The hallmarks of cancer.

The human genome holds an extraordinary trove of information about human development, physiology, medicine and evolution. Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome. We also present an initial analysis of the data, describing some of the insights that can be gleaned from the sequence.

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Initial sequencing and analysis of the human genome.

The emergence of order in natural systems is a constant source of inspiration for both physical and biological sciences. While the spatial order characterizing for example the crystals has been the basis of many advances in contemporary physics, most complex systems in nature do not offer such high degree of order. Many of these systems form complex networks whose nodes are the elements of the system and edges represent the interactions between them. 
Traditionally complex networks have been described by the random graph theory founded in 1959 by Paul Erdohs and Alfred Renyi. One of the defining features of random graphs is that they are statistically homogeneous, and their degree distribution (characterizing the spread in the number of edges starting from a node) is a Poisson distribution. In contrast, recent empirical studies, including the work of our group, indicate that the topology of real networks is much richer than that of random graphs. In particular, the degree distribution of real networks is a power-law, indicating a heterogeneous topology in which the majority of the nodes have a small degree, but there is a significant fraction of highly connected nodes that play an important role in the connectivity of the network. 
The scale-free topology of real networks has very important consequences on their functioning. For example, we have discovered that scale-free networks are extremely resilient to the random disruption of their nodes. On the other hand, the selective removal of the nodes with highest degree induces a rapid breakdown of the network to isolated subparts that cannot communicate with each other. 
The non-trivial scaling of the degree distribution of real networks is also an indication of their assembly and evolution. Indeed, our modeling studies have shown us that there are general principles governing the evolution of networks. Most networks start from a small seed and grow by the addition of new nodes which attach to the nodes already in the system. This process obeys preferential attachment: the new nodes are more likely to connect to nodes with already high degree. We have proposed a simple model based on these two principles wich was able to reproduce the power-law degree distribution of real networks. Perhaps even more importantly, this model paved the way to a new paradigm of network modeling, trying to capture the evolution of networks, not just their static topology.

/pdf/statistical-mechanics-of-complex-networks-1zfjpvxipu.pdf

Statistical mechanics of complex networks

A genetic model for colorectal tumorigenesis

http://www.maths.qmul.ac.uk/%7Elatora/report_06.pdf

Complex networks: Structure and dynamics

In this chapter, we will review how signal transduction pathways have been assembled in the past, bringing us to our present understanding of this area of research. The methods employed have relied heavily upon the genetics of yeast, worms, flies, mice, and humans. The use of second site suppressors and epistasis has permitted the detection of interacting elements and the sequence of genetic activities. Biochemistry has been employed to elucidate metabolic pathways, demonstrate protein complexes, and identify functions of gene products. The tools of molecular biology-knocking concentration of protein products down or up-have been helpful to trace the function of pathways in vivo. The study of disease states has led to the identification of a set of altered genes and helped define a network that is altered and gives rise to the disease. We will also discuss some serious limitations in these approaches. After reviewing how signal transduction pathways are constructed and investigated, we will turn our attention to an example that demonstrates the inter-relationships between pathways and the regulation of a specific set of pathways. We will examine how the p53 pathway in responding to stress shuts down the AKT-1 and mTOR pathways so as to limit the error frequency of cell growth and division during a stressful time where homeostatic mechanisms are required to respond and increase the fidelity of these processes.

Reconstructing signal transduction pathways: challenges and opportunities.

A series of congenic mice on the BALB/c genetic background have been employed to localize a teratocarcinoma transplantation rejection locus, Gt-1, to the K side of the H-2 locus on chromosome 17. Previous studies have placed the Gt-1
sv allele about 8 centimorgans away from the H-2
b or H-2
bv1 locus. Teratocarcinomas derived from 129/sv mice, Gt-1
sv (H-2K

bv1/H-2D

bv1), are rejected by BALB/c (H-2K
d/H-2Dd) and BALB-G mice (H-2K
d/H2D-b, but form tumors in BALB-B (H-2K
b/H2D
b) and BALB/5R5 mice (H-2K
b/H2D
d). In the reciprocal tumor-rejection test, a BALB/c teratocarcinoma was rejected by immunized BALB·B mice, but formed tumors in the immunized isogenic BALB/c mouse. These studies demonstrate the reciprocal expression of two Gt-1 alleles, one Gt-1
c, in BALB/c mice, and the other, Gt-1
sv, in the congenic BALB·B mice. Shedlovsky and co-workers have placed the Gt-1 locus in a similar location on the K side of the H-2 locus on chromosome 17.

