Lifestyle factors and risk of sporadic colorectal cancer by microsatellite instability status: a systematic review and meta-analyses.

Introduction: The association of lifestyle factors with molecular pathological subtypes of colorectal cancer (CRC), such as microsatellite instability (MSI), could provide further knowledge about the colorectal carcinogenic process. The aim of this review was to evaluate possible associations between lifestyle factors and risk of sporadic CRC by MSI status. Methods: PubMed and Web of Science were searched for studies investigating the association between alcohol, body mass index, dietary fiber, hormone replacement therapy (HRT), non-steroidal anti-inflammatory drugs, physical activity, red meat, smoking, or statin use, with MSI-high (MSI-H) and microsatellite stable (MSS) CRC. Meta-analyses were carried out to calculate summary relative risks (sRR). Results: Overall, 31 studies reporting on the association between lifestyle factors and CRC according to MSI status were included in this review. Ever smoking was associated with MSI-H (sRR = 1.62; 95% CI: 1.40-1.88) and MSS/MSI-low CRC (sRR = 1.10; 95% CI: 1.01-1.20), but the association was significantly stronger for MSI-H CRC. The use of HRT was associated with a 20% decrease (sRR = 0.80; 95% CI: 0.73-0.89) in the risk of MSS CRC, but was not associated with MSI-H CRC. An increase in body mass index per 5 kg/m2 was equally associated with MSS and MSI-H CRC (sRR = 1.22, in both cases), but was statistically significant for MSS CRC only (95% CI: 1.11-1.34 and 0.94-1.58, respectively). Limited evidence for associations between other lifestyle factors and CRC by MSI status exists. Conclusions: Lifestyle factors, such as HRT and smoking are differentially associated with the risk of MSI-H and MSS CRC. Further research on associations of lifestyle factors and CRC subtypes is necessary to provide a better understanding of the CRC disease pathway.

OpenStructure: an integrated software framework for computational structural biology.

Research projects in structural biology increasingly rely on combinations of heterogeneous sources of information, e.g. evolutionary information from multiple sequence alignments, experimental evidence in the form of density maps and proximity constraints from proteomics experiments. The OpenStructure software framework, which allows the seamless integration of information of different origin, has previously been introduced. The software consists of C++ libraries which are fully accessible from the Python programming language. Additionally, the framework provides a sophisticated graphics module that interactively displays molecular structures and density maps in three dimensions. In this work, the latest developments in the OpenStructure framework are outlined. The extensive capabilities of the framework will be illustrated using short code examples that show how information from molecular-structure coordinates can be combined with sequence data and/or density maps. The framework has been released under the LGPL version 3 license and is available for download from http://www.openstructure.org.