The role of P16ink4a and P53 immunostaining in predicting recurrence of HG-CIN after conization treatment

Objective: Io evaluate the expression of p16INK4a and p53 biomarkers in conization specimens from patients with high grade cervical intraepithelial neoplasia (HG-CIN), correlating them with the ability to predict the recurrence. Methods : we conducted a retrospective study of patients with HG-CIN in cervical biopsy treated with conization between January 1999 and January 2006 who had a minimum follow-up of 18 months. The expression of the p16 and p53 was assessed by tissue microarrays and correlated with disease recurrence. For analysis, we used the test of proportions (chi-square), considering value p<0.05, 95% CI and calculations of sensitivity, specificity and accuracy of these immunomarkers in predicting recurrence. Results : the series comprised 83 patients aged between 16 and 86 years (35±11.7), divided into two groups: 30 with HG-CIN recurrence (study group) and 53 without recurrence (control group). Mean age, parity, smoking and conization technique were similar in both groups. The p53 expression was present in 43% of the study group and 57% of the control group, and the p16 was present in 43% of the study group and in 57% of the control group (p>0.05). p53 had a positive predictive value (PPV) of 42% and negative predictive value (NPV) of 73%, sensitivity 70%, specificity of 47% and accuracy of 59%. The p16, PPV 42%, NPV 72%, sensitivity 66%, specificity of 49% and accuracy of 56%. Conclusion : immunohistochemistry expression of p53 and p16 showed low sensitivity and low specificity as predictors of HG-CIN recurrence after conization treatment.

Loss of PTEN expression and AKT activation in HER2-positive breast carcinomas

PURPOSE: To examine the expression of AKT and PTEN in a series of HER2-positive primary invasive breast tumors using immunohistochemistry, and to associate these expression profiles with classic pathologic features such as tumor grade, hormone receptor expression, lymphatic vascular invasion, and proliferation.METHODS: A total of 104 HER2-positive breast carcinoma specimens were prepared in tissue microarrays blocks for immunohistochemical detection of PTEN and phosphorylated AKT (pAKT). Original histologic sections were reviewed to assess pathological features, including HER2 status and Ki-67 index values. The associations between categorical and numeric variables were identified using Pearson's chi-square test and the Mann-Whitney, respectively.RESULTS: Co-expression of pAKT and PTEN was presented in 59 (56.7%) cases. Reduced levels of PTEN expression were detected in 20 (19.2%) cases, and these 20 tumors had a lower Ki-67 index value. In contrast, tumors positive for pAKT expression [71 (68.3%)] were associated with a higher Ki-67 index value.CONCLUSION: A role for AKT in the proliferation of HER2-positive breast cancers was confirmed. However, immunohistochemical detection of PTEN expression did not correlate with an inhibition of cellular proliferation or control of AKT phosphorylation, suggesting other pathways in these mechanisms of control.

Novel Functions of ErbB4 and NRG-1 in Development and Cancer

Cells communicate, or signal, with each other constantly to ensure proper functioning of tissues and organs. Cell signaling is often performed by interplay of receptors and ligands that bind these receptors. ErbB receptors (epidermal growth factor receptors, EGFR, HER) bind extracellular growth factors and transduce these signals inside of cells. ErbB dysfunction promotes carcinogenesis, and also results in numerous defects during normal development. This study focused on the functions of one member of the ErbB receptor family, ErbB4, and growth factor, neuregulin-1 (NRG-1), that can bind and activate ErbB4. This study aimed to find novel functions of ErbB4 and NRG-1. Hypoxia, or deficiency of oxygen, is common in cancer and ischemic conditions. One of the key findings of the work was the identification and characterization of a cross-talk between ErbB4 and Hypoxia-inducible factor 1α (HIF-1α), the central mediator of hypoxia signaling. ErbB4 activation by NRG-1 was found to increase HIF-1α activity. Interestingly, this regulation occurred in reciprocal manner as HIF-1α was also able to increase protein levels of NRG-1 and ErbB4. Moreover, expression of NRG-1 and ErbB4 was associated with HIF activity in vivo in human clinical samples and in mice. Reduction of functional ErbB4 in developing zebrafish embryos resulted in defects in development of the skeletal muscles. To study ErbB4 functions in pathological situation in humans, clinical samples of serous ovarian carcinoma were analyzed using tissue microarrays and real-time RT-PCR. A specific isoform of ErbB4, CYT-1, was associated with poor survival in serous ovarian cancer and increased anchorage independent growth of ovarian cancer cells in vitro. These observations demonstrate that ErbB4 and NRG-1 are essential regulators of cellular response to hypoxia, of development, and of ovarian carcinogenesis.

