Quadro geral dos direitos da personalidade

Este artigo pretende oferecer uma visão global dos direitos da personalidade, desde a possibilidade de sua aplicação às pessoas jurídicas, passando pela superposição do estudo de seu objeto por outros ramos do Direito, assim como por dados históricos, classificação, análise jurisprudencial, doutrinária e legislativa dos pontos centrais que envolvem tais direitos.

Multiple testing in spatial epidemiology: a Bayesian approach

In this work we aim to propose a new approach for preliminary epidemiological studies on Standardized Mortality Ratios (SMR) collected in many spatial regions. A preliminary study on SMRs aims to formulate hypotheses to be investigated via individual epidemiological studies that avoid bias carried on by aggregated analyses. Starting from collecting disease counts and calculating expected disease counts by means of reference population disease rates, in each area an SMR is derived as the MLE under the Poisson assumption on each observation. Such estimators have high standard errors in small areas, i.e. where the expected count is low either because of the low population underlying the area or the rarity of the disease under study. Disease mapping models and other techniques for screening disease rates among the map aiming to detect anomalies and possible high-risk areas have been proposed in literature according to the classic and the Bayesian paradigm. Our proposal is approaching this issue by a decision-oriented method, which focus on multiple testing control, without however leaving the preliminary study perspective that an analysis on SMR indicators is asked to. We implement the control of the FDR, a quantity largely used to address multiple comparisons problems in the eld of microarray data analysis but which is not usually employed in disease mapping. Controlling the FDR means providing an estimate of the FDR for a set of rejected null hypotheses. The small areas issue arises diculties in applying traditional methods for FDR estimation, that are usually based only on the p-values knowledge (Benjamini and Hochberg, 1995; Storey, 2003). Tests evaluated by a traditional p-value provide weak power in small areas, where the expected number of disease cases is small. Moreover tests cannot be assumed as independent when spatial correlation between SMRs is expected, neither they are identical distributed when population underlying the map is heterogeneous. The Bayesian paradigm oers a way to overcome the inappropriateness of p-values based methods. Another peculiarity of the present work is to propose a hierarchical full Bayesian model for FDR estimation in testing many null hypothesis of absence of risk.We will use concepts of Bayesian models for disease mapping, referring in particular to the Besag York and Mollié model (1991) often used in practice for its exible prior assumption on the risks distribution across regions. The borrowing of strength between prior and likelihood typical of a hierarchical Bayesian model takes the advantage of evaluating a singular test (i.e. a test in a singular area) by means of all observations in the map under study, rather than just by means of the singular observation. This allows to improve the power test in small areas and addressing more appropriately the spatial correlation issue that suggests that relative risks are closer in spatially contiguous regions. The proposed model aims to estimate the FDR by means of the MCMC estimated posterior probabilities b i's of the null hypothesis (absence of risk) for each area. An estimate of the expected FDR conditional on data (\FDR) can be calculated in any set of b i's relative to areas declared at high-risk (where thenull hypothesis is rejected) by averaging the b i's themselves. The\FDR can be used to provide an easy decision rule for selecting high-risk areas, i.e. selecting as many as possible areas such that the\FDR is non-lower than a prexed value; we call them\FDR based decision (or selection) rules. The sensitivity and specicity of such rule depend on the accuracy of the FDR estimate, the over-estimation of FDR causing a loss of power and the under-estimation of FDR producing a loss of specicity. Moreover, our model has the interesting feature of still being able to provide an estimate of relative risk values as in the Besag York and Mollié model (1991). A simulation study to evaluate the model performance in FDR estimation accuracy, sensitivity and specificity of the decision rule, and goodness of estimation of relative risks, was set up. We chose a real map from which we generated several spatial scenarios whose counts of disease vary according to the spatial correlation degree, the size areas, the number of areas where the null hypothesis is true and the risk level in the latter areas. In summarizing simulation results we will always consider the FDR estimation in sets constituted by all b i's selected lower than a threshold t. We will show graphs of the\FDR and the true FDR (known by simulation) plotted against a threshold t to assess the FDR estimation. Varying the threshold we can learn which FDR values can be accurately estimated by the practitioner willing to apply the model (by the closeness between\FDR and true FDR). By plotting the calculated sensitivity and specicity (both known by simulation) vs the\FDR we can check the sensitivity and specicity of the corresponding\FDR based decision rules. For investigating the over-smoothing level of relative risk estimates we will compare box-plots of such estimates in high-risk areas (known by simulation), obtained by both our model and the classic Besag York Mollié model. All the summary tools are worked out for all simulated scenarios (in total 54 scenarios). Results show that FDR is well estimated (in the worst case we get an overestimation, hence a conservative FDR control) in small areas, low risk levels and spatially correlated risks scenarios, that are our primary aims. In such scenarios we have good estimates of the FDR for all values less or equal than 0.10. The sensitivity of\FDR based decision rules is generally low but specicity is high. In such scenario the use of\FDR = 0:05 or\FDR = 0:10 based selection rule can be suggested. In cases where the number of true alternative hypotheses (number of true high-risk areas) is small, also FDR = 0:15 values are well estimated, and \FDR = 0:15 based decision rules gains power maintaining an high specicity. On the other hand, in non-small areas and non-small risk level scenarios the FDR is under-estimated unless for very small values of it (much lower than 0.05); this resulting in a loss of specicity of a\FDR = 0:05 based decision rule. In such scenario\FDR = 0:05 or, even worse,\FDR = 0:1 based decision rules cannot be suggested because the true FDR is actually much higher. As regards the relative risk estimation, our model achieves almost the same results of the classic Besag York Molliè model. For this reason, our model is interesting for its ability to perform both the estimation of relative risk values and the FDR control, except for non-small areas and large risk level scenarios. A case of study is nally presented to show how the method can be used in epidemiology.

