The DNA methylation landscape of multiple myeloma shows extensive inter- and intrapatient heterogeneity that fuels transcriptomic variability

Abstract Background Cancer evolution depends on epigenetic and genetic diversity. Historically, in multiple myeloma (MM), subclonal diversity and tumor evolution have been investigated mostly from a genetic perspective. Methods Here, we performed an analysis of 42 MM samples from 21 patients by usin...
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Autor*in:	Jennifer Derrien [verfasserIn] Catherine Guérin-Charbonnel [verfasserIn] Victor Gaborit [verfasserIn] Loïc Campion [verfasserIn] Magali Devic [verfasserIn] Elise Douillard [verfasserIn] Nathalie Roi [verfasserIn] Hervé Avet-Loiseau [verfasserIn] Olivier Decaux [verfasserIn] Thierry Facon [verfasserIn] Jan-Philipp Mallm [verfasserIn] Roland Eils [verfasserIn] Nikhil C. Munshi [verfasserIn] Philippe Moreau [verfasserIn] Carl Herrmann [verfasserIn] Florence Magrangeas [verfasserIn] Stéphane Minvielle [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2021

Schlagwörter:	Multiple myeloma Disordered DNA methylation Epipolymorphism Epiallele switching Inter- and intrapatient heterogeneity Transcriptomic variability

Übergeordnetes Werk:	In: Genome Medicine - BMC, 2016, 13(2021), 1, Seite 21
Übergeordnetes Werk:	volume:13 ; year:2021 ; number:1 ; pages:21

