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[Molecular genetic diagnosis and deletion analysis in Type I-III spinal muscular atrophy].

Autosomal recessive spinal muscular atrophy (SMA) is, after cystic fibrosis, the second most common fatal monogenic disorder. The disease is characterized by degeneration of anterior horn cells leading to progressive paralysis with muscular atrophy. Depending on the clinical type (Werdnig-Hoffmann = type I, intermediate form = type II, Kugelberg-Welander = type III), SMA causes early death or increasing disability in childhood. The SMA-critical region on the long arm of chromosome 5q13.1 contains many duplicated genes and polymorphisms. Recently, two presumptive SMA genes (survival motoneuron gene = SMN, and neuronal apoptosis inhibitory protein = NAIP) have been identified. Deletions involving critical regions of these genes are very often associated with SMA, and the extent of the deletions seems to correlate in part with disease severity. We have evaluated the diagnostic and prognostic value of molecular analysis in a large number of SMA patients. 57 patients and 78 healthy relatives were molecularly screened for deletions in the SMA critical region. We demonstrated homozygous deletions removing the SMN genes in over 90% of patients, whereas nearly 45% of patients exhibited NAIP gene deletions. Large deletions involving both genes on each chromosome are generally found in patients with severe SMA (Werdnig-Hoffman cases), while mildly affected Kugelberg-Welander cases frequently show only deleted SMN genes. Molecular classification based on combined deletion sizes, however, seems not to be exact, especially for the group with chronic SMA (type II and III). Direct DNA testing of patients in whom SMA is suspected is a highly reliable, fast, and noninvasive method. The ability to detect homozygous gene deletions in a high percentage of typical SMA patients will much improve genetic counselling and prenatal diagnosis in affected families.

Adult↗

[Molecular factors determine primary and secondary therapy of breast carcinoma].

The clinical oncology realizes that the classical approach with systemic adjuvant chemo- and hormonal therapies is not sufficient and will be challenged by cellular and molecular structures which reflect the targets for new therapeutic approaches. These targets are key proteins involved in the signal transduction cascade. In human tumors these proteins have either lost their biological functionality by oncogenic mutations or are constitutively activated. The molecular classification of primary breast cancer was performed by assessing the following factors: estrogen- and progesterone receptors, ERbB-2 mutated p53, uPA, PAI-I, VEGF, DNA-Index and S-Phase. These factors are of prognostic and predictive value.

Antineoplastic Agents, Hormonal↗

[Usefulness of molecular screening in childhood lymphoblastic leukemias].

PURPOSE: To demonstrate that a molecular screening by reverse transcriptase polymerase chain reaction (RT-PCR) of TEL/AML1, E2A/PBX1 and BCR/ABL genes in pediatric acute lymphoblastic leukaemia is a rapid method that allows one to exceed the percentage of adult patients with the BCR/ABL rearrangement. PATIENTS AND METHODS: 12 Spanish children with acute lymphoblastic leukaemia were studied, 11 of them newly diagnosed and 1 relapsed. The patients were between 18 months and 10 years old. Bone marrow aspiration was collected between april and december 1996, RNA was isolated and cDNA was subjected to PCR amplification for TEL/AML1, E2A/PBX1 and BCR/ABL genes. Normal ABL and E2A genes were studied as amplification controls. RESULTS: One of these hybrid genes was found in 33.3% of patients studied. TEL/AML1 in two cases (16.6%), E2A/PBX1 in one case (8.3%) and BCR/ABL in another one (8.3%). CONCLUSIONS: On the basis of these data it would be useful to achieve a molecular screening of TEL/AML1, E2A/PBX1 and BCR/ABL genes in pediatric acute lymphoblastic leukaemia for allowing a molecular classification in a great percentage of patients that exceed the BCR/ABL positivity in adults.

Aneuploidy↗

Dominant spinocerebellar ataxias: a molecular approach to classification, diagnosis, pathogenesis and the future.

