Meta-analysis Of Expression Profiles Research Articles

Identification of lncRNAs Deregulated in Epithelial Ovarian Cancer Based on a Gene Expression Profiling Meta-Analysis.

Epithelial ovarian cancer (EOC) is one of the deadliest gynecological cancers worldwide, mainly because of its initially asymptomatic nature and consequently late diagnosis. Long non-coding RNAs (lncRNA) are non-coding transcripts of more than 200 nucleotides, whose deregulation is involved in pathologies such as EOC, and are therefore envisaged as future biomarkers. We present a meta-analysis of available gene expression profiling (microarray and RNA sequencing) studies from EOC patients to identify lncRNA genes with diagnostic and prognostic value. In this meta-analysis, we include 46 independent cohorts, along with available expression profiling data from EOC cell lines. Differential expression analyses were conducted to identify those lncRNAs that are deregulated in (i) EOC versus healthy ovary tissue, (ii) unfavorable versus more favorable prognosis, (iii) metastatic versus primary tumors, (iv) chemoresistant versus chemosensitive EOC, and (v) correlation to specific histological subtypes of EOC. From the results of this meta-analysis, we established a panel of lncRNAs that are highly correlated with EOC. The panel includes several lncRNAs that are already known and even functionally characterized in EOC, but also lncRNAs that have not been previously correlated with this cancer, and which are discussed in relation to their putative role in EOC and their potential use as clinically relevant tools.

Expression profiling meta-analysis of ACE2 and TMPRSS2, the putative anti-inflammatory receptor and priming protease of SARS-CoV-2 in human cells, and identification of putative modulators

Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and has resulted in hundreds of thousands of deaths worldwide. While the majority of people with COVID-19 won't require hospitalization, those who do may experience severe life-threatening complications, including acute respiratory distress syndrome. SARS-CoV-2 infects human cells by binding to the cellular surface protein angiotensin-converting enzyme 2 (ACE2); in addition, the cellular transmembrane serine protease 2 (TMPRSS2) is needed for priming of the spike (S) protein of the virus. Virus entry may also depend on the activity of the endosomal/lysosomal cysteine proteases cathepsin B, L (CTSB, CTSL) although their activity is likely dispensable. Given that the uncertainty of how COVID-19 kills, hampers doctors' ability to choose treatments the need for a deep understanding of COVID-19 biology is urgent. Herein, we performed an expression profiling meta-analysis of ACE2, TMPRSS2 and CTSB/L genes (and proteins) in public repository databases and found that all are widely expressed in human tissues; also, the ACE2 and TMPRSS2 genes tend to be co-regulated. The ACE2 and TMPRSS genes expression is (among others) suppressed by TNF, and is induced by pro-inflammatory conditions including obesity, Barrett's esophagus, stomach infection by helicobacter pylori, diabetes, autoimmune diseases and oxidized LDL; by exercise, as well as by growth factors, viruses' infections, cigarette smoke, interferons and androgens. Regarding currently investigated therapies interferon-beta induced ACE2 gene expression in bronchial epithelial cells, while chloroquine tends to upregulate CTSB/L genes. Finally, we analyzed KEGG pathways modulated by ACE2, TMPRSS2 and CTSB/L and probed DrugBank for drugs that target modules of the affected pathways. Our data indicate possible novel high-risk groups for COVID-19; provide a rich resource for future investigations of its pathogenesis and highlight the therapeutic challenges we face.

Characterisation of transcription factor profiles in polycystic kidney disease (PKD): identification and validation of STAT3 and RUNX1 in the injury/repair response and PKD progression

