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Deciphering genetic and nongenetic factors underlying tumour dormancy: insights from multiomics analysis of two syngeneic MRD models of melanoma and leukemia

Title: Deciphering genetic and nongenetic factors underlying tumour dormancy: insights from multiomics analysis of two syngeneic MRD models of melanoma and leukemia
Authors: Laguillaumie, Marie-Oceane; Titah, Sofia; Guillemette, Aurélie; Neve, Bernadette; Leprêtre, Frédéric; Ségard, Pascaline; Shaik, Faruk; Collard, Dominique; Gerbedoen, Jean-Claude; Fléchon, Léa; Hasan Bou Issa, Lama; Vincent, Audrey; Figeac, Martin; Sebda, Shéhérazade; Villenet, Celine; Kluza, Jerome; Laine, William; Fournier, Isabelle; Gimeno, Jean-Pascal; Wisztorski, Maxence; Manier, Salomon; Tarhan, Mehmet-Cagatay; Quesnel, Bruno; Idziorek, Thierry; Touil, Yasmine
Contributors: Université de Lille; Inserm; CHU Lille; Laboratoire de Physiologie Cellulaire - U 1003 PHYCELL; Hétérogénéité, Plasticité et Résistance aux Thérapies des Cancers = Cancer Heterogeneity, Plasticity and Resistance to Therapies - UMR 9020 - U 1277 CANTHER; Cancer Heterogeneity, Plasticity and Resistance to Therapies (CANTHER) - UMR 9020 - UMR 1277; Plateformes Lilloises en Biologie et Santé (PLBS) - UAR 2014 - US 41; The University of Tokyo UTokyo; Laboratory for Integrated Micro Mechatronics Systems LIMMS; JUNIA JUNIA; Protéomique, Réponse Inflammatoire, Spectrométrie de Masse (PRISM) - U1192; Institut d'Électronique, de Microélectronique et de Nanotechnologie (IEMN) - UMR 8520
Publisher Information: Sociedad de Biología de Chile
Publication Year: 2024
Collection: LillOA (Lille Open Archive - Université de Lille)
Subject Terms: Tumour dormancy; Leukemia; Melanoma; Syngeneic model; Multiomics analysis; ChIP-seq; Whole exome sequencing; Copy number variation
Description: Background Tumour dormancy, a resistance mechanism employed by cancer cells, is a significant challenge in cancer treatment, contributing to minimal residual disease (MRD) and potential relapse. Despite its clinical importance, the mechanisms underlying tumour dormancy and MRD remain unclear. In this study, we employed two syngeneic murine models of myeloid leukemia and melanoma to investigate the genetic, epigenetic, transcriptomic and protein signatures associated with tumour dormancy. We used a multiomics approach to elucidate the molecular mechanisms driving MRD and identify potential therapeutic targets. Results We conducted an in-depth omics analysis encompassing whole-exome sequencing (WES), copy number variation (CNV) analysis, chromatin immunoprecipitation followed by sequencing (ChIP-seq), transcriptome and proteome investigations. WES analysis revealed a modest overlap of gene mutations between melanoma and leukemia dormancy models, with a significant number of mutated genes found exclusively in dormant cells. These exclusive genetic signatures suggest selective pressure during MRD, potentially conferring resistance to the microenvironment or therapies. CNV, histone marks and transcriptomic gene expression signatures combined with Gene Ontology (GO) enrichment analysis highlighted the potential functional roles of the mutated genes, providing insights into the pathways associated with MRD. In addition, we compared “murine MRD genes” profiles to the corresponding human disease through public datasets and highlighted common features according to disease progression. Proteomic analysis combined with multi-omics genetic investigations, revealed a dysregulated proteins signature in dormant cells with minimal genetic mechanism involvement. Pathway enrichment analysis revealed the metabolic, differentiation and cytoskeletal remodeling processes involved in MRD. Finally, we identified 11 common proteins differentially expressed in dormant cells from both pathologies. Conclusions Our study underscores the ...
Document Type: article in journal/newspaper
File Description: application/octet-stream; application/rdf+xml; charset=utf-8; application/pdf
Language: English
Relation: Instrumentation intelligente de cytométrie biophysique en flux pour une approche d'apprentissage statistique; Biological Research; Biol Res; http://hdl.handle.net/20.500.12210/116845
Availability: https://hdl.handle.net/20.500.12210/116845
Rights: Attribution 3.0 United States ; info:eu-repo/semantics/openAccess
Accession Number: edsbas.A64A3C38
Database: BASE