The transition of the European Proteomics Association into the future

The following report provides an overview of the discussions and outcome of the EuPA General Council meeting that took place in Estoril 20–21 October 2010. During the annual meeting future policy and action plans in a variety of areas are decided. Several important points were decided upon during this meeting including the expansion of the EuPA Executive Committee by introducing a new EuPA committee – EuPA Developments – that will initially spearhead activities in standardisation, imaging ms and biobanking. The EuPA General Council also invited Russia as its 17th member. More details about these and additional activities are presented in the article

Development and promotion in translational medicine: perspectives from 2012 sino-american symposium on clinical and translational medicine

Background Clinical translational medicine (CTM) is an emerging area comprising multidisciplinary research from basic science to medical applications and entails a close collaboration among hospital, academia and industry. Findings This Session focused discussing on new models for project development and promotion in translational medicine. The conference stimulated the scientific and commercial communication of project development between academies and companies, shared the advanced knowledge and expertise of clinical applications, and created the environment for collaborations. Conclusions Although strategic collaborations between corporate and academic institutions have resulted in a state of resurgence in the market, new cooperation models still need time to tell whether they will improve the translational medicine process

Integrated proteogenomic approach identifying a protein signature of COPD and a new splice variant of SORBS1

Translation of genomic alterations to protein changes in chronic obstructive pulmonary disease (COPD) is largely unexplored. Using integrated proteomic and RNA sequencing analysis of COPD and control lung tissues, we identified a protein signature in COPD characterised by extracellular matrix changes and a potential regulatory role for SUMO2. Furthermore, we identified 61 differentially expressed novel, non-reference, peptides in COPD compared with control lungs. This included two peptides encoding for a new splice variant of SORBS1, of which the transcript usage was higher in COPD compared with control lungs. These explorative findings and integrative proteogenomic approach open new avenues to further unravel the pathology of COPD

Unfolding the Secrets of Small Cell Lung Cancer Progression: Novel Approaches and Insights Through Rapid Autopsies

The understanding of small cell lung cancer (SCLC) biology has increased dramatically in recent years, but the processes that allow SCLC to progress rapidly remain poorly understood. Here, we advocate the integration of rapid autopsies and preclinical models into SCLC research as a comprehensive strategy with the potential to revolutionize current treatment paradigms

The international effort: building the bridge for Translational Medicine: Report of the 1st International Conference of Translational Medicine (ICTM)

Background: Supported by the International Society for Translational Medicine (ISTM), Wenzhou Medical College and the First Affiliated Hospital of Wenzhou Medical College, the International Conference on Translational Medicine (ICTM) was held on October 22–23, 2011 in Wenzhou, China. Nearly 800 registrants attended the meeting, primarily representing institutes and hospitals in Europe, The United States of America, And Asia, and China. The meeting was chaired and organized by Dr. Xiangdong Wang, Xiaoming Chen, Richard Coico, Jeffrey M. Drazen, Richard Horton, Francesco M. Marincola, Laurentiu M. Popescu, Jia Qu and Aamir Shahzad. Findings: The meeting focused on the communication of the need to foster translational medicine (TM) by building and broadening bridges between basic research and clinical studies at the international level. The meeting included distinguished TM experts from academia, the pharmaceutical and diagnostics industries, government agencies, regulators, and clinicians and provided the opportunity to identify shared interests and efforts for collaborative approaches utilizing cutting edge technologies, innovative approaches and novel therapeutic interventions. The meeting defined the concept of TM in its two-way operational scheme and emphasized the need for bed to bench efforts based directly on clinical observation. Conclusions: It was the meeting participants’ realization that the shared main goals of TM include breaking the separation between clinic practice and basic research, establishing positive feedback by understanding the basis of expected and unexpected clinical outcomes and accelerating basic research relevant to human suffering. The primary objectives of the meeting were two-fold: to accelerate the two-way translation by informing the participants representing the different disciplines about the state of art activities around TM approaches; and to identify areas that need to be supported by redirecting limited resources as well as identifying new sources of funding. This report summarizes key concepts presented during the meeting representing the state-of-art translational research and salient aspects of the ensuing discussions

Correlation Queries for Mass Spectrometry Imaging

<p>Mass spectrometry imaging (MSI) generates large volumetric data sets consisting of mass to charge ratio (m/z), ion current, and x,y coordinate location. These data sets usually serve limited purposes centered on measuring the distribution of a small set of ions with known m/z. Such earmarked queries consider only a fraction of the full mass spectrum captured, and there are few tools to assist the exploration of the remaining volume of unknown data in terms of demonstrating similarity or discordance in tissue compartment distribution patterns. Here we present a novel, interactive approach to extract information from MSI data that relies on precalculated data structures to perform queries of large data sets with a typical laptop. We have devised methods to query the full volume to find new m/z values of potential interest based on similarity to biological structures or to the spatial distribution of known ions. We describe these query methods in detail and provide examples demonstrating the power of the methods to "discover" m/z values of ions that have such potentially interesting correlations. The "discovered" ions may be further correlated with either positional locations or the coincident distribution of other ions using successive queries. Finally, we show it is possible to gain insight to the fragmentation pattern of the parent molecule from such correlations. The ability to discover new ions of interest in the unknown bulk of an MSI data set offers the potential to further our understanding of biological and physiological processes related to health and disease.</p>

Clusterwise Peak Detection and Filtering Based on Spatial Distribution to Efficiently Mine Mass Spectrometry Imaging Data

Mass spectrometry imaging (MSI) has the potential to reveal the localization of thousands of biomolecules such as metabolites and lipids in tissue sections. The increase in both mass and spatial resolution of today's instruments brings on considerable challenges in terms of data processing; accurately extracting meaningful signals from the large data sets generated by MSI without losing information that could be clinically relevant is one of the most fundamental tasks of analysis software. Ion images of the biomolecules are generated by visualizing their intensities in 2-D space using mass spectra collected across the tissue section. The intensities are often calculated by summing each compound's signal between predefined sets of borders (bins) in the m/z dimension. This approach, however, can result in mixed signals from different compounds in the same bin or splitting the signal from one compound between two adjacent bins, leading to low quality ion images. To remedy this problem, we propose a novel data processing approach. Our approach consists of a sensitive peak detection method able to discover both faint and localized signals by utilizing clusterwise kernel density estimates (KDEs) of peak distributions. We show that our method can recall more ground-truth molecules, molecule fragments, and isotopes than existing methods based on binning. Furthermore, it automatically detects previously reported molecular ions of lipids, including those close in m/z, in an experimental data set