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PubMed1982

Classification of several tobamoviruses isolated in China on the basis of the amino acid composition of their virion proteins.

The amino acid compositions of the virion proteins of several tobamoviruses isolated in China were determined. A classification computed from these and published data of other tobamoviruses was compared with published data of their relatedness assessed using the cDNA:RNA molecular hybridization technique. The classifications are clearly congruent; that based on amino acid composition appears to be best for determining the hierarchical relationships of members within a taxonomic group, rather than for distinguishing between closely related members, whereas nucleic acid hybridization unequivocally places a virus into the appropriate subgroup but is less useful for determining distant relationships.

Amino Acids↗
PubMed2006

Individualized markers optimize class prediction of microarray data.

BACKGROUND: Identification of molecular markers for the classification of microarray data is a challenging task. Despite the evident dissimilarity in various characteristics of biological samples belonging to the same category, most of the marker--selection and classification methods do not consider this variability. In general, feature selection methods aim at identifying a common set of genes whose combined expression profiles can accurately predict the category of all samples. Here, we argue that this simplified approach is often unable to capture the complexity of a disease phenotype and we propose an alternative method that takes into account the individuality of each patient-sample. RESULTS: Instead of using the same features for the classification of all samples, the proposed technique starts by creating a pool of informative gene-features. For each sample, the method selects a subset of these features whose expression profiles are most likely to accurately predict the sample's category. Different subsets are utilized for different samples and the outcomes are combined in a hierarchical framework for the classification of all samples. Moreover, this approach can innately identify subgroups of samples within a given class which share common feature sets thus highlighting the effect of individuality on gene expression. CONCLUSION: In addition to high classification accuracy, the proposed method offers a more individualized approach for the identification of biological markers, which may help in better understanding the molecular background of a disease and emphasize the need for more flexible medical interventions.

Biomarkers↗
PubMed2006

Specificity of molecular interactions in transient protein-protein interaction interfaces.

In this study, we investigate what types of interactions are specific to their biological function, and what types of interactions are persistent regardless of their functional category in transient protein-protein heterocomplexes. This is the first approach to analyze protein-protein interfaces systematically at the molecular interaction level in the context of protein functions. We perform systematic analysis at the molecular interaction level using classification and feature subset selection technique prevalent in the field of pattern recognition. To represent the physicochemical properties of protein-protein interfaces, we design 18 molecular interaction types using canonical and noncanonical interactions. Then, we construct input vector using the frequency of each interaction type in protein-protein interface. We analyze the 131 interfaces of transient protein-protein heterocomplexes in PDB: 33 protease-inhibitors, 52 antibody-antigens, 46 signaling proteins including 4 cyclin dependent kinase and 26 G-protein. Using kNN classification and feature subset selection technique, we show that there are specific interaction types based on their functional category, and such interaction types are conserved through the common binding mechanism, rather than through the sequence or structure conservation. The extracted interaction types are C(alpha)-- H...O==C interaction, cation...anion interaction, amine...amine interaction, and amine...cation interaction. With these four interaction types, we achieve the classification success rate up to 83.2% with leave-one-out cross-validation at k = 15. Of these four interaction types, C(alpha)--H...O==C shows binding specificity for protease-inhibitor complexes, while cation-anion interaction is predominant in signaling complexes. The amine ... amine and amine...cation interaction give a minor contribution to the classification accuracy. When combined with these two interactions, they increase the accuracy by 3.8%. In the case of antibody-antigen complexes, the sign is somewhat ambiguous. From the evolutionary perspective, while protease-inhibitors and sig-naling proteins have optimized their interfaces to suit their biological functions, antibody-antigen interactions are the happenstance, implying that antibody-antigen complexes do not show distinctive interaction types. Persistent interaction types such as pi...pi, amide-carbonyl, and hydroxyl-carbonyl interaction, are also investigated. Analyzing the structural orientations of the pi...pi stacking interactions, we find that herringbone shape is a major configuration in transient protein-protein interfaces. This result is different from that of protein core, where parallel-displaced configurations are the major configuration. We also analyze overall trend of amide-carbonyl and hydroxyl-carbonyl interactions. It is noticeable that nearly 82% of the interfaces have at least one hydroxyl-carbonyl interactions.

Animals↗
PubMed2005

A data base for 3000 monoclonal immunoglobulin cases and a new classification.