Ruolo di interleuchina-33 sull'espressione di geni profibrotici e sull'ipertrofia dei miofibroblasti nella fibrosi intestinale

Background: Intestinal fibrosis is a serious complication of IBD, with more than a third of Crohn’s disease (CD) patients developing a fibrostenosing phenotype with formation of strictures that will require surgical intervention. Remarkably, SAMP1/YitFc (SAMP) mice, a spontaneous model of CD, develop gut fibrosis; similar to IBD patients, the pathophysiology of SAMP fibrosis is unknown. IL-33 is a member of the IL-1 cytokine family and increased expression is associated with IBD. Emerging evidence suggests its potential role in liver and cutaneous fibrosis, as well as myofibroblast-associated colonic ulcerations . Aim: The aim of this study was to evaluate the role of IL-33 as a potential mediator of profibrotic events leading to intestinal fibrosis and possible stricture formation. Methods: A detailed histologic time course study, with collagen-specific Masson trichrome staining and IHC for ST2 (IL-33 receptor), was performed on SAMP and control AKR (parental strain) mice. qRT-PCR was done on full-thickness ilea for the profibrogenic genes, collagen (coll)-1, coll-3, connective tissue growth factor (CTGF) and insulin-like growth factor 1 (IGF-1). Exogenous IL-33 (33 μg/kg, i.p.) or vehicle was administered daily for 7d to SAMP and AKR mice (N=6/exp group), and ileal tissues evaluated as above. Finally, microarray analysis was performed on full-thickness ilea from SAMP and AKR mice, and IL-33 stimulated subepithelial myofibroblasts (SEMFs). Results: SAMP mice displayed ileal skip lesions with randomly distributed strictures, preceded by typical pre-stricture dilations of the ileum. Ileal wall was visibly thickened with hypertrophy of the serosa, muscularis mucosa, muscularis propria, within which intense collagen deposition was observed, and inflammatory infiltrates in segments showing strictures. Interestingly, intense ST2 staining was present within the inflamed lamina propria of SAMP, notably localized to SEMFs. Fibrosis was first observed at 20 wks, and reached its peak by 50 wks of age. mRNA expression of coll-1 (4.74±0.69-fold; P=0.001), coll-3 (4.92±1.05-fold; P=0.01), IGF1 (12.9±3.45; P=0.006), and CTGF (3.29±0.69; P=0.004) was dramatically elevated in SAMP vs. AKR ilea. IL-33 treatment of AKR mice induced a marked increase in muscle fiber/myofibroblast cellularity and hypertrophy of the muscularis propria (4.13±0.74-fold; P<0.0001), and mRNA expression of coll-1 (5.16±0.89-fold; P=0.0009), coll-3 (1.97±0.14-fold; P=0.01), IGF-1 (9.32±2.27-fold; P=0.004), and CTGF (1.43±0.31-fold; P=0.006) vs. vehicle controls. Microarray data from SAMP ilea and IL-33-treated SEMFs confirmed these trends, displaying a global increase in profibrogenic gene expression. Conclusion: These data suggest an important role for IL-33 in intestinal fibrosis, and may represent a potential target for the treatment of IBD-associated fibrosis and stricture formation.

