Selection with melphalan or paclitaxel (Taxol) yields variants with different patterns of multidrug resistance, integrin expression and in vitro invasiveness

A melphalan-resistant variant (Roswell Park Memorial Institute (RPMI)-2650M1) and a paclitaxel-resistant variant (RPMI-1650Tx) of the drug-sensitive human nasal carcinoma cell line, RPMI-2650. were established. The multidrug resistance (MDR) phenotype in the RPMI-2650Tx appeared to be P-glycoprotein (PgP)-mediated. Overexpression of multidrug resistant protein (MRP) family members was observed in the RPMI-2650M1 cells, which were also much more invasive in vitro than the parental cell line or the paclitaxel-resistant variant. Increased expression of alpha (2), alpha (5), alpha (6), beta (1) and beta (4) integrin subunits, decreased expression of alpha (4) integrin subunit, stronger adhesion to collagen type IV, laminin, fibronectin and matrigel, increased expression of MMP-2 and MMP-9 and significant motility compared with the parental cells were observed, along with a high invasiveness in the RPMI-7650M1 cells. Decreased expression of the alpha (2) integrin subunit, decreased attachment to collagen type IV, absence of cytokeratin 18 expression, no detectable expression of gelatin-degrading proteases and poor motility may be associated with the non-invasiveness of the RPMI-2650Tx variant. These results suggest that melphalan exposure can result in not only a MDR phenotype. but could also make cancer cells more invasive, whereas paclitaxel exposure resulted in MDR without increasing the in vitro invasiveness in the RPMI-2650 cells. (C) 2001 Elsevier Science Ltd. All rights reserved.

Interleukin-8 signaling promotes androgen-independent proliferation of prostate cancer cells via induction of androgen receptor expression and activation

The aim of our study was to assess the importance of the CXC chemokine and interleukin (IL)-8 in promoting the transition of prostate cancer (CaP) to the androgen-independent state. Stimulation of the androgen-dependent cell lines, LNCaP and 22Rv1, with exogenous recombinant human interleukin-8 (rh-IL-8) increased androgen receptor (AR) gene expression at the messenger RNA (mRNA) and protein level, assessed by quantitative polymerase chain reaction and immunoblotting, respectively. Using an androgen response element-luciferase construct, we demonstrated that rh-IL-8 treatment also resulted in increased AR transcriptional activity in both these cell lines, and a subsequent upregulation of prostate-specific antigen and cyclin-dependent kinase 2 mRNA transcript levels in LNCaP cells. Blockade of CXC chemokine receptor-2 signaling using a small molecule antagonist (AZ10397767) attenuated the IL-8-induced increases in AR expression and transcriptional activity. Furthermore, in 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assays, coadministration of AZ10397767 reduced the viability of LNCaP and 22Rv1 cells exposed to bicalutamide. Our data show that IL-8 signaling increases AR expression and promotes ligand-independent activation of this receptor in two androgen-dependent cell lines, describing two mechanisms by which this chemokine may assist in promoting the transition of CaP to the androgen-independent state. In addition, our data show that IL-8-promoted regulation of the AR attenuates the effectiveness of the AR antagonist bicalutamide in reducing CaP cell viability.

SRIF receptor subtype expression and involvement in positive and negative contractile effects of somatostatin-14 (SRIF-14) in ventricular cardiomyocytes.