Autosomal dominant polycystic kidney disease (ADPKD) is the most common genetic renal disease, caused in the majority of the cases by a mutation in either the PKD1 or the PKD2 gene. ADPKD is characterised by a progressive increase in the number and size of cysts, together with fibrosis and distortion of the renal architecture, over the years. This is accompanied by alterations in a complex network of signalling pathways. However, the underlying molecular mechanisms are not well characterised. Previously, we defined the PKD Signature, a set of genes typically dysregulated in PKD across different disease models from a meta-analysis of expression profiles. Given the importance of transcription factors (TFs) in modulating disease, we focused in this paper on characterising TFs from the PKD Signature. Our results revealed that out of the 1515 genes in the PKD Signature, 92 were TFs with altered expression in PKD, and 32 of those were also implicated in tissue injury/repair mechanisms. Validating the dysregulation of these TFs by qPCR in independent PKD and injury models largely confirmed these findings. STAT3 and RUNX1 displayed the strongest activation in cystic kidneys, as demonstrated by chromatin immunoprecipitation (ChIP) followed by qPCR. Using immunohistochemistry, we showed a dramatic increase of expression after renal injury in mice and cystic renal tissue of mice and humans. Our results suggest a role for STAT3 and RUNX1 and their downstream targets in the aetiology of ADPKD and indicate that the meta-analysis approach is a viable strategy for new target discovery in PKD.Key messagesWe identified a list of transcription factors (TFs) commonly dysregulated in ADPKD.Out of the 92 TFs identified in the PKD Signature, 35% are also involved in injury/repair processes.STAT3 and RUNX1 are the most significantly dysregulated TFs after injury and during PKD progression.STAT3 and RUNX1 activity is increased in cystic compared to non-cystic mouse kidneys.Increased expression of STAT3 and RUNX1 is observed in the nuclei of renal epithelial cells, also in human ADPKD samples.

Gene expression profiling meta-analysis reveals novel gene signatures and pathways shared between tuberculosis and rheumatoid arthritis.

Tuberculosis (TB) is among the leading causes of death by infectious diseases. An epidemiological association between Mycobacterium tuberculosis infection and autoimmune diseases like rheumatoid arthritis (RA) has been reported but it remains unclear if there is a causal relationship, and if so, which molecular pathways and regulatory mechanisms contribute to it. Here we used a computational biology approach by global gene expression meta-analysis to identify candidate genes and pathways that may link TB and RA. Data were collected from public expression databases such as NCBI GEO. Studies were selected that analyzed mRNA-expression in whole blood or blood cell populations in human case control studies at comparable conditions. Six TB and RA datasets (41 active TB patients, 33 RA patients, and 67 healthy controls) were included in the downstream analysis. This approach allowed the identification of deregulated genes that had not been identified in the single analysis of TB or RA patients and that were co-regulated in TB and RA patients compared to healthy subjects. The genes encoding TLR5, TNFSF10/TRAIL, PPP1R16B/TIMAP, SIAH1, PIK3IP1, and IL17RA were among the genes that were most significantly deregulated in TB and RA. Pathway enrichment analysis revealed ‘T cell receptor signaling pathway’, ‘Toll-like receptor signaling pathway,’ and ‘virus defense related pathways’ among the pathways most strongly associated with both diseases. The identification of a common gene signature and pathways substantiates the observation of an epidemiological association of TB and RA and provides clues on the mechanistic basis of this association. Newly identified genes may be a basis for future functional and epidemiological studies.

Molecular Portrait of Oral Tongue Squamous Cell Carcinoma Shown by Integrative Meta-Analysis of Expression Profiles with Validations.

Oral Tongue Squamous cell carcinoma (OTSCC), the most frequently affected oral cancer sub-site, is associated with a poor therapeutic outcome and survival despite aggressive multi- modality management. Till date, there are no established biomarkers to indicate prognosis and outcome in patients presenting with tongue cancer. There is an urgent need for reliable molecular prognostic factors to enable identification of patients with high risk of recurrence and treatment failure in OTSCC management. In the current study, we present the meta-analysis of OTSCC microarray based gene expression profiles, deriving a comprehensive molecular portrait of tongue cancer biology, showing the relevant genes and pathways which can be pursued further to derive novel, tailored therapeutics as well as for prognostication. We have studied 5 gene expression profiling data sets available on exclusively oral tongue subsite comprising of sample size; n = 190, consisting of 111 tumors and 79 normals. The meta- analysis results showed 2405 genes differentially regulated comparing OTSCC tumor and normal. The top up regulated genes were found to be involved in Extracellular matrix degradation (ECM) and Epithelial to mesenchymal transition (EMT) pathways. The top down regulated genes were found to be involved in detoxication pathways. We validated the results in clinical samples (n = 206), comprising of histologically normals (n = 10), prospective (n = 29) and retrospective (n = 167) OTSCC by evaluating MMP9 and E-cadherin gene expression by qPCR and immunohistochemistry. Consistent with meta-analysis results, MMP9 mRNA expression was significantly up regulated in OTSCC primary tumors compared to normals. MMP9 protein over expression was found to be a significant predictor of poor prognosis, disease recurrence and poor Disease Free Survival (DFS) in OTSCC patients. Analysis by univariate and multivariate Cox proportional hazard model showed patients with loss of E-cadherin expression in OTSCC tumors having a poorer DFS (HR = 1.566; P value = 0.045) and poorer Overall Survival (OS) (HR = 1.224; P value = 0.003) respectively. Combined over-expression of MMP9 and loss of E-cadherin membrane positivity in the invasive tumor front (ITF) of OTSCC had a significant association with poorer DFS (Log Rank = 16.040; P value = 0.001). These results suggest that along with known clinical indicators of prognosis like occult node positivity, assessment of MMP9 and E-cadherin expression at ITF can be useful to identify patients at high risk and requiring a more intensive treatment strategy for OTSCC. Meta-analysis study of gene expression profiles indicates that OTSCC is a disease of ECM degradation leading to activated EMT processes implying the aggressive nature of the disease. The triggers for these processes should be studied further. Newer clinical application with agents that can inhibit the mediators of ECM degradation may be a key to achieving clinical control of invasion and metastasis of OTSCC.