Effects of metal-induced oxidative stress on endothelial cells in vitro

Aseptic loosening of metal implants is mainly attributed to the formation of metal degradation products. These include particulate debris and corrosion products, such as metal ions (anodic half-reaction) and ROS (cathodic half-reaction). While numerous clinical studies describe various adverse effects of metal degradation products, detailed knowledge of metal-induced cellular reactions, which might be important for possible therapeutic intervention, is not comprehensive. Since endothelial cells are involved in inflammation and angiogenesis, two processes which are critical for wound healing and integration of metal implants, the effects of different metal alloys and their degradation products on these cells were investigated. Endothelial cells on Ti6Al4V alloy showed signs of oxidative stress, which was similar to the response of endothelial cells to cathodic partial reaction of corrosion induced directly on Ti6Al4V surfaces. Furthermore, oxidative stress on Ti6Al4V alloy reduced the pro-inflammatory stimulation of endothelial cells by TNF-α and LPS. Oxidative stress and other stress-related responses were observed in endothelial cells in contact with Co28Cr6Mo alloy. Importantly, these features could be reduced by coating Co28Cr6Mo with a TiO2 layer, thus favouring the use of such surface modification in the development of medical devices for orthopaedic surgery. The reaction of endothelial cells to Co28Cr6Mo alloy was partially similar to the effects exerted by Co2+, which is known to be released from metal implants. Co2+ also induced ROS formation and DNA damage in endothelial cells. This correlated with p53 and p21 up-regulation, indicating the possibility of cell cycle arrest. Since CoCl2 is used as an hypoxia-mimicking agent, HIF-1α-dependence of cellular responses to Co2+ was studied in comparison to anoxia-induced effects. Although important HIF-1α-dependent genes were identified, a more detailed analysis of microarray data will be required to provide additional information about the mechanisms of Co2+ action. All these reactions of endothelial cells to metal degradation products might play their role in the complex processes taking place in the body following metal device implantation. In the worst case this can lead to aseptic loosening of the implant and requirement for revision surgery. Knowledge of molecular mechanisms of metal-induced responses will hopefully provide the possibility to interfere with undesirable processes at the implant/tissue interface, thus extending the life-time of the implant and the overall success of metal implant applications.

Meta-analyses qualify metzincins and related genes as acute rejection markers in renal transplant patients

Definition of acute renal allograft rejection (AR) markers remains clinically relevant. Features of T-cell-mediated AR are tubulointerstitial and vascular inflammation associated with excessive extracellular matrix (ECM) remodeling, regulated by metzincins, including matrix metalloproteases (MMP). Our study focused on expression of metzincins (METS), and metzincins and related genes (MARGS) in renal allograft biopsies using four independent microarray data sets. Our own cases included normal histology (N, n = 20), borderline changes (BL, n = 4), AR (n = 10) and AR + IF/TA (n = 7). MARGS enriched in all data sets were further examined on mRNA and/or protein level in additional patients. METS and MARGS differentiated AR from BL, AR + IF/TA and N in a principal component analysis. Their expression changes correlated to Banff t- and i-scores. Two AR classifiers, based on METS (including MMP7, TIMP1), or on MARGS were established in our own and validated in the three additional data sets. Thirteen MARGS were significantly enriched in AR patients of all data sets comprising MMP7, -9, TIMP1, -2, thrombospondin2 (THBS2) and fibrillin1. RT-PCR using microdissected glomeruli/tubuli confirmed MMP7, -9 and THBS2 microarray results; immunohistochemistry showed augmentation of MMP2, -9 and TIMP1 in AR. TIMP1 and THBS2 were enriched in AR patient serum. Therefore, differentially expressed METS and MARGS especially TIMP1, MMP7/-9 represent potential molecular AR markers.

