42 research outputs found
Molecular Dynamics Simulations of p97 Including Covalent, Allosteric and ATP-Competitive Inhibitors
Binary (nucleotide-protein dimer and hexamer complexes) and ternary (nucleotide-protein-inhibitor complexes) p97 complexes were subjected to molecular dynamics simulations in an attempt to further our understanding of the p97 protein oligomer domain stability and, more importantly, of the recently reported diverse molecular mechanisms of inhibition including allosteric, ATP-competitive and covalent inhibitors. Analysis of stable states following equilibration phases indicated a higher intrinsic stability of the homohexamer as opposed to the dimer, and of N-D1 domains as opposed to the D2 domain. The molecular dynamics of the proposed allosteric binding model reproduced important molecular interactions identified experimentally with high frequency throughout the trajectory. Observed conformational changes occurring in the D2 nucleotide binding site provided a novel bind-rearrange-react hypothesis of stepwise molecular events involved in the specific covalent inhibitor mode of action
Sensitivity to Entrectinib Associated with a Novel LMNA-NTRK1 Gene Fusion in Metastatic Colorectal Cancer
In metastatic colorectal cancer (CRC), actionable genetic lesions represent potential clinical opportunities. NTRK1, 2, and 3 gene rearrangements encode oncogenic fusions of the tropomyosin-receptor kinase (TRK) family of receptor tyrosine kinases in different tumor types. The TPM3-NTRK1 rearrangement is a recurring event in CRC that renders tumors sensitive to TRKA kinase inhibitors in preclinical models. We identified abnormal expression of the TRKA protein in tumor and liver metastases of a CRC patient refractory to standard therapy. Molecular characterization unveiled a novel LMNA-NTRK1 rearrangement within chromosome 1 with oncogenic potential, and the patient was treated with the pan-TRK inhibitor entrectinib, achieving partial response with decrease in hepatic target lesions from 6.8 and 8.2cm in longest diameter to 4.7 and 4.3cm, respectively. To our knowledge, this is the first clinical evidence of efficacy for therapeutic inhibition of TRKA in a solid tumor, illuminating a genomic-driven strategy to identify CRCs reliant on this oncogene to be clinically targeted with entrectinib
Cross platform microarray analysis for robust identification of differentially expressed genes
<p>Abstract</p> <p>Background</p> <p>Microarrays have been widely used for the analysis of gene expression and several commercial platforms are available. The combined use of multiple platforms can overcome the inherent biases of each approach, and may represent an alternative that is complementary to RT-PCR for identification of the more robust changes in gene expression profiles.</p> <p>In this paper, we combined statistical and functional analysis for the cross platform validation of two oligonucleotide-based technologies, Affymetrix (AFFX) and Applied Biosystems (ABI), and for the identification of differentially expressed genes.</p> <p>Results</p> <p>In this study, we analysed differentially expressed genes after treatment of an ovarian carcinoma cell line with a cell cycle inhibitor. Treated versus control RNA was analysed for expression of 16425 genes represented on both platforms.</p> <p>We assessed reproducibility between replicates for each platform using CAT plots, and we found it high for both, with better scores for AFFX. We then applied integrative correlation analysis to assess reproducibility of gene expression patterns across studies, bypassing the need for normalizing expression measurements across platforms. We identified 930 genes as differentially expressed on AFFX and 908 on ABI, with ~80% common to both platforms. Despite the different absolute values, the range of intensities of the differentially expressed genes detected by each platform was similar. ABI showed a slightly higher dynamic range in FC values, which might be associated with its detection system. 62/66 genes identified as differentially expressed by Microarray were confirmed by RT-PCR.</p> <p>Conclusion</p> <p>In this study we present a cross-platform validation of two oligonucleotide-based technologies, AFFX and ABI. We found good reproducibility between replicates, and showed that both platforms can be used to select differentially expressed genes with substantial agreement. Pathway analysis of the affected functions identified themes well in agreement with those expected for a cell cycle inhibitor, suggesting that this procedure is appropriate to facilitate the identification of biologically relevant signatures associated with compound treatment. The high rate of confirmation found for both common and platform-specific genes suggests that the combination of platforms may overcome biases related to probe design and technical features, thereby accelerating the identification of trustworthy differentially expressed genes.</p
Early Th1 Response in Unprimed Nonobese Diabetic Mice to the Tyrosine Phosphatase-Like Insulinoma-Associated Protein 2, an Autoantigen in Type 1 Diabetes
