509 research outputs found
The ansamycin antibiotic, rifamycin SV, inhibits BCL6 transcriptional repression and forms a complex with the BCL6-BTB/POZ domain
BCL6 is a transcriptional repressor that is over-expressed due to chromosomal translocations, or other abnormalities, in ~40% of diffuse large B-cell lymphoma. BCL6 interacts with co-repressor, SMRT, and this is essential for its role in lymphomas. Peptide or small molecule inhibitors, which prevent the association of SMRT with BCL6, inhibit transcriptional repression and cause apoptosis of lymphoma cells in vitro and in vivo. In order to discover compounds, which have the potential to be developed into BCL6 inhibitors, we screened a natural product library. The ansamycin antibiotic, rifamycin SV, inhibited BCL6 transcriptional repression and NMR spectroscopy confirmed a direct interaction between rifamycin SV and BCL6. To further determine the characteristics of compounds binding to BCL6-POZ we analyzed four other members of this family and showed that rifabutin, bound most strongly. An X-ray crystal structure of the rifabutin-BCL6 complex revealed that rifabutin occupies a partly non-polar pocket making interactions with tyrosine58, asparagine21 and arginine24 of the BCL6-POZ domain. Importantly these residues are also important for the interaction of BLC6 with SMRT. This work demonstrates a unique approach to developing a structure activity relationship for a compound that will form the basis of a therapeutically useful BCL6 inhibitor
The Effects of Unilateral Cochlear Implantation on the Tinnitus Handicap Inventory and the Influence on Quality of Life
Objectives/Hypothesis: Cochlear implantation is now the standard of care in patients with significant sensorineural hearing loss. It is well known that patients with severe hearing loss also experience disabling tinnitus. The purpose of this study was to assess the effects of cochlear implants on the perception of tinnitus using the Tinnitus Handicap Inventory (THI). Study Design: Prospective, longitudinal study of 142 cochlear implant patients. Methods: The THI was administered to 142 patients pre-and postimplantation. Outcome measures were obtained 12 months after the implantation. Secondary analyses to examine the correlation between changes in THI scores and outcome measures such as Hearing Handicap Inventory, Hearing in Noise Test (HINT), and short-form 36 (SF-36) quality-of-life scores were performed. Results: Patients demonstrated statistically significant reduction of the THI scores including its subscales (P < .001). Prior to implantation, 37% of patients described their tinnitus as moderate to severe. Postoperatively, this percentage decreased to 10%. Cochlear implantation resulted in complete tinnitus suppression in 37% and tinnitus reduction in another 29% of patients. THI scores significantly correlated with three domains of the SF-36 quality-of-life questionnaire, namely social, emotional, and general health domains. Conclusions: Cochlear implants have a significant suppressive effect on tinnitus in 66% of implant users. Although the reduction in the subjectively perceived tinnitus was statistically significant, it did not correlate with HINT; however, it did correlate with three quality-of-life domains, more significantly for those whose pretreatment conditions were moderate or worse
Detection of CD10, CD34 and their combined expression on Childhood Acute Lymphoblastic Leukemia and the association with clinical outcome in Indonesia
Deterministic Classifiers Accuracy Optimization for Cancer Microarray Data
The objective of this study was to improve classification accuracy in cancer microarray gene expression data using a collection of machine learning algorithms available in WEKA. State of the art deterministic classification methods, such as: Kernel Logistic Regression, Support Vector Machine, Stochastic Gradient Descent and Logistic Model Trees were applied on publicly available cancer microarray datasets aiming to discover regularities that provide insights to help characterization and diagnosis correctness on each cancer typology. The implemented models, relying on 10-fold cross-validation, parameterized to enhance accuracy, reached accuracy above 90%. Moreover, although the variety of methodologies, no significant statistic differences were registered between them, at significance level 0.05, confirming that all the selected methods are effective for this type of analysis.info:eu-repo/semantics/publishedVersio
Metastasis of Tumor Cells Is Enhanced by Downregulation of Bit1
