Modulation of cell death in the tumor micro environment

The microenvironment of solid human tumors is characterized by heterogeneity in oxygenation. Hypoxia arises early in the process of tumor development because rapidly proliferating tumor cells outgrow the capacity of the host vasculature. Formation of solid tumors thus requires coordination of angiogenesis with continued tumor cell proliferation. However, despite such neovascularization, hypoxia is persistent and frequently found in tumors at the time of diagnosis. Tumors with low oxygenation have a poor prognosis, and strong evidence suggests this is because of the effects of hypoxia on malignant progression, angiogenesis, metastasis, and therapy resistance. The presence of viable hypoxic cells is likely a reflection of the development of hypoxia tolerance resulting from modulation of cell death in the microenvironment. This acquired feature has been explained on the basis of clonal selection-the hypoxic microenvironment selects cells capable of surviving in the absence of normal oxygen availability. However, the persistence and frequency of hypoxia in solid tumors raises a second potential explanation. We suggest that stable microregions of hypoxia may play a positive role in tumor growth. Although hypoxia inhibits cell proliferation and in tumor cells will eventually induce cell death, hypoxia also provides angiogenic and metastatic signals. The development of hypoxia tolerance will thus allow prolonged survival in the absence of oxygen and generation of a persistent angiogenic signal. We will discuss the concept of hypoxia tolerance and review mechanisms used by cancer cells to acquire this phenotype. The concept of hypoxia tolerance has important implications for current and future therapeutic approaches. Most therapeutic efforts to combat hypoxia have focused on targeting the presence of hypoxia itself. Our hypothesis predicts that targeting the biological responses to hypoxia and the pathways leading to hypoxia tolerance may also be attractive therapeutic strategies.Copyright 2003, Elsevier Science (USA). All rights reserved

Most vital segment barriers

We study continuous analogues of "vitality" for discrete network flows/paths, and consider problems related to placing segment barriers that have highest impact on a flow/path in a polygonal domain. This extends the graph-theoretic notion of "most vital arcs" for flows/paths to geometric environments. We give hardness results and efficient algorithms for various versions of the problem, (almost) completely separating hard and polynomially-solvable cases

Increased entropy of signal transduction in the cancer metastasis phenotype

Studies into the statistical properties of biological networks have led to important biological insights, such as the presence of hubs and hierarchical modularity. There is also a growing interest in studying the statistical properties of networks in the context of cancer genomics. However, relatively little is known as to what network features differ between the cancer and normal cell physiologies, or between different cancer cell phenotypes. Based on the observation that frequent genomic alterations underlie a more aggressive cancer phenotype, we asked if such an effect could be detectable as an increase in the randomness of local gene expression patterns. Using a breast cancer gene expression data set and a model network of protein interactions we derive constrained weighted networks defined by a stochastic information flux matrix reflecting expression correlations between interacting proteins. Based on this stochastic matrix we propose and compute an entropy measure that quantifies the degree of randomness in the local pattern of information flux around single genes. By comparing the local entropies in the non-metastatic versus metastatic breast cancer networks, we here show that breast cancers that metastasize are characterised by a small yet significant increase in the degree of randomness of local expression patterns. We validate this result in three additional breast cancer expression data sets and demonstrate that local entropy better characterises the metastatic phenotype than other non-entropy based measures. We show that increases in entropy can be used to identify genes and signalling pathways implicated in breast cancer metastasis. Further exploration of such integrated cancer expression and protein interaction networks will therefore be a fruitful endeavour.Comment: 5 figures, 2 Supplementary Figures and Table

