Paolo Fardin

Transcriptome of Hypoxic Immature Dendritic Cells: Modulation of Chemokine/Receptor Expression

Hypoxia is a condition of low oxygen tension occurring in inflammatory tissues. Dendritic cells (DC) are professional antigen-presenting cells whose differentiation, migration, and activities are intrinsically linked to the microenvironment. DCs will home and migrate through pathologic tissues before reaching their final destination in the lymph node. We studied the differentiation of human monocytes into immature DCs (iDCs) in a hypoxic microenvironment. We generated iDC in vitro under normoxic (iDCs) or hypoxic (Hi-DCs) conditions and examined the hypoxia-responsive element in the promoter, gene expression, and biochemical KEGG pathways. Hi-DCs had an interesting phenotype represented by up-regulation of genes associated with cell movement/migration. In addition, the Hi-DC cytokine/receptor pathway showed a dichotomy between down-regulated chemokines and up-regulated chemokine receptor mRNA expression. We showed that CCR3, CX3CR1, and CCR2 are hypoxia-inducible genes and that CCL18, CCL23, CCL26, CCL24, and CCL14 are inhibited by hypoxia. A strong chemotactic response to CCR2 and CXCR4 agonists distinguished Hi-DCs from iDCs at a functional level. The hypoxic microenvironment promotes the differentiation of Hi-DCs, which differs from iDCs for gene expression profile and function. The most prominent characteristic of Hi-DCs is the expression of a mobility/migratory rather than inflammatory phenotype. We speculate that Hi-DCs have the tendency to leave the hypoxic tissue and follow the chemokine gradient toward normoxic areas where they can mature and contribute to the inflammatory process. (Mol Cancer Res 2008;6(2):175–85)

The l1-l2 regularization framework unmasks the hypoxia signature hidden in the transcriptome of a set of heterogeneous neuroblastoma cell lines

BackgroundGene expression signatures are clusters of genes discriminating different statuses of the cells and their definition is critical for understanding the molecular bases of diseases. The identification of a gene signature is complicated by the high dimensional nature of the data and by the genetic heterogeneity of the responding cells. The l1-l2 regularization is an embedded feature selection technique that fulfills all the desirable properties of a variable selection algorithm and has the potential to generate a specific signature even in biologically complex settings. We studied the application of this algorithm to detect the signature characterizing the transcriptional response of neuroblastoma tumor cell lines to hypoxia, a condition of low oxygen tension that occurs in the tumor microenvironment.ResultsWe determined the gene expression profile of 9 neuroblastoma cell lines cultured under normoxic and hypoxic conditions. We studied a heterogeneous set of neuroblastoma cell lines to mimic the in vivo situation and to test the robustness and validity of the l1-l2 regularization with double optimization. Analysis by hierarchical, spectral, and k-means clustering or supervised approach based on t-test analysis divided the cell lines on the bases of genetic differences. However, the disturbance of this strong transcriptional response completely masked the detection of the more subtle response to hypoxia. Different results were obtained when we applied the l1-l2 regularization framework. The algorithm distinguished the normoxic and hypoxic statuses defining signatures comprising 3 to 38 probesets, with a leave-one-out error of 17%. A consensus hypoxia signature was established setting the frequency score at 50% and the correlation parameter ε equal to 100. This signature is composed by 11 probesets representing 8 well characterized genes known to be modulated by hypoxia.ConclusionWe demonstrate that l1-l2 regularization outperforms more conventional approaches allowing the identification and definition of a gene expression signature under complex experimental conditions. The l1-l2 regularization and the cross validation generates an unbiased and objective output with a low classification error. We feel that the application of this algorithm to tumor biology will be instrumental to analyze gene expression signatures hidden in the transcriptome that, like hypoxia, may be major determinant of the course of the disease.

Early response of gene clusters is associated with mouse lung resistance or sensitivity to cigarette smoke.

We have investigated the effects of cigarette smoke exposure in three different strains of mice. DBA/2 and C57BL/6J are susceptible to smoke and develop different lung changes in response to chronic exposure, whereas ICR mice are resistant to smoke and do not develop emphysema. The present study was carried out to determine early changes in the gene expression profile of mice exposed to cigarette smoke with either a susceptible or resistant phenotype. The three strains of mice were exposed to smoke from three cigarettes per day, 5 days/wk, for 4 wk. Microarray analysis was carried out on total RNA extracted from the lung using the Affymetrix platform. Cigarette smoke modulates several clusters of genes (i.e., proemphysematous, acute phase response, and cell adhesion) in smoke-sensitive DBA/2 or C57BL/6J strains, but the same genes are not altered by smoke in ICR resistant mice. Only a few genes were commonly modulated by smoke in the three strains of mice. This pattern of gene expression suggests that the response to smoke is strain-dependent and may involve different molecular signaling pathways. Real-time quantitative PCR was used to verify the pattern of modulation of selected genes and their potential biological relevance. We conclude that gene expression response to smoke is highly dependent on the mouse genetic background. We speculate that the definition of gene clusters associated, to various degrees, with mouse susceptibility or resistance to smoke may be instrumental in defining the molecular basis of the individual response to smoke-induced lung injury in humans.

