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.

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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 a mouse model for neuroendocrine tumors of the pancreas (PanNETs), liver metastasis occurred at a higher frequency in males. Male mice also had higher serum and intratumoral levels of the innate immunity protein complement C5. In mice that lost the ability to express complement C5, there was a lower frequency of metastasis, and males no longer had a higher frequency of metastasis than females. Treatment with PMX53, a small molecule antagonist of C5aR1/CD88, the receptor for complement C5a, also reduced metastasis. Mice lacking a functional gene for complement C5 had smaller primary tumors, which were less invasive and lacked the CD68+ macrophages that have previously been associated with metastasis in this type of tumor. This is the first report of a gene that causes sexual dimorphism of metastasis in a mouse model. In the human disease, which also shows sexual dimorphism for metastasis, clinically advanced tumors expressed more complement C5 than less advanced tumors.

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Sexual dimorphism of liver metastasis by murine pancreatic neuroendocrine tumors is affected by expression of complement C5.

Erratum: The presence of p53 mutations in human osteosarcomas correlates with high levels of genomic instability (Proceedings of the National Academy of Sciences of the United States of America (September 30, 2003) 100:20 (11547-11552))

The p53 protein is structurally and functionally divided into five domains. The proline-rich domain is localized at amino acids 55-100. 319 missense mutations were identified solely in the proline domain from human cancers. Six hotspot mutations were identified at amino acids 72, 73, 82, 84, 89, and 98. Codon 72 contains a polymorphism that changes from proline (and African descent) to arginine (with Caucasian descent) with increasing latitudes northward and is under natural selection for pigmentation and protection from UV light exposure. Cancers associated with mutations in the proline domain were considerably enriched for melanomas and skin cancers compared to mutations in other p53 domains. These hotspot mutations are enriched at UV mutational signatures disrupting amino acid signals for binding SH-3-containing proteins important for p53 function. Among the protein-protein interaction sites identified by hotspot mutations were MDM-2, a negative regulator of p53, XAF-1, promoting p53 mediated apoptosis, and PIN-1, a proline isomerase essential for structural folding of this domain. 

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The genotypes and phenotypes of missense mutations in the proline domain of the p53 protein

It has been said that no matter which direction cancer research turns, the p53 tumour suppressor protein comes into view. If there is truth in this statement, then it has much to do with the ability of this protein to induce programmed cell death, or apoptosis. First discovered in 1979 as a protein complexed with the large T antigen of SV40 virus (Lane and Crawford, 1979; Linzer and Levine, 1979), the complete cDNA sequence of p53 was elucidated in 1984 (Matlashewski et al. 1984), and its activity as a tumour suppressor gene was first suspected in 1985 when deletions of the gene were detected in transformed cells infected with Friend leukemia virus (Mowat et al. 1985). Later it was found that expression of p53 could inhibit the neoplastic transformation of primary cells (Finlay et al. 1989), and that this gene was subject to frequent mutations in human tumours (Baker et al. 1989; Hollstein et al. 1991). Germline mutations of the p53 gene were found in individuals suffering from Li-Fraumeni disorder, which is an autosomal dominant disorder predisposing affected individuals to osteosarcomas as well as tumours of the brain, breast and adrenal cortex (Malkin et al. 1990). Tumours from affected individuals were found to invariably lose expression of the wild type p53 allele, thereby identifying p53 as a classical tumour suppressor gene. Analogously, mice genetically engineered to be nullizygous for p53 (p53 “knock-out” mice) died from tumours at 3-6 months of age, although these were chiefly lymphoid tumours (Donehower et al. 1992). Analyses of p53 mutations in human tumour samples to date indicate that this tumour suppressor gene is mutated in over 50% of human tumours, derived from a wide variety of tissues. The p53 gene continues to hold the distinction as the most frequently mutated gene in human cancer.

Arnold J. Levine

Papers

Sexual dimorphism of liver metastasis by murine pancreatic neuroendocrine tumors is affected by expression of complement C5.

Erratum: The presence of p53 mutations in human osteosarcomas correlates with high levels of genomic instability (Proceedings of the National Academy of Sciences of the United States of America (September 30, 2003) 100:20 (11547-11552))

The genotypes and phenotypes of missense mutations in the proline domain of the p53 protein

The role of p53 in apoptosis

The expression of SV40 large T-antigen in embryonal carcinoma--SV40 transformed somatic cell hybrids.