Convergent network effects along the axis of gene expression during prostate cancer progression
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RESEARCH
Open Access
Convergent network effects along the axis of gene expression during prostate cancer progression Konstantina Charmpi1,2†, Tiannan Guo3,4,5*†, Qing Zhong6,7†, Ulrich Wagner6†, Rui Sun4,5, Nora C. Toussaint6,8,9, Christine E. Fritz6, Chunhui Yuan4,5, Hao Chen4,5, Niels J. Rupp6, Ailsa Christiansen6, Dorothea Rutishauser6, Jan H. Rüschoff6, Christian Fankhauser6, Karim Saba6,10, Cedric Poyet10, Thomas Hermanns10, Kathrin Oehl6, Ariane L. Moore11, Christian Beisel11, Laurence Calzone12, Loredana Martignetti12, Qiushi Zhang4,5, Yi Zhu3,4,5, María Rodríguez Martínez13, Matteo Manica13, Michael C. Haffner14, Ruedi Aebersold3,15*, Peter J. Wild6,16* and Andreas Beyer1,2* * Correspondence: guotiannan@ westlake.edu.cn; aebersold@imsb. biol.ethz.ch; [email protected]; [email protected] † Konstantina Charmpi, Tiannan Guo, Qing Zhong and Ulrich Wagner contributed equally to this work. 3 Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland 6 Department of Pathology and Molecular Pathology, University Hospital Zurich, University of Zurich, Zurich, Switzerland 1 CECAD, University of Cologne, Cologne, Germany Full list of author information is available at the end of the article
Abstract Background: Tumor-specific genomic aberrations are routinely determined by highthroughput genomic measurements. It remains unclear how complex genome alterations affect molecular networks through changing protein levels and consequently biochemical states of tumor tissues. Results: Here, we investigate the propagation of genomic effects along the axis of gene expression during prostate cancer progression. We quantify genomic, transcriptomic, and proteomic alterations based on 105 prostate samples, consisting of benign prostatic hyperplasia regions and malignant tumors, from 39 prostate cancer patients. Our analysis reveals the convergent effects of distinct copy number alterations impacting on common downstream proteins, which are important for establishing the tumor phenotype. We devise a network-based approach that integrates perturbations across different molecular layers, which identifies a subnetwork consisting of nine genes whose joint activity positively correlates with increasingly aggressive tumor phenotypes and is predictive of recurrence-free survival. Further, our data reveal a wide spectrum of intra-patient network effects, ranging from similar to very distinct alterations on different molecular layers. Conclusions: This study uncovers molecular networks with considerable convergent alterations across tumor sites and patients. It also exposes a diversity of network effects: we could not identify a single sub-network that is perturbed in all high-grade tumor regions. Keywords: Molecular aberrations, Network effects, Prostate cancer, Proteogenomic analysis, Tumor heterogeneity
© The Author(s). 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in
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