Algorithmic Techniques in Gene Expression Processing. From Imputation to Visualization

The amount of biological data has grown exponentially in recent decades. Modern biotechnologies, such as microarrays and next-generation sequencing, are capable to produce massive amounts of biomedical data in a single experiment. As the amount of the data is rapidly growing there is an urgent need for reliable computational methods for analyzing and visualizing it. This thesis addresses this need by studying how to efficiently and reliably analyze and visualize high-dimensional data, especially that obtained from gene expression microarray experiments. First, we will study the ways to improve the quality of microarray data by replacing (imputing) the missing data entries with the estimated values for these entries. Missing value imputation is a method which is commonly used to make the original incomplete data complete, thus making it easier to be analyzed with statistical and computational methods. Our novel approach was to use curated external biological information as a guide for the missing value imputation. Secondly, we studied the effect of missing value imputation on the downstream data analysis methods like clustering. We compared multiple recent imputation algorithms against 8 publicly available microarray data sets. It was observed that the missing value imputation indeed is a rational way to improve the quality of biological data. The research revealed differences between the clustering results obtained with different imputation methods. On most data sets, the simple and fast k-NN imputation was good enough, but there were also needs for more advanced imputation methods, such as Bayesian Principal Component Algorithm (BPCA). Finally, we studied the visualization of biological network data. Biological interaction networks are examples of the outcome of multiple biological experiments such as using the gene microarray techniques. Such networks are typically very large and highly connected, thus there is a need for fast algorithms for producing visually pleasant layouts. A computationally efficient way to produce layouts of large biological interaction networks was developed. The algorithm uses multilevel optimization within the regular force directed graph layout algorithm.

Hunting for differentially expressed genes

Differentially expressed genes are usually identified by comparing steady-state mRNA concentrations. Several methods have been used for this purpose, including differential hybridization, cDNA subtraction, differential display and, more recently, DNA chips. Subtractive hybridization has significantly improved after the polymerase chain reaction was incorporated into the original method and many new protocols have been established. Recently, the availability of the well-known coding sequences for some organisms has greatly facilitated gene expression analysis using high-density microarrays. Here, we describe some of these modifications and discuss the benefits and drawbacks of the various methods corresponding to the main advances in this field.

High pressure-sensitive gene expression in Lactobacillus sanfranciscensis

Lactobacillus sanfranciscensis is a Gram-positive lactic acid bacterium used in food biotechnology. It is necessary to investigate many aspects of a model organism to elucidate mechanisms of stress response, to facilitate preparation, application and performance in food fermentation, to understand mechanisms of inactivation, and to identify novel tools for high pressure biotechnology. To investigate the mechanisms of the complex bacterial response to high pressure we have analyzed changes in the proteome and transcriptome by 2-D electrophoresis, and by microarrays and real time PCR, respectively. More than 16 proteins were found to be differentially expressed upon high pressure stress and were compared to those sensitive to other stresses. Except for one apparently high pressure-specific stress protein, no pressure-specific stress proteins were found, and the proteome response to pressure was found to differ from that induced by other stresses. Selected pressure-sensitive proteins were partially sequenced and their genes were identified by reverse genetics. In a transcriptome analysis of a redundancy cleared shot gun library, about 7% of the genes investigated were found to be affected. Most of them appeared to be up-regulated 2- to 4-fold and these results were confirmed by real time PCR. Gene induction was shown for some genes up-regulated at the proteome level (clpL/groEL/rbsK), while the response of others to high hydrostatic pressure at the transcriptome level seemed to differ from that observed at the proteome level. The up-regulation of selected genes supports the view that the cell tries to compensate for pressure-induced impairment of translation and membrane transport.

A conceptual and practical overview of cDNA microarray technology: implications for basic and clinical sciences

cDNA microarray is an innovative technology that facilitates the analysis of the expression of thousands of genes simultaneously. The utilization of this methodology, which is rapidly evolving, requires a combination of expertise from the biological, mathematical and statistical sciences. In this review, we attempt to provide an overview of the principles of cDNA microarray technology, the practical concerns of the analytical processing of the data obtained, the correlation of this methodology with other data analysis methods such as immunohistochemistry in tissue microarrays, and the cDNA microarray application in distinct areas of the basic and clinical sciences.