A meta-analysis approach for characterizing pan-cancer mechanisms of drug sensitivity in cell lines.

Understanding the heterogeneous drug response of cancer patients is essential to precision oncology. Pioneering genomic analyses of individual cancer subtypes have begun to identify key determinants of resistance, including up-regulation of multi-drug resistance (MDR) genes and mutational alterations of drug targets. However, these alterations are sufficient to explain only a minority of the population, and additional mechanisms of drug resistance or sensitivity are required to explain the remaining spectrum of patient responses to ultimately achieve the goal of precision oncology. We hypothesized that a pan-cancer analysis of in vitro drug sensitivities across numerous cancer lineages will improve the detection of statistical associations and yield more robust and, importantly, recurrent determinants of response. In this study, we developed a statistical framework based on the meta-analysis of expression profiles to identify pan-cancer markers and mechanisms of drug response. Using the Cancer Cell Line Encyclopaedia (CCLE), a large panel of several hundred cancer cell lines from numerous distinct lineages, we characterized both known and novel mechanisms of response to cytotoxic drugs including inhibitors of Topoisomerase 1 (TOP1; Topotecan, Irinotecan) and targeted therapies including inhibitors of histone deacetylases (HDAC; Panobinostat) and MAP/ERK kinases (MEK; PD-0325901, AZD6244). Notably, our analysis implicated reduced replication and transcriptional rates, as well as deficiency in DNA damage repair genes in resistance to TOP1 inhibitors. The constitutive activation of several signaling pathways including the interferon/STAT-1 pathway was implicated in resistance to the pan-HDAC inhibitor. Finally, a number of dysregulations upstream of MEK were identified as compensatory mechanisms of resistance to the MEK inhibitors. In comparison to alternative pan-cancer analysis strategies, our approach can better elucidate relevant drug response mechanisms. Moreover, the compendium of putative markers and mechanisms identified through our analysis can serve as a foundation for future studies into these drugs.

Bioinformatics and Biomedical Informatics

New and novel high-throughput systems for measurement of biological and physiological data have created a challenge: processing and analyzing the abundant resulting datastreams. There is a need for advanced computational methods to process these often very large datasets, and more generally to form decision-support systems for complex problems in medicine, biology, and related fields. During the last few decades, the vital role of these computational methods, in particular in emerging fields of life sciences such as translational medicine, has been further recognized. The need for more efficient computational methods has highlighted their roles as fundamental elements of almost any endeavor in today's life sciences. The current focus of these fields is on designing computational methods that facilitate the design and development of systems for clinical applications. This special issue serves as a brief update to the current status of and advances in methods of biomedical informatics and bioinformatics. The computational approaches presented span a number of methods, from newly developed algorithms in DNA microarray analysis to biomedical signal/image processing techniques. The particular diseases as well as remedies addressed, from novel components of schizophrenia to new diagnoses of breast cancer, address major health issues that any society today is likely to be facing. The paper by M. Logotheti et al. provides a comparative genomic study in patients suffering from schizophrenic and bipolar disorders using microarray expression profiling meta-analysis. A. Belle et al. present a survey of biomedical informatics, methods, and applications, as applied to computer-aided decision support systems. The paper by J. H. Phan et al. presents a meta-analysis-based feature selection method to combine multiple microarray datasets and improve reproducibility in identification of informative genes and subsequent clinical prediction. Finally, M. Burton et al. provide a cross-study comparison of classification methods of gene expression profiles for predicting metastasis in breast cancer. With the current burst of new biomedical measurement systems (in particular portable monitoring devices) among many new data sources, there are now petabyte and higher capacity biomedical databases requiring processing via ever-more efficient computational methods. Work on their designs in bioinformatics and biomedical informatics will accelerate further their quality and capacity, as imaging and monitoring technologies produce ever larger quantities of more detailed and more informative data. These works are continuing the advance of the above technologies and their frontiers. Kayvan Najarian Rachid Deriche Mark A. Kon Nina S. T. Hirata

