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Results for “Molecular Classification”

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At least 91 records · Page 5Linked to original sources
PubMed2002

Molecular classification of enteroviruses not identified by neutralization tests.

We isolated six viruses from patients diagnosed with aseptic meningitis or hand, foot, and mouth disease. The cytopathic effect of these viruses on cultured cells was like that of enteroviruses. However, viral neutralization tests against standard antisera were negative. Phylogenetic analysis with the complete VP4 nucleotide sequences of these 6 viruses and 29 serotypes of enteroviruses classified 3 of the viruses as serotype echovirus type 18 (EV18) and 3 as serotype human enterovirus 71 (HEV71). These results were confirmed by remicroneutralization tests with HEV-monospecific antisera or an additional phylogenetic analysis with the complete VP4 nucleotide sequences. Phylogenetic analysis with complete VP4 genes is more useful than neutralization tests with enterovirus serotype-specific antisera in identifying enterovirus serotypes.

Enterovirus↗
PubMed2004

Molecular classification of parathyroid neoplasia by gene expression profiling.

The current classification of sporadic parathyroid neoplasia, specifically the distinction of adenoma from multiple gland neoplasia (double adenoma and nonfamilial primary hyperplasia) is problematic and results in a relatively high rate of clinical error. Oligonucleotide microarrays (Affymetrix U133A) were used to evaluate parathyroid samples from 61 patients; 35 adenomas, 10 nonfamilial multiple gland neoplasia, 3 familial primary hyperplasia, 8 renal-induced hyperplasia, and 5 from patients without parathyroid disease (normals). A multiclass comparison using supervised clustering identified distinct gene signatures for each class of parathyroid samples. We developed a predictor model that correctly identified 34 of 35 cases of adenoma, 9 of 10 cases of nonfamilial multiple gland neoplasia, and identified a minimum set of 11 genes for the distinction of adenoma versus multiple gland neoplasia. All methods of unsupervised clustering showed two related but different types of parathyroid adenomas that we have arbitrarily designated as type 1 and type 2 adenomas. Multiple gland parathyroid neoplasia, which represents either synchronous or asynchronous autonomous growth in two, three, or all four parathyroid glands, is a distinct molecular entity and does not represent the molecular pathogenesis of adenoma occurring in multiple glands.

Adenoma↗
PubMed2002

Molecular classification of coxsackie A viruses on the basis of the 5'-UTR: structural and evolutionary aspects.

The sequences from a large part of the 5'-UTR of 21 coxsackie A virus (CAV) reference strains for which such data did not exist in the past were obtained. Those sequences, along with the respective available sequences from the rest of the CAV reference strains and many other enteroviruses, were compared. According to the results of this comparison, enteroviruses are classified into two genetic clusters on the basis of 5'-UTR, and CAVs are divided into these two clusters. Specifically, it was found that CAV1, -11, -13, -15, -17 to -22, and -24 are classified together with polioviruses and enterovirus 70, whereas the rest of the CAVs are classified along with coxsackie B viruses, echoviruses, and the rest of the other enteroviruses. No correlation between overall 5'-UTR identity and the currently recognized human enterovirus species was found. The phenomenon of "covariance" in the 5'-UTR was followed for the prediction of the possible secondary structure of the 5'-UTR of the CAVs sequenced in the present study.

5' Untranslated Regions↗
PubMed2004

Molecular classification and survival prediction in human gliomas based on proteome analysis.

The biological features of gliomas, which are characterized by highly heterogeneous biological aggressiveness even in the same histological category, would be precisely described by global gene expression data at the protein level. We investigated whether proteome analysis based on two-dimensional gel electrophoresis and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry can identify differences in protein expression between high- and low-grade glioma tissues. Proteome profiling patterns were compared in 85 tissue samples: 52 glioblastoma multiforme, 13 anaplastic astrocytomas, 10 atrocytomas, and 10 normal brain tissues. We could completely distinguish the normal brain tissues from glioma tissues by cluster analysis based on the proteome profiling patterns. Proteome-based clustering significantly correlated with the patient survival, and we could identify a biologically distinct subset of astrocytomas with aggressive nature. Discriminant analysis extracted a set of 37 proteins differentially expressed based on histological grading. Among them, many of the proteins that were increased in high-grade gliomas were categorized as signal transduction proteins, including small G-proteins. Immunohistochemical analysis confirmed the expression of identified proteins in glioma tissues. The present study shows that proteome analysis is useful to develop a novel system for the prediction of biological aggressiveness of gliomas. The proteins identified here could be novel biomarkers for survival prediction and rational targets for antiglioma therapy.

