Biomedical subjects

Chiara Romualdi

Publications and source records attributed to Chiara Romualdi.

At least 19 recordsLinked to original sources

PubMed2006

Defining the gene expression signature of rhabdomyosarcoma by meta-analysis.

BACKGROUND: Rhabdomyosarcoma is a highly malignant soft tissue sarcoma in childhood and arises as a consequence of regulatory disruption of the growth and differentiation pathways of myogenic precursor cells. The pathogenic pathways involved in this tumor are mostly unknown and therefore a better characterization of RMS gene expression profile would represent a considerable advance. The availability of publicly available gene expression datasets have opened up new challenges especially for the integration of data generated by different research groups and different array platforms with the purpose of obtaining new insights on the biological process investigated. RESULTS: In this work we performed a meta-analysis on four microarray and two SAGE datasets of gene expression data on RMS in order to evaluate the degree of agreement of the biological results obtained by these different studies and to identify common regulatory pathways that could be responsible of tumor growth. Regulatory pathways and biological processes significantly enriched has been investigated and a list of differentially meta-profiles have been identified as possible candidate of aggressiveness of RMS. CONCLUSION: Our results point to a general down regulation of the energy production pathways, suggesting a hypoxic physiology for RMS cells. This result agrees with the high malignancy of RMS and with its resistance to most of the therapeutic treatments. In this context, different isoforms of the ANT gene have been consistently identified for the first time as differentially expressed in RMS. This gene is involved in anti-apoptotic processes when cells grow in low oxygen conditions. These new insights in the biological processes responsible of RMS growth and development demonstrate the effective advantage of the use of integrated analysis of gene expression studies.

Apoptosis↗

PubMed2006

Differential gene expression profiling in genetic and multifactorial cardiovascular diseases.

Gene expression profiling by microarray technologies has been successfully applied to study the transcriptional changes that occur in tissues such as heart, vessels and blood cells in different cardiovascular disorders. Such studies have been performed in human cardiovascular syndromes and in animal models with the aim of unraveling the complex molecular pictures underlying human pathophysiology. As already observed in cancer research, gene expression studies in humans may provide a finer molecular classification of patients with cardiovascular diseases and indicate new markers useful for prognostic and therapeutic strategies. In this paper, we present the findings obtained with microarray platforms to explore transcriptome alterations in cardiovascular diseases. To describe the potential of global expression profiling approach in this field, we have chosen to review the genomic findings obtained in some classic heart diseases with genetic transmission such as hyperthrophic cardiomyopathy and Fabry disease, together with findings obtained in common multifactorial cardiovascular disorders such as heart failure, atherosclerosis and infarction. Wherever feasible, we present the results obtained in patients together with those obtained in the corresponding animal and cellular models.

Animals↗

PubMed2006

Development of mussel mRNA profiling: Can gene expression trends reveal coastal water pollution?

Marine bivalves of the genus Mytilus are intertidal filter-feeders commonly used as biosensors of coastal pollution. Mussels adjust their functions to ordinary environmental changes, e.g. temperature fluctuations and emersion-related hypoxia, and react to various contaminants, accumulated from the surrounding water and defining a potential health risk for sea-food consumers. Despite the increasing use of mussels in environmental monitoring, their genome and gene functions are largely unexplored. Hence, we started the systematic identification of expressed sequence tags and prepared a cDNA microarray of Mytilus galloprovincialis including 1714 mussel probes (76% singletons, approximately 50% putatively identified transcripts) plus unrelated controls. To assess the potential use of the gene set represented in MytArray 1.0, we tested different tissues and groups of mussels. The resulting data highlighted the transcriptional specificity of the mussel tissues. Further testing of the most responsive digestive gland allowed correct classification of mussels treated with mixtures of heavy metals or organic contaminants (expression changes of specific genes discriminated the two pollutant cocktails). Similar analyses made a distinction possible between mussels living in the Venice lagoon (Italy) at the petrochemical district and mussels close to the open sea. The suggestive presence of gene markers tracing organic contaminants more than heavy metals in mussels from the industrial district is consistent with reported trends of chemical contamination. Further study is necessary in order to understand how much gene expression profiles can disclose the signatures of pollutants in mussel cells and tissues. Nevertheless, the gene expression patterns described in this paper support a wider characterization of the mussel transcriptome and point to the development of novel environmental metrics.

Animals↗

PubMed2006

Expression profiling characterization of laminin alpha-2 positive MDC.

