Faculty Bibliography

The immune response to cancer has been long recognized, including both innate and adaptive responses, showing that the immune system can recognize protein products of genetic and epigenetic changes in transformed cells. The accumulation of antigen-specific T cells within the tumor, the draining lymph node, and the circulation, either in newly diagnosed patients or resultant from experimental immunotherapy, proves that tumors produce antigens and that priming occurs. Unfortunately, just as obviously, tumors grow, implying that anti-tumor immune responses are either not sufficiently vigorous to eliminate the cancer or that anti-tumor immunity is suppressed. Both possibilities are supported by current data. In experimental animal models of cancer and also in patients, systemic immunity is usually not dramatically suppressed, because tumor-bearing animals and patients develop T-cell-dependent immune responses to microbes and to either model antigens or experimental cancer vaccines. However, inhibition of specific anti-tumor immunity is common, and several possible explanations of tolerance to tumor antigens or tumor-induced immunesuppression have been proposed. Inhibition of effective anti-tumor immunity results from the tumor or the host response to tumor growth, inhibiting the activation, differentiation, or function of anti-tumor immune cells. As a consequence, anti-tumor T cells cannot respond productively to developmental, targeting, or activation cues. While able to enhance the number and phenotype of anti-tumor T cells, the modest success of immunotherapy has shown the necessity to attempt to reverse tolerance in anti-tumor T cells, and the vanguard of experimental therapy now focuses on vaccination in combination with blockade of immunosuppressive mechanisms. This review discusses several potential mechanisms by which anti-tumor T cells may be inhibited in function

Triazole resistance in Aspergillus fumigatus is an uncommon but rising phenomenon. Susceptibility testing is rarely performed and can take 48 h or longer, which is an impediment to effective therapy. Molecular diagnostic probing of well-defined resistance mechanisms, which serve as surrogate markers, provides an alternative approach to rapidly (within hours) and efficiently identify resistant strains. The mechanisms of triazole resistance in A. fumigatus are limited to amino acid substitutions in the drug target Cyp51A and include amino acid substitutions at the positions Gly 54, Gly 138, Met 220, and Leu 98, coupled with a tandem repetition in the gene promoter. We report the development of a real-time PCR assay utilizing molecular beacons to assess triazole resistance markers in A. fumigatus. When combined in a multiplex platform, the assay provides a comprehensive evaluation of drug resistance in A. fumigatus.

BACKGROUND: Diabetes impairs the ability of tissue to respond adequately to ischemia. The underlying mechanisms contributing to this impaired response remain unknown. Because increases in apoptosis have been linked to a spectrum of diabetic complications, the authors examined whether programmed cell death is involved in the pathogenesis of poor diabetic tissue responses to ischemia. METHODS: Analysis for apoptosis and levels of proaptotic protein, p53, were performed on streptozocin-induced diabetic mice and wild-type controls in a murine model of soft-tissue ischemia (n = 6). In vitro, chronic hyperglycemic culture conditions were used to test inducibility and reversibility of the diabetic phenotype. Small interfering RNA was used to assess the role of p53. RESULTS: Ischemia-induced apoptosis and p53 levels were increased significantly in diabetic dermal fibroblasts both in vivo and in vitro. Chronic hyperglycemic culture was sufficient to induce the increased apoptotic phenotype, and this was not reversible with long-term normoglycemic conditions. Blocking p53 with small interfering RNA resulted in significant protection against ischemic apoptosis. CONCLUSIONS: These findings suggest that diabetes causes an increased apoptotic response to ischemia through a p53-mediated mechanism. This increase is not reversible by exposure to low-glucose conditions. This suggests that glycemic control alone will be unable to prevent tissue necrosis in diabetic patients and suggests novel therapeutic strategies for this condition

A detailed phylogenetic analysis of tetraspanins from 10 fully sequenced metazoan genomes and several fungal and protist genomes gives insight into their evolutionary origins and organization. Our analysis suggests that the superfamily can be divided into four large families. These four families-the CD family, CD63 family, uroplakin family, and RDS family-are further classified as consisting of several ortholog groups. The clustering of several ortholog groups together, such as the CD9/Tsp2/CD81 cluster, suggests functional relatedness of those ortholog groups. The fact that our studies are based on whole genome analysis enabled us to estimate not only the phylogenetic relationships among the tetraspanins, but also the first appearance in the tree of life of certain tetraspanin ortholog groups. Taken together, our data suggest that the tetraspanins are derived from a single (or a few) ancestral gene(s) through sequence divergence, rather than convergence, and that the majority of tetraspanins found in the human genome are vertebrate (21 instances), tetrapod (4 instances), or mammalian (6 instances) inventions

