Suchergebnisse

Multiple myeloma (MM) is a plasma cell neoplasm associated with a broad variety of genetic lesions. In spite of this genetic heterogeneity, MMs share a characteristic malignant phenotype whose underlying molecular basis remains poorly characterized. In the present study, we examined plasma cells from MM using a multi-epigenomics approach and demonstrated that, when compared to normal B cells, malignant plasma cells showed an extensive activation of regulatory elements, in part affecting coregulated adjacent genes. Among target genes up-regulated by this process, we found members of the NOTCH, NF-kB, MTOR signaling, and TP53 signaling pathways. Other activated genes included sets involved in osteoblast differentiation and response to oxidative stress, all of which have been shown to be associated with the MM phenotype and clinical behavior. We functionally characterized MM-specific active distant enhancers controlling the expression of thioredoxin (TXN), a major regulator of cellular redox status and, in addition, identified PRDM5 as a novel essential gene for MM. Collectively, our data indicate that aberrant chromatin activation is a unifying feature underlying the malignant plasma cell phenotype. ; This research was funded by the European Union's Seventh Framework Programme through the Blueprint Consortium (grant agreement 282510), Fundació La Marató de TV3, Instituto de Salud Carlos III (ISCIII) PI14/01867, PI16/02024, and PI17/00701, TRASCAN (EPICA), MINECO Explora (RTHALMY), Departamento de Salud del Gobierno de Navarra 40/2016, Gilead Fellowship Program (GLD16/00142), Multiple Myeloma Research Foundation Networks of excellence, the International Myeloma Foundation (Brian van Novis) and the Qatar National Research Fund award 7-916-3-237. Furthermore, the authors acknowledge the support of the Generalitat de Catalunya Suport Grups de Recerca AGAUR 2017-SGR-736 and 2017-SGR-1142, TRASCAN-iMMunocelland European Research Council starting grant (MYELOMANEXT), CIBERONC (CB16/12/00489, CB16/12/00369 and CB16/12/00225), co-financed with FEDER funds, the Accelerator award CRUK/AIRC/AECC joint funder-partnership, as well as NCI R01 CA180475 and a MMRF collaborative grant. R.O. was supported by a FPU Fellowship of the Spanish Government, M.K. by an AOI grant of the Spanish Association Against Cancer and N.R. by the Acció instrumental d'incorporació de scientífics i tecnòlegs PERIS 2016 from the Generalitat de Catalunya. This work was partially developed at the Centro Esther Koplowitz (CEK, Barcelona, Spain). We particularly acknowledge the patients for their participation and the Biobank of the University of Navarra for its collaboration.

Robust protocols and automation now enable large-scale single-cell RNA and ATAC sequencing experiments and their application on biobank and clinical cohorts. However, technical biases introduced during sample acquisition can hinder solid, reproducible results, and a systematic benchmarking is required before entering large-scale data production. Here, we report the existence and extent of gene expression and chromatin accessibility artifacts introduced during sampling and identify experimental and computational solutions for their prevention. ; HH is a Miguel Servet (CP14/00229) researcher funded by the Spanish Institute of Health Carlos III (ISCIII). CM and MK are supported by AECC postdoctoral fellowships. This work has received funding from the Ministerio de Ciencia, Innovación y Universidades (SAF2017-89109-P; AEI/FEDER, UE). This study was further funded by the Spanish Ministry of Economy and Competitiveness (grant number: IPT-010000-2010- 36, cofunded by the European Regional Development Fund). Core funding is from the ISCIII and the Generalitat de Catalunya. We acknowledge support of the Spanish Ministry of Economy, Industry and Competitiveness (MEIC) to the EMBL partnership, the Centro de Excelencia Severo Ochoa, the CERCA Programme/Generalitat de Catalunya, the Spanish Ministry of Economy, Industry and Competitiveness (MEIC) through the Instituto de Salud Carlos III and the Generalitat de Catalunya through Departament de Salut and Departament d'Empresa i Coneixement. We also acknowledge the Co-financing by the Spanish Ministry of Economy, Industry and Competitiveness (MEIC) with funds from the European Regional Development Fund (ERDF) corresponding to the 2014–2020 Smart Growth Operating Program. We acknowledge the Generalitat de Catalunya Suport Grups de Recerca AGAUR 2017-SGR-736 (to JIMS) and 2017-SGR-1142 (to EC), and CIBERONC (CB16/12/00225 and CB16/12/00334). EC is an ICREA Academia Researcher. This project received support from the European Commission under the projects DocTIS (H2020, SEP-210574908). This publication is part of a project (BCLLATLAS) that has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program (grant agreement No 810287)