Muscle plasticity and high throughput gene expression studies

Changes in gene expression are known to contribute to muscle plasticity. Until recently most studies have described differences of one or few genes at a time, in the last few years, however, the development of new technology of high throughput mRNA expression analysis has allowed the study of a large part if not all transcripts in the same experiment. Knowledge on any muscle adaptive response has already gained from the application of this novel approach, but the most important new findings have come from studies on muscle atrophy. A new and unexpected groups of genes, which increase their expression during atrophy, designated as atrogins, have been discovered. In spite of the impressive power of the new technology many problems are still to be resolved to optimize the experimental design and to extract all information which are provided by the outcome of the global mRNA assessment

MICROARRAYS AND 2-D GELS: NEW TOOLS FOR POST-GENOMIC MUSCLE BIOLOGY

The complete genome sequencing has opened the way to the investigation of the transcriptional activity of thousands of genes (i.e the transcriptome) through DNA microarrays. In parallel to these technological developments high-resolution twodimensional gels combined with sensitive mass spectrometry and other new methods provide the possibility of studying all proteins present in cells (i.e. the proteome). Both transcriptome and proteome investigations are characterized by an unprecedented resolution power (high throughput) and by their totally descriptive character, so that a physiological condition or a specific tissue is explored without any preliminary hypothesis to be tested; on the other hand, the results of the high throughput studies are very often the starting point for the generation of new hypothesis to be validated in subsequent experiments. This paper aims to briefly review the most recent technological developments and their application to muscle physiology and pathology

EXPANDING THE KNOWLEDGE OF BLOOD TRANSCRIPTOME: CIRCULAR RNAS IN HEMATOPOIESIS

open3openA Bonizzato, E Gaffo, G te Kronnie, S BortoluzziBonizzato, A; Gaffo, E; TE KRONNIE, Geertruij; Bortoluzzi,

Non-medical applications of non-invasive prenatal diagnosis: Ethical issues.

Non-invasive prenatal diagnosis (NIPD) is becoming increasingly important and its application in prenatal diagnosis is reaching consensus in the scientific research community. We discuss the opportunities and ethics of non-invasive prenatal testing for non-medical purposes, including forensic genetics. A number of ethical issues arise from non-medical applications of NIPD, such as sex determination and paternity testing in earlier gestational age and subsequent offspring selection. NIPD provides a source of information about the genetic make-up of the foetus, avoiding the small but significant risk of pregnancy loss related to invasive testing such as amniocentesis or chorionic villi sampling. NIPD is characterized by: safety, early detection and easy sampling. These features of NIPD increase the opportunity of prenatal testing also for non-medical reasons. Even if NIPD can be qualified as a good practice prenatal diagnosis tout court remains a topic of ethical judgements. The non-medical use of NIPD will benefit from an informed and open debate involving both pregnant women and physicians

Validation of NG2 antigen in identifying BP-ALL patients with MLL rearrangements using qualitative and quantitative flow cytometry: a prospective study

Timely diagnosis of mixed lineage leukemia (MLL) rearrangements in pediatric patients with B-cell precursor acute lymphoblastic leukemia (BP-ALL) is highly relevant in patient stratification. The presence of t(4;11)-MLL rearrangement is the most important criteria for high-risk stratification in protocols for childhood precursor BP-ALL. Current tests to identify t(4;11)-MLL involve karyotyping, fluorescence in situ hybridization and reverse transcription-PCR. The tests, however, are expensive both in terms of personnel and reagents. They do not provide a fast diagnosis and may fail due to technical reasons or high variability in the breakpoint that does not allow for standard reverse transcription-PCR detection. Therefore, a fast and reliable test that identifies MLL rearranged BP-ALL is highly welcome, particularly in low-income countries

Computational analysis of flow cytometry antigen expression profiles in childhood acute lymphoblastic leukemia: a MLL/AF4 identification

Precursor B-acute lymphoblastic leukemia (pB-ALL) is a heterogeneous disease and multiparameter flow cytometry, molecular genetics, and cytogenetic studies have all contributed to classification of subgroups with prognostic significance. Recently, gene expression microarray technology has been used to investigate lymphoblastic leukemias, demonstrating that known and novel pB-ALL subclasses can be separated on the basis of gene expression profiles. The strength of microarray technique lays in part in the multivariate nature of the expression data. We propose a parallel multiparametric approach based on immunophenotypic flow-cytometry expression data for the analysis of leukemia patients. Specifically, we tested the potential of this approach on a data set of 145 samples of pediatric pB-ALL that included 46 samples positive for mixed lineage leukemia (MLL) translocations (MLL+) and 99 control pB-ALLs, negative for this translocation (MLL-). The expression levels of 16 marker proteins have been monitored by four-color flow cytometry using a standardized diagnostic panel of antibodies. The protein expression database has been then analyzed using those univariate and multivariate computational techniques normally applied to mine and model large microarray data sets. Marker protein expression profiling not only allowed separating pB-ALL cases with an MLL rearrangement from other ALLs, but also demonstrates that MLL+ leukemias constitute a heterogeneous group in which MLL/AF4 leukemias represent a homogenous subclass described by a specific expression fingerprin

Two independent gene signatures in pediatric t(4;11) acute lymphoblastic leukemia patients

Gene expression profiles become increasingly more important for diagnostic procedures, allowing clinical predictions including treatment response and outcome. However, the establishment of specific and robust gene signatures from microarray data sets requires the analysis of large numbers of patients and the application of complex biostatistical algorithms. Especially in case of rare diseases and due to these constrains, diagnostic centers with limited access to patients or bioinformatic resources are excluded from implementing these new technologies. Method: In our study we sought to overcome these limitations and for proof of principle, we analyzed the rare t(4;11) leukemia disease entity. First, gene expression data of each t(4;11) leukemia patient were normalized by pairwise subtraction against normal bone marrow (n = 3) to identify significantly deregulated gene sets for each patient. Result: A 'core signature' of 186 commonly deregulated genes present in each investigated t(4;11) leukemia patient was defined. Linking the obtained gene sets to four biological discriminators (HOXA gene expression, age at diagnosis, fusion gene transcripts and chromosomal breakpoints) divided patients into two distinct subgroups: the first one comprised infant patients with low HOXA genes expression and the MLL breakpoints within introns 11/12. The second one comprised non-infant patients with high HOXA expression and MLL breakpoints within introns 9/10. Conclusion: A yet homogeneous leukemia entity was further subdivided, based on distinct genetic properties. This approach provided a simplified way to obtain robust and disease-specific gene signatures even in smaller cohort