Translational cancer research is highly dependent of large series of cases including high quality samples and their associated data. Comprehensive Cancer Centers should be involved in networks to enable large‐scale multi‐center research projects between the centers [Ringborg, U., de Valeriola, D., van Harten, W., Llombart‐Bosch, A., Lombardo, C., Nilsson, K., Philip, T., Pierotti, M.A., Riegman, P., Saghatchian, M., Storme, G., Tursz, T., Verellen, D, 2008. Improvement of European translational cancer research. Collaboration between comprehensive cancer centers. Tumori 94, 143–146.]. Combating cancer knows many frontiers. Research is needed for prevention as well as better care for those who have acquired the disease. This implies that human samples for cancer research need to be sourced from distinct forms of biobanking. An easier access to these samples for the scientific community is considered as the main bottleneck for research for health, and biobanks are the most adequate site to try to resolve this issue [Ozols, R.F., Herbst, R.S., Colson, Y.L., Gralow, J., Bonner, J., Curran Jr., W.J., Eisenberg, B.L., Ganz, P.A., Kramer, B.S., Kris, M.G., Markman, M., Mayer, R.J., Raghavan, D., Reaman, G.H., Sawaya, R., Schilsky, R.L., Schuchter, L.M., Sweetenham, J.W., Vahdat, L.T., Winn, R.J., and the American Society of Clinical Oncology, 2007. Clinical cancer advances 2006: major research advances in cancer treatment, prevention, and screening: a report from the American Society of Clinical Oncology. J. Clin. Oncol. 25, 146–162.]. However, biobanks should not be considered a static activity. On the contrary, biobanking is a young discipline [Morente, M.M., Fernandez, P.L., de Alava, E. Biobanking: old activity or young discipline? Semin. Diagn. Pathol., in press.], which need continuously evolve according to the permanent development of new techniques and new scientific goals. To accomplish current requirements of the scientific community biobanks need to face some essential challenges including an appropriate design, harmonized and more suitable procedures, and sustainability, all of them in the framework of their ethic, legal and social dimensions. This review therefore presents an overview on these issues, based on the works and discussions of the Marble Arch International Working Group on Biobanking for Biomedical Research, integrated by experts in biobanking from five continents.

Background Parkinson’s disease (PD) is a systemic disease clinically defined by the degeneration of dopaminergic neurons in the brain. While alterations in the gut microbiome composition have been reported in PD, their functional consequences remain unclear. Herein, we addressed this question by an analysis of stool samples from the Luxembourg Parkinson’s Study (n = 147 typical PD cases, n = 162 controls). Results All individuals underwent detailed clinical assessment, including neurological examinations and neuropsychological tests followed by self-reporting questionnaires. Stool samples from these individuals were first analysed by 16S rRNA gene sequencing. Second, we predicted the potential secretion for 129 microbial metabolites through personalised metabolic modelling using the microbiome data and genome-scale metabolic reconstructions of human gut microbes. Our key results include the following. Eight genera and seven species changed significantly in their relative abundances between PD patients and healthy controls. PD-associated microbial patterns statistically depended on sex, age, BMI, and constipation. Particularly, the relative abundances of Bilophila and Paraprevotella were significantly associated with the Hoehn and Yahr staging after controlling for the disease duration. Furthermore, personalised metabolic modelling of the gut microbiomes revealed PD-associated metabolic patterns in the predicted secretion potential of nine microbial metabolites in PD, including increased methionine and cysteinylglycine. The predicted microbial pantothenic acid production potential was linked to the presence of specific non-motor symptoms. Conclusion Our results suggest that PD-associated alterations of the gut microbiome can translate into substantial functional differences affecting host metabolism and disease phenotype.

Background: Management and traceability of biospecimen preanalytical variations are necessary to provide effective and efficient interconnectivity and interoperability between Biobanks.Methods: Therefore, the International Society for Biological and Environmental Repositories Biospecimen Science Working Group developed a "Standard PREanalytical Code" (SPREC) that identifies the main preanalytical factors of clinical fluid and solid biospecimens and their simple derivatives.Results: The SPREC is easy to implement and can be integrated into Biobank quality management systems and databases. It can also be extended to nonhuman biorepository areas. Its flexibility allows integration of new novel technological developments in future versions. SPREC version 01 is presented in this article.Conclusions and Impact: Implementation of the SPREC is expected to facilitate and consolidate international multicenter biomarker identification research and biospecimen research in the clinical Biobank environment. Cancer Epidemiol Biomarkers Prev; 19(4); 1004-11. ©2010 AACR.

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The first version of the Standard PREanalytical Code (SPREC) was developed in 2009 by the International Society for Biological and Environmental Repositories (ISBER) Biospecimen Science Working Group to facilitate documentation and communication of the most important preanalytical quality parameters of different types of biospecimens used for research. This same Working Group has now updated the SPREC to version 2.0, presented here, so that it contains more options to allow for recent technological developments. Existing elements have been fine tuned. An interface to the Biospecimen Reporting for Improved Study Quality (BRISQ) has been defined, and informatics solutions for SPREC implementation have been developed. A glossary with SPREC-related definitions has also been added.