TY  - JOUR
A1  - Gröbner, Susanne N.
A1  - Worst, Barbara C.
A1  - Weischenfeldt, Joachim
A1  - Buchhalter, Ivo
A1  - Kleinheinz, Kortine
A1  - Rudneva, Vasilisa A.
A1  - Johann, Pascal D.
A1  - Balasubramanian, Gnana Prakash
A1  - Segura-Wang, Maia
A1  - Brabetz, Sebastian
A1  - Bender, Sebastian
A1  - Hutter, Barbara
A1  - Sturm, Dominik
A1  - Pfaff, Elke
A1  - Hübschmann, Daniel
A1  - Zipprich, Gideon
A1  - Heinold, Michael
A1  - Eils, Jürgen
A1  - Lawerenz, Christian
A1  - Erkek, Serap
A1  - Lambo, Sander
A1  - Waszak, Sebastian
A1  - Blattmann, Claudia
A1  - Borkhardt, Arndt
A1  - Kuhlen, Michaela
A1  - Eggert, Angelika
A1  - Fulda, Simone
A1  - Gessler, Manfred
A1  - Wegert, Jenny
A1  - Kappler, Roland
A1  - Baumhoer, Daniel
A1  - Stefan, Burdach
A1  - Kirschner-Schwabe, Renate
A1  - Kontny, Udo
A1  - Kulozik, Andreas E.
A1  - Lohmann, Dietmar
A1  - Hettmer, Simone
A1  - Eckert, Cornelia
A1  - Bielack, Stefan
A1  - Nathrath, Michaela
A1  - Niemeyer, Charlotte
A1  - Richter, Günther H.
A1  - Schulte, Johannes
A1  - Siebert, Reiner
A1  - Westermann, Frank
A1  - Molenaar, Jan J.
A1  - Vassal, Gilles
A1  - Witt, Hendrik
A1  - Burkhardt, Birgit
A1  - Kratz, Christian P.
A1  - Witt, Olaf
A1  - van Tilburg, Cornelis M.
A1  - Kramm, Christof M.
A1  - Fleischhack, Gudrun
A1  - Dirksen, Uta
A1  - Rutkowski, Stefan
A1  - Frühwald, Michael
A1  - Hoff, Katja von
A1  - Wolf, Stephan
A1  - Klingebeil, Thomas
A1  - Koscielniak, Ewa
A1  - Landgraf, Pablo
A1  - Koster, Jan
A1  - Resnick, Adam C.
A1  - Zhang, Jinghui
A1  - Liu, Yanling
A1  - Zhou, Xin
A1  - Waanders, Angela J.
A1  - Zwijnenburg, Danny A.
A1  - Raman, Pichai
A1  - Brors, Benedikt
A1  - Weber, Ursula D.
A1  - Northcott, Paul A.
A1  - Pajtler, Kristian W.
A1  - Kool, Marcel
A1  - Piro, Rosario M.
A1  - Korbel, Jan O.
A1  - Schlesner, Matthias
A1  - Eils, Roland
A1  - Jones, David T. W.
A1  - Lichter, Peter
A1  - Chavez, Lukas
A1  - Zapatka, Marc
A1  - Pfister, Stefan M.
T1  - The landscape of genomic alterations across childhood cancers
JF  - Nature
N2  - Pan-cancer analyses that examine commonalities and differences among various cancer types have emerged as a powerful way to obtain novel insights into cancer biology. Here we present a comprehensive analysis of genetic alterations in a pan-cancer cohort including 961 tumours from children, adolescents, and young adults, comprising 24 distinct molecular types of cancer. Using a standardized workflow, we identified marked differences in terms of mutation frequency and significantly mutated genes in comparison to previously analysed adult cancers. Genetic alterations in 149 putative cancer driver genes separate the tumours into two classes: small mutation and structural/copy-number variant (correlating with germline variants). Structural variants, hyperdiploidy, and chromothripsis are linked to TP53 mutation status and mutational signatures. Our data suggest that 7–8% of the children in this cohort carry an unambiguous predisposing germline variant and that nearly 50% of paediatric neoplasms harbour a potentially druggable event, which is highly relevant for the design of future clinical trials.
KW  - cancer genomics
KW  - oncogenesis
KW  - paediatric cancer
KW  - predictive markers
KW  - translational research
Y1  - 2018
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-229579
VL  - 555
ER  - 
TY  - JOUR
A1  - Sommer, Kim K.
A1  - Amr, Ali
A1  - Bavendiek, Udo
A1  - Beierle, Felix
A1  - Brunecker, Peter
A1  - Dathe, Henning
A1  - Eils, Jürgen
A1  - Ertl, Maximilian
A1  - Fette, Georg
A1  - Gietzelt, Matthias
A1  - Heidecker, Bettina
A1  - Hellenkamp, Kristian
A1  - Heuschmann, Peter
A1  - Hoos, Jennifer D. E.
A1  - Kesztyüs, Tibor
A1  - Kerwagen, Fabian
A1  - Kindermann, Aljoscha
A1  - Krefting, Dagmar
A1  - Landmesser, Ulf
A1  - Marschollek, Michael
A1  - Meder, Benjamin
A1  - Merzweiler, Angela
A1  - Prasser, Fabian
A1  - Pryss, Rüdiger
A1  - Richter, Jendrik
A1  - Schneider, Philipp
A1  - Störk, Stefan
A1  - Dieterich, Christoph
T1  - Structured, harmonized, and interoperable integration of clinical routine data to compute heart failure risk scores
JF  - Life
N2  - Risk prediction in patients with heart failure (HF) is essential to improve the tailoring of preventive, diagnostic, and therapeutic strategies for the individual patient, and effectively use health care resources. Risk scores derived from controlled clinical studies can be used to calculate the risk of mortality and HF hospitalizations. However, these scores are poorly implemented into routine care, predominantly because their calculation requires considerable efforts in practice and necessary data often are not available in an interoperable format. In this work, we demonstrate the feasibility of a multi-site solution to derive and calculate two exemplary HF scores from clinical routine data (MAGGIC score with six continuous and eight categorical variables; Barcelona Bio-HF score with five continuous and six categorical variables). Within HiGHmed, a German Medical Informatics Initiative consortium, we implemented an interoperable solution, collecting a harmonized HF-phenotypic core data set (CDS) within the openEHR framework. Our approach minimizes the need for manual data entry by automatically retrieving data from primary systems. We show, across five participating medical centers, that the implemented structures to execute dedicated data queries, followed by harmonized data processing and score calculation, work well in practice. In summary, we demonstrated the feasibility of clinical routine data usage across multiple partner sites to compute HF risk scores. This solution can be extended to a large spectrum of applications in clinical care.
KW  - medical informatics initiative
KW  - HiGHmed
KW  - medical data integration center
KW  - clinical routine data
KW  - heart failure
KW  - risk prediction scores
KW  - semantic interoperability
KW  - openEHR
Y1  - 2022
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-275239
SN  - 2075-1729
VL  - 12
IS  - 5
ER  -