Amino Acid Sequence↗
PubMed2002

Molecular classification of borderline ovarian tumors using hierarchical cluster analysis of protein expression profiles.

Ovarian tumors range from benign to aggressive malignant tumors, including an intermediate class referred to as borderline carcinoma. The prognosis of the disease is strongly dependent on tumor classification, where patients with borderline tumors have much better prognosis than patients with carcinomas. We here describe the use of hierarchical clustering analysis of quantitative protein expression data for classification of this type of tumor. An accurate classification was not achieved using an unselected set of 1,584 protein spots for clustering analysis. Different approaches were used to select spots that were differentially expressed between tumors of different malignant potential and to use these sets of spots for classification. When sets of proteins were selected that differentiated benign and malignant tumors, borderline tumors clustered in the benign group. This is consistent with the biologic properties of these tumors. Our results indicate that hierarchical clustering analysis is a useful approach for analysis of protein profiles and show that this approach can be used for differential diagnosis of ovarian carcinomas and borderline tumors.

Adult↗
PubMed2004

Molecular classification of liver cirrhosis in a rat model by proteomics and bioinformatics.

Liver cirrhosis is a worldwide health problem. Reliable, noninvasive methods for early detection of liver cirrhosis are not available. Using a three-step approach, we classified sera from rats with liver cirrhosis following different treatment insults. The approach consisted of: (i) protein profiling using surface-enhanced laser desorption/ionization (SELDI) technology; (ii) selection of a statistically significant serum biomarker set using machine learning algorithms; and (iii) identification of selected serum biomarkers by peptide sequencing. We generated serum protein profiles from three groups of rats: (i) normal (n=8), (ii) thioacetamide-induced liver cirrhosis (n=22), and (iii) bile duct ligation-induced liver fibrosis (n=5) using a weak cation exchanger surface. Profiling data were further analyzed by a recursive support vector machine algorithm to select a panel of statistically significant biomarkers for class prediction. Sensitivity and specificity of classification using the selected protein marker set were higher than 92%. A consistently down-regulated 3495 Da protein in cirrhosis samples was one of the selected significant biomarkers. This 3495 Da protein was purified on-chip and trypsin digested. Further structural characterization of this biomarkers candidate was done by using cross-platform matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) peptide mass fingerprinting (PMF) and matrix-assisted laser desorption/ionization time of flight/time of flight (MALDI-TOF/TOF) tandem mass spectrometry (MS/MS). Combined data from PMF and MS/MS spectra of two tryptic peptides suggested that this 3495 Da protein shared homology to a histidine-rich glycoprotein. These results demonstrated a novel approach to discovery of new biomarkers for early detection of liver cirrhosis and classification of liver diseases.

Algorithms↗
PubMed2002

A reliable RT-PCR/RFLP assay for the molecular classification of enterovirus reference and wild type strains to either of the two genetic clusters on the basis of 5'-UTR.

The available sequence data from a large segment of the 5'-UTR of all enterovirus reference and wild type strains were analysed in an attempt to discover possible restriction sites for reliable, serotypic identification of wild type isolates. No combination of restriction endonucleases, though, was found to produce serotype-, or group-specific haplotypes. Thirteen restriction enzymes were predicted to differentiate between representatives of the two enterovirus genetic clusters on the basis of 5'-UTR. One of these enzymes, BstOI, was tested in practice for the differentiation of 61 enterovirus reference strains from 56 different serotypes and 82 wild type strains which belong to the two genetic clusters on the basis of 5'-UTR. All the representatives of the two clusters were successfully differentiated with the specific restriction enzyme. Consequently, the simple RFLP-based assay presented here could be used as a very rapid and reliable means for the initial determination of whether a clinical isolate of unknown identity belongs to either of the 'poliovirus-like', or the 'CBV-like' genetic cluster on the basis of 5'-UTR classification of human enteroviruses.

5' Untranslated Regions↗
PubMed1996

Immunological and molecular classification of mucosa-associated lymphoid tissue lymphoma.