A subset of metzincins and related genes constitutes a marker of human solid organ fibrosis

Metzincins and functionally related genes play important roles in extracellular matrix remodeling both in healthy and fibrotic conditions. We recently presented a transcriptomic classifier consisting of 19 metzincins and related genes (MARGS) discriminating biopsies from renal transplant patients with or without interstitial fibrosis/tubular atrophy (IF/TA) by virtue of gene expression measurement (Roedder et al., Am J Transplant 9:517-526, 2009). Here we demonstrate that the same algorithm has diagnostic value in non-transplant solid organ fibrosis. We used publically available microarray datasets of 325 human heart, liver, lung, kidney cortex, and pancreas microarray samples (265 with fibrosis, 60 healthy controls). Expression of nine commonly differentially expressed genes was confirmed by TaqMan low-density arrays (Applied Biosystems, USA) in 50 independent archival tissue specimens with matched histological diagnoses to microarray patients. In separate and in combined, integrated microarray data analyses of five datasets with 325 samples, the previously published MARGS classifier for renal post-transplant IF/TA had a mean AUC of 87% and 82%, respectively. These data demonstrate that the MARGS gene panel classifier not only discriminates IF/TA from normal renal transplant tissue, but also classifies solid organ fibrotic conditions of human pancreas, liver, heart, kidney, and lung tissue samples with high specificity and accuracy, suggesting that the MARGS classifier is a cross-platform, cross-organ classifier of fibrotic conditions of different etiologies when compared to normal tissue.

An integrated nano-scale approach to profile miRNAs in limited clinical samples

Profiling miRNA expression in cells that directly contribute to human disease pathogenesis is likely to aid the discovery of novel drug targets and biomarkers. However, tissue heterogeneity and the limited amount of human diseased tissue available for research purposes present fundamental difficulties that often constrain the scope and potential of such studies. We established a flow cytometry-based method for isolating pure populations of pathogenic T cells from bronchial biopsy samples of asthma patients, and optimized a high-throughput nano-scale qRT-PCR method capable of accurately measuring 96 miRNAs in as little as 100 cells. Comparison of circulating and airway T cells from healthy and asthmatic subjects revealed asthma-associated and tissue-specific miRNA expression patterns. These results establish the feasibility and utility of investigating miRNA expression in small populations of cells involved in asthma pathogenesis, and set a precedent for application of our nano-scale approach in other human diseases. The microarray data from this study (Figure 7) has been submitted to the NCBI Gene Expression Omnibus (GEO; http://ncbi.nlm.nih.gov/geo) under accession no. GSE31030.

Comparison of the gene expression profiles from normal and Fgfrl1 deficient mouse kidneys reveals downstream targets of Fgfrl1 signaling

Fgfrl1 (fibroblast growth factor receptor-like 1) is a transmembrane receptor that is essential for the development of the metanephric kidney. It is expressed in all nascent nephrogenic structures and in the ureteric bud. Fgfrl1 null mice fail to develop the metanephric kidneys. Mutant kidney rudiments show a dramatic reduction of ureteric branching and a lack of mesenchymal-to-epithelial transition. Here, we compared the expression profiles of wildtype and Fgfrl1 mutant kidneys to identify genes that act downstream of Fgfrl1 signaling during the early steps of nephron formation. We detected 56 differentially expressed transcripts with 2-fold or greater reduction, among them many genes involved in Fgf, Wnt, Bmp, Notch, and Six/Eya/Dach signaling. We validated the microarray data by qPCR and whole-mount in situ hybridization and showed the expression pattern of candidate genes in normal kidneys. Some of these genes might play an important role during early nephron formation. Our study should help to define the minimal set of genes that is required to form a functional nephron.

Multiple Testing With an Empirical Alternative Hypothesis

An optimal multiple testing procedure is identified for linear hypotheses under the general linear model, maximizing the expected number of false null hypotheses rejected at any significance level. The optimal procedure depends on the unknown data-generating distribution, but can be consistently estimated. Drawing information together across many hypotheses, the estimated optimal procedure provides an empirical alternative hypothesis by adapting to underlying patterns of departure from the null. Proposed multiple testing procedures based on the empirical alternative are evaluated through simulations and an application to gene expression microarray data. Compared to a standard multiple testing procedure, it is not unusual for use of an empirical alternative hypothesis to increase by 50% or more the number of true positives identified at a given significance level.

The Optimal Confidence Region for a Random Parameter

Under a two-level hierarchical model, suppose that the distribution of the random parameter is known or can be estimated well. Data are generated via a fixed, but unobservable realization of this parameter. In this paper, we derive the smallest confidence region of the random parameter under a joint Bayesian/frequentist paradigm. On average this optimal region can be much smaller than the corresponding Bayesian highest posterior density region. The new estimation procedure is appealing when one deals with data generated under a highly parallel structure, for example, data from a trial with a large number of clinical centers involved or genome-wide gene-expession data for estimating individual gene- or center-specific parameters simultaneously. The new proposal is illustrated with a typical microarray data set and its performance is examined via a small simulation study.