Data from monoclonal immunoglobulin cases screened in our laboratory for 40 years were used to assemble a cohort of 3094 cases selected according to immunoelectrophoresis and immunofixation interpretation and clinical data availability. Molecular distribution and original classification were used to establish five categories of cases: multiple myeloma (MM) and Waldenstrom macroglobulinemia (WM), other lymphoproliferative diseases, cases associated with heavy immunological diseases or other tumors, and benign cases. Free light chain (FLC) cases comprise 7% of the cohort, pluriclonal Ig, 6%. More than 50% of 1335 cases with identified diagnoses are not malignant hemopathies. Male/female ratio is less than 1 for MM cases and close to 1 for benign and other lymphoproliferative cases. Males are a majority in MW and associated cases. Follow-up periods range from 5 to 30 years for 263 cases. The main characteristics of this data base have been defined and the benefit of the original classification is highlighted. Future studies will investigate improvements resulting from immunofixation and current urinary analysis practices, as well as long-term follow-up, pluriclonal Ig cases, cryoglobulins, the meaning of the presence of FLC and malignant transformation.

Adolescent↗
PubMed1997

Cytogenetic classification of renal cell cancer.

Cytogenetic and molecular genetic investigations in cancer are important tools to address problems of oncogenesis and tumor progression, of classification, and of diagnosis of tumors. A combination of advanced molecular genetic, cytogenetic, and (immuno) histopathologic analysis will contribute significantly to the elucidation of the oncogenic steps that lead to immortalization and subsequent malignant behavior. In this review written on the occasion of Dr. Avery Sandberg's 75th anniversary, we will present a model for the pathogenesis of renal cell tumors based on a new cytomorphologic classification and our (cyto)genetic analysis of about 175 renal cell tumors, together with the accumulated data in the literature.

Carcinoma, Renal Cell↗
PubMed2004

Molecular diagnosis of human adenoviruses d and e by a phylogeny-based classification method using a partial hexon sequence.

Human adenoviruses (HAdVs) are the major causes of a variety of acute illnesses. Virus isolation and neutralization tests are usually done to identify the causative virus, but these tests are labor-intensive and time-consuming, and standardized antisera are in limited supply. This study investigated a rapid and reliable method of virus identification based on PCR and phylogenetic analysis. The phylogenetic tree constructed by neighbor joining on the basis of the newly determined partial hexon sequences from 33 prototypes of HAdV-D and -E, along with 11 available prototypes of HAdV-A to -C and -F from GenBank, allowed HAdVs to be grouped into six distinct clusters. These clusters correspond closely to the six newly designated species, HAdV-A to -F. The partial hexon sequences of 57 isolates from patients with acute conjunctivitis obtained over 20 years plus those of 44 prototype strains were analyzed. Each isolate formed a monophyletic cluster along with its respective prototype strain, allowing serotype identification. Partial-hexon-based classification appears to be an effective tool for studying the molecular epidemiology of HAdVs.

Adenovirus Infections, Human↗
PubMed2006

An update on molecular genetics of gastrointestinal stromal tumours.

Gastrointestinal stromal tumours (GISTs) are the most common primary mesenchymal tumours of the gastrointestinal tract. Most of them show activating mutations of the genes coding for KIT or platelet-derived growth factor receptor alpha (PDGFRalpha), two receptor tyrosine kinases (RTKs). The RTK inhibitor Imatinib (Gleevec, Novartis, Switzerland), induces regression of the tumour. The level of response to treatment, together with other clinicopathological parameters is related to the type and site of the activating mutation, thus suggesting that these tumours should be classified according to the molecular context. This is confirmed also by the phenomenon of the resistance to treatment, which arises because of different mechanisms (second mutation, amplification, activation of other RTKs) and can be fought only by specific RTK inhibitors, that are at present under development. RTK activation involves an homogeneous transduction pathway whose components (MAPK, AKT, PI3K, mTOR and RAS) are possible targets of new molecular treatment. A new paradigm of classification integrating the classic pathological criteria with the molecular changes will permit personalised prognosis and treatment.

Adolescent↗
PubMed2003

[Molecular cancer biology--from research to clinical practice].

Recent progress in our understanding of the mechanism of transformation has contributed to the development of novel molecular approaches for the detection and classification of cancer. The review focuses on the molecular background of cancer, the role of oncogenic kinases, genetic instability and embryonal signalling pathways. Moreover, examples of novel diagnostic and therapeutic possibilities are described.

Cell Transformation, Neoplastic↗
PubMed1999

Histopathology and molecular genetics of renal tumors toward unification of a classification system.

PURPOSE: We characterize the genetic abnormalities associated with pathological subtypes of renal tumors, which may help diagnosis or prognostication. MATERIALS AND METHODS: A comprehensive literature review of genetic abnormalities associated with different renal tumor subtypes was performed. RESULTS: Studies of sporadic and hereditary forms suggest that abnormalities in the von Hippel-Lindau and met genes are the earliest changes in conventional (clear cell) and papillary basophilic renal cancers, respectively. Renal oncocytoma and chromophobe carcinoma have common genetic abnormalities, suggesting a relationship. A similar finding has been observed between papillary adenoma and papillary basophilic renal cancer. CONCLUSIONS: These findings suggest that molecular diagnostic testing will help determine histopathological diagnosis, identify tumor types with similar genetic abnormalities suggesting a common origin and indicate potential prognostic markers for future study.

