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

Transformation by adenovirus early region 2A temperature-sensitive mutants and their revertants

DNA replication in SV40-infected cells: V. Circular and catenated oligomers of SV40 DNA

The p53 regulatory network responds to cellular stresses by initiating processes such as cell cycle arrest and apoptosis. These responses inhibit cellular transformation and mediate the response to many forms of cancer therapies. Functional variants in the genes comprising this network could help identify individuals at greater risk for cancer and patients with poorer responses to therapies, but few such variants have been identified as yet. We use the NCI60 human tumor cell line anticancer drug screen in a scan of single nucleotide polymorphisms (SNP) in 142 p53 stress response genes and identify 7 SNPs that exhibit allelic differences in cellular responses to a large panel of cytotoxic chemotherapeutic agents. The greatest differences are observed for SNPs in 14-3-3tau (YWHAQ; rs6734469, P=5.6x10(-47)) and CD44 (rs187115, P=8.1x10(-24)). In soft-tissue sarcoma patients, we find that the alleles of these SNPs that associate with weaker growth responses to chemotherapeutics associate with poorer overall survival (up to 2.89 relative risk, P=0.011) and an earlier age of diagnosis (up to 10.7 years earlier, P=0.002). Our findings define genetic markers in 14-3-3tau and CD44 that might improve the treatment and prognosis of soft-tissue sarcomas.

https://cancerres.aacrjournals.org/content/canres/70/1/172.full.pdf

Chemosensitivity Profiles Identify Polymorphisms in the p53 Network Genes 14-3-3τ and CD44 That Affect Sarcoma Incidence and Survival

Adenovirus-infected, cell-specific, DNA-binding proteins.

Endogenous c-MYC (MYC) has been reported to be a potential pharmacological target to trigger ubiquitous tumor regression of pancreatic neuroendocrine tumors (PanNETs) and lung tumors. Recently inhibitors of bromodomain and extra-terminal (BET) family proteins have shown antitumor effects through the suppression of MYC in leukemia and lymphoma. In this paper, we investigated the antitumor activity of a BET protein bromodomain inhibitor (BETi) CPI203 as a single agent and in combination with rapamycin in human PanNETs. We found that exposure of human PanNET cell lines to CPI203 led to downregulation of MYC expression, G1 cell cycle arrest and nearly complete inhibition of cell proliferation. In addition, overexpression of MYC suppressed the growth inhibition caused by CPI203 and knockdown of MYC phenocopied the effects of CPI203 treatment. These findings indicate that suppression of MYC contributed to the antiproliferative effects of BETi inhibition in human PanNET cells. Importantly, CPI203 treatment enhanced the antitumor effects of rapamycin in PanNET cells grown in monolayer and in three-dimensional cell cultures, as well as in a human PanNET xenograft model in vivo. Furthermore, the combination treatment attenuated rapamycin-induced AKT activation, a major limitation of rapamycin therapy. Collectively, our data suggest that targeting MYC with a BETi may increase the therapeutic benefits of rapalogs in human PanNET patients. This provides a novel clinical strategy for PanNETs, and possibly for other tumors as well.

/pdf/the-bromodomain-and-extra-terminal-inhibitor-cpi203-enhances-3lki8e07s1.pdf

Arnold J. Levine

Papers

Transformation by adenovirus early region 2A temperature-sensitive mutants and their revertants

DNA replication in SV40-infected cells: V. Circular and catenated oligomers of SV40 DNA

Chemosensitivity Profiles Identify Polymorphisms in the p53 Network Genes 14-3-3τ and CD44 That Affect Sarcoma Incidence and Survival

Adenovirus-infected, cell-specific, DNA-binding proteins.

The bromodomain and extra-terminal inhibitor CPI203 enhances the antiproliferative effects of rapamycin on human neuroendocrine tumors.