Expression Omnibus (GEO) that represent 12 cell lines from 6 cancer types across 95 observations (45 unique samples and 50 replicates) with different modes of induction of EMT or the reverse transition, mesenchymal to epithelial transition (MET). We integrated multiple gene expression datasets while considering study differences, batch effects, and noise in gene expression measurements. A universal differential EMT gene list was obtained by normalizing and correcting the data using four approaches, computing differential expression from each, and identifying a consensus ranking. We confirmed our discovery of novel EMT genes at mRNA and protein levels in an in vitro EMT model of prostate cancer – PC3 epi, EMT and Taxol resistant cell lines. We validate our discovery of C1orf116 as a novel EMT regulator by siRNA knockdown of C1orf116 in PC3 epithelial cells.

Results

Among differentially expressed genes, we found known epithelial and mesenchymal marker genes such as CDH1 and ZEB1. Additionally, we discovered genes known in a subset of carcinomas that were unknown in prostate cancer. This included epithelial specific LSR and S100A14 and mesenchymal specific DPYSL3. Furthermore, we also discovered novel EMT genes including a poorly-characterized gene C1orf116. We show that decreased expression of C1orf116 is associated with poor prognosis in lung and prostate cancer patients. We demonstrate that knockdown of C1orf116 expression induced expression of mesenchymal genes in epithelial prostate cancer cell line PC3-epi cells, suggesting it as a candidate driver of the epithelial phenotype.

Conclusions

This comprehensive approach of statistical analysis and functional validation identified global expression patterns in EMT and candidate regulatory genes, thereby both extending current knowledge and identifying novel drivers of EMT.

Electronic supplementary material

The online version of this article (doi:10.1186/s12885-017-3413-3) contains supplementary material, which is available to authorized users.

Cycling hypoxia induces a specific amplified inflammatory phenotype in endothelial cells and enhances tumor-promoting inflammation in vivo

Abnormal architecture of the tumor blood network, as well as heterogeneous erythrocyte flow, leads to temporal fluctuations in tissue oxygen tension exposing tumor and stromal cells to cycling hypoxia. Inflammation is another feature of tumor microenvironment and is considered as a new enabling characteristic of tumor progression. As cycling hypoxia is known to participate in tumor aggressiveness, the purpose of this study was to evaluate its role in tumor-promoting inflammation. Firstly, we assessed the impact of cycling hypoxia in vitro on endothelial inflammatory response induced by tumor necrosis factor α. Results showed that endothelial cells exposed to cycling hypoxia displayed an amplified proinflammatory phenotype, characterized by an increased expression of inflammatory cytokines, namely, interleukin (IL)-6 and IL-8; by an increased expression of adhesion molecules, in particular intercellular adhesion molecule-1 (ICAM-1); and consequently by an increase in THP-1 monocyte adhesion. This exacerbation of endothelial inflammatory phenotype occurs through nuclear factor-κB overactivation. Secondly, the role of cycling hypoxia was studied on overall tumor inflammation in vivo in tumor-bearing mice. Results showed that cycling hypoxia led to an enhanced inflammation in tumors as prostaglandin-endoperoxide synthase 2 (PTGS2), IL-6, CXCL1 (C-X-C motif ligand 1), and macrophage inflammatory protein 2 (murine IL-8 functional homologs) mRNA expression was increased and as a higher leukocyte infiltration was evidenced. Furthermore, cycling hypoxia-specific inflammatory phenotype, characterized by a simultaneous (baculoviral inhibitor of apoptosis repeat-containing 5)(low)/PTGS2(high)/ICAM-1(high)/IL-6(high)/IL-8(high) expression, is associated with a poor prognosis in human colon cancer. This new phenotype could thus be used in clinic to more precisely define prognosis for colon cancer patients. In conclusion, our findings evidenced for the first time the involvement of cycling hypoxia in tumor-promoting inflammation amplification.

Meta-Analysis of Microarray Data of Rainbow Trout Fry Gonad Differentiation Modulated by Ethynylestradiol

Sex differentiation in fish is a highly labile process easily reversed by the use of exogenous hormonal treatment and has led to environmental concerns since low doses of estrogenic molecules can adversely impact fish reproduction. The goal of this study was to identify pathways altered by treatment with ethynylestradiol (EE2) in developing fish and to find new target genes to be tested further for their possible role in male-to-female sex transdifferentiation. To this end, we have successfully adapted a previously developed bioinformatics workflow to a meta-analysis of two datasets studying sex reversal following exposure to EE2 in juvenile rainbow trout. The meta-analysis consisted of retrieving the intersection of the top gene lists generated for both datasets, performed at different levels of stringency. The intersecting gene lists, enriched in true positive differentially expressed genes (DEGs), were subjected to over-representation analysis (ORA) which allowed identifying several statistically significant enriched pathways altered by EE2 treatment and several new candidate pathways, such as progesterone-mediated oocyte maturation and PPAR signalling. Moreover, several relevant key genes potentially implicated in the early transdifferentiation process were selected. Altogether, the results show that EE2 has a great effect on gene expression in juvenile rainbow trout. The feminization process seems to result from the altered transcription of genes implicated in normal female gonad differentiation, resulting in expression similar to that observed in normal females (i.e. the repression of key testicular markers cyp17a1, cyp11b, tbx1), as well as from other genes (including transcription factors) that respond specifically to the EE2 treatment. The results also showed that the bioinformatics workflow can be applied to different types of microarray platforms and could be generalized to (eco)toxicogenomics studies for environmental risk assessment purposes.