Humans↗
PubMed2006

Histopathology in the light of molecular profiling.

The 2001 WHO classification distinguishes five variants (centroblastic, immunoblastic, plasmablastic, anaplastic and T-cell rich) and three subtypes (primary mediastinal, intravascular and primary effusion large B-cell lymphoma) of diffuse large B-cell lymphomas (DLBCLs).The recognition of the three subtypes as distinct disease entities can be considered as an advance in our understanding of these tumours. However, the variants of DLBCLs, which significantly outnumber the subtypes in frequency, represent an unresolved area. Gene expression profiling (GEP) of the variants led to a discrepancy in results and produced more questions than answers. The authors, therefore, initiated a multi-institutional collaborative research project in Germany aimed at a subtle morphologic, genomic and transcriptional characterisation of DLBCLs and Burkitt lymphoma (BL). We included BL in our study for two reasons: (1) it belongs to aggressive B-NHLs; and (2) at present, there are no reliable criteria that can be applied to distinguish BL from DLBCL. The GEPs derived from 200 patient samples were correlated with reviewed histology, the degree of genetic imbalances and clinical features. The results of this approach show that: (i) the DLBCL can be divided into more than four molecular groups; and (ii) the BL cases, identified by the consensus of five out of six lymphoma expert pathologists, displayed a genomic and gene expression profile that was clearly distinct from those of most DLBCLs. The group of DLBCLs that resembled BL in their GEP had a remarkably good prognosis, whereas those that differed in their GEP from the consensus BLs had unfavourable survival rates. In conclusion, combined application of genomic and gene expression profiling in conjunction with consensus reviewed histology and clinical features, appears to be a reliable approach that enables a reproducible and clinically meaningful characterisation of mature aggressive B-NHLs.

Gene Expression Profiling↗
PubMed2004

Genomic approaches to hematologic malignancies.

In the past several years, experiments using DNA microarrays have contributed to an increasingly refined molecular taxonomy of hematologic malignancies. In addition to the characterization of molecular profiles for known diagnostic classifications, studies have defined patterns of gene expression corresponding to specific molecular abnormalities, oncologic phenotypes, and clinical outcomes. Furthermore, novel subclasses with distinct molecular profiles and clinical behaviors have been identified. In some cases, specific cellular pathways have been highlighted that can be therapeutically targeted. The findings of microarray studies are beginning to enter clinical practice as novel diagnostic tests, and clinical trials are ongoing in which therapeutic agents are being used to target pathways that were identified by gene expression profiling. While the technology of DNA microarrays is becoming well established, genome-wide surveys of gene expression generate large data sets that can easily lead to spurious conclusions. Many challenges remain in the statistical interpretation of gene expression data and the biologic validation of findings. As data accumulate and analyses become more sophisticated, genomic technologies offer the potential to generate increasingly sophisticated insights into the complex molecular circuitry of hematologic malignancies. This review summarizes the current state of discovery and addresses key areas for future research.

Gene Expression Profiling↗
PubMed2005

[X-linked mental retardation].

X-linked mental retardation (XLMR) affects 1.8 per thousand male births and is usually categorized as "syndromic" (MRXS) or "non-specific" (MRX) forms according to the presence or absence of specific signs in addition to the MR. Up to 60 genes have been implicated in XLMR and certain mutations can alternatively lead to MRXS or MRX. Indeed the extreme phenotypic and allelic heterogeneity of XLMR makes the classification of most genes difficult. Therefore, following identification of new genes, accurate retrospective clinical evaluation of patients and their families is necessary to aid the molecular diagnosis and the classification of this heterogeneous group of disorders. Analyses of the protein products corresponding to XLMR genes show a great diversity of cellular pathways involved in MR. Common mechanisms are beginning to emerge : a first group of proteins belongs to the Rho and Rab GTPase signaling pathways involved in neuronal differentiation and synaptic plasticity and a second group is related to the regulation of gene expression. In this review, we illustrate the complexity of XLMR conditions and present recent data about the FMR1, ARX and Oligophrenin 1 genes.

Carrier State↗
PubMed2003

Modification of topoisomerase genes copy number in newly diagnosed childhood acute lymphoblastic leukemia.

