Gastroenteropancreatic (GEP) neuroendocrine neoplasms (NENs) are increasing in both incidence and prevalence. A delay in correct diagnosis is common for these lesions. This reflects the absence of specific blood biomarkers to detect NENs. Measurement of the neuroendocrine secretory peptide Chromogranin A (CgA) is used, but is a single value, is non-specific and assay data are highly variable. To facilitate tumor detection, we developed a multi-transcript molecular signature for PCR-based blood analysis. NEN transcripts were identified by computational analysis of 3 microarray datasets: NEN tissue (n = 15), NEN peripheral blood (n = 7), and adenocarcinoma (n = 363 tumors). The candidate gene signature was examined in 130 blood samples (NENs: n = 63) and validated in two independent sets (Set 1 [n = 115, NENs: n = 72]; Set 2 [n = 120, NENs: n = 58]). Comparison with CgA (ELISA) was undertaken in 176 samples (NENs: n = 81). 51 significantly elevated transcript markers were identified. Gene-based classifiers detected NENs in independent sets with high sensitivity (85–98%), specificity (93–97%), PPV (95–96%) and NPV (87–98%). The AUC for the NEN gene-based classifiers was 0.95–0.98 compared to 0.64 for CgA (Z-statistic 6.97–11.42, p<0.0001). Overall, the gene-based classifier was significantly (χ2 = 12.3, p<0.0005) more accurate than CgA. In a sub-analysis, pancreatic NENs and gastrointestinal NENs could be identified with similar efficacy (79–88% sensitivity, 94% specificity), as could metastases (85%). In patients with low CgA, 91% exhibited elevated transcript markers. A panel of 51 marker genes differentiates NENs from controls with a high PPV and NPV (>90%), identifies pancreatic and gastrointestinal NENs with similar efficacy, and confirms GEP-NENs when CgA levels are low. The panel is significantly more accurate than the CgA assay. This reflects its utility to identify multiple diverse biological components of NENs. Application of this sensitive and specific PCR-based blood test to NENs will allow accurate detection of disease, and potentially define disease progress enabling monitoring of treatment efficacy.
In inflammatory bowel disease (IBD), genetic susceptibility together with environmental factors disturbs gut homeostasis producing chronic inflammation. The two main IBD subtypes are Ulcerative colitis (UC) and Crohn’s disease (CD). We present the to-date largest microarray gene expression study on IBD encompassing both inflamed and un-inflamed colonic tissue. A meta-analysis including all available, comparable data was used to explore important aspects of IBD inflammation, thereby validating consistent gene expression patterns.
Colon pinch biopsies from IBD patients were analysed using Illumina whole genome gene expression technology. Differential expression (DE) was identified using LIMMA linear model in the R statistical computing environment. Results were enriched for gene ontology (GO) categories. Sets of genes encoding antimicrobial proteins (AMP) and proteins involved in T helper (Th) cell differentiation were used in the interpretation of the results. All available data sets were analysed using the same methods, and results were compared on a global and focused level as t-scores.
Gene expression in inflamed mucosa from UC and CD are remarkably similar. The meta-analysis confirmed this. The patterns of AMP and Th cell-related gene expression were also very similar, except for IL23A which was consistently higher expressed in UC than in CD. Un-inflamed tissue from patients demonstrated minimal differences from healthy controls.
There is no difference in the Th subgroup involvement between UC and CD. Th1/Th17 related expression, with little Th2 differentiation, dominated both diseases. The different IL23A expression between UC and CD suggests an IBD subtype specific role. AMPs, previously little studied, are strongly overexpressed in IBD. The presented meta-analysis provides a sound background for further research on IBD pathobiology.
Perhexiline is a potent anti-anginal drug used for treatment of refractory angina and other forms of heart disease. It provides an oxygen sparing effect in the myocardium by creating a switch from fatty acid to glucose metabolism through partial inhibition of carnitine palmitoyltransferase 1 and 2. However, the precise molecular mechanisms underlying the cardioprotective effects elicited by perhexiline are not fully understood. The present study employed a combined proteomics, metabolomics and computational approach to characterise changes in murine hearts upon treatment with perhexiline. According to results based on difference in-gel electrophoresis, the most profound change in the cardiac proteome related to the activation of the pyruvate dehydrogenase complex. Metabolomic analysis by high-resolution nuclear magnetic resonance spectroscopy showed lower levels of total creatine and taurine in hearts of perhexiline-treated mice. Creatine and taurine levels were also significantly correlated in a cross-correlation analysis of all metabolites. Computational modelling suggested that far from inducing a simple shift from fatty acid to glucose oxidation, perhexiline may cause complex rebalancing of carbon and nucleotide phosphate fluxes, fuelled by increased lactate and amino acid uptake, to increase metabolic flexibility and to maintain cardiac output. This article is part of a Special Issue entitled "Focus on Cardiac Metabolism".