Adaptation of a Bioinformatics Microarray Analysis Workflow for a Toxicogenomic Study in Rainbow Trout

Sex steroids play a key role in triggering sex differentiation in fish, the use of exogenous hormone treatment leading to partial or complete sex reversal. This phenomenon has attracted attention since the discovery that even low environmental doses of exogenous steroids can adversely affect gonad morphology (ovotestis development) and induce reproductive failure. Modern genomic-based technologies have enhanced opportunities to find out mechanisms of actions (MOA) and identify biomarkers related to the toxic action of a compound. However, high throughput data interpretation relies on statistical analysis, species genomic resources, and bioinformatics tools. The goals of this study are to improve the knowledge of feminisation in fish, by the analysis of molecular responses in the gonads of rainbow trout fry after chronic exposure to several doses (0.01, 0.1, 1 and 10 μg/L) of ethynylestradiol (EE2) and to offer target genes as potential biomarkers of ovotestis development. We successfully adapted a bioinformatics microarray analysis workflow elaborated on human data to a toxicogenomic study using rainbow trout, a fish species lacking accurate functional annotation and genomic resources. The workflow allowed to obtain lists of genes supposed to be enriched in true positive differentially expressed genes (DEGs), which were subjected to over-representation analysis methods (ORA). Several pathways and ontologies, mostly related to cell division and metabolism, sexual reproduction and steroid production, were found significantly enriched in our analyses. Moreover, two sets of potential ovotestis biomarkers were selected using several criteria. The first group displayed specific potential biomarkers belonging to pathways/ontologies highlighted in the experiment. Among them, the early ovarian differentiation gene foxl2a was overexpressed. The second group, which was highly sensitive but not specific, included the DEGs presenting the highest fold change and lowest p-value of the statistical workflow output. The methodology can be generalized to other (non-model) species and various types of microarray platforms.

Exosomes released from breast cancer carcinomas stimulate cell movement

For metastasis to occur cells must communicate with to their local environment to initiate growth and invasion. Exosomes have emerged as an important mediator of cell-to-cell signalling through the transfer of molecules such as mRNAs, microRNAs, and proteins between cells. Exosomes have been proposed to act as regulators of cancer progression. Here, we study the effect of exosomes on cell migration, an important step in metastasis. We performed cell migration assays, endocytosis assays, and exosome proteomic profiling on exosomes released from three breast cancer cell lines that model progressive stages of metastasis. Results from these experiments suggest: (1) exosomes promote cell migration and (2) the signal is stronger from exosomes isolated from cells with higher metastatic potentials; (3) exosomes are endocytosed at the same rate regardless of the cell type; (4) exosomes released from cells show differential enrichment of proteins with unique protein signatures of both identity and abundance. We conclude that breast cancer cells of increasing metastatic potential secrete exosomes with distinct protein signatures that proportionally increase cell movement and suggest that released exosomes could play an active role in metastasis.

Taxol-induced unfolded protein response activation in breast cancer cells exposed to hypoxia: ATF4 activation regulates autophagy and inhibits apoptosis

Understanding the mechanisms responsible for the resistance against chemotherapy-induced cell death is still of great interest since the number of patients with cancer increases and relapse is commonly observed. Indeed, the development of hypoxic regions as well as UPR (unfolded protein response) activation is known to promote cancer cell adaptive responses to the stressful tumor microenvironment and resistance against anticancer therapies. Therefore, the impact of UPR combined to hypoxia on autophagy and apoptosis activation during taxol exposure was investigated in MDA-MB-231 and T47D breast cancer cells. The results showed that taxol rapidly induced UPR activation and that hypoxia modulated taxol-induced UPR activation differently according to the different UPR pathways (PERK, ATF6, and IRE1α). The putative involvement of these signaling pathways in autophagy or in apoptosis regulation in response to taxol exposure was investigated. However, while no link between the activation of these three ER stress sensors and autophagy or apoptosis regulation could be evidenced, results showed that ATF4 activation, which occurs independently of UPR activation, was involved in taxol-induced autophagy completion. In addition, an ATF4-dependent mechanism leading to cancer cell adaptation and resistance against taxol-induced cell death was evidenced. Finally, our results demonstrate that expression of ATF4, in association with hypoxia-induced genes, can be used as a biomarker of a poor prognosis for human breast cancer patients supporting the conclusion that ATF4 might play an important role in adaptation and resistance of breast cancer cells to chemotherapy in hypoxic tumors.