Topoisomerase genes were analyzed at both DNA and RNA levels in 25 cases of newly diagnosed childhood acute lymphoblastic leukemia (ALL). The results of molecular analysis were compared to risk group classification of children in order to identify molecular characteristics associated with response to therapy. At diagnosis, allelic imbalance at topo-isomerase IIalpha (TOP2A) gene locus was found in 75% of informative cases whereas topoisomerase I and IIbeta gene loci are altered in none or only one case, respectively. By semi-quantitative Polymerase chain reaction, we found a 2.5 to 8-fold TOP2A gene amplification in 72% of the children, which was correlated to gene overexpression in every case. These results show that TOP2A gene amplification is a frequent event in ALL at diagnosis. Interestingly, we also identified a small population of children that do not present TOP2A gene amplification or gene overexpression and who are significantly associated with very high risk classified patients showing glucocorticoid resistance. In conclusion, characterization of TOP2A gene status in childhood ALL at diagnosis provides useful complementary information for risk assessment.

Adolescent↗
PubMed2001

Gene expression profiling of clear cell renal cell carcinoma: gene identification and prognostic classification.

To better understand the molecular mechanisms that underlie the tumorigenesis and progression of clear cell renal cell carcinoma (ccRCC), we studied the gene expression profiles of 29 ccRCC tumors obtained from patients with diverse clinical outcomes by using 21,632 cDNA microarrays. We identified gene expression alterations that were both common to most of the ccRCC studied and unique to clinical subsets. There was a significant distinction in gene expression profile between patients with a relatively nonaggressive form of the disease [100% survival after 5 years with the majority (15/17 or 88%) having no clinical evidence of metastasis] versus patients with a relatively aggressive form of the disease (average survival time 25.4 months with a 0% 5-year survival rate). Approximately 40 genes most accurately make this distinction, some of which have previously been implicated in tumorigenesis and metastasis. To test the robustness and potential clinical usefulness of this molecular distinction, we simulated its use as a prognostic tool in the clinical setting. In 96% of the ccRCC cases tested, the prediction was compatible with the clinical outcome, exceeding the accuracy of prediction by staging. These results suggest that two molecularly distinct forms of ccRCC exist and that the integration of expression profile data with clinical parameters could serve to enhance the diagnosis and prognosis of ccRCC. Moreover, the identified genes provide insight into the molecular mechanisms of aggressive ccRCC and suggest intervention strategies.

Adenocarcinoma, Clear Cell↗
PubMed2004

3D-chiral quadratic indices of the 'molecular pseudograph's atom adjacency matrix' and their application to central chirality codification: classification of ACE inhibitors and prediction of sigma-receptor antagonist activities.

Quadratic indices of the 'molecular pseudograph's atom adjacency matrix' have been generalized to codify chemical structure information for chiral drugs. These 3D-chiral quadratic indices make use of a trigonometric 3D-chirality correction factor. These indices are nonsymmetric and reduced to classical (2D) descriptors when symmetry is not codified. By this reason, it is expected that they will be useful to predict symmetry-dependent properties. 3D-Chirality quadratic indices are real numbers and thus, can be easily calculated in TOMOCOMD-CARDD software. These descriptors circumvent the inability of conventional 2D quadratic indices (Molecules 2003, 8, 687-726. http://www.mdpi.org) and other (chirality insensitive) topological indices to distinguish sigma-stereoisomers. In this paper, we extend our earlier work by applying 3D-chirality quadratic indices to two data sets containing chiral compounds. Consequently, in order to test the potential of this novel approach in drug design we have modelled the angiotesin-converting enzyme inhibitory activity of perindoprilate's sigma-stereoisomers combinatorial library. Two linear discriminant analysis (LDA) models were obtained. The first one model was performed considering all data set as training series and classifies correctly 88.89% of active compounds and 100.00% of nonactive one for a global good classification of 96.87%. The second one LDA-QSAR model classified correctly 83.33% of the active and 100.00% of the inactive compounds in a training set, result that represent a total of 95.65% accuracy in classification. On the other hand, the model classifies 100.00% of these compounds in the test set. Similar predictive behaviour was observed in a leave-one-out cross-validation procedure for both equations. Canonical regression analysis corroborated the statistical quality of these models (R(can) of 0.82 and of 0.76, respectively) and was also used to compute biology activity canonical scores for each compound. Finally, prediction of the biological activities of chiral 3-(3-hydroxyphenyl)piperidines, which are sigma-receptor antagonists, by linear multiple regression analysis was carried out. Two statistically significant QSAR models were obtained (R2=0.940, s=0.270 and R2=0.977, s=0.175). These models showed high stability to data variation in the leave-one-out cross-validation procedure (q2=0.912, scv=0.289 and q2=0.957, scv=0.211). The results of this study compare favourably with those obtained with other chirality descriptors applied to the same data set. The 3D-chiral TOMOCOMD-CARDD approach provides a powerful alternative to 3D-QSAR.

Angiotensin-Converting Enzyme Inhibitors↗