The capacity to use molecular techniques to establish the genetic diagnoses of the autosomal dominant ataxias has revolutionized the field. It is now possible to systematically classify these disorders according to the nature of the causative mutation, with implications for diagnostic testing, analysis of pathogenesis and therapeutic strategies. Here, the disorders are grouped into ataxias caused by CAG repeat expansions that encode polyglutamine, ataxias caused by mutations in ion channels, ataxias caused by repeat expansions that do not encode polyglutamine, and ataxias caused by point mutations. The clinical, pathological, genetic and pathogenic features of each disorder are considered and the current status and future of diagnosis and therapy are reviewed in light of this classification scheme.

Humans↗

Molecular voting for glioma classification reflecting heterogeneity in the continuum of cancer progression.

Gliomas, the most common brain tumors, are generally categorized into two lineages (astrocytic and oligodendrocytic) and further classified as low-grade (astrocytoma and oligodendroglioma), mid-grade (anaplastic astrocytoma and anaplastic oligodendroglioma), and high-grade (glioblastoma multiforme) based on morphological features. A strict classification scheme has limitations because a specific glioma can be at any stage of the continuum of cancer progression and may contain mixed features. Thus, a more comprehensive classification based on molecular signatures may reflect the biological nature of specific tumors more accurately. In this study, we used microarray technology to profile the gene expression of 49 human brain tumors and applied the k-nearest neighbor algorithm for classification. We first trained the classification gene set with 19 of the most typical glioma cases and selected a set of genes that provide the lowest cross-validation classification error with k=5. We then applied this gene set to the 30 remaining cases, including several that do not belong to gliomas such as atypical meningioma. The results showed that not only does the algorithm correctly classify most of the gliomas, but the detailed voting results also provide more subtle information regarding the molecular similarities to neighboring classes. For atypical meningioma, the voting was equally split among the four classes, indicating a difficulty in placement of meningioma into the four classes of gliomas. Thus, the actual voting results, which are typically used only to decide the winning class label in k-nearest neighbor algorithms, provide a useful method for gaining deeper insight into the stage of a tumor in the continuum of cancer development.

Algorithms↗

Molecular and prognostic classification of advanced melanoma: a multi-marker microcontamination assay of peripheral blood stem cells.

The presence or absence of melanoma cells in human peripheral blood has recently been shown to be associated with disease prognosis, including overall survival. The detection of tyrosinase mRNA-positive circulating melanoma cells by reverse transcription-polymerase chain reaction (RT-PCR) has been limited to disseminated tumours expressing measurable amounts of this melanocyte-specific enzyme. To biologically classify both melanotic and amelanotic melanomas and to evaluate the clinical and prognostic relevance of tumour cell microcontamination, we examined autologous peripheral blood stem cell (PBSC) harvests from patients with advanced malignant melanoma prior to dose-escalated chemotherapy. To assay heterogeneous melanoma cell antigen expression, we developed a highly sensitive RT-PCR using four melanoma- and one tumour-associated antigen as molecular markers. Expression of the melanocyte-associated transcripts of tyrosinase, MART1/Melan-A, tyrosinase-related protein-1 (TRP-1) and tyrosinase-related protein-2 (TRP-2) as well as the tumour-specific transcript of MAGE-3 was analysed by RT-PCR in PBSC harvests from 31 patients. Seven of the 31 PBSC harvests tested positive for one or more molecular markers: two patients for tyrosinase only, and one patient for MAGE-3 only, one patient for tyrosinase and MAGE-3, one for tyrosinase and MART1/Melan-A, and two patients for tyrosinase, MART1/Melan-A, TRP-2 and MAGE-3. mRNA-positive patients exhibited a significantly impaired overall survival (P = 0.0032), with a median survival of 3 months as opposed to 10 months in PBSC mRNA-negative patients. In conclusion, the use of this multiple-marker microcontamination assay allowed for molecular and prognostic classification of advanced malignant melanoma.

Adult↗

Development of binary classification of structural chromosome aberrations for a diverse set of organic compounds from molecular structure.