In the Caucasian population, patients affected by the most frequent forms of congenital muscular dystrophies (MDC) are commonly divided into two groups. The first is characterized by mutations of the gene for the laminin alpha-2 (LAMA2). The second is positive for this protein, highly heterogeneous, and has no specific genetic defect associated yet. We studied the skeletal muscle transcriptome of four LAMA2 deficient and six LAMA2 positive MDC patients by cDNA microarrays. The expression profiling defined two patients groups: one mild and one severe phenotype. This result was in agreement with histopathological features but only partially with the clinical classification. The mild phenotype is characterized by a delayed maturation from slow to fast muscle fibers. Other muscle transcripts, such as telethonin, myosin light-chains 3 and 1V, are underexpressed in this group. We suggest that expression profiling will provide important information to improve our understanding of the molecular basis of laminin alpha-2 positive MDC.

Creatine Kinase↗

PubMed2006

Gene expression profiling identifies potential relevant genes in alveolar rhabdomyosarcoma pathogenesis and discriminates PAX3-FKHR positive and negative tumors.

We analyzed the expression signatures of 14 tumor biopsies from children affected by alveolar rhabdomyosarcoma (ARMS) to identify genes correlating to biological features of this tumor. Seven of these patients were positive for the PAX3-FKHR fusion gene and 7 were negative. We used a cDNA platform containing a large majority of probes derived from muscle tissues. The comparison of transcription profiles of tumor samples with fetal skeletal muscle identified 171 differentially expressed genes common to all ARMS patients. The functional classification analysis of altered genes led to the identification of a group of transcripts (LGALS1, BIN1) that may be relevant for the tumorigenic processes. The muscle-specific microarray platform was able to distinguish PAX3-FKHR positive and negative ARMS through the expression pattern of a limited number of genes (RAC1, CFL1, CCND1, IGFBP2) that might be biologically relevant for the different clinical behavior and aggressiveness of the 2 ARMS subtypes. Expression levels for selected candidate genes were validated by quantitative real-time reverse-transcription PCR.

Adolescent↗

PubMed2006

Parallel protein and transcript profiles of FSHD patient muscles correlate to the D4Z4 arrangement and reveal a common impairment of slow to fast fibre differentiation and a general deregulation of MyoD-dependent genes.

Here, we present the first study of a human neuromuscular disorder at transcriptional and proteomic level. Autosomal dominant facio-scapulo-humeral muscular dystrophy (FSHD) is caused by a deletion of an integral number of 3.3-kb KpnI repeats inside the telomeric region D4Z4 at the 4q35 locus. We combined a muscle-specific cDNA microarray platform with a proteomic investigation to analyse muscle biopsies of patients carrying a variable number of KpnI repeats. Unsupervised cluster analysis divides patients into three classes, according to their KpnI repeat number. Expression data reveal a transition from fast-glycolytic to slow-oxidative phenotype in FSHD muscle, which is accompanied by a deficit of proteins involved in response to oxidative stress. Besides, FSHD individuals show a disruption in the MyoD-dependent gene network suggesting a coregulation at transcriptional level during myogenesis. We also discuss the hypothesis that D4Z4 contraction may affect in trans the expression of a set of genes involved in myogenesis, as well as in the regeneration pathway of satellite cells in adult tissue. Muscular wasting could result from the inability of satellite cells to successfully differentiate into mature fibres and from the accumulation of structural damages caused by a reactive oxygen species (ROS) imbalance induced by an increased oxidative metabolism in fibres.

Adolescent↗

PubMed2006

Longitudinal analysis of immune cell phenotypes in early stage multiple sclerosis: distinctive patterns characterize MRI-active patients.