A Comparative Genomic Study in Schizophrenic and in Bipolar Disorder Patients, Based on Microarray Expression Profiling Meta-Analysis

Schizophrenia affecting almost 1% and bipolar disorder affecting almost 3%–5% of the global population constitute two severe mental disorders. The catecholaminergic and the serotonergic pathways have been proved to play an important role in the development of schizophrenia, bipolar disorder, and other related psychiatric disorders. The aim of the study was to perform and interpret the results of a comparative genomic profiling study in schizophrenic patients as well as in healthy controls and in patients with bipolar disorder and try to relate and integrate our results with an aberrant amino acid transport through cell membranes. In particular we have focused on genes and mechanisms involved in amino acid transport through cell membranes from whole genome expression profiling data. We performed bioinformatic analysis on raw data derived from four different published studies. In two studies postmortem samples from prefrontal cortices, derived from patients with bipolar disorder, schizophrenia, and control subjects, have been used. In another study we used samples from postmortem orbitofrontal cortex of bipolar subjects while the final study was performed based on raw data from a gene expression profiling dataset in the postmortem superior temporal cortex of schizophrenics. The data were downloaded from NCBI's GEO datasets.

Abstract 4575: Three-gene diagnostic classifier for ALK negative ALCL

Abstract Anaplastic Large Cell Lymphomas (ALCL) comprise approximately 12% of all T-cell Non-Hodgkin's lymphomas (T-NHL), representing a heterogeneous group whose definition, origin and relationship with other T-NHL remains controversial. The notion that ALCL strongly express CD30, and display recurrent chromosomal translocations involving the Anaplastic Lymphoma Kinase (ALK) gene, led to recognition of two subsets, according to ALK expression. Although ALK positive ALCL can be readily diagnosed, ALK negative ALCL still lack unique genetic features and their distinction from other CD30 positive Peripheral T-Cell Lymphomas (PTCL) is not trivial. To unravel the regulatory network underlying lymphomagenesis of ALCL, and to discover new genomic classifiers for the recognition of ALK-positive and ALK-negative ALCL patients, we undertook a systematic approach of pathway discovery through a gene expression profiling meta-analysis of 309 cases, using data generated by five sets of experiments. In agreement with previous studies, unsupervised analyses were not able to distinguish ALCL from the other T-NHL categories. However, pathway discovery and prediction analyses defined a minimum set of genes useful for the stratification of ALK negative ALCL and strengthened the hypothesis that ALCL correspond to a distinctive pathological subgroup within T-NHL. Application of RT-qPCR in independent data sets of cryo-preserved and formalin-fixed paraffin embedded samples confirmed the gene expression profiling predictions and validated a simple model based on the measurement of three genes. These data suggest the possibility to translate RT-qPCR protocols to routine clinical settings as a new approach to precisely define T-NHL and to select more appropriate therapeutic protocols. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 4575. doi:1538-7445.AM2012-4575

Epithelial and Mesenchymal Subpopulations Within Normal Basal Breast Cell Lines Exhibit Distinct Stem Cell/Progenitor Properties