Resistance to anoikis, which is defined as apoptosis induced by loss of integrin-mediated cell attachment to the extracellular matrix, is a determinant of tumor progression and metastasis. We have previously identified the mitochondrial Bit1 (Bcl-2 inhibitor of transcription) protein as a novel anoikis effector whose apoptotic function is independent from caspases and is uniquely controlled by integrins. In this report, we examined the possibility that Bit1 is suppressed during tumor progression and that Bit1 downregulation may play a role in tumor metastasis.Using a human breast tumor tissue array, we found that Bit1 expression is suppressed in a significant fraction of advanced stages of breast cancer. Targeted disruption of Bit1 via shRNA technology in lowly aggressive MCF7 cells conferred enhanced anoikis resistance, adhesive and migratory potential, which correlated with an increase in active Extracellular kinase regulated (Erk) levels and a decrease in Erk-directed phosphatase activity. These pro-metastasis phenotypes were also observed following downregulation of endogenous Bit1 in Hela and B16F1 cancer cell lines. The enhanced migratory and adhesive potential of Bit1 knockdown cells is in part dependent on their high level of Erk activation since down-regulating Erk in these cells attenuated their enhanced motility and adhesive properties. The Bit1 knockdown pools also showed a statistically highly significant increase in experimental lung metastasis, with no differences in tumor growth relative to control clones in vivo using a BALB/c nude mouse model system. Importantly, the pulmonary metastases of Bit1 knockdown cells exhibited increased phospho-Erk staining.These findings indicate that downregulation of Bit1 conferred cancer cells with enhanced anoikis resistance, adhesive and migratory properties in vitro and specifically potentiated tumor metastasis in vivo. These results underscore the therapeutic importance of restoring Bit1 expression in cancer cells to circumvent metastasis at least in part through inhibition of the Erk pathway
Discriminating lymphomas and reactive lymphadenopathy in lymph node biopsies by gene expression profiling
<p>Abstract</p> <p>Background</p> <p>Diagnostic accuracy of lymphoma, a heterogeneous cancer, is essential for patient management. Several ancillary tests including immunophenotyping, and sometimes cytogenetics and PCR are required to aid histological diagnosis. In this proof of principle study, gene expression microarray was evaluated as a single platform test in the differential diagnosis of common lymphoma subtypes and reactive lymphadenopathy (RL) in lymph node biopsies.</p> <p>Methods</p> <p>116 lymph node biopsies diagnosed as RL, classical Hodgkin lymphoma (cHL), diffuse large B cell lymphoma (DLBCL) or follicular lymphoma (FL) were assayed by mRNA microarray. Three supervised classification strategies (global multi-class, local binary-class and global binary-class classifications) using diagonal linear discriminant analysis was performed on training sets of array data and the classification error rates calculated by leave one out cross-validation. The independent error rate was then evaluated by testing the identified gene classifiers on an independent (test) set of array data.</p> <p>Results</p> <p>The binary classifications provided prediction accuracies, between a subtype of interest and the remaining samples, of 88.5%, 82.8%, 82.8% and 80.0% for FL, cHL, DLBCL, and RL respectively. Identified gene classifiers include LIM domain only-2 (<it>LMO2</it>), Chemokine (C-C motif) ligand 22 (<it>CCL22</it>) and Cyclin-dependent kinase inhibitor-3 (<it>CDK3</it>) specifically for FL, cHL and DLBCL subtypes respectively.</p> <p>Conclusions</p> <p>This study highlights the ability of gene expression profiling to distinguish lymphoma from reactive conditions and classify the major subtypes of lymphoma in a diagnostic setting. A cost-effective single platform "mini-chip" assay could, in principle, be developed to aid the quick diagnosis of lymph node biopsies with the potential to incorporate other pathological entities into such an assay.</p
Diagnostic and prognostic prediction using gene expression profiles in high-dimensional microarray data
Improving Cancer Classification Accuracy Using Gene Pairs
Recent studies suggest that the deregulation of pathways, rather than individual genes, may be critical in triggering carcinogenesis. The pathway deregulation is often caused by the simultaneous deregulation of more than one gene in the pathway. This suggests that robust gene pair combinations may exploit the underlying bio-molecular reactions that are relevant to the pathway deregulation and thus they could provide better biomarkers for cancer, as compared to individual genes. In order to validate this hypothesis, in this paper, we used gene pair combinations, called doublets, as input to the cancer classification algorithms, instead of the original expression values, and we showed that the classification accuracy was consistently improved across different datasets and classification algorithms. We validated the proposed approach using nine cancer datasets and five classification algorithms including Prediction Analysis for Microarrays (PAM), C4.5 Decision Trees (DT), Naive Bayesian (NB), Support Vector Machine (SVM), and k-Nearest Neighbor (k-NN)
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