► Mice were fed perhexiline to achieve steady state concentrations. ► Hearts were analysed using a combined proteomic and metabolomic approach. ► Computer modelling was used to cross-validate the findings. ► Perhexiline has more wide-ranging and complex metabolic effects than previously thought.
CPT, carnitine palmitoyltransferase; DIGE, difference in-gel electrophoresis; FCS, foetal calf serum; FDR, false discovery rate; GO, Gene ontology; 1H NMR, proton nuclear magnetic resonance spectroscopy; LC-MS/MS, liquid chromatography tandem mass spectrometry; TCA, tricarboxylic acid; Metabolomics; Proteomics; Cardioprotection; Metabolism; Heart failure
Rectal instillation of trinitrobenzene sulphonic acid (TNBS) in ethanol is an established model for inflammatory bowel disease (IBD). We aimed to 1) set up a TNBS-colitis protocol resulting in an endoscopic and histologic picture resembling IBD, 2) study the correlation between endoscopic, histologic and gene expression alterations at different time points after colitis induction, and 3) compare rat and human IBD mucosal transcriptomic data to evaluate whether TNBS-colitis is an appropriate model of IBD.
Five female Sprague Daley rats received TNBS diluted in 50% ethanol (18 mg/0.6 ml) rectally. The rats underwent colonoscopy with biopsy at different time points. RNA was extracted from rat biopsies and microarray was performed. PCR and in situ hybridization (ISH) were done for validation of microarray results. Rat microarray profiles were compared to human IBD expression profiles (25 ulcerative colitis Endoscopic score demonstrated mild to moderate colitis after three and seven days, but declined after twelve days. Histologic changes corresponded with the endoscopic appearance. Over-represented Gene Ontology Biological Processes included: Cell Adhesion, Immune Response, Lipid Metabolic Process, and Tissue Regeneration. IL-1α, IL-1β, TLR2, TLR4, PRNP were all significantly up-regulated, while PPARγ was significantly down-regulated. Among genes with highest fold change (FC) were SPINK4, LBP, ADA, RETNLB and IL-1α. The highest concordance in differential expression between TNBS and IBD transcriptomes was three days after colitis induction. ISH and PCR results corresponded with the microarray data. The most concordantly expressed biologically relevant pathways included TNF signaling, Cell junction organization, and Interleukin-1 processing.
Endoscopy with biopsies in TNBS-colitis is useful to follow temporal changes of inflammation visually and histologically, and to acquire tissue for gene expression analyses. TNBS-colitis is an appropriate model to study specific biological processes in IBD.
The conventional reductionist approach to cardiovascular research investigates individual candidate factors or linear signalling pathways but ignores more complex interactions in biological systems. The advent of molecular profiling technologies that focus on a global characterization of whole complements allows an exploration of the interconnectivity of pathways during pathophysiologically relevant processes, but has brought about the issue of statistical analysis and data integration. Proteins identified by differential expression as well as those in protein–protein interaction networks identified through experiments and through computational modelling techniques can be used as an initial starting point for functional analyses. In combination with other ‘-omics’ technologies, such as transcriptomics and metabolomics, proteomics explores different aspects of disease, and the different pillars of observations facilitate the data integration in disease-specific networks. Ultimately, a systems biology approach may advance our understanding of cardiovascular disease processes at a ‘biological pathway’ instead of a ‘single molecule’ level and accelerate progress towards disease-modifying interventions.