To investigate whether peripheral immune abnormalities are associated with brain inflammation in multiple sclerosis, and whether differences in MRI activity are paralleled by changes in leukocyte composition, we conducted a prospective longitudinal study in patients at their clinical onset. Twenty patients presenting a first inflammatory event in the central nervous system suggestive of multiple sclerosis underwent, every 45 days for one year, immunophenotyping of 98 blood cell subsets together with brain MRI and clinical evaluation. Six patients showed intense MRI activity, six patients did not display MRI activity, while the remaining 8 patients had low (i.e. intermediate) MRI activity during the follow-up. Our results show that MRI-active and MRI-inactive patients display significant differences in ten lymphocyte subsets. Among these, there are both effector (CCR7-CD45RA-CD4+ alphabeta T cells, CCR5+ gammadelta T cells) and regulatory (DN CD28+ alphabeta T cells and CD25+CD8+ alphabeta T cells) lymphocytes pertaining to the innate and the acquired arms of the immune system. Moreover, these differences were, upon employment of a class prediction procedure based on "support vector machines" algorithm utilizing leave-one-out cross validation procedures, able to correctly assign patients to their respective MRI activity group. All 6 MRI-active and 6 MRI-inactive patients were correctly classified, and, upon application of a class prediction model in an unsupervised manner to the 8 patients with intermediate MRI activity, 6 were predicted as MRI-active and 2 as MRI-inactive patients. Also, when the mean values of the first three time points (T0, T1 and T2) were used for the prediction of all patients, the selected lymphocyte subsets correctly classified 90% of patients. Sensitivity was 91.7% and specificity was 87.5%. These results provide evidence showing that brain inflammation in multiple sclerosis is associated with distinct changes in peripheral lymphocyte subsets, and raise the possibility that the identified subsets may, after adequate validation, assist in the prediction of MRI activity in the early stages of multiple sclerosis.

Adult↗

PubMed2005

Denervation in murine fast-twitch muscle: short-term physiological changes and temporal expression profiling.

Denervation deeply affects muscle structure and function, the alterations being different in slow and fast muscles. Because the effects of denervation on fast muscles are still controversial, and high-throughput studies on gene expression in denervated muscles are lacking, we studied gene expression during atrophy progression following denervation in mouse tibialis anterior (TA). The sciatic nerve was cut close to trochanter in adult CD1 mice. One, three, seven, and fourteen days after denervation, animals were killed and TA muscles were dissected out and utilized for physiological experiments and gene expression studies. Target cDNAs from TA muscles were hybridized on a dedicated cDNA microarray of muscle genes. Seventy-one genes were found differentially expressed. Microarray results were validated, and the expression of relevant genes not probed on our array was monitored by real-time quantitative PCR (RQ-PCR). Nuclear- and mitochondrial-encoded genes implicated in energy metabolism were consistently downregulated. Among genes implicated in muscle contraction (myofibrillar and sarcoplasmic reticulum), genes typical of fast fibers were downregulated, whereas those typical of slow fibers were upregulated. Electrophoresis and Western blot showed less pronounced changes in myofibrillar protein expression, partially confirming changes in gene expression. Isometric tension of skinned fibers was little affected by denervation, whereas calcium sensitivity decreased. Functional studies in mouse extensor digitorum longus muscle showed prolongation in twitch time parameters and shift to the left in force-frequency curves after denervation. We conclude that, if studied at the mRNA level, fast muscles appear not less responsive than slow muscles to the interruption of neural stimulation.

Animals↗

PubMed2005

MIDAW: a web tool for statistical analysis of microarray data.

MIDAW (microarray data analysis web tool) is a web interface integrating a series of statistical algorithms that can be used for processing and interpretation of microarray data. MIDAW consists of two main sections: data normalization and data analysis. In the normalization phase the simultaneous processing of several experiments with background correction, global and local mean and variance normalization are carried out. The data analysis section allows graphical display of expression data for descriptive purposes, estimation of missing values, reduction of data dimension, discriminant analysis and identification of marker genes. The statistical results are organized in dynamic web pages and tables, where the transcript/gene probes contained in a specific microarray platform can be linked (according to user choice) to external databases (GenBank, Entrez Gene, UniGene). Tutorial files help the user throughout the statistical analysis to ensure that the forms are filled out correctly. MIDAW has been developed using Perl and PHP and it uses R/Bioconductor languages and routines. MIDAW is GPL licensed and freely accessible at http://muscle.cribi.unipd.it/midaw/. Perl and PHP source codes are available from the authors upon request.

Algorithms↗

PubMed2005

Novel genes, possibly relevant for molecular diagnosis or therapy of human rhabdomyosarcoma, detected by genomic expression profiling.

Transcriptional profiles of an alveolar rhabdomyosarcoma (RMS) and of a RMS cell line were reconstructed by a computational and statistical approach. Expression data of 29,963 genes in 11 adult human healthy tissues and in 37 tumour tissues were analysed for comparison. We identified 202 genes differentially expressed in at least one RMS sample, as compared with normal skeletal muscle. Among them, 107 resulted specifically overexpressed in RMS, but in no tumour affecting other tissues. Cluster analysis applied to expression data detected a series of genes presumably co-expressed with genes encoding known tumour markers and/or reportedly involved in genesis or development of rhabdomyosarcoma. This study succeeded in identifying a number of genes, which become candidates for in vitro study, thus facilitating discovery of novel tumour markers or targets for drug therapy.

