Multi-Determinants Analysis of Molecular Alterations for Predicting Clinical Benefit to EGFR-Targeted Monoclonal Antibodies in Colorectal Cancer

KRAS mutations occur in 35-45% of metastatic colorectal cancers (mCRC) and preclude responsiveness to EGFR-targeted therapy with cetuximab or panitumumab. However, less than 20% patients displaying wild-type KRAS tumors achieve objective response. Alterations in other effectors downstream of the EGFR, such as BRAF, and deregulation of the PIK3CA/PTEN pathway have independently been found to give rise to resistance. We present a comprehensive analysis of KRAS, BRAF, PIK3CA mutations, and PTEN expression in mCRC patients treated with cetuximab or panitumumab, with the aim of clarifying the relative contribution of these molecular alterations to resistance.We retrospectively analyzed objective tumor response, progression-free (PFS) and overall survival (OS) together with the mutational status of KRAS, BRAF, PIK3CA and expression of PTEN in 132 tumors from cetuximab or panitumumab treated mCRC patients. Among the 106 non-responsive patients, 74 (70%) had tumors with at least one molecular alteration in the four markers. The probability of response was 51% (22/43) among patients with no alterations, 4% (2/47) among patients with 1 alteration, and 0% (0/24) for patients with > or =2 alterations (p<0.0001). Accordingly, PFS and OS were increasingly worse for patients with tumors harboring none, 1, or > or =2 molecular alteration(s) (p<0.001).When expression of PTEN and mutations of KRAS, BRAF and PIK3CA are concomitantly ascertained, up to 70% of mCRC patients unlikely to respond to anti-EGFR therapies can be identified. We propose to define as 'quadruple negative', the CRCs lacking alterations in KRAS, BRAF, PTEN and PIK3CA. Comprehensive molecular dissection of the EGFR signaling pathways should be considered to select mCRC patients for cetuximab- or panitumumab-based therapies

Identifying potential survival strategies of HIV-1 through virus-host protein interaction networks

Background: The National Institute of Allergy and Infectious Diseases has launched the HIV-1 Human Protein Interaction Database in an effort to catalogue all published interactions between HIV-1 and human proteins. In order to systematically investigate these interactions functionally and dynamically, we have constructed an HIV-1 human protein interaction network. This network was analyzed for important proteins and processes that are specific for the HIV life-cycle. In order to expose viral strategies, network motif analysis was carried out showing reoccurring patterns in virus-host dynamics.Results: Our analyses show that human proteins interacting with HIV form a densely connected and central sub-network within the total human protein interaction network. The evaluation of this sub-network for connectivity and centrality resulted in a set of proteins essential for the HIV life-cycle. Remarkably, we were able to associate proteins involved in RNA polymerase II transcription with hubs and proteasome formation with bottlenecks. Inferred network motifs show significant over-representation of positive and negative feedback patterns between virus and host. Strikingly, such patterns have never been reported in combined virus-host systems.Conclusions: HIV infection results in a reprioritization of cellular processes reflected by an increase in the relative importance of transcriptional machinery and proteasome formation. We conclude that during the evolution of HIV, some patterns of interaction have been selected for resulting in a system where virus proteins preferably interact with central human proteins for direct control and with proteasomal proteins for indirect control over the cellular processes. Finally, the patterns described by network motifs illustrate how virus and host interact with one another

Sizing Up Allometric Scaling Theory

Metabolic rate, heart rate, lifespan, and many other physiological properties vary with body mass in systematic and interrelated ways. Present empirical data suggest that these scaling relationships take the form of power laws with exponents that are simple multiples of one quarter. A compelling explanation of this observation was put forward a decade ago by West, Brown, and Enquist (WBE). Their framework elucidates the link between metabolic rate and body mass by focusing on the dynamics and structure of resource distribution networks—the cardiovascular system in the case of mammals. Within this framework the WBE model is based on eight assumptions from which it derives the well-known observed scaling exponent of 3/4. In this paper we clarify that this result only holds in the limit of infinite network size (body mass) and that the actual exponent predicted by the model depends on the sizes of the organisms being studied. Failure to clarify and to explore the nature of this approximation has led to debates about the WBE model that were at cross purposes. We compute analytical expressions for the finite-size corrections to the 3/4 exponent, resulting in a spectrum of scaling exponents as a function of absolute network size. When accounting for these corrections over a size range spanning the eight orders of magnitude observed in mammals, the WBE model predicts a scaling exponent of 0.81, seemingly at odds with data. We then proceed to study the sensitivity of the scaling exponent with respect to variations in several assumptions that underlie the WBE model, always in the context of finite-size corrections. Here too, the trends we derive from the model seem at odds with trends detectable in empirical data. Our work illustrates the utility of the WBE framework in reasoning about allometric scaling, while at the same time suggesting that the current canonical model may need amendments to bring its predictions fully in line with available datasets

Discovering Networks of Perturbed Biological Processes in Hepatocyte Cultures

The liver plays a vital role in glucose homeostasis, the synthesis of bile acids and the detoxification of foreign substances. Liver culture systems are widely used to test adverse effects of drugs and environmental toxicants. The two most prevalent liver culture systems are hepatocyte monolayers (HMs) and collagen sandwiches (CS). Despite their wide use, comprehensive transcriptional programs and interaction networks in these culture systems have not been systematically investigated. We integrated an existing temporal transcriptional dataset for HM and CS cultures of rat hepatocytes with a functional interaction network of rat genes. We aimed to exploit the functional interactions to identify statistically significant linkages between perturbed biological processes. To this end, we developed a novel approach to compute Contextual Biological Process Linkage Networks (CBPLNs). CBPLNs revealed numerous meaningful connections between different biological processes and gene sets, which we were successful in interpreting within the context of liver metabolism. Multiple phenomena captured by CBPLNs at the process level such as regulation, downstream effects, and feedback loops have well described counterparts at the gene and protein level. CBPLNs reveal high-level linkages between pathways and processes, making the identification of important biological trends more tractable than through interactions between individual genes and molecules alone. Our approach may provide a new route to explore, analyze, and understand cellular responses to internal and external cues within the context of the intricate networks of molecular interactions that control cellular behavior