Meta-analysis and gene set analysis of archived microarrays suggest implication of the spliceosome in metastatic and hypoxic phenotypes

We propose to make use of the wealth of underused DNA chip data available in public repositories to study the molecular mechanisms behind the adaptation of cancer cells to hypoxic conditions leading to the metastatic phenotype. We have developed new bioinformatics tools and adapted others to identify with maximum sensitivity those genes which are expressed differentially across several experiments. The comparison of two analytical approaches, based on either Over Representation Analysis or Functional Class Scoring, by a meta-analysis-based approach, led to the retrieval of known information about the biological situation - thus validating the model - but also more importantly to the discovery of the previously unknown implication of the spliceosome, the cellular machinery responsible for mRNA splicing, in the development of metastasis.

Reuse of public genome-wide gene expression data

Our understanding of gene expression has changed dramatically over the past decade, largely catalysed by technological developments. High-throughput experiments - microarrays and next-generation sequencing - have generated large amounts of genome-wide gene expression data that are collected in public archives. Added-value databases process, analyse and annotate these data further to make them accessible to every biologist. In this Review, we discuss the utility of the gene expression data that are in the public domain and how researchers are making use of these data. Reuse of public data can be very powerful, but there are many obstacles in data preparation and analysis and in the interpretation of the results. We will discuss these challenges and provide recommendations that we believe can improve the utility of such data.

TMEM45A is essential for hypoxia-induced chemoresistance in breast and liver cancer cells

BACKGROUND

Hypoxia is a common characteristic of solid tumors associated with reduced response to radio- and chemotherapy, therefore increasing the probability of tumor recurrence. The aim of this study was to identify new mechanisms responsible for hypoxia-induced resistance in breast cancer cells.

METHODS

MDA-MB-231 and HepG2 cells were incubated in the presence of taxol or etoposide respectively under normoxia and hypoxia and apoptosis was analysed. A whole transcriptome analysis was performed in order to identify genes whose expression profile was correlated with apoptosis. The effect of gene invalidation using siRNA was studied on drug-induced apoptosis.

RESULTS

MDA-MB-231 cells incubated in the presence of taxol were protected from apoptosis and cell death by hypoxia. We demonstrated that TMEM45A expression was associated with taxol resistance. TMEM45A expression was increased both in MDA-MB-231 human breast cancer cells and in HepG2 human hepatoma cells in conditions where protection of cells against apoptosis induced by chemotherapeutic agents was observed, i.e. under hypoxia in the presence of taxol or etoposide. Moreover, this resistance was suppressed by siRNA-mediated silencing of TMEM45A. Kaplan Meier curve showed an association between high TMEM45A expression and poor prognostic in breast cancer patients. Finally, TMEM45 is highly expressed in normal differentiated keratinocytes both in vitro and in vivo, suggesting that this protein is involved in epithelial functions.

CONCLUSION

Altogether, our results unravel a new mechanism for taxol and etoposide resistance mediated by TMEM45A. High levels of TMEM45A expression in tumors may be indicative of potential resistance to cancer therapy, making TMEM45A an interesting biomarker for resistance.

Strategies to explore functional genomics data sets in NCBI's GEO database

The Gene Expression Omnibus (GEO) database is a major repository that stores high-throughput functional genomics data sets that are generated using both microarray-based and sequence-based technologies. Data sets are submitted to GEO primarily by researchers who are publishing their results in journals that require original data to be made freely available for review and analysis. In addition to serving as a public archive for these data, GEO has a suite of tools that allow users to identify, analyze, and visualize data relevant to their specific interests. These tools include sample comparison applications, gene expression profile charts, data set clusters, genome browser tracks, and a powerful search engine that enables users to construct complex queries.

PathEx: a novel multi factors based datasets selector web tool

Background

Microarray experiments have become very popular in life science research. However, if such experiments are only considered independently, the possibilities for analysis and interpretation of many life science phenomena are reduced. The accumulation of publicly available data provides biomedical researchers with a valuable opportunity to either discover new phenomena or improve the interpretation and validation of other phenomena that partially understood or well known. This can only be achieved by intelligently exploiting this rich mine of information.

Description

Considering that technologies like microarrays remain prohibitively expensive for researchers with limited means to order their own experimental chips, it would be beneficial to re-use previously published microarray data. For certain researchers interested in finding gene groups (requiring many replicates), there is a great need for tools to help them to select appropriate datasets for analysis. These tools may be effective, if and only if, they are able to re-use previously deposited experiments or to create new experiments not initially envisioned by the depositors. However, the generation of new experiments requires that all published microarray data be completely annotated, which is not currently the case. Thus, we propose the PathEx approach.

Conclusion

This paper presents PathEx, a human-focused web solution built around a two-component system: one database component, enriched with relevant biological information (expression array, omics data, literature) from different sources, and another component comprising sophisticated web interfaces that allow users to perform complex dataset building queries on the contents integrated into the PathEx database.