Classification models are generated to predict in vitro cytogenetic results for a diverse set of 383 organic compounds. Both k-nearest neighbor and support vector machine models are developed. They are based on calculated molecular structure descriptors. Endpoints used are the labels clastogenic or nonclastogenic according to an in vitro chromosomal aberration assay with Chinese hamster lung cells. Compounds that were tested with both a 24 and 48 h exposure are included. Each compound is represented by calculated molecular structure descriptors encoding the topological, electronic, geometrical, or polar surface area aspects of the structure. Subsets of informative descriptors are identified with genetic algorithm feature selection coupled to the appropriate classification algorithm. The overall classification success rate for a k-nearest neighbor classifier built with just six topological descriptors is 81.2% for the training set and 86.5% for an external prediction set. The overall classification success rate for a three-descriptor support vector machine model is 99.7% for the training set, 92.1% for the cross-validation set, and 83.8% for an external prediction set.

Algorithms↗

Monophyly of brachiopods and phoronids: reconciliation of molecular evidence with Linnaean classification (the subphylum Phoroniformea nov.).

Molecular phylogenetic analyses of aligned 18S rDNA gene sequences from articulate and inarticulate brachiopods representing all major extant lineages, an enhanced set of phoronids and several unrelated protostome taxa, confirm previous indications that in such data, brachiopod and phoronids form a well-supported clade that (on previous evidence) is unambiguously affiliated with protostomes rather than deuterostomes. Within the brachiopod-phoronid clade, an association between phoronids and inarticulate brachiopods is moderately well supported, whilst a close relationship between phoronids and craniid inarticulates is weakly indicated. Brachiopod-phoronid monophyly is reconciled with the most recent Linnaean classification of brachiopods by abolition of the phylum Phoronida and rediagnosis of the phylum Brachiopoda to include tubiculous, shell-less forms. Recognition that brachiopods and phoronids are close genealogical allies of protostome phyla such as molluscs and annelids, but are much more distantly related to deuterostome phyla such as echinoderms and chordates, implies either (or both) that the morphology and ontogeny of blastopore, mesoderm and coelom formation have been widely misreported or misinterpreted, or that these characters have been subject to extensive homoplasy. This inference, if true, undermines virtually all morphology-based reconstructions of phylogeny made during the past century or more.

Animals↗

[Combined analysis on morphology, immunology, cytogenetics and molecular biology (MICM) classification of 55 patients with acute promyelocytic leukemia].

To investigate the value of bone marrow morphology, immunology, cytogenetics and molecular biology (MICM) examination in the diagnosis of acute promyelocytic leukemia (APL) and their relations of each other, the MICM data of 55 APL patients were analyzed retrospectively. The result showed that the accuracy rate of morphological diagnosis based on FAB classification could reach 96.4%; CD33 and CD13 antigen were co-expressed the highest in immunophenotyping (CD33(+)CD13(+) occupied 96.4%); cytogenetic abnormality containing t (15; 17)(q22; 21) accounted for 87.3%, translocation of chromosomes (simple type) of 100% t (15; 17)(q22; 21) occupied 75%, other involved chromosomes included 1, 8, 9, 11, 12, 21; the positive rate of PML/RARalpha gene also reached 96.4%; the accuracy rate of APL diagnosis by combining MICM measure was 100%. In conclusion, the bone marrow morphology still remains to be base for diagnosis of APL, but the combined analysis of MICM could obviously enhance the accuracy of diagnosis for APL. The MICM examination may provide a new approach to find subtype of APL.

Adolescent↗

Molecular findings and classification of malignant lymphomas.

We review the problem of lymphoma classification in the light of the Revised European-American Lymphoma (REAL) scheme, recently proposed by the International Lymphoma Study Group (ILSG). The REAL classification is a list of clinicopathologic entities, all well known from the literature, upon which the ILSG members agreed. Although it contains nothing new, for the first time all the elements, including immunophenotype and molecular data, which characterise a given lymphoma entity are considered. This approach corresponds to the need for objective criteria integrating the often puzzling morphologic findings. Furthermore, better knowledge of the molecular events which contribute to tumour development and progression if of paramount importance for the development of more specific and successful therapies. Some relevant molecular findings included in the classification and additional data obtained by the ILSG members following its publication are discussed.

Chromosome Aberrations↗

Molecular profiling and classification of sporadic renal cell carcinoma by quantitative methylation analysis.

