Claude Gérard1, Mickaël Di-Luoffo1, Léolo Gonay2, Stefano Caruso3, Gabrielle Couchy3, Axelle Loriot1, Darko Castven4, Junyan Tao5, Katarzyna Konobrocka1, Sabine Cordi1, Satdarshan P Monga5, Emmanuel Hanert6, Jens U Marquardt4, Jessica Zucman-Rossi3, Frédéric P Lemaigre7. 1. de Duve Institute, Université catholique de Louvain, Brussels, Belgium. 2. de Duve Institute, Université catholique de Louvain, Brussels, Belgium; Earth and Life Institute, Université catholique de Louvain, Louvain-la-Neuve, Belgium. 3. Centre de Recherche des Cordeliers, Sorbonne Universités, Inserm, UMRS-1138, F-75006 Paris, France; Functional Genomics of Solid Tumors, USPC, Université Paris Descartes, Université Paris Diderot, Université Paris 13, Labex Immuno-Oncology, équipe labellisée Ligue Contre le Cancer, F-75000 Paris, France. 4. Department of Medicine I, Johannes Gutenberg University, Mainz, Germany. 5. Department of Pathology, Medicine and the Pittsburgh Liver Research Center, University of Pittsburgh, School of Medicine and University of Pittsburgh Medical Center, Pittsburgh, PA, USA. 6. Earth and Life Institute, Université catholique de Louvain, Louvain-la-Neuve, Belgium. 7. de Duve Institute, Université catholique de Louvain, Brussels, Belgium. Electronic address: frederic.lemaigre@uclouvain.be.
Abstract
BACKGROUND & AIMS: Alterations of individual genes variably affect the development of hepatocellular carcinoma (HCC). Thus, we aimed to characterize the function of tumor-promoting genes in the context of gene regulatory networks (GRNs). METHODS: Using data from The Cancer Genome Atlas, from the LIRI-JP (Liver Cancer - RIKEN, JP project), and from our transcriptomic, transfection and mouse transgenic experiments, we identify a GRN which functionally links LIN28B-dependent dedifferentiation with dysfunction of β-catenin (CTNNB1). We further generated and validated a quantitative mathematical model of the GRN using human cell lines and in vivo expression data. RESULTS: We found that LIN28B and CTNNB1 form a GRN with SMARCA4, Let-7b (MIRLET7B), SOX9, TP53 and MYC. GRN functionality is detected in HCC and gastrointestinal cancers, but not in other cancer types. GRN status negatively correlates with HCC prognosis, and positively correlates with hyperproliferation, dedifferentiation and HGF/MET pathway activation, suggesting that it contributes to a transcriptomic profile typical of the proliferative class of HCC. The mathematical model predicts how the expression of GRN components changes when the expression of another GRN member varies or is inhibited by a pharmacological drug. The dynamics of GRN component expression reveal distinct cell states that can switch reversibly in normal conditions, and irreversibly in HCC. The mathematical model is available via a web-based tool which can evaluate the GRN status of HCC samples and predict the impact of therapeutic agents on the GRN. CONCLUSIONS: We conclude that identification and modelling of the GRN provide insights into the prognosis of HCC and the mechanisms by which tumor-promoting genes impact on HCC development. LAY SUMMARY: Hepatocellular carcinoma (HCC) is a heterogeneous disease driven by the concomitant deregulation of several genes functionally organized as networks. Here, we identified a gene regulatory network involved in a subset of HCCs. This subset is characterized by increased proliferation and poor prognosis. We developed a mathematical model which uncovers the dynamics of the network and allows us to predict the impact of a therapeutic agent, not only on its specific target but on all the genes belonging to the network.
BACKGROUND & AIMS: Alterations of individual genes variably affect the development of hepatocellular carcinoma (HCC). Thus, we aimed to characterize the function of tumor-promoting genes in the context of gene regulatory networks (GRNs). METHODS: Using data from The Cancer Genome Atlas, from the LIRI-JP (Liver Cancer - RIKEN, JP project), and from our transcriptomic, transfection and mouse transgenic experiments, we identify a GRN which functionally links LIN28B-dependent dedifferentiation with dysfunction of β-catenin (CTNNB1). We further generated and validated a quantitative mathematical model of the GRN using human cell lines and in vivo expression data. RESULTS: We found that LIN28B and CTNNB1 form a GRN with SMARCA4, Let-7b (MIRLET7B), SOX9, TP53 and MYC. GRN functionality is detected in HCC and gastrointestinal cancers, but not in other cancer types. GRN status negatively correlates with HCC prognosis, and positively correlates with hyperproliferation, dedifferentiation and HGF/MET pathway activation, suggesting that it contributes to a transcriptomic profile typical of the proliferative class of HCC. The mathematical model predicts how the expression of GRN components changes when the expression of another GRN member varies or is inhibited by a pharmacological drug. The dynamics of GRN component expression reveal distinct cell states that can switch reversibly in normal conditions, and irreversibly in HCC. The mathematical model is available via a web-based tool which can evaluate the GRN status of HCC samples and predict the impact of therapeutic agents on the GRN. CONCLUSIONS: We conclude that identification and modelling of the GRN provide insights into the prognosis of HCC and the mechanisms by which tumor-promoting genes impact on HCC development. LAY SUMMARY:Hepatocellular carcinoma (HCC) is a heterogeneous disease driven by the concomitant deregulation of several genes functionally organized as networks. Here, we identified a gene regulatory network involved in a subset of HCCs. This subset is characterized by increased proliferation and poor prognosis. We developed a mathematical model which uncovers the dynamics of the network and allows us to predict the impact of a therapeutic agent, not only on its specific target but on all the genes belonging to the network.
Authors: Anne Gaza; Valerie Fritz; Lara Malek; Laura Wormser; Nora Treiber; Johannes Danner; Andreas E Kremer; Wolfgang E Thasler; Jürgen Siebler; Gunter Meister; Markus F Neurath; Claus Hellerbrand; Anja K Bosserhoff; Peter Dietrich Journal: Neoplasia Date: 2021-04-24 Impact factor: 5.715
Authors: Alejandra Ortiz-González; Pedro Pablo González-Pérez; Maura Cárdenas-García; María Guadalupe Hernández-Linares Journal: Cancer Inform Date: 2022-03-25