Citations

The mitochondrial enzyme, dihydrolipoamide dehydrogenase (DLD), is essential for energy metabolism across eukaryotes. Here, conditions known to destabilize the DLD homodimer enabled the mouse, pig, or human enzyme to function as a protease. A catalytic dyad (S456–E431) buried at the homodimer interface was identified. Serine protease inhibitors and an S456A or an E431A point mutation abolished the proteolytic activity, whereas other point mutations at the homodimer interface domain enhanced the proteolytic activity, causing partial or complete loss of DLD activity. In humans, mutations in the DLD homodimer interface have been linked to an atypical form of DLD deficiency. These findings reveal a previously unrecognized mechanism by which certain DLD mutations can simultaneously induce the loss of a primary metabolic activity and the gain of a moonlighting proteolytic activity. The latter could contribute to the metabolic derangement associated with DLD deficiency and represent a target for therapies of this condition.

Abstract Purpose: To evaluate the effects of combining the multiple receptor tyrosine kinase inhibitor AEE788 and histone deacetylase (HDAC) inhibitors on cytotoxicity in a broad spectrum of cancer cell lines, including cisplatin-resistant ovarian adenocarcinoma cells. Experimental Design: Multiple cancer cell lines were treated in vitro using AEE788 and HDAC inhibitors (LBH589, LAQ824, and trichostatin A), either alone or in combination. Effects on cytotoxicity were determined by growth and morphologic assays. Effects of the combination on cell signaling pathways were determined by Western blotting, and the results were confirmed using pathway-specific inhibitors and transfection of constitutively active proteins. Results: Cell treatment with AEE788 and HDAC inhibitors (LBH589, LAQ824, and trichostatin A) in combination resulted in synergistic induction of apoptosis in non–small cell lung cancer (MV522, A549), ovarian cancer (SKOV-3), and leukemia (K562, Jurkat, and ML-1) cells and in OV202hp cisplatin-resistant human ovarian cancer cells. AEE788 alone or in combination with LBH589 inactivated mitogen-activated protein kinase (MAPK) and Akt cascades. Inhibition of either MAPK and/or Akt enhanced LBH589-induced apoptosis. In contrast, constitutively active MAPK or Akt attenuated LBH589 or LBH589 + AEE788–induced apoptosis. Increased apoptosis was correlated with enhanced reactive oxygen species (ROS) generation. The free radical scavenger N-acetyl-l-cysteine not only substantially suppressed the ROS accumulation but also blocked the induction of apoptosis mediated by cotreatment with AEE788 and LBH589. Conclusion: Collectively, these results show that MAPK and Akt inactivation along with ROS generation contribute to the synergistic cytotoxicity of the combination of AEE788 and HDAC inhibitors in a variety of human cancer cell types. This combination regimen warrants further preclinical and possible clinical study for a broad spectrum of cancers.

Abstract In this study, we observed loss of heterozygosity (LOH) in human chromosomal fragment 6q25.1 in sporadic lung cancer patients. LOH was observed in 65% of the 26 lung tumors examined and was narrowed down to a 2.2-Mb region. Single-nucleotide polymorphism (SNP) analysis of genes located within this region identified a candidate gene, termed p34. This gene, also designated as ZC3H12D, C6orf95, FLJ46041, or dJ281H8.1, carries an A/G nonsynonymous SNP at codon 106, which alters the amino acid from lysine to arginine. Nearly 73% of heterozygous lung cancer tissues with LOH and the A/G SNP also exhibited loss of the A allele. In vitro clonogenic and in vivo nude mouse studies showed that overexpression of the A allele exerts tumor suppressor function compared with the G allele. p34 is located within a recently mapped human lung cancer susceptibility locus, and association of the p34 A/G SNP was tested among these families. No significant association between the less frequent G allele and lung cancer susceptibility was found. Our results suggest that p34 may be a novel tumor suppressor gene involved in sporadic lung cancer but it seems not to be the candidate familial lung cancer susceptibility gene linked to chromosomal region 6q23-25. [Cancer Res 2007;67(1):93–9]

Abstract DNA microarray has been widely used in cancer research to better predict clinical outcomes and potentially improve patient management. The new approach provides accurate tumor classification and outcome predictions, such as tumor stage, metastatic status, and patient survival, and offers some hope for individualized medicine. However, growing evidence suggests that gene-based prediction is not stable and little is known about the prediction power of gene expression profiles compared with well-known clinical and pathologic predictors. This review summarized up-to-date publications in microarray-based lung cancer clinical outcome prediction and conducted secondary analyses for those with sufficient sample sizes and associated clinical information. Among the most commonly used analytic approaches, unsupervised clustering mainly recaptures tumor histology and provides variable degrees of prediction for tumor stage, lymph node status, or survival. Overall, most studies lack an independent validation. Supervised learning and testing generally offer a better prediction. Noted is that when conventional predictors of age, gender, stage, cell type, and tumor grade are considered collectively, the predictive advantage of the gene expression profiles diminishes. We conclude that outcome prediction from gene expression signatures selected by current analytic approaches can be mostly explained by well-known conventional predictors, particularly histologic subtype and grade of differentiation. A strategy for establishing independent or more accurate signatures is commented. (Cancer Epidemiol Biomarkers Prev 2006;15(11):2063–8)