Proteins; Metabolites; Mass spectrometry; Systems biology; Bioinformatics
Hepatocellular carcinoma (HCC) is a leading cause of global cancer mortality. However, little is known about the precise molecular mechanisms involved in tumor formation and pathogenesis. The primary goal of this study was to elucidate genome-wide molecular networks involved in development of HCC with multiple etiologies by exploring high quality microarray data. We undertook a comparative network analysis across 264 human microarray profiles monitoring transcript changes in healthy liver, liver cirrhosis, and HCC with viral and alcoholic etiologies. Gene co-expression profiling was used to derive a consensus gene relevance network of HCC progression that consisted of 798 genes and 2,012 links. The HCC interactome was further confirmed to be phenotype-specific and non-random. Additionally, we confirmed that co-expressed genes are more likely to share biological function, but not sub-cellular localization. Analysis of individual HCC genes revealed that they are topologically central in a human protein-protein interaction network. We used quantitative RT-PCR in a cohort of normal liver tissue (n = 8), hepatitis C virus (HCV)-induced chronic liver disease (n = 9), and HCC (n = 7) to validate co-expressions of several well-connected genes, namely ASPM, CDKN3, NEK2, RACGAP1, and TOP2A. We show that HCC is a heterogeneous disorder, underpinned by complex cross talk between immune response, cell cycle, and mRNA translation pathways. Our work provides a systems-wide resource for deeper understanding of molecular mechanisms in HCC progression and may be used further to define novel targets for efficient treatment or diagnosis of this disease.
Cellular constituents such as proteins, DNA, and RNA form a complex web of interactions that regulate biochemical homeostasis and determine the dynamic cellular response to external stimuli. It follows that detailed understanding of these patterns is critical for the assessment of fundamental processes in cell biology and pathology. Representation and analysis of cellular constituents through network principles is a promising and popular analytical avenue towards a deeper understanding of molecular mechanisms in a system-wide context.
We present Functional Genomics Assistant (FUGA) - an extensible and portable MATLAB toolbox for the inference of biological relationships, graph topology analysis, random network simulation, network clustering, and functional enrichment statistics. In contrast to conventional differential expression analysis of individual genes, FUGA offers a framework for the study of system-wide properties of biological networks and highlights putative molecular targets using concepts of systems biology.
FUGA offers a simple and customizable framework for network analysis in a variety of systems biology applications. It is freely available for individual or academic use at http://code.google.com/p/fuga.
The recent discovery that microRNAs (miRNAs) are present in the circulation sparked interest in their use as potential biomarkers. In this review, we will summarize the latest findings on circulating miRNAs and cardiovascular disease but also discuss analytical challenges. While research on circulating miRNAs is still in its infancy, high analytical standards in statistics and study design are a prerequisite to obtain robust data and avoid repeating the mistakes of the early genetic association studies. Otherwise, studies tend to get published because of their novelty despite low numbers, poorly matched cases and controls and no multivariate adjustment for conventional risk factors. Research on circulating miRNAs can only progress by bringing more statistical rigour to bear in this field and by evaluating changes of individual miRNAs in the context of the overall miRNA network. Such miRNA signatures may have better diagnostic and prognostic value.
MicroRNA; Cardiovascular disease; Diabetes; Atherosclerosis; Systems biology
The requirement for large amounts of good quality DNA for whole-genome applications prohibits their use for small, laser capture micro-dissected (LCM), and/or rare clinical samples, which are also often formalin-fixed and paraffin-embedded (FFPE). Whole-genome amplification of DNA from these samples could, potentially, overcome these limitations. However, little is known about the artefacts introduced by amplification of FFPE-derived DNA with regard to genotyping, and subsequent copy number and loss of heterozygosity (LOH) analyses. Using a ligation adaptor amplification method, we present data from a total of 22 Affymetrix SNP 6.0 experiments, using matched paired amplified and non-amplified DNA from 10 LCM FFPE normal and dysplastic oral epithelial tissues, and an internal method control. An average of 76.5% of SNPs were called in both matched amplified and non-amplified DNA samples, and concordance was a promising 82.4%. Paired analysis for copy number, LOH, and both combined, showed that copy number changes were reduced in amplified DNA, but were 99.5% concordant when detected, amplifications were the changes most likely to be ‘missed’, only 30% of non-amplified LOH changes were identified in amplified pairs, and when copy number and LOH are combined ∼50% of gene changes detected in the unamplified DNA were also detected in the amplified DNA and within these changes, 86.5% were concordant for both copy number and LOH status. However, there are also changes introduced as ∼20% of changes in the amplified DNA are not detected in the non-amplified DNA. An integrative network biology approach revealed that changes in amplified DNA of dysplastic oral epithelium localize to topologically critical regions of the human protein-protein interaction network, suggesting their functional implication in the pathobiology of this disease. Taken together, our results support the use of amplification of FFPE-derived DNA, provided sufficient samples are used to increase power and compensate for increased error rates.
Ciliary dysfunction leads to a number of human pathologies, including primary ciliary dyskinesia, nephronophthisis, situs inversus pathology or infertility. The mechanism of cilia beating regulation is complex and despite extensive experimental characterization remains poorly understood. We develop a detailed systems model for calcium, membrane potential and cyclic nucleotide-dependent ciliary motility regulation.
