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spongEffects: ceRNA modules offer patient-specific insights into the miRNA regulatory landscape

Fabio Boniolo, View ORCID ProfileMarkus Hoffmann, Norman Roggendorf, Bahar Tercan, View ORCID ProfileJan Baumbach, View ORCID ProfileMauro A. A. Castro, A. Gordon Robertson, Dieter Saur, View ORCID ProfileMarkus List
doi: https://doi.org/10.1101/2022.03.29.486212
Fabio Boniolo
1Big Data in BioMedicine Group, Chair of Experimental Bioinformatics, TUM School of Life Sciences, Technical University of Munich, Munich, Germany
2Chair of Translational Cancer Research and Institute of Experimental Cancer Therapy, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
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Markus Hoffmann
1Big Data in BioMedicine Group, Chair of Experimental Bioinformatics, TUM School of Life Sciences, Technical University of Munich, Munich, Germany
3Institute for Advanced Study (Lichtenbergstrasse 2 a, D-85748 Garching, Germany), Technical University of Munich, Germany
4National Institute of Diabetes, Digestive, and Kidney Diseases, Bethesda, MD 20892, United States of America
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  • For correspondence: markus.daniel.hoffmann@tum.de markus.list@tum.de
Norman Roggendorf
1Big Data in BioMedicine Group, Chair of Experimental Bioinformatics, TUM School of Life Sciences, Technical University of Munich, Munich, Germany
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Bahar Tercan
5Institute for Systems Biology, Seattle, WA, USA
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Jan Baumbach
6Chair of Computational Systems Biology, University of Hamburg, Hamburg, Germany
7Computational BioMedicine Lab, University of Southern Denmark, Odense, Denmark
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Mauro A. A. Castro
8Bioinformatics and Systems Biology Laboratory, Universidade Federal do Paraná, Curitiba, Brazil
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A. Gordon Robertson
9BC Cancer Genome Sciences Centre, Vancouver, Canada; Dxige Research Inc., Courtenay BC Canada
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Dieter Saur
2Chair of Translational Cancer Research and Institute of Experimental Cancer Therapy, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
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Markus List
1Big Data in BioMedicine Group, Chair of Experimental Bioinformatics, TUM School of Life Sciences, Technical University of Munich, Munich, Germany
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  • For correspondence: markus.daniel.hoffmann@tum.de markus.list@tum.de
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ABSTRACT

Motivation Cancer is one of the leading causes of death worldwide. Despite significant improvements in prevention and treatment, mortality remains high for many cancer types. Hence, innovative methods that use molecular data to stratify patients and identify biomarkers are needed. Promising biomarkers can also be inferred from competing endogenous RNA (ceRNA) networks that capture the gene-miRNA gene regulatory landscape. Thus far, the role of these biomarkers could only be studied globally but not in a sample-specific manner. To mitigate this, we introduce spongEffects, a novel method that infers subnetworks (or modules) from ceRNA networks and calculates patient- or sample-specific scores related to their regulatory activity.

Results We show how spongEffects can be used for downstream interpretation and machine learning tasks such as tumor classification and for identifying subtype-specific regulatory interactions. In a concrete example of breast cancer subtype classification, we prioritize modules impacting the biology of the different subtypes. In summary, spongEffects prioritizes ceRNA modules as biomarkers and offers insights into the miRNA regulatory landscape. Notably, these module scores can be inferred from gene expression data alone and can thus be applied to cohorts where miRNA expression information is lacking.

Availability https://bioconductor.org/packages/devel/bioc/html/SPONGE.html

Contact markus.daniel.hoffmann{at}tum.de; markus.list{at}tum.de

Supplementary information Supplementary data are available at Bioinformatics online.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • ↵* The authors wish it to be known that, in their opinion, the first two authors should be regarded as Joint First Authors

  • We enhanced the script with many additional analyses to give the user trust in the spongEffects method.

  • https://github.com/biomedbigdata/SPONGE

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted February 03, 2023.
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spongEffects: ceRNA modules offer patient-specific insights into the miRNA regulatory landscape
Fabio Boniolo, Markus Hoffmann, Norman Roggendorf, Bahar Tercan, Jan Baumbach, Mauro A. A. Castro, A. Gordon Robertson, Dieter Saur, Markus List
bioRxiv 2022.03.29.486212; doi: https://doi.org/10.1101/2022.03.29.486212
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spongEffects: ceRNA modules offer patient-specific insights into the miRNA regulatory landscape
Fabio Boniolo, Markus Hoffmann, Norman Roggendorf, Bahar Tercan, Jan Baumbach, Mauro A. A. Castro, A. Gordon Robertson, Dieter Saur, Markus List
bioRxiv 2022.03.29.486212; doi: https://doi.org/10.1101/2022.03.29.486212

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