A mixture model with random-effects components for classifying sibling pairs.

In healthy aging research, typically multiple health outcomes are measured, representing health status. The aim of this paper was to develop a model-based clustering approach to identify homogeneous sibling pairs according to their health status. Model-based clustering approaches will be considered on the basis of linear mixed effect model for the mixture components. Class memberships of siblings within pairs are allowed to be correlated, and within a class the correlation between siblings is modeled using random sibling pair effects. We propose an expectation-maximization algorithm for maximum likelihood estimation. Model performance is evaluated via simulations in terms of estimating the correct parameters, degree of agreement, and the ability to detect the correct number of clusters. The performance of our model is compared with the performance of standard model-based clustering approaches. The methods are used to classify sibling pairs from the Leiden Longevity Study according to their health status. Our results suggest that homogeneous healthy sibling pairs are associated with a longer life span. Software is available for fitting the new models.

Novel P53 mutations detected by FAMA in colorectal cancers.

BACKGROUND: The aim of the study was to identify p53 gene mutations by FAMA (fluorescence-assisted mismatch analysis) in colorectal cancers. PATIENTS AND METHODS: Analytical scanning of the p53 gene (exons 5-9) was performed in colon cancer samples from 44 consecutive patients by FAMA. FAMA is a semiautomatic scanning approach based on the chemical cleavage of the mismatch in fluorescently labeled heteroduplex DNA, obtained from the combination of a normal and a mutated allele. FAMA has already shown optimal levels of diagnostic accuracy and sensitivity in detecting gene mutations (nucleotide substitutions, insertions/deletions) both at the germline and somatic level. The peculiar feature of FAMA is its ability to detect and localize mutations, by a redundant pattern of signals due to fluorescent DNA fragments generated by chemical cleavage. Moreover, previous data have demonstrated that normal contaminating DNA from stromal cells in the sample does not affect the sensitivity of the procedure, leading to the identification of the mutation even when the ratio mutant/normal allele is 10%. RESULTS: Eighteen mutations (12 missense, one nonsense, two deletions, three nucleotide substitutions at the level of the splice-junctions) and two polymorphisms were detected by FAMA in 17 patients (39%) and then confirmed by automated sequence analysis. Six of 18 mutations (33%) were not previously reported for colon cancer samples and two of 18 lesions (11%) were identified as novel p53 mutations. CONCLUSIONS: Analytical scanning of the p53 gene by FAMA in DNA from colon cancer samples provides a sensitive, accurate and specific diagnostic procedure for routine clinical application.

[Can analysis of the molecular status of the p53 gene contribute to improving the therapeutic strategy for breast carcinoma?]. / L'analisi dello stato molecolare del gene p53 può contribuire ad innovare le strategie terapeutiche nel carcinoma della mammella?

The occurrence of mutations in the p53 tumor suppressor gene is a specific and recurring genetic event in solid tumors. P53 plays a pivotal role in multiple cellular processes such as cell growth control, DNA repair and programmed cell death. Genotoxic damage, also induced by chemotherapy or radiotherapy, induces p53 overexpression in order to control the rate of proliferating damaged cells, thus triggering the mismatch repair or apoptotic pathways. P53 inactivation determines a condition of genetic instability, justifying the subsequent susceptibility to acquire mutations of different other genes. P53 mutations are associated with worse prognosis and with chemo/radioresistance, due to the inability to trigger p53-dependent programmed cell death. Molecular diagnostic strategies show 32% p53 mutations in breast cancer. The analysis of the p53 gene performed by FAMA (Fluorescence Assisted Mismatch Analysis) in high-risk breast cancer patients with > or = 10 involved axillary nodes may help identify a subset of very high risk BC patients (vHR-BC) with poorer prognosis and a subset with better prognosis, potentially responsive to medical treatments. The accurate evaluation of the p53 status can predict prognosis and sensitivity to chemotherapy, thus representing the first step toward better definition of therapeutic strategies according to the molecular characterization of the individual patient.

[A case of watermelon stomach]. / Su un caso di "Watermelon Stomach".