Teratocarcinoma transplantation rejection loci: genetic localization of the Gt-1 locus on chromosome 17 and the expression of alternate alleles.

Oncogenes and cell proliferation

The p53 protein was first uncovered as a tumor antigen. Animals bearing tumors initiated by some viruses or transformed cells produced antibodies directed against a cellular protein of 53,000 Daltons.1,2 The p53 protein was also shown to form a complex with the viral oncogenic products from SV40,1,2 the adenoviruses,3 and subsequently the human papilloma viruses.4 The early c-DNA clones of the mouse or human p53 gene cooperated with other oncogenes to transform cells in culture,5,6 but these c-DNAs proved to encode a mutant p53 protein that acted as a dominant negative mutation and that had properties of a gain-of-function mutation.7 Later the wild-type p53 gene was shown to function as a tumor suppressor gene in cell culture8 and in human tumors.9 From attempts to understand the functions of the p53 protein it became apparent that it responded to a wide variety of cellular stresses, such as DNA damage, resulting in the modification of the p53 protein and increased concentrations of the p53 protein in a cell. This activated the p53 protein so it functioned as a transcription factor. The genes regulated by the p53 protein form the p53 pathway10 and can result in cell cycle arrest, apoptosis, and cell senescence. These observations helped to explain how the p53 protein functioned as a tumor suppressor by eliminating cells that make errors or mutations at a high rate in attempting to duplicate themselves under conditions of stress. In this way, p53 functions act to prevent cancers over a lifetime of exposures to stress. Just how important this process is to understanding cancer origins comes from the growing awareness that p53 gene mutations are the most common type of mutations observed in a wide variety of cancers. More than half of all cancers harbor p53 mutations, and in some cancers a p53 mutation can be found in 95% of the tumors produced in humans. In addition, a number of other mutations inactivate or dampen p53 functions in a cell. Gene amplifications in the MDM-2 and MDM-4 genes (the ubiquitin ligase complex that helps to degrade p53) and WIP-1 (a protein phosphatase) in cancers lower or eliminate p53 activities.11 Inherited mutations in the p53 gene increase the frequency of cancers in a family and lower the age of onset of those cancers.12

/pdf/introduction-the-changing-directions-of-p53-research-33ikw43yjt.pdf

Introduction: The Changing Directions of p53 Research:

Interactions between survival pathways and apoptotic cascades play a determinant role in the maintenance of neoplastic clone proliferation and impaired response to apoptosis. Recently, we established a novel interplay between the NF-kappaB survival- and p53 death-pathways in a tumor model system that represents the most common extranodal lymphoid cell neoplasia, MALT (Mucosa Associated Lymphoid Tissue) lymphoma. MALTs are genetically characterized by the t(11;18)(q21;q21) chromosomal translocation that results in API2/MALT1 fusion products. It was shown that distinct API2/MALT1 chimeric proteins function as oncogenes that bilaterally confer a proliferative advantage to the neoplastic clone by activating the NF-kappaB signaling pathway and also inhibiting p53 mediated cell death. Here, we demonstrate that API2/MALT1 mediated inhibition of apoptosis is p53 specific, as distinct API2/MALT1 fusion proteins fail to protect cells from FAS induced cell death. Furthermore, we demonstrate that API2/MALT1 mediated NF-kappaB activation does not alter p53 protein levels or subcellular localization suggesting a post-translational or indirect mechanism of p53 deregulation.

Arnold J. Levine

Papers

Reconstructing signal transduction pathways: challenges and opportunities.

Teratocarcinoma transplantation rejection loci: genetic localization of the Gt-1 locus on chromosome 17 and the expression of alternate alleles.

Oncogenes and cell proliferation

Introduction: The Changing Directions of p53 Research:

Actvation of NF-kappaB by the API2/MALT1 fusions inhibits p53 dependant but not FAS induced apoptosis: a directional link between NF-kappaB and p53.