It has been proposed that epithelial-mesenchymal transition (EMT) in mammary epithelial cells and breast cancer cells generates stem cell features, and that the presence of EMT characteristics in claudin-low breast tumors reveals their origin in basal stem cells. It remains to be determined, however, whether EMT is an inherent property of normal basal stem cells, and if the presence of a mesenchymal-like phenotype is required for the maintenance of all their stem cell properties. We used nontumorigenic basal cell lines as models of normal stem cells/progenitors and demonstrate that these cell lines contain an epithelial subpopulation ("EpCAM+," epithelial cell adhesion molecule positive [EpCAM(pos)]/CD49f(high)) that spontaneously generates mesenchymal-like cells ("Fibros," EpCAM(neg)/CD49f(med/low)) through EMT. Importantly, stem cell/progenitor properties such as regenerative potential, high aldehyde dehydrogenase 1 activity, and formation of three-dimensional acini-like structures predominantly reside within EpCAM+ cells, while Fibros exhibit invasive behavior and mammosphere-forming ability. A gene expression profiling meta-analysis established that EpCAM+ cells show a luminal progenitor-like expression pattern, while Fibros most closely resemble stromal fibroblasts but not stem cells. Moreover, Fibros exhibit partial myoepithelial traits and strong similarities with claudin-low breast cancer cells. Finally, we demonstrate that Slug and Zeb1 EMT-inducers control the progenitor and mesenchymal-like phenotype in EpCAM+ cells and Fibros, respectively, by inhibiting luminal differentiation. In conclusion, nontumorigenic basal cell lines have intrinsic capacity for EMT, but a mesenchymal-like phenotype does not correlate with the acquisition of global stem cell/progenitor features. Based on our findings, we propose that EMT in normal basal cells and claudin-low breast cancers reflects aberrant/incomplete myoepithelial differentiation.

Notch signalling is off and is uncoupled from HES1 expression in Ewing's sarcoma

Notch can act as an oncogene or as a tumour suppressor and thus can either promote or inhibit tumour cell growth. To establish Notch status in Ewing's sarcoma family of tumours (ESFT), we investigated the Notch pathway by gene expression profiling meta-analysis or immunohistochemistry in samples obtained from 96 and 24 ESFT patients, respectively. We found that although Notch receptors were highly expressed, Notch did not appear to be active, as evidenced by the absence of Notch receptors in cell nuclei. In contrast, we show that Notch receptors known to be active in colon adenocarcinoma, hepatocarcinoma, and pancreatic carcinoma stain cell nuclei in these tumours. High expression of the Notch effector HES1 transcription factor, usually used as a surrogate marker for active Notch, was also restricted to outside of the nucleus in the majority of ESFT, and analysis of HES1 gene targets indicated HES1 to be transcriptionally inactive. Neither forced activation nor pharmacological or genetic blocking of Notch affected HES1 expression in ESFT cells, indicating HES1 expression to be uncoupled from the Notch pathway. Additional functional studies in ESFT cell lines confirmed Notch to be switched off. Finally, unlike experiments in which HES1 expression was modulated, experimental activation of Notch in ESFT cell lines via several means blocked cell proliferation and reduced their clonogenic potential in soft agar. These indicate that HES1 is uncoupled from Notch in ESFT, that EWS-FLI1-mediated inhibition of Notch contributes to ESFT aggressive cell growth, and support a role for Notch in ESFT tumour suppression, at least partly through the Notch effector HEY1.

Abstract 1936: Notch signaling is switched off and displays properties of a tumor suppressor in Ewing's sarcoma

Abstract Notch can act as an oncogene or as a tumor suppressor and thus can either promote or inhibit tumor cell growth. To establish Notch status in Ewing's sarcoma family of tumors (ESFT), we investigated the Notch pathway by gene expression profiling meta-analysis or immunohistochemistry in samples obtained from 96 and 24 ESFT patients, respectively. We find that although Notch receptors were highly expressed, Notch did not appear to be active as evidenced by the absence of Notch receptors in cell nuclei. High expression of the Notch effector HES1 transcription factor, usually used as a surrogate marker for active Notch, was also restricted to outside of the nucleus in the majority of tumors, and analysis of HES1 gene targets indicated HES1 to be transcriptionally inactive. Neither forced activation nor pharmacological or genetic blocking of Notch affected HES1 expression in ESFT cells, indicating HES1 expression to be uncoupled from the Notch pathway. Additional functional studies in ESFT cell lines confirmed Notch to be switched off. Finally, unlike experiments in which HES1 expression was modulated, experimental activation of Notch in ESFT cell lines via several means blocked cell proliferation. These indicate that HES1 is uncoupled from Notch in ESFT, that EWS-FLI1-mediated inhibition of Notch contributes to ESFT aggressive cell growth, and supports a role for Notch in ESFT tumor suppression, at least partly through the Notch effector HEY1. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 1936. doi:10.1158/1538-7445.AM2011-1936

