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The MM500 meta‐study aims to establish a knowledge basis of the tumor proteome to serve as a complement to genome and transcriptome studies. Somatic mutations and their effect on the transcriptome have been extensively characterized in melanoma. However, the effects of these genetic changes on the proteomic landscape and the impact on cellular processes in melanoma remain poorly understood. In this study, the quantitative mass‐spectrometry‐based proteomic analysis is interfaced with pathological tumor characterization, and associated with clinical data. The melanoma proteome landscape, obtained by the analysis of 505 well‐annotated melanoma tumor samples, is defined based on almost 16 000 proteins, including mutated proteoforms of driver genes. More than 50 million MS/MS spectra were analyzed, resulting in approximately 13,6 million peptide spectrum matches (PSMs). Altogether 13 176 protein‐coding genes, represented by 366 172 peptides, in addition to 52 000 phosphorylation sites, and 4 400 acetylation sites were successfully annotated. This data covers 65% and 74% of the predicted and identified human proteome, respectively. A high degree of correlation (Pearson, up to 0.54) with the melanoma transcriptome of the TCGA repository, with an overlap of 12 751 gene products, was found. Mapping of the expressed proteins with quantitation, spatiotemporal localization, mutations, splice isoforms, and PTM variants was proven not to be predicted by genome sequencing alone. The melanoma tumor molecular map was complemented by analysis of blood protein expression, including data on proteins regulated after immunotherapy. By adding these key proteomic pillars, the MM500 study expands the knowledge on melanoma disease., The MM500 meta‐study aims to establish a knowledge basis of the tumor proteome to serve as a complement to genome and transcriptome studies. The melanoma proteome landscape, obtained by the analysis of 505 well‐annotated melanoma tumor samples, is defined based on almost 16 000 proteins, including mutated proteoforms of driver genes. This data covers 65% and 74% of the predicted and identified human proteome, respectively.

The MM500 study is an initiative to map the protein levels in malignant melanoma tumor samples, focused on in‐depth histopathology coupled to proteome characterization. The protein levels and localization were determined for a broad spectrum of diverse, surgically isolated melanoma tumors originating from multiple body locations. More than 15,500 proteoforms were identified by mass spectrometry, from which chromosomal and subcellular localization was annotated within both primary and metastatic melanoma. The data generated by global proteomic experiments covered 72% of the proteins identified in the recently reported high stringency blueprint of the human proteome. This study contributes to the NIH Cancer Moonshot initiative combining detailed histopathological presentation with the molecular characterization for 505 melanoma tumor samples, localized in 26 organs from 232 patients., The MM500 study is an initiative to map the protein levels in malignant melanoma tumor samples, focused on in‐depth histopathology coupled to proteome characterization. The protein levels and localization were determined for a broad spectrum of diverse melanoma tumors originating from multiple body locations. More than 15,500 proteoforms were identified by mass spectrometry, from which chromosomal and sub‐cellular localization was annotated within both primary and metastatic melanoma.

Human genomics is undergoing a step change from being a predominantly research-driven activity to one driven through health care as many countries in Europe now have nascent precision medicine programmes. To maximize the value of the genomic data generated, these data will need to be shared between institutions and across countries. In recognition of this challenge, 21 European countries recently signed a declaration to transnationally share data on at least 1 million human genomes by 2022. In this Roadmap, we identify the challenges of data sharing across borders and demonstrate that European research infrastructures are well-positioned to support the rapid implementation of widespread genomic data access.

