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Identification of transcriptional network disruptions in drug-resistant prostate cancer with TraRe

Charles Blatti, Jesús de la Fuente, Huanyao Gao, Irene Marín, Zikun Chen, Sihai. D. Zhao, Winston Tan, Richard Weinshilbaum, Krishna R. Kalari, Liewei Wang, Mikel Hernaez
doi: https://doi.org/10.1101/2022.05.10.491360
Charles Blatti
1NCSA, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
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Jesús de la Fuente
2TECNUN School of Engineering, University of Navarra, San Sebastián, 20018, Spain
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Huanyao Gao
3College of Medicine, Mayo Clinic, Rochester, MN, 55905, USA
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Irene Marín
4Computational Biology Program, CIMA University of Navarra, Pamplona, 31080, Spain
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Zikun Chen
5Depart. of Computer Science, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
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Sihai. D. Zhao
6Depart. of Statistics, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
7Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
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Winston Tan
3College of Medicine, Mayo Clinic, Rochester, MN, 55905, USA
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Richard Weinshilbaum
3College of Medicine, Mayo Clinic, Rochester, MN, 55905, USA
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Krishna R. Kalari
3College of Medicine, Mayo Clinic, Rochester, MN, 55905, USA
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Liewei Wang
3College of Medicine, Mayo Clinic, Rochester, MN, 55905, USA
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  • For correspondence: mhernaez@unav.es Wang.Liewei@mayo.edu
Mikel Hernaez
4Computational Biology Program, CIMA University of Navarra, Pamplona, 31080, Spain
7Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
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  • For correspondence: mhernaez@unav.es Wang.Liewei@mayo.edu
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Abstract

Metastatic castration-resistant prostate cancer (mCRPC) presents very low survival rates due to lack of response or acquired resistance to the available therapies. To date no molecular mechanisms of resistance have been identified, pointing out their complex dynamics. To identify key genes and processes associated with phenotypically-driven regulatory differences, we developed TraRe, a computational method that provides a three-tier analysis: i) at the network level, inferring differentially regulated modules; ii) at the regulon level, identifying regulatory relationships linked to phenotypic differences; and iii) at the single gene level, identifying TFs consistently linked to rewired modules. We applied TraRe (available in Bioconductor with full documentation) to transcriptomic data from 46 mCRPC patients with Abiraterone-response clinical data and uncovered abrogated immune response regulatory modules that showed strong differential regulation in Abi-resistant patients. These modules were replicated in an independent mCRPC study. Further, we experimentally validated key rewiring predictions and their associated transcription factors. Among them, ELK3, MXD1, and MYB were found to have a differential role in cell survival for Abi-response-specific settings. Moreover, we identified the role of ELK3 in cell migration capacity, which could have direct impact on mCRPC. Collectively, these findings shed light on the underlying regulatory mechanisms driving abiraterone response.

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.

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 May 11, 2022.
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Identification of transcriptional network disruptions in drug-resistant prostate cancer with TraRe
Charles Blatti, Jesús de la Fuente, Huanyao Gao, Irene Marín, Zikun Chen, Sihai. D. Zhao, Winston Tan, Richard Weinshilbaum, Krishna R. Kalari, Liewei Wang, Mikel Hernaez
bioRxiv 2022.05.10.491360; doi: https://doi.org/10.1101/2022.05.10.491360
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Identification of transcriptional network disruptions in drug-resistant prostate cancer with TraRe
Charles Blatti, Jesús de la Fuente, Huanyao Gao, Irene Marín, Zikun Chen, Sihai. D. Zhao, Winston Tan, Richard Weinshilbaum, Krishna R. Kalari, Liewei Wang, Mikel Hernaez
bioRxiv 2022.05.10.491360; doi: https://doi.org/10.1101/2022.05.10.491360

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