EATRIS
Published November 20, 2023 | Version 1.0
Project deliverable Open

The Multi-omics Toolbox (MOTBX): Empowering Multi-omics Research and Analysis for the Translational Medicine Community

Creators

  • 1. European Infrastructure for Translational Medicine (EATRIS), Amsterdam, Netherlands
  • 2. Translational Metabolomic Laboratory, Department of Laboratory Medicine, Radboud University Medical Center, Nijmegen, Netherlands
  • 3. Department of Medical BioSciences, Radboud University Medical Center, Nijmegen, Netherlands
  • 4. Biomarkers and Therapeutic Targets Group, Ramon and Cajal Health Research Institute (IRYCIS), Madrid, Spain
  • 5. Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland
  • 6. Integrated Biobank of Luxembourg (IBBL), Luxembourg Institute of Health, Luxembourg
  • 7. Institute of Molecular and Translational Medicine, Faculty of Medicine and Dentistry, Palacky University and University Hospital in Olomouc, Olomouc, Czechia
  • 8. Department of Medical Sciences, Molecular Precision Medicine and Science for Life Laboratory, Uppsala University, Uppsala, Sweden

Description

Personalised medicine (PM) research seeks to identify interventions that can be targeted to individual patients based on their predicted response. Efficient advancement of PM depends on the availability of validated patient-targeted biomarkers. In order to deliver them, we need a more precise understanding of the molecular profiles of individuals, which is facilitated by multi-omics approaches. To turn the multi-omics promises into a reality, systemic bottlenecks impacting the biomarker field need to be overcome. As part of the EATRIS-Plus project, we developed the Multi-omics Toolbox (MOTBX), to support the translational medicine research community by providing validated resources, such as standardised protocols for individual omics performance and analysis, quality, and data management guidelines, for the development, the implementation and the adoption of multi-omics approaches in real PM. The MOTBX is a resource that has been built with, and for the community. This means that researchers are not only welcome to use the MOTBX, but to support its further development by actively contributing with valuable resources. 

Files

EATRIS MOTBX comms piece_2023-11-20.pdf

Files (297.1 kB)

Name Size Download all
md5:9069b499e08093c4658118119a731647
297.1 kB Preview Download

Additional details

Funding

European Commission
EATRIS-Plus - Consolidating the capacities of EATRIS-ERIC for Personalised Medicine 871096
European Commission
EOSC Future - EOSC Future 101017536

References

  • Shendure J, Findlay GM, Snyder MW. Genomic medicine -- progress, pitfalls, and promise. Cell 2019;177:45. doi:10.1016/J.CELL.2019.02.003
  • Olivier M, Asmis R, Hawkins GA, et al. The need for multi-omics biomarker signatures in precision medicine. Int J Mol Sci 2019;20. doi:10.3390/ijms20194781
  • Syn NLX, Yong WP, Goh BC, et al. Evolving landscape of tumor molecular profiling for personalized cancer therapy: a comprehensive review. Expert Opin Drug Metab Toxicol 2016;12:911–22. doi:10.1080/17425255.2016.1196187
  • Chen HZ, Bonneville R, Roychowdhury S. Implementing precision cancer medicine in the genomic era. Semin Cancer Biol 2019;55:16–27. doi:10.1016/j.semcancer.2018.05.009
  • Berger MF, Mardis ER. The emerging clinical relevance of genomics in cancer medicine. Nat Rev Clin Oncol 2018;15:353–65. doi:10.1038/S41571-018-0002-6
  • Baynam G, Bowman F, Lister K, et al. Improved diagnosis and care for rare diseases through implementation of precision public health framework. Adv Exp Med Biol 2017;1031:55–94. doi:10.1007/978-3-319-67144-4_4
  • Alves ITS, Condinho M, Custódio S, et al. Genetics of personalized medicine: cancer and rare diseases. Cell Oncol (Dordr) 2018;41:335–41. doi:10.1007/S13402-018-0379-3
  • Klein C, Gahl WA. Patients with rare diseases: from therapeutic orphans to pioneers of personalized treatments. EMBO Mol Med 2018;10:1–3. doi:10.15252/emmm.201708365
  • Chung RH, Kang CY. A multi-omics data simulator for complex disease studies and its application to evaluate multi-omics data analysis methods for disease classification. Gigascience 2019;8. doi:10.1093/gigascience/giz045
  • Pineda S, Gomez-Rubio P, Picornell A, et al. Framework for the Integration of Genomics, Epigenomics and Transcriptomics in Complex Diseases. Hum Hered 2015;79:124–36. doi:10.1159/000381184
  • Sun Y V., Hu YJ. Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases. Adv Genet 2016;93:147–90. doi:10.1016/BS.ADGEN.2015.11.004
  • Dar MA, Arafah A, Bhat KA, et al. Multiomics technologies: Role in disease biomarker discoveries and therapeutics. Brief Funct Genomics 2023;22:76–96. doi:10.1093/bfgp/elac017
  • Nassar SF, Raddassi K, Wu T. Single-Cell Multiomics Analysis for Drug Discovery. Metabolites 2021;11. doi:10.3390/METABO11110729
  • Oldoni E, Saunders G, Bietrix F, et al. Tackling the translational challenges of multi-omics research in the realm of European personalised medicine: A workshop report. Front Mol Biosci 2022;9. doi:10.3389/FMOLB.2022.974799
  • Tarazona S, Arzalluz-Luque A, Conesa A. Undisclosed, unmet and neglected challenges in multi-omics studies. Nat Comput Sci 2021 16 2021;1:395–402. doi:10.1038/s43588-021-00086-z