The breast cancer somatic 'muta-ome': tackling the complexity

Acquired somatic mutations are responsible for approximately 90% of breast tumours. However, only one somatic aberration, amplification of the HER2 locus, is currently used to define a clinical subtype, one that accounts for approximately 10% to 15% of breast tumours. In recent years, a number of mutational profiling studies have attempted to further identify clinically relevant mutations. While these studies have confirmed the oncogenic or tumour suppressor role of many known suspects, they have exposed complexity as a main feature of the breast cancer mutational landscape (the 'muta-ome'). The two defining features of this complexity are (a) a surprising richness of low-frequency mutants contrasting with the relative rarity of high-frequency events and (b) the relatively large number of somatic genomic aberrations (approximately 20 to 50) driving an average tumour. Structural features of this complex landscape have begun to emerge from follow-up studies that have tackled the complexity by integrating the spectrum of genomic mutations with a variety of complementary biological knowledge databases. Among these structural features are the growing links between somatic gene disruptions and those conferring breast cancer risk, mutually exclusive coexistence and synergistic mutational patterns, and a clearly non-random distribution of mutations implicating specific molecular pathways in breast tumour initiation and progression. Recognising that a shift from a gene-centric to a pathway-centric approach is necessary, we envisage that further progress in identifying clinically relevant genomic aberration patterns and associated breast cancer subtypes will require not only multi-dimensional integrative analyses that combine mutational and functional profiles, but also larger profiling studies that use second- and third-generation sequencing technologies in order to fill out the important gaps in the current mutational landscape

The atm-1 gene is required for genome stability in Caenorhabditis elegans

The Ataxia-telangiectasia-mutated (ATM) gene in humans was identified as the basis of a rare autosomal disorder leading to cancer susceptibility and is now well known as an important signal transducer in response to DNA damage. An approach to understanding the conserved functions of this gene is provided by the model system, Caenorhabditis elegans. In this paper we describe the structure and loss of function phenotype of the ortholog atm-1. Using bioinformatic and molecular analysis we show that the atm-1 gene was previously misannotated. We find that the transcript is in fact a product of three gene predictions, Y48G1BL.2 (atm-1), K10E9.1, and F56C11.4 that together make up the complete coding region of ATM-1. We also characterize animals that are mutant for two available knockout alleles, gk186 and tm5027. As expected, atm-1 mutant animals are sensitive to ionizing radiation. In addition, however, atm-1 mutants also display phenotypes associated with genomic instability, including low brood size, reduced viability and sterility. We document several chromosomal fusions arising from atm-1 mutant animals. This is the first time a mutator phenotype has been described for atm-1 in C. elegans. Finally we demonstrate the use of a balancer system to screen for and capture atm-1-derived mutational events. Our study establishes C. elegans as a model for the study of ATM as a mutator potentially leading to the development of screens to identify therapeutic targets in humans

The Raf-1 inhibitor GW5074 and dexamethasone suppress sidestream smoke-induced airway hyperresponsiveness in mice

<p>Abstract</p> <p>Background</p> <p>Sidestream smoke is closely associated with airway inflammation and hyperreactivity. The present study was designed to investigate if the Raf-1 inhibitor GW5074 and the anti-inflammatory drug dexamethasone suppress airway hyperreactivity in a mouse model of sidestream smoke exposure.</p> <p>Methods</p> <p>Mice were repeatedly exposed to smoke from four cigarettes each day for four weeks. After the first week of the smoke exposure, the mice received either dexamethasone intraperitoneally every other day or GW5074 intraperitoneally every day for three weeks. The tone of the tracheal ring segments was recorded with a myograph system and concentration-response curves were obtained by cumulative administration of agonists. Histopathology was examined by light microscopy.</p> <p>Results</p> <p>Four weeks of exposure to cigarette smoke significantly increased the mouse airway contractile response to carbachol, endothelin-1 and potassium. Intraperitoneal administration of GW5074 or dexamethasone significantly suppressed the enhanced airway contractile responses, while airway epithelium-dependent relaxation was not affected. In addition, the smoke-induced infiltration of inflammatory cells and mucous gland hypertrophy were attenuated by the administration of GW5074 or dexamethasone.</p> <p>Conclusion</p> <p>Sidestream smoke induces airway contractile hyperresponsiveness. Inhibition of Raf-1 activity and airway inflammation suppresses smoking-associated airway hyperresponsiveness.</p

The Raf-1 inhibitor GW5074 and dexamethasone suppress sidestream smoke-induced airway hyperresponsiveness in mice

© 2008 Lei et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution Licens