Additional file 1: of KAOS: a new automated computational method for the identification of overexpressed genes
Protein expression of ZAP70 in DU4475 breast cancer cell line. Characterization by Western Blot analysis of ZAP-70 protein. Total cell lysated were subjected to Western Blot analysis using anti-ZAP70 (sc-1526) goat polyclonal antibody raised against a peptide mapping at the C-terminus of ZAP-70. 1) DU4475 (20Â ng); 2) MCF7 (20Â ng); 3) HisGST-ZAP70 recombinant protein (15Â ng), positive control. (PNG 68Â kb
Comprehensive kinome NGS targeted expression profiling by KING-REX
Abstract Background Protein kinases are enzymes controlling different cellular functions. Genetic alterations often result in kinase dysregulation, making kinases a very attractive class of druggable targets in several human diseases. Existing approved drugs still target a very limited portion of the human ‘kinome’, demanding a broader functional knowledge of individual and co-expressed kinase patterns in physiologic and pathologic settings. The development of novel rapid and cost-effective methods for kinome screening is therefore highly desirable, potentially leading to the identification of novel kinase drug targets. Results In this work, we describe the development of KING-REX (KINase Gene RNA EXpression), a comprehensive kinome RNA targeted custom assay-based panel designed for Next Generation Sequencing analysis, coupled with a dedicated data analysis pipeline. We have conceived KING-REX for the gene expression analysis of 512 human kinases; for 319 kinases, paired assays and custom analysis pipeline features allow the evaluation of 3′- and 5′-end transcript imbalances as readout for the prediction of gene rearrangements. Validation tests on cell line models harboring known gene fusions demonstrated a comparable accuracy of KING-REX gene expression assessment as in whole transcriptome analyses, together with a robust detection of transcript portion imbalances in rearranged kinases, even in complex RNA mixtures or in degraded RNA. Conclusions These results support the use of KING-REX as a rapid and cost effective kinome investigation tool in the field of kinase target identification for applications in cancer biology and other human diseases
Inhibitor affinity chromatography: Profiling the specific reactivity of the proteome with immobilized molecules
An inhibitor affinity chromatography (IAC) method has been developed for the analysis of inhibitor-protein interactions as a complementary approach to two-dimensional electrophoresis for functional proteomics studies. The procedure was developed utilizing a cyclin-dependent kinase 2 (Cdk2) inhibitor coupled to a polymeric resin and validated using a number of proteins interacting with the inhibitor with different specificities. Cdk2 and the other kinases bound and eluted from the resin in accordance with the relative in vitro potency of the inhibitor for each enzyme. Molecular interactions with the Cdk2 inhibitor were compared for HCT116 cancer cells versus rat pancreatic acinar cells. Proteins interacting with the ligand on the IAC matrix were identified by mass spectrometry. Isothermal calorimetry was used to confirm and quantitatively evaluate the binding affinity of some of the interacting proteins. Heat-shock protein (Hsp) 70 and Hsp27 were the strongest interactors with the inhibitor, displaying binding affinities comparable to those of Cdk2. These results support the use of IAC as a general method for the rapid identification and qualitative evaluation of the in vivo targets and potential side effects of a given drug
Cross platform microarray analysis for robust identification of differentially expressed genes-1
<p><b>Copyright information:</b></p><p>Taken from "Cross platform microarray analysis for robust identification of differentially expressed genes"</p><p>http://www.biomedcentral.com/1471-2105/8/S1/S5</p><p>BMC Bioinformatics 2007;8(Suppl 1):S5-S5.</p><p>Published online 8 Mar 2007</p><p>PMCID:PMC1885857.</p><p></p>ray precision within each microarray platform for the three replicates. CAT Plots describe the proportion of genes in common between replicates as function of list size. To generate CAT Plots on treated samples we used the lists of genes ranked b
Cross platform microarray analysis for robust identification of differentially expressed genes-2
<p><b>Copyright information:</b></p><p>Taken from "Cross platform microarray analysis for robust identification of differentially expressed genes"</p><p>http://www.biomedcentral.com/1471-2105/8/S1/S5</p><p>BMC Bioinformatics 2007;8(Suppl 1):S5-S5.</p><p>Published online 8 Mar 2007</p><p>PMCID:PMC1885857.</p><p></p>xpressed genes
Cross platform microarray analysis for robust identification of differentially expressed genes-0
<p><b>Copyright information:</b></p><p>Taken from "Cross platform microarray analysis for robust identification of differentially expressed genes"</p><p>http://www.biomedcentral.com/1471-2105/8/S1/S5</p><p>BMC Bioinformatics 2007;8(Suppl 1):S5-S5.</p><p>Published online 8 Mar 2007</p><p>PMCID:PMC1885857.</p><p></p>BrdU was added 30 min before harvesting and samples were processed for cell cycle analysis and BrdU incorporation analysis