Rapid, reliable and inexpensive quality assessment of biotinylated cRNA

The interpretation of oligonucleotide array experiments depends on the quality of the target cRNA used. cRNA target quality is assessed by quantitative analysis of the representation of 5' and 3' sequences of control genes using commercially available Test arrays. The Test array provides an economically priced means of determining the quality of labeled target prior to analysis on whole genome expression arrays. This manuscript validates the use of a duplex RT-PCR assay as a faster (6 h) and less expensive (microarrays from Affymetrix. Ten cRNA samples with a ß-actin 3'/5' ratio >6 were chosen and classified as degraded cRNAs, and 31 samples with a ß-actin 3'/5' ratio <6 were selected as good quality cRNAs. Blinded samples were then used for the RT-PCR assay. After gel electrophoresis, optical densities of the amplified 3' and 5' fragments of ß-actin were measured and the 3'/5' ratio was calculated. There was a strong correlation (r² = 0.6802) between the array and the RT-PCR ß-actin 3'/5' ratios. Moreover, the RT-PCR 3'/5' ratio was significantly different (P < 0.0001) between undegraded (mean ± SD, 0.34 ± 0.09) and degraded (1.71 ± 0.83) samples. None of the other parameters analyzed, such as i) the starting amount of RNA, ii) RNA quality assessed using the Bioanalyzer Chip technology, or iii) the concentration and OD260/OD280 ratio of the purified biotinylated cRNA, correlated with cRNA quality.

Differential gene expression profiles of hepatocellular carcinomas associated or not with viral infection

Chronic hepatitis B (HBV) and C (HCV) virus infections are the most important factors associated with hepatocellular carcinoma (HCC), but tumor prognosis remains poor due to the lack of diagnostic biomarkers. In order to identify novel diagnostic markers and therapeutic targets, the gene expression profile associated with viral and non-viral HCC was assessed in 9 tumor samples by oligo-microarrays. The differentially expressed genes were examined using a z-score and KEGG pathway for the search of ontological biological processes. We selected a non-redundant set of 15 genes with the lowest P value for clustering samples into three groups using the non-supervised algorithm k-means. Fisher’s linear discriminant analysis was then applied in an exhaustive search of trios of genes that could be used to build classifiers for class distinction. Different transcriptional levels of genes were identified in HCC of different etiologies and from different HCC samples. When comparing HBV-HCC vs HCV-HCC, HBV-HCC/HCV-HCC vs non-viral (NV)-HCC, HBC-HCC vs NV-HCC, and HCV-HCC vs NV-HCC of the 58 non-redundant differentially expressed genes, only 6 genes (IKBKβ, CREBBP, WNT10B, PRDX6, ITGAV, and IFNAR1) were found to be associated with hepatic carcinogenesis. By combining trios, classifiers could be generated, which correctly classified 100% of the samples. This expression profiling may provide a useful tool for research into the pathophysiology of HCC. A detailed understanding of how these distinct genes are involved in molecular pathways is of fundamental importance to the development of effective HCC chemoprevention and treatment.

Cardiac gene expression and systemic cytokine profile are complementary in a murine model of post-ischemic heart failure

After myocardial infarction (MI), activation of the immune system and inflammatory mechanisms, among others, can lead to ventricular remodeling and heart failure (HF). The interaction between these systemic alterations and corresponding changes in the heart has not been extensively examined in the setting of chronic ischemia. The main purpose of this study was to investigate alterations in cardiac gene and systemic cytokine profile in mice with post-ischemic HF. Plasma was tested for IgM and IgG anti-heart reactive repertoire and inflammatory cytokines. Heart samples were assayed for gene expression by analyzing hybridization to AECOM 32k mouse microarrays. Ischemic HF significantly increased the levels of total serum IgM (by 5.2-fold) and total IgG (by 3.6-fold) associated with a relatively high content of anti-heart specificity. A comparable increase was observed in the levels of circulating pro-inflammatory cytokines such as IL-1β (3.8X) and TNF-α (6.0X). IFN-γ was also increased by 3.1-fold in the MI group. However, IL-4 and IL-10 were not significantly different between the MI and sham-operated groups. Chemokines such as MCP-1 and IL-8 were 1.4- and 13-fold increased, respectively, in the plasma of infarcted mice. We identified 2079 well annotated unigenes that were significantly regulated by post-ischemic HF. Complement activation and immune response were among the most up-regulated processes. Interestingly, 21 of the 101 quantified unigenes involved in the inflammatory response were significantly up-regulated and none were down-regulated. These data indicate that post-ischemic heart remodeling is accompanied by immune-mediated mechanisms that act both systemically and locally.