The model describes the intimate relationship between calcium and potassium ionic concentrations inside and outside of cilia with membrane voltage and, for the first time, describes a novel type of ciliary excitability which plays the major role in ciliary movement regulation. Our model describes a mechanism that allows ciliary excitation to be robust over a wide physiological range of extracellular ionic concentrations. The model predicts the existence of several dynamic modes of ciliary regulation, such as the generation of intraciliary Ca2+ spike with amplitude proportional to the degree of membrane depolarization, the ability to maintain stable oscillations, monostable multivibrator regimes, all of which are initiated by variability in ionic concentrations that translate into altered membrane voltage.
Computational investigation of the model offers several new insights into the underlying molecular mechanisms of ciliary pathologies. According to our analysis, the reported dynamic regulatory modes can be a physiological reaction to alterations in the extracellular environment. However, modification of the dynamic modes, as a result of genetic mutations or environmental conditions, can cause a life threatening pathology.
Small intestinal (SI) neuroendocrine tumors (NET) are increasing in incidence, however little is known about their biology. High throughput techniques such as inference of gene regulatory networks from microarray experiments can objectively define signaling machinery in this disease. Genome-wide co-expression analysis was used to infer gene relevance network in SI-NETs. The network was confirmed to be non-random, scale-free, and highly modular. Functional analysis of gene co-expression modules revealed processes including ‘Nervous system development’, ‘Immune response’, and ‘Cell-cycle’. Importantly, gene network topology and differential expression analysis identified over-expression of the GPCR signaling regulators, the cAMP synthetase, ADCY2, and the protein kinase A, PRKAR1A. Seven CREB response element (CRE) transcripts associated with proliferation and secretion: BEX1, BICD1, CHGB, CPE, GABRB3, SCG2 and SCG3 as well as ADCY2 and PRKAR1A were measured in an independent SI dataset (n = 10 NETs; n = 8 normal preparations). All were up-regulated (p<0.035) with the exception of SCG3 which was not differently expressed. Forskolin (a direct cAMP activator, 10−5 M) significantly stimulated transcription of pCREB and 3/7 CREB targets, isoproterenol (a selective ß-adrenergic receptor agonist and cAMP activator, 10−5 M) stimulated pCREB and 4/7 targets while BIM-53061 (a dopamine D2 and Serotonin [5-HT2] receptor agonist, 10−6 M) stimulated 100% of targets as well as pCREB; CRE transcription correlated with the levels of cAMP accumulation and PKA activity; BIM-53061 stimulated the highest levels of cAMP and PKA (2.8-fold and 2.5-fold vs. 1.8–2-fold for isoproterenol and forskolin). Gene network inference and graph topology analysis in SI NETs suggests that SI NETs express neural GPCRs that activate different CRE targets associated with proliferation and secretion. In vitro studies, in a model NET cell system, confirmed that transcriptional effects are signaled through the cAMP/PKA/pCREB signaling pathway and that a SI NET cell line was most sensitive to a D2 and 5-HT2 receptor agonist BIM-53061.
A transgenic mouse model for conditional induction of long-term hibernation via myocardium-specific expression of a VEGF-sequestering soluble receptor allowed the dissection of the hibernation process into an initiation and a maintenance phase. The hypoxic initiation phase was characterized by peak levels of K(ATP) channel and glucose transporter 1 (GLUT1) expression. Glibenclamide, an inhibitor of K(ATP) channels, blocked GLUT1 induction. In the maintenance phase, tissue hypoxia and GLUT1 expression were reduced. Thus, we employed a combined “-omics” approach to resolve this cardioprotective adaptation process. Unguided bioinformatics analysis on the transcriptomic, proteomic and metabolomic datasets confirmed that anaerobic glycolysis was affected and that the observed enzymatic changes in cardiac metabolism were directly linked to hypoxia-inducible factor (HIF)-1 activation. Although metabolite concentrations were kept relatively constant, the combination of the proteomic and transcriptomic dataset improved the statistical confidence of the pathway analysis by 2 orders of magnitude. Importantly, proteomics revealed a reduced phosphorylation state of myosin light chain 2 and cardiac troponin I within the contractile apparatus of hibernating hearts in the absence of changes in protein abundance. Our study demonstrates how combining different “-omics” datasets aids in the identification of key biological pathways: chronic hypoxia resulted in a pronounced adaptive response at the transcript and the protein level to keep metabolite levels steady. This preservation of metabolic homeostasis is likely to contribute to the long-term survival of the hibernating myocardium.