Meta-analysis of expression profiles of 5-aza-C treated cancer cells

Meta-analysis of expression profiles of 5-aza-C treated cancer cells

Profiling Meta‐Analysis Reveals Primarily Gene Coexpression Concordance between Systemic Lupus Erythematosus and Rheumatoid Arthritis

Consensus gene expression profiling by meta-analysis of 4,500 cDNA sequence microarray data obtained from patients with systemic lupus erythematosus (SLE) and rheumatoid arthritis (RA) was assembled and systematically analyzed. The normalized data were statistically analyzed by the significance analysis of microarray (SAM) program (false discovery rate <or= 0.01). Patient data input was realized together, in the Cluster and Tree-View program, using the unsupervised function. Individual expression signatures permitted a hierarchical clustering of samples, separately identifying SLE and RA patients and the transcriptome profiling featured modules of the specifically induced or repressed and the comodulated genes. Gene expression profiling meta-analysis showed that patients with SLE or RA share gene modulation but also present genes whose expression patterns are exclusive (induced or repressed) in corroboration with their clinical features. Among the genes that were differentially expressed, we found those that could play specific roles in these two diseases. This approach permits a clearer understanding of the molecular basis of SLE and RA concordance/divergence.

An integrated approach of immunogenomics and bioinformatics to identify new Tumor Associated Antigens (TAA) for mammary cancer immunological prevention

BackgroundNeoplastic transformation is a multistep process in which distinct gene products of specific cell regulatory pathways are involved at each stage. Identification of overexpressed genes provides an unprecedented opportunity to address the immune system against antigens typical of defined stages of neoplastic transformation. HER-2/neu/ERBB2 (Her2) oncogene is a prototype of deregulated oncogenic protein kinase membrane receptors. Mice transgenic for rat Her2 (BALB-neuT mice) were studied to evaluate the stage in which vaccines can prevent the onset of Her2 driven mammary carcinomas. As Her2 is not overexpressed in all mammary carcinomas, definition of an additional set of tumor associated antigens (TAAs) expressed at defined stages by most breast carcinomas would allow a broader coverage of vaccination. To address this question, a meta-analysis was performed on two transcription profile studies [1,2] to identify a set of new TAA targets to be used instead of or in conjunction with Her2.ResultsThe five TAAs identified (Tes, Rcn2, Rnf4, Cradd, Galnt3) are those whose expression is linearly related to the tumor mass increase in BALB-neuT mammary glands. Moreover, they have a low expression in normal tissues and are generally expressed in human breast tumors, though at a lower level than Her2.ConclusionAlthough the number of putative TAAs identified is limited, this pilot study suggests that meta-analysis of expression profiles produces results that could assist in the designing of pre-clinical immunopreventive vaccines.

CLOE: Identification of putative functional relationships among genes by comparison of expression profiles between two species

BackgroundPublic repositories of microarray data contain an incredible amount of information that is potentially relevant to explore functional relationships among genes by meta-analysis of expression profiles. However, the widespread use of this resource by the scientific community is at the moment limited by the limited availability of effective tools of analysis. We here describe CLOE, a simple cDNA microarray data mining strategy based on meta-analysis of datasets from pairs of species. The method consists in ranking EST probes in the datasets of the two species according to the similarity of their expression profiles with that of two EST probes from orthologous genes, and extracting orthologous EST pairs from a given top interval of the ranked lists. The Gene Ontology annotation of the obtained candidate partners is then analyzed for keywords overrepresentation.ResultsWe demonstrate the capabilities of the approach by testing its predictive power on three proteomically-defined mammalian protein complexes, in comparison with single and multiple species meta-analysis approaches. Our results show that CLOE can find candidate partners for a greater number of genes, if compared to multiple species co-expression analysis, but retains a comparable specificity even when applied to species as close as mouse and human. On the other hand, it is much more specific than single organisms co-expression analysis, strongly reducing the number of potential candidate partners for a given gene of interest.ConclusionsCLOE represents a simple and effective data mining approach that can be easily used for meta-analysis of cDNA microarray experiments characterized by very heterogeneous coverage. Importantly, it produces for genes of interest an average number of high confidence putative partners that is in the range of standard experimental validation techniques.