IDENTIFICATION OF GENES CONTROLLING BIOLOGICAL PROCESSES AND PATHWAYS THROUGH STATISTICAL ANALYSIS AND NETWORK RECONSTRUCTION

The developmental processes and functions of an organism are controlled by the genes and the proteins that are derived from these genes. The identification of key genes and the reconstruction of gene networks can provide a model to help us understand the regulatory mechanisms for the initiation and progression of biological processes or functional abnormalities (e.g. diseases) in living organisms. In this dissertation, I have developed statistical methods to identify the genes and transcription factors (TFs) involved in biological processes, constructed their regulatory networks, and also evaluated some existing association methods to find robust methods for coexpression analyses. Two kinds of data sets were used for this work: genotype data and gene expression microarray data. On the basis of these data sets, this dissertation has two major parts, together forming six chapters. The first part deals with developing association methods for rare variants using genotype data (chapter 4 and 5). The second part deals with developing and/or evaluating statistical methods to identify genes and TFs involved in biological processes, and construction of their regulatory networks using gene expression data (chapter 2, 3, and 6). For the first part, I have developed two methods to find the groupwise association of rare variants with given diseases or traits. The first method is based on kernel machine learning and can be applied to both quantitative as well as qualitative traits. Simulation results showed that the proposed method has improved power over the existing weighted sum method (WS) in most settings. The second method uses multiple phenotypes to select a few top significant genes. It then finds the association of each gene with each phenotype while controlling the population stratification by adjusting the data for ancestry using principal components. This method was applied to GAW 17 data and was able to find several disease risk genes. For the second part, I have worked on three problems. First problem involved evaluation of eight gene association methods. A very comprehensive comparison of these methods with further analysis clearly demonstrates the distinct and common performance of these eight gene association methods. For the second problem, an algorithm named the bottom-up graphical Gaussian model was developed to identify the TFs that regulate pathway genes and reconstruct their hierarchical regulatory networks. This algorithm has produced very significant results and it is the first report to produce such hierarchical networks for these pathways. The third problem dealt with developing another algorithm called the top-down graphical Gaussian model that identifies the network governed by a specific TF. The network produced by the algorithm is proven to be of very high accuracy.

Integrative analysis of RUNX1 downstream pathways and target genes

BACKGROUND: The RUNX1 transcription factor gene is frequently mutated in sporadic myeloid and lymphoid leukemia through translocation, point mutation or amplification. It is also responsible for a familial platelet disorder with predisposition to acute myeloid leukemia (FPD-AML). The disruption of the largely unknown biological pathways controlled by RUNX1 is likely to be responsible for the development of leukemia. We have used multiple microarray platforms and bioinformatic techniques to help identify these biological pathways to aid in the understanding of why RUNX1 mutations lead to leukemia. RESULTS: Here we report genes regulated either directly or indirectly by RUNX1 based on the study of gene expression profiles generated from 3 different human and mouse platforms. The platforms used were global gene expression profiling of: 1) cell lines with RUNX1 mutations from FPD-AML patients, 2) over-expression of RUNX1 and CBFbeta, and 3) Runx1 knockout mouse embryos using either cDNA or Affymetrix microarrays. We observe that our datasets (lists of differentially expressed genes) significantly correlate with published microarray data from sporadic AML patients with mutations in either RUNX1 or its cofactor, CBFbeta. A number of biological processes were identified among the differentially expressed genes and functional assays suggest that heterozygous RUNX1 point mutations in patients with FPD-AML impair cell proliferation, microtubule dynamics and possibly genetic stability. In addition, analysis of the regulatory regions of the differentially expressed genes has for the first time systematically identified numerous potential novel RUNX1 target genes. CONCLUSION: This work is the first large-scale study attempting to identify the genetic networks regulated by RUNX1, a master regulator in the development of the hematopoietic system and leukemia. The biological pathways and target genes controlled by RUNX1 will have considerable importance in disease progression in both familial and sporadic leukemia as well as therapeutic implications.