► The hibernation process was dissected into an initiation and a maintenance phase. ► Glibenclamide, an inhibitor of K(ATP) channels, blocked GLUT1 induction. ► The maintenance phase was characterized by attenuated tissue hypoxia. ► Phosphorylation of myosin light chain 2 and cardiac troponin I was reduced. ► Combining of proteomics and transcriptomics improved the bioinformatic pathway analysis.
DIGE, difference in-gel electrophoresis; 2-DE, two-dimensional gel electrophoresis; 1H-NMR, proton nuclear magnetic resonance spectroscopy; LC-MS/MS, liquid chromatography tandem mass spectrometry; Hibernation; Hypoxia; Metabolomics; Myocardium; Proteomics
Survival rates for gastrointestinal (GI) and bronchopulmonary (BP) neuroendocrine tumors (NETs) have not significantly altered (5yr survival: 64.1% and 87–89%) in thirty years (1973–2004). No effective or specific anti-neoplastic agent(s) is available although somatostatin analogs inhibit NET serotonin (5-HT) secretion. Given the expression of 5-HT receptors on NETs, we hypothesized that 5-HT autoregulated NET proliferation.
Proliferation was evaluated in three NET cell lines using MTT uptake while real-time PCR and ELISA studies were performed to delineate 5-HT-mediated signaling pathways. To determine the receptor and role of endogenous 5-HT production, the effects of ketanserin (5-HT2A/C receptor antagonist), ondansetron (5-HT3 antagonist) and the suicide inhibitor 7-Hydroxytryptophan (7-HTP) were investigated.
Exogenously added 5-HT stimulated proliferation in the atypical BP-NET, NCI-H720 (+50%, EC50=10nM), the typical BP-NET, NCI-H727 (+40%, EC50=0.01nM), and the GI-NET, KRJ-I (+60%, EC50=25nM). In NCI-H720, proliferation was inhibited by ketanserin (IC50=0.06nM) and ondansetron (IC50=0.4nM) as well as 7-HTP (IC50=0.3nM). In NCI-H727, ketanserin and 7-HTP inhibited proliferation (IC50=0.3nM and 2.3nM respectively) while ondansetron had no effect. In KRJ-I, ketanserin (IC50=0.1nM) and 7-HTP (IC50=0.6nM) but not ondansetron inhibited proliferation. In all cell lines, 5-HT activated proliferation through ERK1/2 phosphorylation and JNK-mediated pathways (c-JUN and Ki67 transcription). An auto-regulatory effect was indicated by 7-HTP-mediated inhibition of extracellular 5-HT and downstream effects on NET proliferation.
Lung and GI-NET proliferation is autoregulated by 5-HT through alterations in ERK and JNK signaling. Targeting NET cells with 5-HT2 receptor antagonists and 7-HTP reversed proliferation. 5-HT2 receptor subtype-specific antagonists may represent a viable antiproliferative therapeutic strategy.
bronchopulmonary; carcinoid; gastrointestinal; serotonin; ERK; H720; H727; KRJ-I; neuroendocrine tumor; proliferation
Genome-wide expression patterns in physiological cardiac hypertrophy. Co-expression patterns in physiological cardiac hypertrophy
In this study, the first large-scale analysis of publicly available genome-wide expression data of several in vivo murine models of physiological LVH was carried out using network analysis. On evaluating 3 million gene co-expression patterns across 141 relevant microarray experiments, it was found that physiological adaptation is an evolutionarily conserved processes involving preservation of the function of cytochrome c oxidase, induction of autophagy compatible with cell survival, and coordinated regulation of angiogenesis.
This analysis not only identifies known biological pathways involved in physiological LVH, but also offers novel insights into the molecular basis of this phenotype by identifying key networks of co-expressed genes, as well as their topological and functional properties, using relevant high-quality microarray experiments and network inference.
