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

On dynamic network entropy in cancer

The cellular phenotype is described by a complex network of molecular interactions. Elucidating network properties that distinguish disease from the healthy cellular state is therefore of critical importance for gaining systems-level insights into disease mechanisms and ultimately for developing improved therapies. By integrating gene expression data with a protein interaction network to induce a stochastic dynamics on the network, we here demonstrate that cancer cells are characterised by an increase in the dynamic network entropy, compared to cells of normal physiology. Using a fundamental relation between the macroscopic resilience of a dynamical system and the uncertainty (entropy) in the underlying microscopic processes, we argue that cancer cells will be more robust to random gene perturbations. In addition, we formally demonstrate that gene expression differences between normal and cancer tissue are anticorrelated with local dynamic entropy changes, thus providing a systemic link between gene expression changes at the nodes and their local network dynamics. In particular, we also find that genes which drive cell-proliferation in cancer cells and which often encode oncogenes are associated with reductions in the dynamic network entropy. In summary, our results support the view that the observed increased robustness of cancer cells to perturbation and therapy may be due to an increase in the dynamic network entropy that allows cells to adapt to the new cellular stresses. Conversely, genes that exhibit local flux entropy decreases in cancer may render cancer cells more susceptible to targeted intervention and may therefore represent promising drug targets.Comment: 10 pages, 3 figures, 4 tables. Submitte

The Met oncogene and basal-like breast cancer: another culprit to watch out for?

Recent findings suggest the involvement of the MET oncogene, encoding the tyrosine kinase receptor for hepatocyte growth factor, in the onset and progression of basal-like breast carcinoma. The expression profiles of basal-like tumors - but not those of other breast cancer subtypes - are enriched for gene sets that are coordinately over-represented in transcriptional signatures regulated by Met. Consistently, tissue microarray analyses have revealed that Met immunoreactivity is much higher in basal-like cases of human breast cancer than in other tumor types. Finally, mouse models expressing mutationally activated forms of Met develop a high incidence of mammary tumors, some of which exhibit basal characteristics. The present review summarizes current knowledge on the role and activity of Met in basal-like breast cancer, with a special emphasis on the correlation between this tumor subtype and the cellular hierarchy of the normal mammary gland

The clinical and functional significance of c-Met in breast cancer: a review

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited.CMH-Y is funded by a Cancer Research UK Clinical Research Fellowship. JLJ is funded by the Breast Cancer Campaign Tissue Bank

A922 Sequential measurement of 1 hour creatinine clearance (1-CRCL) in critically ill patients at risk of acute kidney injury (AKI)

Meeting abstrac

Molecular interactions between Hel2 and RNA supporting ribosome-associated quality control

Ribosome-associated quality control (RQC) pathways monitor and respond to stalling of the translating ribosome. Here the authors show that the ribosome associated RQC factor Hel2/ZNF598, an E3 ubiquitin ligase, generally interacts with mRNAs in the vicinity of stop codons

What are the effects of having an illness or injury whilst deployed on post deployment mental health? A population based record linkage study of UK army personnel who have served in Iraq or Afghanistan.

BACKGROUND: The negative impact of sustaining an injury on a military deployment on subsequent mental health is well-documented, however, the relationship between having an illness on a military operation and subsequent mental health is unknown. METHODS: Population based study, linking routinely collected data of attendances at emergency departments in military hospitals in Iraq and Afghanistan [Operational Emergency Department Attendance Register (OpEDAR)], with data on 3896 UK Army personnel who participated in a military health study between 2007 and 2009 and deployed to Iraq or Afghanistan between 2003 to 2009. RESULTS: In total, 13.8% (531/3896) of participants had an event recorded on OpEDAR during deployment; 2.3% (89/3884) were medically evacuated. As expected, those medically evacuated for an injury were at increased risk of post deployment probable PTSD (odds ratio 4.27, 95% confidence interval 1.80-10.12). Less expected was that being medically evacuated for an illness was also associated with a similarly increased risk of probable PTSD (4.39, 1.60-12.07) and common mental disorders (2.79, 1.41-5.51). There was no association between having an OpEDAR event and alcohol misuse. Having an injury caused by hostile action was associated with increased risk of probable PTSD compared to those with a non-hostile injury (3.88, 1.15 to 13.06). CONCLUSIONS: Personnel sustaining illnesses on deployment are just as, if not more, at risk of having subsequent mental health problems as personnel who have sustained an injury. Monitoring of mental health problems should consider those with illnesses as well as physical injuries