Signaling-induced systematic repression of miRNAs uncovers cancer vulnerabilities and targeted therapy sensitivity

Alexander Arthur Wurm(Helmholtz-Zentrum Dresden-Rossendorf), Silke Brilloff(Helmholtz-Zentrum Dresden-Rossendorf), Sofia Kolovich(Helmholtz-Zentrum Dresden-Rossendorf), Silvia Schäfer(Helmholtz-Zentrum Dresden-Rossendorf), Elahe Rahimian(Helmholtz-Zentrum Dresden-Rossendorf), Vida Kufrin(Helmholtz-Zentrum Dresden-Rossendorf), Marius Bill(Helmholtz-Zentrum Dresden-Rossendorf), Zunamys I. Carrero(Helmholtz-Zentrum Dresden-Rossendorf), Stephan Drukewitz(Helmholtz-Zentrum Dresden-Rossendorf), Alexander Krüger(Helmholtz-Zentrum Dresden-Rossendorf), Melanie Hüther(Helmholtz-Zentrum Dresden-Rossendorf), Sebastian Uhrig(Heidelberg University), Sandra Oster(Helmholtz-Zentrum Dresden-Rossendorf), Dana Westphal(University Hospital Carl Gustav Carus), Friedegund Meier(National Center for Tumor Diseases), Katrin Pfütze(German Cancer Research Center), Daniel Hübschmann(German Cancer Research Center), Peter Horak(German Cancer Research Center), Simon Kreutzfeldt(German Cancer Research Center), Daniela Richter(Helmholtz-Zentrum Dresden-Rossendorf), Evelin Schröck(Helmholtz-Zentrum Dresden-Rossendorf), Gustavo Baretton(Helmholtz-Zentrum Dresden-Rossendorf), Christoph Heining(Helmholtz-Zentrum Dresden-Rossendorf), Lino Möhrmann(Helmholtz-Zentrum Dresden-Rossendorf), Stefan Fröhling(German Cancer Research Center), Claudia R. Ball(Helmholtz-Zentrum Dresden-Rossendorf), Hanno Glimm(Heidelberg University)
Cell Reports Medicine
September 20, 2023
Cited by 16Open Access
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Abstract

Targeted therapies are effective in treating cancer, but success depends on identifying cancer vulnerabilities. In our study, we utilize small RNA sequencing to examine the impact of pathway activation on microRNA (miRNA) expression patterns. Interestingly, we discover that miRNAs capable of inhibiting key members of activated pathways are frequently diminished. Building on this observation, we develop an approach that integrates a low-miRNA-expression signature to identify druggable target genes in cancer. We train and validate our approach in colorectal cancer cells and extend it to diverse cancer models using patient-derived in vitro and in vivo systems. Finally, we demonstrate its additional value to support genomic and transcriptomic-based drug prediction strategies in a pan-cancer patient cohort from the National Center for Tumor Diseases (NCT)/German Cancer Consortium (DKTK) Molecularly Aided Stratification for Tumor Eradication (MASTER) precision oncology trial. In conclusion, our strategy can predict cancer vulnerabilities with high sensitivity and accuracy and might be suitable for future therapy recommendations in a variety of cancer subtypes.


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