The mechanisms of stress tolerance in sessile animals, such as molluscs, can offer fundamental insights into the adaptation of organisms for a wide range of environmental challenges. One of the best studied processes at the molecular level relevant to stress tolerance is the heat shock response in the genus Mytilus. We focus on the upstream region of Mytilus galloprovincialis Hsp90 genes and their structural and functional associations, using comparative genomics and network inference. Sequence comparison of this region provides novel evidence that the transcription of Hsp90 is regulated via a dense region of transcription factor binding sites, also containing a region with similarity to the Gamera family of LINE-like repetitive sequences and a genus-specific element of unknown function. Furthermore, we infer a set of gene networks from tissue-specific expression data, and specifically extract an Hsp class-associated network, with 174 genes and 2,226 associations, exhibiting a complex pattern of expression across multiple tissue types. Our results (i) suggest that the heat shock response in the genus Mytilus is regulated by an unexpectedly complex upstream region, and (ii) provide new directions for the use of the heat shock process as a biosensor system for environmental monitoring.
Adaptation of sessile animals, such as molluscs, to stress is achieved by a number of molecular mechanisms, few of which are clearly understood. Insights from this research can provide clues about stress tolerance both for sessile and mobile organisms. The Mediterranean mussel, of the genus Mytilus, is a model organism for the study of stress at the molecular level, with sufficient gene structure and function data available. We have thus investigated a key stress response gene, Hsp90, and in particular its upstream region, using a combination of sequence and expression analysis approaches. We demonstrate that this region, responsible for the regulation of heat shock-associated gene expression, exhibits an unparalleled structural and functional complexity compared to other model organisms, as well as subtle gene expression patterns across multiple tissues. These results form the basis upon which the heat shock response can be used as a molecular biosensor for environmental monitoring in the future.
A more accurate taxonomy of small intestinal (SI) neuroendocrine tumors (NETs) is necessary to accurately predict tumor behavior, prognosis and define therapeutic strategy. We identified a panel of such markers implicated in tumorogenicity, metastasis, and hormone production and hypothesized that transcript levels of MAGE-D2, MTA1, NAP1L1, Ki-67, Survivin, FZD7, Kiss1, NRP2, and CgA could be used to define primary SI NETs and predict the development of metastases.
Seventy three clinically and World Health Organization (WHO) pathologically classified NET samples (primary: n=44; liver metastases: n=29) and 30 normal human Enterochromaffin (EC) cell preparations were analyzed using real-time PCR. Transcript levels were normalized to three NET house-keeping genes, ALG9, TFCP2 and ZNF410, using GeNorm. A predictive gene-based model was constructed using supervised learning algorithms from the transcript expression levels.
Primary SI NETs could be differentiated from normal human EC cell preparations with 100% specificity and 92% sensitivity. Well-differentiated NETs (WDNETs), well-differentiated neuroendocrine carcinomas (WDNECs), and poorly differentiated NETs (PDNETs) were classified with specificities of 78%, 78%, and 71% respectively, while poorly differentiated neuroendocrine carcinomas (PDNECs) were misclassified as either WDNETs or PDNETs. Metastases were predicted in all cases with 100% sensitivity and specificity.
Gene expression profiling and supervised machine learning can be used to classify SI NET subtypes and accurately predict metastasis. Application of this technique will facilitate accurate molecular pathological delineation of NET disease, better define its extent and facilitate the assessment of prognosis as well as providing a guide to identification of an appropriate strategy for individualized patient treatment.
algorithm; gene; neuroendocrine; predict; real-time PCR
Iron regulatory proteins, IRP1 and IRP2, bind to mRNAs harboring iron responsive elements and control their expression. IRPs may also perform additional functions. Thus, IRP1 exhibited apparent tumor suppressor properties in a tumor xenograft model. Here we examined the effects of IRP2 in a similar setting. Human H1299 lung cancer cells or clones engineered for tetracycline-inducible expression of wild type IRP2, or the deletion mutant IRP2Δ73 (lacking a specific insert of 73 amino acids), were injected subcutaneously into nude mice. The induction of IRP2 profoundly stimulated the growth of tumor xenografts, and this response was blunted by addition of tetracycline in the drinking water of the animals, to turnoff the IRP2 transgene. Interestingly, IRP2Δ73 failed to promote tumor growth above control levels. As expected, xenografts expressing the IRP2 transgene exhibited high levels of transferrin receptor 1 (TfR1); however, the expression of other known IRP targets was not affected. Moreover, these xenografts manifested increased c-MYC levels and ERK1/2 phosphorylation. A microarray analysis identified distinct gene expression patterns between control and tumors containing IRP2 or IRP1 transgenes. By contrast, gene expression profiles of control and IRP2Δ73-related tumors were more similar, consistently with their growth phenotype. Collectively, these data demonstrate an apparent pro-oncogenic activity of IRP2 that depends on its specific 73 amino acids insert, and provide further evidence for a link between IRPs and cancer biology.