The authors describe a case of antral Watermelon Stomach (WS) in a seventy-eight year old woman with severe iron-deficient chronic anemia, liver cirrhosis and diabetes mellitus. Endoscopy was diagnostic on the 3rd-4th examination because of the disease's rarity and the concomitance of systemic pathologies, such as portal hypertension, in which often a congestive gastropathy with similar aspects is associated. Whether out of clinical evolution, or capillary thrombosis, or vertical fibromuscular hyperplasia of the lamina propria were considered distinctive elements. By means of literature review it wasn't possible to establish the portal hypertension's prevalence out of the WS cases, but it could be a chance factor. In this way some polycentric prospective trials could be useful. The endoscopic practice is important not only for diagnosis but also for therapeutical means, even if in our case surgery was the chosen treatment.

Model-based approaches to synthesize microarray data: a unifying review using mixture of SEMs.

Several statistical methods are nowadays available for the analysis of gene expression data recorded through microarray technology. In this article, we take a closer look at several Gaussian mixture models which have recently been proposed to model gene expression data. It can be shown that these are special cases of a more general model, called the mixture of structural equation models (mixture of SEMs), which has been developed in psychometrics. This model combines mixture modelling and SEMs by assuming that component-specific means and variances are subject to a SEM. The connection with SEM is useful for at least two reasons: (1) it shows the basic assumptions of existing methods more explicitly and (2) it helps in straightforward development of alternative mixture models for gene expression data with alternative mean/covariance structures. Different specifications of mixture of SEMs for clustering gene expression data are illustrated using two benchmark datasets.

Triplet schedule of weekly 5-fluorouracil and alternating irinotecan or oxaliplatin in advanced colorectal cancer: a dose-finding and phase II study.

A weekly administration of alternating irinotecan or oxaliplatin associated to 5-Fluorouracil in advanced colorectal cancer was planned in order to evaluate a new schedule maintaining dose intensities of each drug as in double combinations and tolerability of the triplet association. The following weekly schedule was administered: irinotecan, days 1 and 15; oxaliplatin, days 8 and 22; 5-fluorouracil (5-FU) over 12-h (from 10:00 p.m. to 10:00 a.m.) timed flat infusion, days 1-2, 8-9, 15-16 and 22-23, every 4 weeks. Dose- finding and phase II study were planned. Thirteen patients were enrolled in the dose-finding study and 23 in the phase II study. The recommended doses of our study are: irinotecan 160 mg/m(2); oxaliplatin 80 mg/m(2); 5-FU 900 mg/m(2). The dose-limiting toxicity was diarrhea (35% of patients) but no cases of febrile neutropenia were observed. In 30 patients assessable for response two complete (6.7%) and 18 partial (60%) responses were observed, for an overall response rate of 66.7% (alpha 0.05, CI+/-17). The triplet association using this weekly alternating schedule is an active and well-tolerated outpatient regimen. Surgical removal of residual disease was considered in 5 patients and a radical resection was performed in 5 patients (147 %).

An ultrastructural study of six cases of chronic active C hepatitis. A comparison with chronic active B hepatitis.

Liver biopsies from six patients affected by chronic active hepatitis (CAH) induced by hepatitis C virus (HCV) have been investigated ultrastructurally and their features compared with those of five cases of CAH induced by hepatitis B virus (HBV). Clusters of deeply packed nuclear inclusions (18 to 22 nm in diameter) were found in patients with HCV-CAH. They were irregularly round and ill-delimited. These inclusions were distinct from the regular round and well-delimited nuclear inclusions associated with HBV. HCV-associated nuclear inclusions were similar to a peculiar type of intranuclear particle described in non-A, non-B hepatitis before the HCV disease had been recognized as a distinct entity. These inclusions have never been hitherto reported in infections caused by HBV or other known hepatotropic viruses. Together, these data suggest that the occurrence of these inclusions can be related to HCV activity in hepatocytes. Changes in the microarchitecture of the liver cell and its microenvironment were similar in HCV- and HBV-CAH. They were heterogeneous in different cases and did not display a clear correlation with the severity of the disease.