Background/Aims: Somatostatin-14 (SRIF-14), a neuropeptide co-stored with acetylcholine in the cardiac parasympathetic innervation, exerts both positive and negative influences directly on contraction of ventricular cardiomyocytes, indicative of involvement of more than one of five known SRIF (SSTR) receptor subtypes. The aim was to characterize receptor subtype expression in adult rat ventricular cardiomyocytes and to investigate the influence of a series of SRIF (SSTR) subtype-selective agonists on contractile parameters. Methods: mRNA and protein expression of each receptor subtype were quantified by RT-PCR and immunoblotting respectively; for contraction studies, cells were stimulated at 0.5 Hz under basal conditions and in the presence of isoprenaline (ISO, 10-8M). Results: all five SRIF (SSTR) receptor subtypes were expressed in cardiomyocytes although SRIF1A (SSTR2) and SRIF2A (SSTR1) were less abundant than the other subtypes. L803087 (10-8M), a SRIF2B (SSTR4) agonist, attenuated ISO-stimulated peak contractile amplitude and prolonged relaxation time (T50). L796778 (10-7M), a SRIF1C (SSTR3) agonist, augmented basal and ISO-stimulated peak contractile amplitude; L779976 (10-8M) and L817818 (10-9M), agonists at SRIF1A (SSTR2) and SRIF1B (SSTR5) receptors, respectively, also augmented ISO-stimulated peak amplitude. Conclusion: these data support involvement of SRIF2B (SSTR4) receptors in the negative contractile effects of SRIF-14, while one or more of the three SRIF1 receptor subtypes (SSTR2, 3 or 5) may contribute to the positive contractile effects of SRIF-14.

MMP expression and abnormal lung permeability are important determinants of outcome in IPF

Matrix metalloproteinases (MMPs) degrade all of the extracellular matrix components of the intersititium and may play a role in abnormal alveolar permeability, which is a feature of idiopathic pulmonary fibrosis (IPF). The aims of the present study were to evaluate MMP protein levels in patients with IPF and determine any relationship to treatment and markers of permeability.

A Ligand predication tool based on modeling and reasoning with imprecise probabilistic knowledge

Ligand prediction has been driven by a fundamental desire to understand more about how biomolecules recognize their ligands and by the commercial imperative to develop new drugs. Most of the current available software systems are very complex and time-consuming to use. Therefore, developing simple and efficient tools to perform initial screening of interesting compounds is an appealing idea. In this paper, we introduce our tool for very rapid screening for likely ligands (either substrates or inhibitors) based on reasoning with imprecise probabilistic knowledge elicited from past experiments. Probabilistic knowledge is input to the system via a user-friendly interface showing a base compound structure. A prediction of whether a particular compound is a substrate is queried against the acquired probabilistic knowledge base and a probability is returned as an indication of the prediction. This tool will be particularly useful in situations where a number of similar compounds have been screened experimentally, but information is not available for all possible members of that group of compounds. We use two case studies to demonstrate how to use the tool.

A survey of formalisms for representing and reasoning with scientific knowledge

With the rapid growth in the quantity and complexity of scientific knowledge available for scientists, and allied professionals, the problems associated with harnessing this knowledge are well recognized. Some of these problems are a result of the uncertainties and inconsistencies that arise in this knowledge. Other problems arise from heterogeneous and informal formats for this knowledge. To address these problems, developments in the application of knowledge representation and reasoning technologies can allow scientific knowledge to be captured in logic-based formalisms. Using such formalisms, we can undertake reasoning with the uncertainty and inconsistency to allow automated techniques to be used for querying and combining of scientific knowledge. Furthermore, by harnessing background knowledge, the querying and combining tasks can be carried out more intelligently. In this paper, we review some of the significant proposals for formalisms for representing and reasoning with scientific knowledge.

Modeling and reasoning with qualitative comparative clinical knowledge

The number of clinical trials reports is increasing rapidly due to a large number of clinical trials being conducted; it, therefore, raises an urgent need to utilize the clinical knowledge contained in the clinical trials reports. In this paper, we focus on the qualitative knowledge instead of quantitative knowledge. More precisely, we aim to model and reason with the qualitative comparison (QC for short) relations which consider qualitatively how strongly one drug/therapy is preferred to another in a clinical point of view. To this end, first, we formalize the QC relations, introduce the notions of QC language, QC base, and QC profile; second, we propose a set of induction rules for the QC relations and provide grading interpretations for the QC bases and show how to determine whether a QC base is consistent. Furthermore, when a QC base is inconsistent, we analyze how to measure inconsistencies among QC bases, and we propose different approaches to merging multiple QC bases. Finally, a case study on lowering intraocular pressure is conducted to illustrate our approaches.