The last several decades have witnessed a vast accumulation of biological data and data analysis. Many of these data sets represent only a small fraction of the system's behavior, making the visualization of full system behavior difficult. A more complete understanding of a biological system is gained when different types of data (and/or conclusions drawn from the data) are integrated into a larger-scale representation or model of the system. Ideally, this type of model is consistent with all available data about the system, and it is then used to generate additional hypotheses to be tested. Computer-based methods intended to formulate models that integrate various events and to test the consistency of these models with respect to the laboratory-based observations on which they are based are potentially very useful. In addition, in contrast to informal models, the consistency of such formal computer-based models with laboratory data can be tested rigorously by methods of formal verification. We combined two formal modeling approaches in computer science that were originally developed for non-biological system design. One is the inter-object approach using the language of live sequence charts (LSCs) with the Play-Engine tool, and the other is the intra-object approach using the language of statecharts and Rhapsody as the tool. Integration is carried out using InterPlay, a simulation engine coordinator. Using these tools, we constructed a combined model comprising three modules. One module represents the early lineage of the somatic gonad of C. elegans in LSCs, while a second more detailed module in statecharts represents an interaction between two cells within this lineage that determine their developmental outcome. Using the advantages of the tools, we created a third module representing a set of key experimental data using LSCs. We tested the combined statechart-LSC model by showing that the simulations were consistent with the set of experimental LSCs. This small-scale modular example demonstrates the potential for using similar approaches for verification by exhaustive testing of models by LSCs. It also shows the advantages of these approaches for modeling biology

We reported earlier that exposure of rats to 3-methylcholanthrene (MC) causes sustained induction of hepatic cytochrome P450 (CYP)1A expression for up to 45 days by mechanisms other than persistence of the parent MC (Moorthy, J. 2000. Pharmacology. Exp. Ther. 294, 313-322). The CYP1A genes are members of the Ah gene battery that also encode CYP1B1 and phase II enzymes such as glutathione S-transferase (GST-alpha), UDP glucuronyl transferase (UGT)1A, NAD(P)H (nicotinamide adenine dinucleotide phosphate, reduced):quinone oxidoreductase I (NQO1), aldehyde dehydrogenase (ALDH), etc. Therefore, in this investigation, we tested the hypothesis that MC elicits persistent induction of CYP1B1 and phase II genes, which are in part regulated by the Ah receptor (AHR). Female Sprague-Dawley rats were treated with MC (100 mumol/kg), ip, once daily for 4 days, and expression of CYP1B1 and several phase II (e.g., GST-alpha, NQO1) genes and their corresponding proteins were determined in lung and liver. The major finding was that MC persistently induced (3- to 10-fold) the expression of several phase II enzymes, including GST-alpha, NQO1, UGT1A1, ALDH, and epoxide hydrolase in both tissues for up to 28 days. However, MC did not elicit sustained induction of CYP1B1. Our results thus support the hypothesis that MC elicits coordinated and sustained induction of phase II genes presumably via persistent activation of the AHR, a phenomenon that may have implications for chemical-induced carcinogenesis and chemopreventive strategies in humans.

Glucocorticoids (GCs) display both protective and destructive effects in the nervous system. In excess, GCs produce neuronal damage after stress or brain injury; however, the neuroprotective effects of adrenal steroids also have been reported. The mechanisms that account for the positive actions are not well understood. Here we report that GCs can selectively activate Trk receptor tyrosine kinases after in vivo administration in the brain and in cultures of hippocampal and cortical neurons. Trk receptors are normally activated by neurotrophins, such as NGF and brain-derived neurotrophic factor, but the activation of Trk receptors by GCs does not depend on increased production of neurotrophins. Other tyrosine kinase receptors, such as EGF and FGF receptors, were not activated by GCs. The ability of GCs to increase Trk receptor activity resulted in the neuroprotection of neurons deprived of trophic support and could be modulated by steroid-converting enzymes. Pharmacological and shRNA experiments indicate that Trk receptor activation by GCs depends on a genomic action of the GC receptor. The ability of GCs to promote Trk receptor activity represents a molecular mechanism that integrates the actions of GCs and neurotrophins