EXECUTIVE SUMMARY AND 2018 GOAL TREE ‘A customer is someone who has not found a better alternative yet’ Nirmalya Kumar The way biobanks see it, researchers have no alternative than to connect and partner up with them when looking for high-quality samples and associated data. In other words, researchers cannot go find a better alternative because there is none. The researchers themselves, however, are often convinced that there are many alternatives to biobanks, which is mainly due to the fact that sample collections hosted by biobanks lack visibility, findability, and accessibility or simply because researchers have a strong desire to have their own collections of specific material. In order to bridge this gap between biobanks, the research community and the different stakeholders, BBMRI-ERIC’s goal for 2018 will be to build and strengthen value-added, sustainable biobanking. This ambitious goal and its various sub-goals, laid out on the following pages, can only be achieved if the BBMRI-ERIC team in Graz, the National Nodes, and the various biobanks join efforts. To gain a better understanding of who we actually serve, communication and dissemination will play a central role in 2018. Focussing on these activities will allow us to respond better to different requirements and tackle the challenges ahead. However, it will also help us map the environment in which we operate and identify areas in which we need to adapt or where we can place ourselves in an even stronger position. To that end, we will gather information that will then be fed back to the National Nodes in order for them to benefit as well. The various services offered by BBMRI-ERIC will be continuously improved and expanded, while also creating additional awareness. Quality Management will continue to expand its Self-Assessment Survey, launch a quality grade and develop a concept paper for an audit programme. The Common Service IT will focus on improving and supporting the Directory, the Negotiator, the Connector, and BIBBOX, with the Locator due for a first release across five member states. The Common Service ELSI will centre its efforts around a number of services and support, including optimising the recently launched Help Desk, adapting the Ethics Check and drafting the Code of Conduct. In order to maintain the leading position of BBMRI-ERIC and its Members and Observers, it is absolutely crucial to explore new, innovative ideas in more detail. To that end, there will be small working groups to analyse the potential and added value of these innovations and developments for the wider community. These working groups will also be designed to give advice on risks and investment in necessary resources while exploring whether this could be something to develop into a specific BBMRI-ERIC service. Finally, strategic efforts concerning funding will be intensified in 2018. By actively monitoring market developments, we can detect upcoming calls at an early stage and take action. Additionally, BBMRI-ERIC will start to explore fundraising activities outside of the regular H2020 projects, relying, among other things, on input from the Stakeholder Forum. Last but not least, I would like to thank the team in Graz as well as our Members and Observers and the various governing bodies of BBMRI-ERIC for their input to this Work Programme for 2018. I look forward to working with all of you to deliver on our commitments. Erik Steinfelder – Director General

The Table 1 (EU declaration signatory and membership status) of the original article published online contained several errors: the IARC was incorrectly listed in the table, which only includes countries, and footnote; Croatia, Lithuania, Poland and Portugal were not listed as full EMBL members; Estonia is now listed as a Prospect Member of EMBL; Hungary, Ireland and Israel were incorrectly listed as BBMRI-ERIC members; Iceland was omitted from the table. Hyphens stand for ‘not applicable’; the table and footnote have been corrected accordingly. These errors have now been corrected online and in print.

We introduce a novel automated sample-processing concept that will be of mandatory importance to proteomics and future clinical research, performing patient studies from resulting blood fractions in various disease areas. Biobank storage of small sample volumes allows for high replicate numbers to be processed and aliquoted, where each sample aliquot can be used for a dedicated clinical analysis and end-point measurement. In order to preserve sample integrity and value over time, the principle of single usage is gaining recognition. We hereby present a 384-format sample tube system for the preservation and archiving of clinical patient samples that will form the basis for future proteomics studies. This high density scaling allows for reproducible aliquoting 70-µL volumes of blood fractions. Blood plasma with EDTA, Li-heparin, and citrate, as anti-coagulants, are fractioned along with the buffy coat and the erythrocyte fraction, in addition to the serum fraction. We demonstrate an automated sample handling for biobanking: samples from patients were processed and aliquoted in both 96- and 384-sample racks by liquid handling robotics and Laboratory Intelligence Management System (LIMS) overview and control. Within this study, the blood samples were analyzed by the Clinical Chemistry department at the Southern University Hospital in Malmo, using standard biomarker assays, quantifying 23 common markers used in everyday healthcare around the world. We were able to prove that the 384-format using an aluminum foil with a thin polymer film coating for sealing, is stable and can reproducibly be processed for automated biobank freezer units. (Less)

BackgroundIn the postgenomic era, it has become evident that analysis of genetic and protein expression changes alone is not sufficient to understand most disease processes in e.g. cardiovascular and cancer disease. Biobanking has been identified as an important area for development and discovery of better diagnostic tools and new treatment modalities. Biobanks are developed in order to integrate the collection of clinical samples from both healthy individuals and patients and provide valuable information that will make possible improved patient care. Modern healthcare developments are intimately linked to information based on studies of patient samples from biobank archives in large scale studies. Today biobanks form important national, as well as international, networks that share and combine global resources. MethodsWe have developed and validated a novel biobanking workflow process that utilizes 384‐tube systems with a high speed sample array robot with unique processing principles. ResultsThe 384‐tube format and robotic processing is incorporated into a cancer and cardiovascular diagnostic/prognostic research program with therapeutic interventions. Our biobank practice has gained acceptance within many hospitals and research units and is based on high‐density sample storage with small aliquot sample volumes. The previous standard of 5–10 mL sample volume tubes is being replaced by smaller volumes of 50–70 μL blood fractions that typically result in hundreds of thousands of aliquot fractions in 384‐tube systems. ConclusionsOur novel biobanking workflow process is robust and well suited for clinical studies.