Whole transcriptome organisation in the dehydrated supraoptic nucleus

The supraoptic nucleus (SON) is part of the central osmotic circuitry that synthesises the hormone vasopressin (Avp) and transports it to terminals in the posterior lobe of the pituitary. Following osmotic stress such as dehydration, this tissue undergoes morphological, electrical and transcriptional changes to facilitate the appropriate regulation and release of Avp into the circulation where it conserves water at the level of the kidney. Here, the organisation of the whole transcriptome following dehydration is modelled to fit Zipf's law, a natural power law that holds true for all natural languages, that states if the frequency of word usage is plotted against its rank, then the log linear regression of this is -1. We have applied this model to our previously published euhydrated and dehydrated SON data to observe this trend and how it changes following dehydration. In accordance with other studies, our whole transcriptome data fit well with this model in the euhydrated SON microarrays, but interestingly, fit better in the dehydrated arrays. This trend was observed in a subset of differentially regulated genes and also following network reconstruction using a third-party database that mines public data. We make use of language as a metaphor that helps us philosophise about the role of the whole transcriptome in providing a suitable environment for the delivery of Avp following a survival threat like dehydration.

Molecular patterns behind immunological and metabolic alterations in lysinuric protein intolerance

Lysinuric protein intolerance (LPI) is a recessively inherited disorder characterised by reduced plasma and increased urinary levels of cationic amino acids (CAAs), protein malnutrition, growth failure and hyperlipidemia. Some patients develop severe immunological, renal and pulmonary complications. All Finnish patients share the same LPIFin mutation in the SLC7A7 gene that encodes CAA transporter y+LAT1. The aim of this study was to examine molecular factors contributing to the various symptoms, systemic metabolic and lipid profiles, and innate immune responses in LPI. The transcriptomes, metabolomes and lipidomes were analysed in whole-blood cells and plasma using RNA microarrays and gas or liquid chromatography-mass spectrometry techniques, respectively. Toll-like receptor (TLR) signalling in monocyte-derived macrophages exposed to pathogens was scrutinised using qRT-PCR and the Luminex technology. Altered levels of transcripts participating in amino acid transport, immune responses, apoptosis and pathways of hepatic and renal metabolism were identified in the LPI whole-blood cells. The patients had increased non-essential amino acid, triacylglycerol and fatty acid levels, and decreased plasma levels of phosphatidylcholines and practically all essential amino acids. In addition, elevated plasma levels of eight metabolites, long-chain triacylglycerols, two chemoattractant chemokines and nitric oxide correlated with the reduced glomerular function in the patients with kidney disease. Accordingly, it can be hypothesised that the patients have increased autophagy, inflammation, oxidative stress and apoptosis, leading to hepatic steatosis, uremic toxicity and altered intestinal microbe metabolism. Furthermore, the LPI macrophages showed disruption in the TLR2/1, TLR4 and TLR9 pathways, suggesting innate immune dysfunctions with an excessive response to bacterial infections but a deficient viral DNA response.

Caractérisation de la SERPINA1, une antiprotéase différentiellement exprimée dans le cancer épithélial de l’ovaire

Le cancer épithélial de l’ovaire est le cancer gynécologique le plus létal. La survie à 5 ans est de 30-40% chez les patientes atteintes d’une tumeur invasive (TOV), comparativement à 95% chez les patientes diagnostiquées pour une tumeur à faible potentiel de malignité ou borderline (LMP). Au laboratoire, l’analyse de l’expression des gènes de la micropuce à ADN U133 d’Affymetrix a révélé que la SERPINA1 est un gène dont l’expression varie entre les tumeurs LMP et TOV. La validation par Q-PCR nous a confirmé que cette antiprotéase est majoritairement surexprimée dans les tumeurs LMP, par rapport aux tumeurs bénignes (BOV) et aux tumeurs TOV. Nous avons donc surexprimé la SERPINA1 dans les lignées cellulaires invasives TOV 112D et TOV 1946 du cancer de l’ovaire et dérivé des clones stables. Les résultats obtenus nous indiquent que la surexpression de la SERPINA1 a un effet sur la capacité d’invasion et de migration cellulaire et non au niveau de la croissance cellulaire et la formation de structures tridimensionnelles. Les résultats issus de l’étude in vivo dans les souris SCID nous permettront de déterminer si la surexpression de la SERPINA1 a un effet sur la tumorigénèse ovarienne. Ainsi, la SERPINA1 demeure à notre avis un candidat d’intérêt pour tenter de mieux comprendre les différences biologiques entre les tumeurs LMP et TOV, ainsi que le rôle des protéases et de leurs inhibiteurs dans la progression tumorale du cancer de l’ovaire.