PURPOSE: Preoperative histologic classification of solid renal masses remains limited with current technology. We determine the utility of molecular profiling based on quantitative methylation analysis for characterization of sporadic renal cell carcinoma. EXPERIMENTAL DESIGN: Primary renal cell carcinomas representing three different histologic subtypes were obtained from a total of 38 patients who underwent radical nephrectomy for suspected malignant disease. Genomic DNA was isolated from tumors and was subjected to sodium bisulfite modification. The normalized index of methylation (NIM) for each sample was determined by quantitative real-time methylation-specific PCR at 17 different gene promoters. Hierarchical cluster analysis was performed by using an unsupervised neural network with binary tree topology. RESULTS: The majority of gene promoters that were analyzed in this study demonstrated very low levels of methylation (NIM <1.0). The RASSF1A gene promoter, however, was methylated in 30 of 38 (79%) cases. The frequency of RASSF1A methylation in papillary, clear-cell, and oncocytoma subtypes was 100, 90, and 25%, respectively. The highest levels of RASSF1A methylation were observed in the papillary (mean NIM = 78.9) and clear-cell (mean NIM = 13.4) subtypes. The vast majority of oncocytomas were completely unmethylated, and none demonstrated >1% methylation (mean NIM = 0.11). Hierarchical cluster analysis based on quantitative methylation levels resulted in stratification of sporadic renal cell carcinomas into their discrete histologic subtypes. CONCLUSIONS: Classification of sporadic renal cell carcinomas into histologic subtypes can be accomplished via multigene quantitative methylation profiling. Validation of this approach and selection of appropriate methylation markers may ultimately lead to use of this technology in the preoperative assessment of suspicious renal masses.

Aged↗

Risk assignment in childhood brain tumors: the emerging role of molecular and biologic classification.

Brain tumors as a group are the most common solid tumors of childhood and currently have the highest mortality rate. A major emphasis has historically been placed on stratifying therapy for these tumors based on histologic and clinical prognostic factors. However, with the increasing application of molecular approaches to refine the categorization of these tumors, it has become apparent that histologically comparable lesions may exhibit diverse patterns of gene expression and genomic alterations, which may correspond with important prognostic distinctions. This paper summarizes these observations and discusses how they are being applied in a preliminary fashion as a foundation for risk-adapted stratification of childhood brain tumor therapy.

Biomarkers, Tumor↗

[Solid tumors. Classification based on molecular biology, prognosis and therapy].

The introduction of molecular techniques into the routine diagnostic analysis of solid tumours has been slower than for hematological neoplasias, both because the former in general genetically are more heterogeneous and because their tumour cells are less accessible. This review presents examples of methods which can be used in the identification of risk groups, classification and prognosis of tumours, detection of minimal residual disease, choice of therapeutic strategy and tracing of possible hereditary cases. It is concluded that molecular laboratories should be established in connection with departments of pathology at the larger hospitals and that further development should take place through close collaboration between pathologists, molecular biologists, and clinicians.

Genetic Predisposition to Disease↗

Protein classification using comparative molecular interaction profile analysis system.

We recently introduced a new molecular description factor, interaction profile Factor (IPF) that is useful for evaluating molecular interactions. IPF is a data set of interaction energies calculated by the Comparative Molecular Interaction Profile Analysis system (CoMIPA). CoMIPA utilizes AutoDock 3.0 docking program, and the system has shown to be a powerful tool in clustering the interacting properties between small molecules and proteins. In this report, we describe the application of CoMIPA for protein clustering. A sample set of 15 proteins that share less than 20% homology and have no common functional motifs in primary structure were chosen. Using CoMIPA, we were able to cluster proteins that bound to the same small molecule. Other structural homology-based clustering programs such as PSI-BLAST or PFAM were unable to achieve the same classification. The results are striking because it is difficult to find any common features in the active sites of these proteins that share the same ligand. CoMIPA adds new dimensions for protein classification and has the potential to be a helpful tool in predicting and analyzing molecular interactions.

