Protein Kinase Inhibitors; Insulins; NRAS protein, human; Membrane Proteins; GTP Phosphohydrolases; Humans; Multiomics; Cell Line, Tumor; Protein Kinase Inhibitors/pharmacology; Protein Kinase Inhibitors/therapeutic use; Cellular Senescence/genetics; Membrane Proteins/genetics; GTP Phosphohydrolases/genetics; GTP Phosphohydrolases/therapeutic use; Melanoma/drug therapy; Melanoma/genetics; Insulins/therapeutic use; Cellular Senescence; Melanoma; Molecular Medicine; Molecular Biology; Cancer Research
Abstract :
[en] Therapy Induced Senescence (TIS) leads to sustained growth arrest of cancer cells. The associated cytostasis has been shown to be reversible and cells escaping senescence further enhance the aggressiveness of cancers. Chemicals specifically targeting senescent cells, so-called senolytics, constitute a promising avenue for improved cancer treatment in combination with targeted therapies. Understanding how cancer cells evade senescence is needed to optimise the clinical benefits of this therapeutic approach. Here we characterised the response of three different NRAS mutant melanoma cell lines to a combination of CDK4/6 and MEK inhibitors over 33 days. Transcriptomic data show that all cell lines trigger a senescence programme coupled with strong induction of interferons. Kinome profiling revealed the activation of Receptor Tyrosine Kinases (RTKs) and enriched downstream signaling of neurotrophin, ErbB and insulin pathways. Characterisation of the miRNA interactome associates miR-211-5p with resistant phenotypes. Finally, iCell-based integration of bulk and single-cell RNA-seq data identifies biological processes perturbed during senescence and predicts 90 new genes involved in its escape. Overall, our data associate insulin signaling with persistence of a senescent phenotype and suggest a new role for interferon gamma in senescence escape through the induction of EMT and the activation of ERK5 signaling.
Disciplines :
Life sciences: Multidisciplinary, general & others
Author, co-author :
GUREGHIAN, Vincent ; University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Life Sciences and Medicine (DLSM)
HERBST, Hailee ; University of Luxembourg > Faculty of Science, Technology and Medicine > Department of Life Sciences and Medicine > Team Iris BEHRMANN
KOZAR, Ines ; University of Luxembourg > Faculty of Science, Technology and Medicine > Department of Life Sciences and Medicine > Team Iris BEHRMANN ; Laboratoire National de Santé, Dudelange, Luxembourg
MIHAJLOVIC, Katarina ; University of Luxembourg ; Barcelona Supercomputing Center, 08034, Barcelona, Spain
Malod-Dognin, Noël; Barcelona Supercomputing Center, 08034, Barcelona, Spain
Ceddia, Gaia; Barcelona Supercomputing Center, 08034, Barcelona, Spain
ANGELI, Cristian ; University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Life Sciences and Medicine (DLSM)
WURTH-MARGUE, Christiane ; University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Life Sciences and Medicine (DLSM)
RANDIC, Tijana ; University of Luxembourg > Faculty of Science, Technology and Medicine > Department of Life Sciences and Medicine > Team Stephanie KREIS
PHILIPPIDOU, Demetra ; University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Life Sciences and Medicine (DLSM)
TETSI NOMIGNI, Milène ; University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Life Sciences and Medicine (DLSM)
HEMEDAN, Ahmed ; University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > Bioinformatics Core
TRANCHEVENT, Leon-Charles ; University of Luxembourg > Luxembourg Centre for Systems Biomedicine > Biomedical Data Science > Team Enrico GLAAB
LONGWORTH, Joseph ; University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > Immunology and Genetics ; Experimental and Molecular Immunology, Department of Infection and Immunity, Luxembourg Institute of Health, Esch-sur-Alzette, Luxembourg
Bauer, Mark; Department of Life Sciences and Medicine, University of Luxembourg, 6, Avenue du Swing, L-4367, Belvaux, Luxembourg
BADKAS, Apurva ; University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Life Sciences and Medicine (DLSM)
GAIGNEAUX, Anthoula ; University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Life Sciences and Medicine (DLSM)
Muller, Arnaud ; LuxGen, TMOH and Bioinformatics platform, Data Integration and Analysis unit, Luxembourg Institute of Health, Esch-sur-Alzette, Luxembourg
OSTASZEWSKI, Marek ; University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > Bioinformatics Core
TOLLE, Fabrice ; University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Life Sciences and Medicine (DLSM)
Pržulj, Nataša; Barcelona Supercomputing Center, 08034, Barcelona, Spain ; Department of Computer Science, University College London, London, WC1E 6BT, UK ; ICREA, Pg. Lluís Companys 23, 08010, Barcelona, Spain
KREIS, Stephanie ; University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Life Sciences and Medicine (DLSM)
VG is supported by the Luxembourg National Research Fond (FNR) PRIDE DTU CanBIO [grant reference: 21/16763386]. TR is supported by the FNR PRIDE DTU CriTiCS [grant reference: 10907093]. Project-related work performed by VG, HH, CM, DP, MTN, MB, AG, FT and SK were also supported by the University of Luxembourg and the Fondation Cancer, Luxembourg (grant “SecMelPro”). KM and NP are supported by funding from the European Union’s EU Framework Programme for Research and Innovation Horizon 2020, Innovative Training Networks (MSCA-ITN-2019), funded under EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions, Grant Agreement No 860895. KM, NMD, GC and NP are supported by funding from the European Research Council (ERC) Consolidator Grant 770827. NP is also supported by funding from the Spanish State Research Agency AEI 10.13039/501100011033 grant number PID2019-105500GB-I00.The authors want to thank L. Sinkonnen for his suggestions regarding the qCLASH method and its extended applications, J.P. Wroblewska for her feedback and her insights regarding the biology of amelanotic melanoma, A. Ginolhac for his help in the analysis of our RNA-seq data and his tips regarding R language. Several in silico experiments presented in this paper were carried out using the HPC facilities of the University of Luxembourg, Varrette et al. 2022, https://hpc.uni.lu.
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