AbstractBackground: Laboratory testing in suspected α-1-antitrypsin (A1AT) deficiency involves analysis of A1AT concentrations and identification of specific alleles by genotyping or phenotyping. The purpose of this study was to define and evaluate a strategy that provides reliable laboratory evaluation of A1AT deficiency.Methods: Samples from 512 individuals referred for A1AT phenotype analysis were analyzed by quantification, phenotype, and genotype. A1AT concentrations were measured by nephelometry. Phenotype analysis was performed by isoelectric focusing electrophoresis. The genotype assay detected the S and Z deficiency alleles by a melting curve analysis.Results: Of the 512 samples analyzed, 2% of the phenotype and genotype results were discordant. Among these 10 discordant results, 7 were attributed to phenotyping errors. On the basis of these data we formulated an algorithm, according to which we analyzed samples by genotyping and quantification assays, with a reflex to phenotyping when the genotype and quantification results were not concordant. Retrospective analyses demonstrated that 4% of samples submitted for genotype and quantitative analysis were reflexed to phenotyping. Of the reflexed samples, phenotyping confirmed the genotype result in 85% of cases. In the remaining 15%, phenotyping provided further information, including identifying rare deficiency alleles and suggesting the presence of a null allele, and allowed for a more definitive interpretation of the genotype result.Conclusions: The combination of genotyping and quantification, with a reflex to phenotyping, is the optimal strategy for the laboratory evaluation of A1AT deficiency.

Abstract This study was undertaken to characterize preclinical cytotoxic interactions for human malignancies between the multikinase inhibitor sorafenib (BAY 43-9006) and proteasome inhibitors bortezomib or MG132. Multiple tumor cell lines of varying histiotypes, including A549 (lung adenocarcinoma), 786-O (renal cell carcinoma), HeLa (cervical carcinoma), MDA-MB-231 (breast), K562 (chronic myelogenous leukemia), Jurkat (acute T-cell leukemia), MEC-2 (B-chronic lymphocytic leukemia), and U251 and D37 (glioma), as well as cells derived from primary human glioma tumors that are likely a more clinically relevant model were treated with sorafenib or bortezomib alone or in combination. Sorafenib and bortezomib synergistically induced a marked increase in mitochondrial injury and apoptosis, reflected by cytochrome c release, caspase-3 cleavage, and poly(ADP-ribose) polymerase degradation in a broad range of solid tumor and leukemia cell lines. These findings were accompanied by several biochemical changes, including decreased phosphorylation of vascular endothelial growth factor receptor-2, platelet-derived growth factor receptor-β, and Akt and increased phosphorylation of stress-related c-Jun NH2-terminal kinase (JNK). Inhibition of Akt was required for synergism, as a constitutively active Akt protected cells against apoptosis induced by the combination. Alternatively, the JNK inhibitor SP600125 could also protect cells from apoptosis induced by the combination, indicating that both inhibition of Akt and activation of JNK were required for the synergism. These findings show that sorafenib interacts synergistically with bortezomib to induce apoptosis in a broad spectrum of neoplastic cell lines and show an important role for the Akt and JNK pathways in mediating synergism. Further clinical development of this combination seems warranted. [Mol Cancer Ther 2006;5(9):2378–87]

Vascular endothelial growth factor-A (VEGF) is critical for angiogenesis but fails to induce neovascularization in ischemic tissue lesions in mice lacking endothelial nitric oxide synthase (eNOS). VEGF receptor-2 (VEGFR-2) is critical for angiogenesis, although little is known about the precise role of endothelial VEGFR-1 and its downstream effectors in this process. Here we have used a chimeric receptor approach in which the extracellular domain of the epidermal growth factor receptor was substituted for that of VEGFR-1 (EGLT) or VEGFR-2 (EGDR) and transduced into primary cultures of human umbilical vein endothelial cells (HUVECs) using a retroviral system. Activation of HUVECs expressing EGLT or EGDR induced rapid phosphorylation of eNOS at Ser1177, release of NO, and formation of capillary networks, similar to VEGF. Activation of eNOS by VEGFR-1 was dependent on Tyr794 and was mediated via phosphatidylinositol 3-kinase, whereas VEGFR-2 Tyr951 was involved in eNOS activation via phospholipase Cγ1. Consistent with these findings, the VEGFR-1–specific ligand placenta growth factor-1 activated phosphatidylinositol 3-kinase and VEGF-E, which is selective for VEGFR-2–activated phospholipase Cγ1. Both VEGFR-1 and VEGFR-2 signal pathways converged on Akt, as dominant-negative Akt inhibited the NO release and in vitro tube formation induced following activation of EGLT and EGDR. The identification Tyr794 of VEGFR-1 as a key residue in this process provides direct evidence of endothelial VEGFR-1 in NO-driven in vitro angiogenesis. These studies provide new sites of modulation in VEGF-mediated vascular morphogenesis and highlight new therapeutic targets for management of vascular diseases.

A study of the statistics of ultrasound speckle indicates that the noise-to-signal ratio (NSR) of the echo envelope peaks (EEP) in a B scan is monotonically related to the variance of the mean power of the backscattered echoes. If it is assumed that the backscattered echoes all have the same mean power, the NSR of the EEP’s in a B scan will be expected to reach a theoretical minimum value NSR0 (0.40∼0.42). In practical situations, the variance of the mean power of the echoes is increased due to the presence of both attenuation (including beam spreading) and the spatial variation in the backscattering cross section (BCS) of the tissue. Accordingly, the measured value of the NSR of the EEP’s is expected to be greater than the NSR0. In principle, the effects of beam pattern and the attenuation can be compensated for by system calibration and a depth-related gain function, respectively. The attenuation coefficient of the tissue may then be obtained by adjusting the gain function to minimize the NSR of the EEP’s. Due to the random nature of the heterogeneity of diseased tissue, the effect of the variation in the BCS, however, cannot be compensated for by the depth-related gain function. Therefore, the minimum value of the NSR indicates the spatial variation in the BCS and may finally correlate to the disease state of the tissue.