Algorithms↗

[Endocrine tumors of the pancreas: classification, clinical and molecular prognostic factors].

Pancreatic endocrine tumors are uncommon. Although the great majority of these tumors are well differentiated, their malignant potential varies sometimes greatly. Thus, a variety of clinicopathologic features have been developed in the past to assist in distinguishing pancreatic endocrine tumors with benign, indeterminate and aggressive behavior. Recently, a revised classification of pancreatic endocrine tumors has been proposed including, in addition to previous parameters, the number of mitoses and a Ki-67 index. In this review, the potential diagnostic utility of these different criteria is discussed.

Endocrine Gland Neoplasms↗

Eosinophilic disorders: molecular pathogenesis, new classification, and modern therapy.

Before the 1990s, lack of evidence for a reactive cause of hypereosinophilia or chronic eosinophilic leukemia (e.g. presence of a clonal cytogenetic abnormality or increased blood or bone marrow blasts) resulted in diagnosticians characterizing such nebulous cases as 'idiopathic hypereosinophilic syndrome (HES)'. However, over the last decade, significant advances in our understanding of the molecular pathophysiology of eosinophilic disorders have shifted an increasing proportion of cases from this idiopathic HES 'pool' to genetically defined eosinophilic diseases with recurrent molecular abnormalities. The majority of these genetic lesions result in constitutively activated fusion tyrosine kinases, the phenotypic consequence of which is an eosinophilia-associated myeloid disorder. Most notable among these is the recent discovery of the cryptic FIP1L1-PDGFRA gene fusion in karyotypically normal patients with systemic mast cell disease with eosinophilia or idiopathic HES, redefining these diseases as clonal eosinophilias. Rearrangements involving PDGFRA and PDGFRB in eosinophilic chronic myeloproliferative disorders, and of fibroblast growth factor receptor 1 (FGFR1) in the 8p11 stem cell myeloproliferative syndrome constitute additional examples of specific genetic alterations linked to clonal eosinophilia. The identification of populations of aberrant T-lymphocytes secreting eosinophilopoietic cytokines such as interleukin-5 establish a pathophysiologic basis for cases of lymphocyte-mediated hypereosinophilia. This recent revival in understanding the biologic basis of eosinophilic disorders has permitted more genetic specificity in the classification of these diseases, and has translated into successful therapeutic approaches with targeted agents such as imatinib mesylate and recombinant anti-IL-5 antibody.

Clone Cells↗

[Classification, pathology and molecular biology of pituitary adenoma].

Pituitary adenomas were once considered a homogenous collection of morphologic entities distinguishable pathologically by differences in cytoplasmic staining affinities. Methodological and conceptual advances over the past decade have since confirmed the contrary demonstrating that pituitary adenomas are morphologically and biologically diverse, and that designations such as acidophilic, basophilic and chromophobic, beyond their descriptive merit, are without consistent morphologic, endocrinologic or practical significance. The application of electron microscopy and immunohistochemistry has brought forth a new classification of pituitary adenomas based on ultrastructure and hormonal content, updating understanding of their pathology, secretory function and cytogenesis. As a primary objective, current functional classification of pituitary tumors is discussed in detail. In addition to reviewing the morphology of pituitary tumors, special emphasis is also placed on the important clinicopathologic correlations relevant to these lesions.

Adenoma↗

Statistical modeling and visualization of molecular profiles in cancer.

Current cancer classifications using morphological criteria produce heterogeneous classes with variable prognosis and clinical course. By measuring gene expression for thousands of genes in a single hybridization experiment, microarrays have the potential to contribute to more effective classifications based on molecular information. This gives hope to improve both prognosis and treatment. Statistical methods for molecular classification have focused on using high dimensional representations of molecular profiles to identify subclasses. These can be noisy, unstable, and highly platform-specific. In this article, we emphasize the notion of molecular profiles based on latent categories signifying under-, over-, and baseline expression. Following this approach, we can generate results that are more easily interpretable, more easily translated into clinical tools, more robust to noise, and less platform-dependent. We illustrate both the methods and the associated software for molecular class discovery on a data set of 244 microarrays comprising six known leukemia classes.

Child↗