Malignant B-cell lymphoma of mucosa-associated lymphoid tissue (MALT) type is now considered to be a tumor of marginal zone cells of native or, more frequently, acquired MALT. The relationship of MALT lymphoma to the normal counterpart population is acknowledged by the revised European-American classification of lymphoid neoplasms (R.E.A.L.). It fits into the extranodal subtype of marginal zone lymphoma listed as a distinct entity in this recent classification scheme. A typical feature of this lymphoma type is a close lymphocyte-epithelium interaction as reflected by lymphoepithelial lesions. The immunophenotype is characterized by the expression of Sig and B-cell-associated antigens and by the lack of CD5 and CD10. Frequent occurrence of trisomy 3 has been reported. There is now overwhelming evidence that low-grade MALT lymphomas are subject to immunologic drive. In the stomach, the presence of Helicobacter pylori and locally activated T cells appears to be critical for the growth of neoplastic cells. This finding is of clinical significance since the eradication of H. pylori has been shown to reverse low-grade MALT lymphoma.

Gastrointestinal Neoplasms↗
PubMed2002

Risk assignment in pediatric soft-tissue sarcomas: an evolving molecular classification.

Pediatric soft-tissue sarcomas are increasingly being defined by both histologic appearance and underlying chromosomal abnormalities to determine their biologic behavior. Most sarcomas of this type have specific chromosomal translocations that create unique fusion genes. Expression of such fusion genes may have diagnostic, prognostic, and surveillance implications for the patient. This review analyzes the fusion gene expressions seen with seven of the major types of pediatric soft-tissue tumors and their impact on biologic behavior. In nearly 50% of the malignancies discussed, the diagnostic, prognostic, and surveillance implications of their specific fusion gene expressions are already defined or becoming established (alveolar rhabdomyosarcoma, Ewing sarcoma/primitive neuroectodermal tumor, and synovial sarcoma). In the remainder of the tumors, these questions are rapidly being addressed. To facilitate future fusion gene studies, pediatric surgeons, pathologists, and oncologists need to work as a coordinated team to ensure proper tumor procurement. Large clinical cooperative trials involving biologic studies of pediatric soft-tissue sarcomas could facilitate advancement of knowledge in this area of pediatric oncology.

Adolescent↗
PubMed2004

Molecular classification of scrapie strains in mice using gene expression profiling.

Transmissible spongiform encephalopathy strains demonstrate specific prion characteristics, each with specific incubation times, and strain-specific patterns of deposition of the misfolded isoform of prion, PrPSc, in the brains of infected individuals. Different biochemical properties, including glycosylation profiles and the degree of proteinase resistance, have been shown to be strain-specific. However, no relationship between these properties and the phenotypic differences in the subsequent diseases has as yet been determined. Here we explore the utility of gene expression profiles to identify differences in the host response to different strains of prion agent. We identify 114 genes that exhibit significantly different levels of expression in mice infected with three strains of scrapie. These genes represent a pool of genes involved in a strain-specific response to prion disease. We have identified the most discriminatory genes from this list utilizing a wrapper-based feature selection algorithm with external cross-validation.

Algorithms↗
PubMed2003

Accurate molecular classification of human cancers based on gene expression using a simple classifier with a pathological tree-based framework.

Recent studies suggest accurate prediction of tissue of origin for human cancers can be achieved by applying sophisticated statistical learning procedures to gene expression data obtained from DNA microarrays. We have pursued the hypothesis that a more straightforward and equally accurate strategy for classifying human tumors is to use a simple algorithm that considers gene expression levels within a tree-based framework that encodes limited information about pathology and tissue ontogeny. By considering gene expression data within this framework, we found only a small number of genes were required to achieve a relatively high accuracy level in tumor classification. Using as few as 45 genes we were able to classify 157 of 190 human malignant tumors correctly, which is comparable to previous results obtained with sophisticated classifiers using thousands of genes. Our simple classifier accurately predicted the origin of metastatic tumors even when the classifier was trained using only primary tumors, and the classifier produced accurate predictions when trained and tested on expression data from different labs, and from different microarray platforms. Our findings suggest that accurate and robust cancer diagnosis from gene expression profiles can be achieved by mimicking the classification strategies routinely used by surgical pathologists.

Algorithms↗
PubMed2000

Primary CNS lymphoma: clinical presentation, pathological classification, molecular pathogenesis and treatment.