Adult↗

PubMed2005

A leukemia-enriched cDNA microarray platform identifies new transcripts with relevance to the biology of pediatric acute lymphoblastic leukemia.

BACKGROUND AND OBJECTIVES: Microarray gene expression profiling has been widely applied to characterize hematologic malignancies, has attributed a molecular signature to leukemia subclasses and has allowed new subclasses to be distinguished. We set out to use microarray technology to identify novel genes relevant for leukemogenesis. To this end we used a unique leukemia-enriched cDNA microarray platform. DESIGN AND METHODS: The systematic sequencing of cDNA libraries of normal and leukemic bone marrow allowed us to increase the number of genes to yield a new release of a previously generated cDNA microarray. Using this platform we analyzed the expression profiles of 4,670 genes in bone marrow samples from 18 pediatric patients with acute lymphoblastic leukemia (ALL). RESULTS: Expression profiling consistently distinguished the leukemia patients into three groups, those with T-ALL, B-ALL and B-ALL with MLL/AF4 rearrangement, in agreement with the clinical classification. Our platform identified 30 genes that best discriminate these three subtypes. Using mini-array technology these 30 genes were validated in another cohort of 17 patients. In particular we identified two novel genes not previously reported: endomucin (EMCN) and ubiquitin specific protease 33 (USP33) that appear to be over-expressed in B-ALL relative to their expression in T-ALL. INTERPRETATION AND CONCLUSIONS: Microarray technology not only allows the distinction between disease subclasses but also offers a chance to identify new genes involved in leukemogenesis. Our approach of using a unique platform has proven to be fruitful in identifying new genes and we suggest exploration of other malignancies using this approach.

Adolescent↗

PubMed2004

RAP: a new computer program for de novo identification of repeated sequences in whole genomes.

MOTIVATION: DNA repeats are a common feature of most genomic sequences. Their de novo identification is still difficult despite being a crucial step in genomic analysis and oligonucleotides design. Several efficient algorithms based on word counting are available, but too short words decrease specificity while long words decrease sensitivity, particularly in degenerated repeats. RESULTS: The Repeat Analysis Program (RAP) is based on a new word-counting algorithm optimized for high resolution repeat identification using gapped words. Many different overlapping gapped words can be counted at the same genomic position, thus producing a better signal than the single ungapped word. This results in better specificity both in terms of low-frequency detection, being able to identify sequences repeated only once, and highly divergent detection, producing a generally high score in most intron sequences. AVAILABILITY: The program is freely available for non-profit organizations, upon request to the authors. CONTACT: giorgio.valle@unipd.it SUPPLEMENTARY INFORMATION: The program has been tested on the Caenorhabditis elegans genome using word lengths of 12, 14 and 16 bases. The full analysis has been implemented in the UCSC Genome Browser and is accessible at http://genome.cribi.unipd.it.

Algorithms↗

PubMed2003

Improved detection of differentially expressed genes in microarray experiments through multiple scanning and image integration.

The variability of results in microarray technology is in part due to the fact that independent scans of a single hybridised microarray give spot images that are not quite the same. To solve this problem and turn it to our advantage, we introduced the approach of multiple scanning and of image integration of microarrays. To this end, we have developed specific software that creates a virtual image that statistically summarises a series of consecutive scans of a microarray. We provide evidence that the use of multiple imaging (i) enhances the detection of differentially expressed genes; (ii) increases the image homogeneity; and (iii) reveals false-positive results such as differentially expressed genes that are detected by a single scan but not confirmed by successive scanning replicates. The increase in the final number of differentially expressed genes detected in a microarray experiment with this approach is remarkable; 50% more for microarrays hybridised with targets labelled by reverse transcriptase, and 200% more for microarrays developed with the tyramide signal amplification (TSA) technique. The results have been confirmed by semi-quantitative RT-PCR tests.

False Negative Reactions↗

PubMed2003

Pattern recognition in gene expression profiling using DNA array: a comparative study of different statistical methods applied to cancer classification.