Identification of Multiple Hypoxia Signatures in Neuroblastoma Cell Lines by l1-l2 Regularization and Data Reduction

Hypoxia is a condition of low oxygen tension occurring in the tumor and negatively correlated with the progression of the disease. We studied the gene expression profiles of nine neuroblastoma cell lines grown under hypoxic conditions to define gene signatures that characterize hypoxic neuroblastoma. The l1-l2 regularization applied to the entire transcriptome identified a single signature of 11 probesets discriminating the hypoxic state. We demonstrate that new hypoxia signatures, with similar discriminatory power, can be generated by a prior knowledge-based filtering in which a much smaller number of probesets, characterizing hypoxia-related biochemical pathways, are analyzed. l1-l2 regularization identified novel and robust hypoxia signatures within apoptosis, glycolysis, and oxidative phosphorylation Gene Ontology classes. We conclude that the filtering approach overcomes the noisy nature of the microarray data and allows generating robust signatures suitable for biomarker discovery and patients risk assessment in a fraction of computer time.

Induction of Epithelial Mesenchimal Transition and Vasculogenesis in the Lenses of Dbl Oncogene Transgenic Mice

Background The Dbl family of proteins represents a large group of proto-oncogenes involved in cell growth regulation. The numerous domains that are present in many Dbl family proteins suggest that they act to integrate multiple inputs in complicated signaling networks involving the Rho GTPases. Alterations of the normal function of these proteins lead to pathological processes such as developmental disorders and neoplastic transformation. We generated transgenic mice introducing the cDNA of Dbl oncogene linked to the metallothionein promoter into the germ line of FVB mice and found that onco-Dbl expression in mouse lenses affected proliferation, migration and differentiation of lens epithelial cells. Results We used high density oligonucleotide microarray to define the transcriptional profile induced by Dbl in the lenses of 2 days, 2 weeks, and 6 weeks old transgenic mice. We observed modulation of genes encoding proteins promoting epithelial-mesenchymal transition (EMT), such as down-regulation of epithelial cell markers and up-regulation of fibroblast markers. Genes encoding proteins involved in the positive regulation of apoptosis were markedly down regulated while anti-apoptotic genes were strongly up-regulated. Finally, several genes encoding proteins involved in the process of angiogenesis were up-regulated. These observations were validated by histological and immunohistochemical examination of the transgenic lenses where vascularization can be readily observed. Conclusion Onco-Dbl expression in mouse lens correlated with modulation of genes involved in the regulation of EMT, apoptosis and vasculogenesis leading to disruption of the lens architecture, epithelial cell proliferation, and aberrant angiogenesis. We conclude that onco-Dbl has a potentially important, previously unreported, capacity to dramatically alter epithelial cell migration, replication, polarization and differentiation and to induce vascularization of an epithelial tissue.

Growth arrest-inducing genes are activated in Dbl-transformed mouse fibroblasts

The Dbl oncogene is a guanine nucleotide exchange factor for Rho GTPases and its activity has been linked to the regulation of gene transcription. Dbl oncogene expression in NIH3T3 cells leads to changes in morphological and proliferative properties of these cells, inducing a highly transformed phenotype. To gain insights into Dbl oncogene-induced transformation we compared gene expression profiles between Dbl oncogene-transformed and parental NIH3T3 cells by cDNA microarray. We found that Dbl oncogene expression is associated with gene expression modulation involving upregulation of 51 genes and downregulation of 49 genes. Five of the overexpressed genes identified are known to exert antiproliferative functions. Our observations suggest that the expression of Dbl oncogene in NIH3T3 may lead to the induction of genes associated with cell cycle arrest, possibly through the activation of stress-induced kinases.

Abstract 2002: Cell reprogramming by hypoxia

Background Low oxygen tension (hypoxia) is an important determinant in tumor progression. In this study we assess the prognostic value of an in vitro derived hypoxia gene signature in neuroblastoma patients. Material and Methods l1-l2 regularization framework has been applied on gene expression profiles of 11 neuroblastoma cell lines to define the neuroblastoma hypoxia signature. We applied k-means clustering on the expression level of the signature 62 probesets to segregate 88 neuroblastoma patients and subgroups obtained by common risk factors stratification. We analyzed the classes by Kaplan-Meier curves and log-rank test for overall survival (OS) and event-free survival (EFS). Multivariate Cox analysis was performed to define the predictive power of the signature. Results The neuroblastoma hypoxia signature distinguished two groups of neuroblastoma patients classifying them as poor prognosis (21 patients), those having OS rate of 25.5% and EFS rate of 27.7%, and as good prognosis (67 patients), those having OS rate of 73.2% and EFS rate of 67.7%. The poor prognosis patients show an over-expression of the hypoxia probesets. Multivariate Cox analysis revealed that the neuroblastoma hypoxia signature is a significant independent predictor after controlling for commonly used risk factors. When applied to MYCN not amplified patients, the hypoxia signature was capable to stratify patients with OS rate of 24.2% and EFS rate of 27.3% for the patients with poor prognosis, compared with OS rate of 81.4% and EFS rate of 74.8% for the patients with good prognosis. Conclusions We demonstrate that the NB-hypo signature is a significant prognostic factor capable of stratify neuroblastoma patients. Furthermore, we obtained the proof of principle that the approach of hypoxia genes selection from in vitro controlled tumor cell lines, is a feasible method to identify specific contribution of the microenvironment to the tumors’ biology. Note: This abstract was not presented at the AACR 101st Annual Meeting 2010 because the presenter was unable to attend. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 2002.