The sequence of addition of IL-3 and IgE-dependent/IgE-independent stimuli regulates RANKL expression in human basophils

Background: Receptor Activator of Nuclear Factor kappaB Ligand (RANKL), a member of the TNF superfamily, contributes to the imbalance of bone resorption and immunoregulation in rheumatoid arthritis. In mice, collagen induced arthritis was exacerbated by IL-3 and anti-IgER antibodies, two mediators activating basophils that are known as effector cells of allergy. Interestingly, our unpublished microarray data revealed that IL-3 induces RANKL mRNA in human basophils. Here we further investigate under which conditions human basophils express surface and/or soluble RANKL. Methods: One part of purified human basophils was co-stimulated with IL-3 and either IgE-dependent or IgE-independent stimuli. The other part of purified basophils was first primed with IL-3 and subsequently triggered with IgE-dependent or IgE-independent stimuli. Expression of surface and soluble RANKL were detected by flow cytometry, ELISA and real-time PCR. Results: By flow cytometry we show that IL-3 induces de novo expression of surface RANKL on human basophils in a time and dose dependent manner. Co-stimulation of basophils with IL-3 and an IgE-dependent stimulus reduces IL-3-induced expression of surface RANKL in a dose dependent manner while IgE-independent stimuli have no effect. In contrast, both IgE-dependent and IgE-independent stimuli enhance expression of surface and soluble RANKL in basophils that were first primed with IL-3 and then triggered. Real-time PCR analysis shows that surface hRANKL1 and soluble hRANKL3 are induced by IL-3 and reduced by co-stimulation with IL-3 and an IgE-dependent stimulus and thus confirms our flow cytometry data. Conclusion: RANKL expression in human basophils is not only dependent on IL-3 and IgE-dependent/IgE-independent stimuli but also on the sequence of their addition to cell culture. Based on our data, we suggest that basophils might have previously unidentified functions in bone resorption or immunoregulation via RANKL.

THE MECHANISM OF TUMORIGENESIS IN THE IMMORTALIZED HUMAN PANCREATIC CELL LINES: CELL CULTURE MODELS OF HUMAN PANCREATIC CANCER

The mechanism of tumorigenesis in the immortalized human pancreatic cell lines: cell culture models of human pancreatic cancer Pancreatic ductal adenocarcinoma (PDAC) is the most lethal cancer in the world. The most common genetic lesions identified in PDAC include activation of K-ras (90%) and Her2 (70%), loss of p16 (95%) and p14 (40%), inactivation p53 (50-75%) and Smad4 (55%). However, the role of these signature gene alterations in PDAC is still not well understood, especially, how these genetic lesions individually or in combination contribute mechanistically to human pancreatic oncogenesis is still elusive. Moreover, a cell culture transformation model with sequential accumulation of signature genetic alterations in human pancreatic ductal cells that resembles the multiple-step human pancreatic carcinogenesis is still not established. In the present study, through the stepwise introduction of the signature genetic alterations in PDAC into the HPV16-E6E7 immortalized human pancreatic duct epithelial (HPDE) cell line and the hTERT immortalized human pancreatic ductal HPNE cell line, we developed the novel experimental cell culture transformation models with the most frequent gene alterations in PDAC and further dissected the molecular mechanism of transformation. We demonstrated that the combination of activation of K-ras and Her2, inactivation of p16/p14 and Smad4, or K-ras mutation plus p16 inactivation, was sufficient for the tumorigenic transformation of HPDE or HPNE cells respectively. We found that these transformed cells exhibited enhanced cell proliferation, anchorage-independent growth in soft agar, and grew tumors with PDAC histopathological features in orthotopic mouse model. Molecular analysis showed that the activation of K-ras and Her2 downstream effector pathways –MAPK, RalA, FAK, together with upregulation of cyclins and c-myc were involved in the malignant transformation. We discovered that MDM2, BMP7 and Bmi-1 were overexpressed in the tumorigenic HPDE cells, and that Smad4 played important roles in regulation of BMP7 and Bmi-1 gene expression and the tumorigenic transformation of HPDE cells. IPA signaling pathway analysis of microarray data revealed that abnormal signaling pathways are involved in transformation. This study is the first complete transformation model of human pancreatic ductal cells with the most common gene alterations in PDAC. Altogether, these novel transformation models more closely recapitulate the human pancreatic carcinogenesis from the cell origin, gene lesion, and activation of specific signaling pathway and histopathological features.