Large-scale parallel measurements of the expression of many thousands genes are now available with high-density array made with collections of cDNA fragments, or oligonucleotide corresponding to different transcripts. These technologies have been applied to cancer investigations since the availability of such a large number of markers makes DNA array a powerful diagnostic tool for tumour and patient classification. Over the last two years, a series of computational tools have been developed for the analysis of different aspects of gene profiling. Our work tries to compare a series of supervised statistical techniques on the basis of their ability to correctly classify different types of tumours. A simulation approach was initially used to control the huge source of variation among and between patients, and to evaluate the ability of algorithms to classify tumours in relation to different types of experimental variables. Different techniques for reduction of data dimension were then added to the discriminant analysis and compared according to their ability to capture the main genetic information. The simulation results have been tested by applying the selected classification algorithms to two experimental microarray datasets of human cancers, and by measuring the correspondent rates of misclassification. Our analyses identify in these datasets a series of genes principally involved in tumour characterization. The functional role of these discriminant transcripts is discussed.

Algorithms↗

PubMed2003

TRAIT (TRAnscript Integrated Table): a knowledgebase of human skeletal muscle transcripts.

TRAIT is a knowledgebase integrating information on transcripts with related data from genome, proteins, ortholog genes and diseases. It was initially built as a system to manage an EST-based gene discovery project on human skeletal muscle, which yielded over 4500 independent sequence clusters. Transcripts are annotated using automatic as well as manual procedures, linking known transcripts to public databases and unknown transcripts to tables of predicted features. Data are stored in a MySQL database. Complex queries are automatically built by means of a user-friendly web interface that allows the concurrent selection of many fields such as ontology, expression level, map position and protein domains. The results are parsed by the system and returned in a ranked order, in respect to the number of satisfied criteria.

Database Management Systems↗

PubMed2003

IDEG6: a web tool for detection of differentially expressed genes in multiple tag sampling experiments.

Here we present a novel web tool for the statistical analysis of gene expression data in multiple tag sampling experiments. Differentially expressed genes are detected by using six different test statistics. Result tables, linked to the GenBank, UniGene, or LocusLink database, can be browsed or searched in different ways. Software is freely available at the site: http://telethon.bio.unipd.it/bioinfo/IDEG6_form/, together with additional information on statistical methodologies.

Database Management Systems↗

PubMed2002

Gene expression profiling in dysferlinopathies using a dedicated muscle microarray.

We have performed expression profiling to define the molecular changes in dysferlinopathy using a novel dedicated microarray platform made with 3'-end skeletal muscle cDNAs. Eight dysferlinopathy patients, defined by western blot, immunohistochemistry and mutation analysis, were investigated with this technology. In a first experiment RNAs from different limb-girdle muscular dystrophy type 2B patients were pooled and compared with normal muscle RNA to characterize the general transcription pattern of this muscular disorder. Then the expression profiles of patients with different clinical traits were independently obtained and hierarchical clustering was applied to discover patient-specific gene variations. MHC class I genes and genes involved in protein biosynthesis were up-regulated in relation to muscle histopathological features. Conversely, the expression of genes codifying the sarcomeric proteins titin, nebulin and telethonin was down-regulated. Neither calpain-3 nor caveolin, a sarcolemmal protein interacting with dysferlin, was consistently reduced. There was a major up-regulation of proteins interacting with calcium, namely S100 calcium-binding proteins and sarcolipin, a sarcoplasmic calcium regulator.

Adolescent↗

PubMed2002

Simplifying amino acid alphabets by means of a branch and bound algorithm and substitution matrices.

MOTIVATION: Protein and DNA are generally represented by sequences of letters. In a number of circumstances simplified alphabets (where one or more letters would be represented by the same symbol) have proved their potential utility in several fields of bioinformatics including searching for patterns occurring at an unexpected rate, studying protein folding and finding consensus sequences in multiple alignments. The main issue addressed in this paper is the possibility of finding a general approach that would allow an exhaustive analysis of all the possible simplified alphabets, using substitution matrices like PAM and BLOSUM as a measure for scoring. RESULTS: The computational approach presented in this paper has led to a computer program called AlphaSimp (Alphabet Simplifier) that can perform an exhaustive analysis of the possible simplified amino acid alphabets, using a branch and bound algorithm together with standard or user-defined substitution matrices. The program returns a ranked list of the highest-scoring simplified alphabets. When the extent of the simplification is limited and the simplified alphabets are maintained above ten symbols the program is able to complete the analysis in minutes or even seconds on a personal computer. However, the performance becomes worse, taking up to several hours, for highly simplified alphabets. AVAILABILITY: AlphaSimp and other accessory programs are available at http://bioinformatics.cribi.unipd.it/alphasimp

Algorithms↗