Étude de l’activité de Staufen1 dans la régulation traductionnelle de certains ARNm

Le transport et la traduction localisée des ARN messagers sont observés chez plusieurs organismes et sont requis pour de multiples phénomènes tels la mémoire, la division cellulaire asymétrique et l’établissement des axes durant le développement. Staufen, une protéine liant l’ARN double-brin, a été identifié dans un premier temps chez la mouche à fruits Drosophila melanogaster. Il a été montré, chez cet organisme, que Staufen est requis pour la localisation des messagers bicoid et oskar aux pôles antérieur et postérieur de l’ovocyte, respectivement. Également, Staufen est requis afin que la répression traductionnelle du messager oskar soit levée une fois qu’il est bien localisé. Chez les mammifères, Stau1 est une protéine ubiquiste qui est présente dans des complexes prenant la forme de granules dans les dendrites des neurones. Également, Stau1 peut interagir de façon indépendante de l’ARN avec le ribosome et cofractionner tant avec la sous-unité 40S qu’avec la sous-unité 60S du ribosome dans un gradient de saccharose. L’implication de Stau1 dans un mécanisme permettant la dérépression traductionnelle de certains ARNm chez les mammifères était donc une voie d’investigation intéressante. Nous avons donc décidé de vérifier si Stau1 mammifère avait la capacité de stimuler la traduction d’un ARNm cellulaire via un mécanisme régulé. Au moment où cette thèse a été entreprise, aucun ARNm cellulaire lié par Stau1 n’avait été identifié chez les mammifères. Des structures d’ARN double-brin ont donc été employées afin de réprimer la traduction d’un ARNm rapporteur. C’est ainsi que nous avons montré que Stau1 peut stimuler la traduction d’un ARNm lorsqu’il lie celui-ci dans sa région 5’ non-traduite. Par la suite, en employant des micropuces d’ADN, nous avons identifié des messagers cellulaires dont la distribution dans les polysomes lourds est modifiée par Stau1. En effet, un groupe de messagers est enrichi dans les polysomes lourds suite à une surexpression de Stau1, ce qui suggère que Stau1 stimule la traduction de cette population d’ARNm. Afin d’identifier un mécanisme potentiel de régulation de l’activité traductionnelle de Stau1, nous nous sommes intéressés à la capacité d’auto-association de cette protéine. Nous avons montré que Stau1, tout comme plusieurs protéines liant l’ARN double-brin, est en mesure de s’associer à lui-même, et ce, d’une façon indépendante de l’ARN. Nous avons identifié les déterminants impliqués mettant ainsi au jour un nouveau mécanisme pouvant influencer les activités cellulaires de Stau1. Les résultats présentés dans cette thèse suggèrent donc que Stau1 est en mesure de stimuler la traduction d’une sous-population précise d’ARN messagers au sein de la cellule permettant ainsi de jeter un regard nouveau sur l’implication de cette protéine dans divers phénomènes au sein de l’organisme.

Caractérisation du potentiel métastatique des carcinomes mammaires de phénotype basal

Au Canada, on estime qu'une femme sur neuf développera un cancer du sein et qu'une femme sur vingt-huit en mourra. Les carcinomes mammaires de phénotype basal qui comprennent environ 15 à 25% des cancers envahissants du sein sont des tumeurs malignes ayant un très mauvais pronostic. Dans ce type tumoral, les métastases sont fréquentes et les décès nombreux. La formation des métastases est un processus complexe qui comprend plusieurs étapes; chacune peut être étudiée par des marqueurs spécifiques. Notre hypothèse de recherche est que le carcinome mammaire de phénotype basal possède des caractéristiques spécifiques qui permettent d'expliquer son potentiel métastatique élevé. Six micromatrices tissulaires comprenant un total de 213 tumeurs mammaires ont été confectionnées. L'expression des marqueurs usuels de la métastase et celle de nouveaux marqueurs a été étudiée par des techniques d'immunohistochimie. L'étude comparative de l’expression des marqueurs du potentiel métastatique par les carcinomes mammaires de phénotype basal indique que les protéines Ki-67, EGFR, CD276 et galectine-7 sont étroitement reliées à ce type de cancer. De plus, l'expression du marqueur GATA-3, un marqueur anti-métastatique, fait complètement défaut. Nos résultats confirment que le cancer du sein de phénotype basal possède un plus grand potentiel métastatique que les autres sous-types génétiques et suggèrent que la galectine-7 puisse être impliquée.