Primary CNS lymphomas (PCNSL) represent malignant non-Hodgkin's B cell lymphomas, which are confined to the central nervous system. They show a dramatic increase in frequency in the immunocompromised as well as in the immunocompetent population. Recent studies have identified germinal center B cells as the cellular origin of PCNSL; however, the details of their molecular pathogenesis still remain to be elucidated. Treatment recommendations are not clearly established. Radiotherapy (RT) is efficient in terms of tumor response, but not curative. Median survival after RT alone is about 1 year. According to the results of uncontrolled studies the combination of RT and chemotherapy based on high-dose methotrexate (HD-MTX) is most efficient in terms of survival rates. However, long-term neurotoxicity overshadows treatment efficacy, especially in patients over 60 years of age. The authors favor the systematic evaluation of chemotherapy alone with protocols including HD MTX, because unicenter results are promising in terms of both survival as well as quality of life in long term survivors.

Central Nervous System Neoplasms↗
PubMed2000

Molecular classification of the dementias.

Most patients with frontotemporal dementia do not have taupathology as shown by immunohistochemistry. The use of the term tauopathy to classify frontotemporal dementia is inappropriate.

Brain↗
PubMed2004

Molecular classification of head and neck squamous cell carcinomas using patterns of gene expression.

The prognostication of head and neck squamous cell carcinoma (HNSCC) is largely based upon the tumor size and location and the presence of lymph node metastases. Here we show that gene expression patterns from 60 HNSCC samples assayed on cDNA microarrays allowed categorization of these tumors into four distinct subtypes. These subtypes showed statistically significant differences in recurrence-free survival and included a subtype with a possible EGFR-pathway signature, a mesenchymal-enriched subtype, a normal epithelium-like subtype, and a subtype with high levels of antioxidant enzymes. Supervised analyses to predict lymph node metastasis status were approximately 80% accurate when tumor subsite and pathological node status were considered simultaneously. This work represents an important step toward the identification of clinically significant biomarkers for HNSCC.

Adult↗
PubMed2004

DNA-microarray analysis of brain cancer: molecular classification for therapy.

Primary brain tumours are among the most lethal of all cancers, largely as a result of their lack of responsiveness to current therapy. Numerous new therapies hold great promise for the treatment of patients with brain cancer, but the main challenge is to determine which treatment is most likely to benefit an individual patient. DNA-microarray-based technologies, which allow simultaneous analysis of expression of thousands of genes, have already begun to uncover previously unrecognized patient subsets that differ in their survival. Here, we review the progress made so far in using DNA microarrays to optimize brain cancer therapy.

Animals↗
PubMed2002

Molecular classification of selective oestrogen receptor modulators on the basis of gene expression profiles of breast cancer cells expressing oestrogen receptor alpha.

The purpose of this study was to classify selective oestrogen receptor modulators based on gene expression profiles produced in breast cancer cells expressing either wtERalpha or mutant(351)ERalpha. In total, 54 microarray experiments were carried out by using a commercially available Atlas cDNA Expression Arrays (Clontech), containing 588 cancer-related genes. Nine sets of data were generated for each cell line following 24 h of treatment: expression data were obtained for cells treated with vehicle EtOH (Control); with 10(-9) or 10(-8) M oestradiol; with 10(-6) M 4-hydroxytamoxifen; with 10(-6) M raloxifene; with 10(-6) M idoxifene, with 10(-6) M EM 652, with 10(-6) M GW 7604; with 5 x 10(-5) M resveratrol and with 10(-6) M ICI 182,780. We developed a new algorithm 'Expression Signatures' to classify compounds on the basis of differential gene expression profiles. We created dendrograms for each cell line, in which branches represent relationships between compounds. Additionally, clustering analysis was performed using different subsets of genes to assess the robustness of the analysis. In general, only small differences between gene expression profiles treated with compounds were observed with correlation coefficients ranged from 0.83 to 0.98. This observation may be explained by the use of the same cell context for treatments with compounds that essentially belong to the same class of drugs with oestrogen receptors related mechanisms. The most surprising observation was that ICI 182,780 clustered together with oestrodiol and raloxifene for cells expressing wtERalpha and clustered together with EM 652 for cells expressing mutant(351)ERalpha. These data provide a rationale for a more precise and elaborate study in which custom made oligonucleotide arrays can be used with comprehensive sets of genes known to have consensus and putative oestrogen response elements in their promoter regions.

Breast Neoplasms↗