Classificazione su base molecolare dei tumori mammari della cagna mediante metodica immunoistochimica

Background. A new classification system of human breast tumours based on the immunohistochemical characterization has been applied to mammary tumours of the female dog with the aim to verify its association with invasion and grade, and prognostic aid in veterinary medicine. Methods. Forty-five canine mammary carcinomas with a two-year post-mastectomy follow-up were selected from our database, and the following antibodies were applied: anti-cytokeratines 14, 5/6, oestrogen receptor (ER), progesterone receptor (PR), and ERB-B2. . The tumours were grouped for phenotype as: luminal-like (ER+ and/or PR+, CK14-, CK5/6-) type A (ERB-B2-), and B (ERB-B2+); basal-like (ER-, PR-, CK14+ and/or CK5/6+, ERB-B2-); ERB-B2 (ER-, PR-, CK14-, CK5/6-, ERB-B2+). Association with invasion, grade and histotypes were evaluated and Kaplan-Meier survival curves estimated, then compared by survival analysis. Results. Thirty-five cases with luminal pattern (ER+ and PR+) were subgrouped into 13 A type and 22 B type, if ERB-B2 positive or negative . Most luminal-like A and basal-like cases were grade 1 carcinomas, while the percentage of luminal B cases was higher in grade 2 and 3 (Pearson Chi-square P=0.009). No difference in the percentage of molecular subtypes was evidenced between simple and complex/mixed carcinomas (Pearson Chi-square P=0.47). No significant results were obtained by survival analysis, even if basal-like had a more favourable prognosis than luminal-like. Conclusion. The panel of antibodies identified only 3 groups (luminal-like A and B, and basal-like) in the dog. Even though canine mammary tumours may be a model of human breast cancer, the existence of the same types of carcinoma as in the woman need to be confirmed. Canine mammary carcinomas show high molecular heterogeneity, which would benefit from a classification based on molecular differences. However, by multivariate analysis, the molecular classification appears a variable with a dependent value if compared to invasion and grade that are independent, suggesting that, at present, caution should be used in the application of such a classification to the dog, in which invasion and grade supply the most important prognostic information.

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.

Meccanismi evolutivi dei parapoxvirus: caratterizzazione genomica di pseudocowpoxvirus e messa a punto di sistemi per lo studio delle ricombinazioni

The Poxviruses are a family of double stranded DNA (dsDNA) viruses that cause disease in many species, both vertebrate and invertebrate. Their genomes range in size from 135 to 365 kbp and show conservation in both organization and content. In particular, the central genomic regions of the chordopoxvirus subfamily (those capable of infecting vertebrates) contain 88 genes which are present in all the virus species characterised to date and which mostly occur in the same order and orientation. In contrast, however, the terminal regions of the genomes frequently contain genes that are species or genera-specific and that are not essential for the growth of the virus in vitro but instead often encode factors with important roles in vivo including modulation of the host immune response to infection and determination of the host range of the virus. The Parapoxviruses (PPV), of which Orf virus is the prototypic species, represent a genus within the chordopoxvirus subfamily of Poxviridae and are characterised by their ability to infect ruminants and humans. The genus currently contains four recognised species of virus, bovine papular stomatitis virus (BPSV) and pseudocowpox virus (PCPV) both of which infect cattle, orf virus (OV) that infects sheep and goats, and parapoxvirus of red deer in New Zealand (PVNZ). The ORFV genome has been fully sequenced, as has that of BPSV, and is ~138 kb in length encoding ~132 genes. The vast majority of these genes allow the virus to replicate in the cytoplasm of the infected host cell and therefore encode proteins involved in replication, transcription and metabolism of nucleic acids. These genes are well conserved between all known genera of poxviruses. There is however another class of genes, located at either end of the linear dsDNA genome, that encode proteins which are non-essential for replication and generally dictate host range and virulence of the virus. The non-essential genes are often the most variable within and between species of virus and therefore are potentially useful for diagnostic purposes. Given their role in subverting the host-immune response to infection they are also targets for novel therapeutics. The function of only a relatively small number of these proteins has been elucidated and there are several genes whose function still remains obscure principally because there is little similarity between them and proteins of known function in current sequence databases. It is thought that by selectively removing some of the virulence genes, or at least neutralising the proteins in some way, current vaccines could be improved. The evolution of poxviruses has been proposed to be an adaptive process involving frequent events of gene gain and loss, such that the virus co-evolves with its specific host. Gene capture or horizontal gene transfer from the host to the virus is considered an important source of new viral genes including those likely to be involved in host range and those enabling the virus to interfere with the host immune response to infection. Given the low rate of nucleotide substitution, recombination can be seen as an essential evolutionary driving force although it is likely underestimated. Recombination in poxviruses is intimately linked to DNA replication with both viral and cellular proteins participate in this recombination-dependent replication. It has been shown, in other poxvirus genera, that recombination between isolates and perhaps even between species does occur, thereby providing another mechanism for the acquisition of new genes and for the rapid evolution of viruses. Such events may result in viruses that have a selective advantage over others, for example in re-infections (a characteristic of the PPV), or in viruses that are able to jump the species barrier and infect new hosts. Sequence data related to viral strains isolated from goats suggest that possible recombination events may have occurred between OV and PCPV (Ueda et al. 2003). The recombination events are frequent during poxvirus replication and comparative genomic analysis of several poxvirus species has revealed that recombinations occur frequently on the right terminal region. Intraspecific recombination can occur between strains of the same PPV species, but also interspecific recombination can happen depending on enough sequence similarity to enable recombination between distinct PPV species. The most important pre-requisite for a successful recombination is the coinfection of the individual host by different virus strains or species. Consequently, the following factors affecting the distribution of different viruses to shared target cells need to be considered: dose of inoculated virus, time interval between inoculation of the first and the second virus, distance between the marker mutations, genetic homology. At present there are no available data on the replication dynamics of PPV in permissive and non permissive hosts and reguarding co-infetions there are no information on the interference mechanisms occurring during the simultaneous replication of viruses of different species. This work has been carried out to set up permissive substrates allowing the replication of different PPV species, in particular keratinocytes monolayers and organotypic skin cultures. Furthermore a method to isolate and expand ovine skin stem cells was has been set up to indeep further aspects of viral cellular tropism during natural infection. The study produced important data to elucidate the replication dynamics of OV and PCPV virus in vitro as well as the mechanisms of interference that can arise during co-infection with different viral species. Moreover, the analysis carried on the genomic right terminal region of PCPV 1303/05 contributed to a better knowledge of the viral genes involved in host interaction and pathogenesis as well as to locate recombination breakpoints and genetic homologies between PPV species. Taken together these data filled several crucial gaps for the study of interspecific recombinations of PPVs which are thought to be important for a better understanding of the viral evolution and to improve the biosafety of antiviral therapy and PPV-based vectors.