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1186/s13073-021-00938-3

Katalog-ID:	DOAJ055476376

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520			\|a Abstract Background Cancer evolution depends on epigenetic and genetic diversity. Historically, in multiple myeloma (MM), subclonal diversity and tumor evolution have been investigated mostly from a genetic perspective. Methods Here, we performed an analysis of 42 MM samples from 21 patients by using enhanced reduced representation bisulfite sequencing (eRRBS). We combined several metrics of epigenetic heterogeneity to analyze DNA methylation heterogeneity in MM patients. Results We show that MM is characterized by the continuous accumulation of stochastic methylation at the promoters of development-related genes. High combinatorial entropy change is associated with poor outcomes in our pilot study and depends predominantly on partially methylated domains (PMDs). These PMDs, which represent the major source of inter- and intrapatient DNA methylation heterogeneity in MM, are linked to other key epigenetic aberrations, such as CpG island (CGI)/transcription start site (TSS) hypermethylation and H3K27me3 redistribution as well as 3D organization alterations. In addition, transcriptome analysis revealed that intratumor methylation heterogeneity was associated with low-level expression and high variability. Conclusions We propose that disrupted DNA methylation in MM is responsible for high epigenetic and transcriptomic instability allowing tumor cells to adapt to environmental changes by tapping into a pool of evolutionary trajectories.
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650		4	\|a Disordered DNA methylation
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allfields	10.1186/s13073-021-00938-3 doi (DE-627)DOAJ055476376 (DE-599)DOAJ4a911b1129d149468316660d33d6e2e4 DE-627 ger DE-627 rakwb eng QH426-470 Jennifer Derrien verfasserin aut The DNA methylation landscape of multiple myeloma shows extensive inter- and intrapatient heterogeneity that fuels transcriptomic variability 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Background Cancer evolution depends on epigenetic and genetic diversity. Historically, in multiple myeloma (MM), subclonal diversity and tumor evolution have been investigated mostly from a genetic perspective. Methods Here, we performed an analysis of 42 MM samples from 21 patients by using enhanced reduced representation bisulfite sequencing (eRRBS). We combined several metrics of epigenetic heterogeneity to analyze DNA methylation heterogeneity in MM patients. Results We show that MM is characterized by the continuous accumulation of stochastic methylation at the promoters of development-related genes. High combinatorial entropy change is associated with poor outcomes in our pilot study and depends predominantly on partially methylated domains (PMDs). These PMDs, which represent the major source of inter- and intrapatient DNA methylation heterogeneity in MM, are linked to other key epigenetic aberrations, such as CpG island (CGI)/transcription start site (TSS) hypermethylation and H3K27me3 redistribution as well as 3D organization alterations. In addition, transcriptome analysis revealed that intratumor methylation heterogeneity was associated with low-level expression and high variability. Conclusions We propose that disrupted DNA methylation in MM is responsible for high epigenetic and transcriptomic instability allowing tumor cells to adapt to environmental changes by tapping into a pool of evolutionary trajectories. Multiple myeloma Disordered DNA methylation Epipolymorphism Epiallele switching Inter- and intrapatient heterogeneity Transcriptomic variability Medicine R Genetics Catherine Guérin-Charbonnel verfasserin aut Victor Gaborit verfasserin aut Loïc Campion verfasserin aut Magali Devic verfasserin aut Elise Douillard verfasserin aut Nathalie Roi verfasserin aut Hervé Avet-Loiseau verfasserin aut Olivier Decaux verfasserin aut Thierry Facon verfasserin aut Jan-Philipp Mallm verfasserin aut Roland Eils verfasserin aut Nikhil C. Munshi verfasserin aut Philippe Moreau verfasserin aut Carl Herrmann verfasserin aut Florence Magrangeas verfasserin aut Stéphane Minvielle verfasserin aut In Genome Medicine BMC, 2016 13(2021), 1, Seite 21 (DE-627)594424275 (DE-600)2484394-5 1756994X nnns volume:13 year:2021 number:1 pages:21 https://doi.org/10.1186/s13073-021-00938-3 kostenfrei https://doaj.org/article/4a911b1129d149468316660d33d6e2e4 kostenfrei https://doi.org/10.1186/s13073-021-00938-3 kostenfrei https://doaj.org/toc/1756-994X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 13 2021 1 21
spelling	10.1186/s13073-021-00938-3 doi (DE-627)DOAJ055476376 (DE-599)DOAJ4a911b1129d149468316660d33d6e2e4 DE-627 ger DE-627 rakwb eng QH426-470 Jennifer Derrien verfasserin aut The DNA methylation landscape of multiple myeloma shows extensive inter- and intrapatient heterogeneity that fuels transcriptomic variability 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Background Cancer evolution depends on epigenetic and genetic diversity. Historically, in multiple myeloma (MM), subclonal diversity and tumor evolution have been investigated mostly from a genetic perspective. Methods Here, we performed an analysis of 42 MM samples from 21 patients by using enhanced reduced representation bisulfite sequencing (eRRBS). We combined several metrics of epigenetic heterogeneity to analyze DNA methylation heterogeneity in MM patients. Results We show that MM is characterized by the continuous accumulation of stochastic methylation at the promoters of development-related genes. High combinatorial entropy change is associated with poor outcomes in our pilot study and depends predominantly on partially methylated domains (PMDs). These PMDs, which represent the major source of inter- and intrapatient DNA methylation heterogeneity in MM, are linked to other key epigenetic aberrations, such as CpG island (CGI)/transcription start site (TSS) hypermethylation and H3K27me3 redistribution as well as 3D organization alterations. In addition, transcriptome analysis revealed that intratumor methylation heterogeneity was associated with low-level expression and high variability. Conclusions We propose that disrupted DNA methylation in MM is responsible for high epigenetic and transcriptomic instability allowing tumor cells to adapt to environmental changes by tapping into a pool of evolutionary trajectories. Multiple myeloma Disordered DNA methylation Epipolymorphism Epiallele switching Inter- and intrapatient heterogeneity Transcriptomic variability Medicine R Genetics Catherine Guérin-Charbonnel verfasserin aut Victor Gaborit verfasserin aut Loïc Campion verfasserin aut Magali Devic verfasserin aut Elise Douillard verfasserin aut Nathalie Roi verfasserin aut Hervé Avet-Loiseau verfasserin aut Olivier Decaux verfasserin aut Thierry Facon verfasserin aut Jan-Philipp Mallm verfasserin aut Roland Eils verfasserin aut Nikhil C. Munshi verfasserin aut Philippe Moreau verfasserin aut Carl Herrmann verfasserin aut Florence Magrangeas verfasserin aut Stéphane Minvielle verfasserin aut In Genome Medicine BMC, 2016 13(2021), 1, Seite 21 (DE-627)594424275 (DE-600)2484394-5 1756994X nnns volume:13 year:2021 number:1 pages:21 https://doi.org/10.1186/s13073-021-00938-3 kostenfrei https://doaj.org/article/4a911b1129d149468316660d33d6e2e4 kostenfrei https://doi.org/10.1186/s13073-021-00938-3 kostenfrei https://doaj.org/toc/1756-994X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 13 2021 1 21
allfields_unstemmed	10.1186/s13073-021-00938-3 doi (DE-627)DOAJ055476376 (DE-599)DOAJ4a911b1129d149468316660d33d6e2e4 DE-627 ger DE-627 rakwb eng QH426-470 Jennifer Derrien verfasserin aut The DNA methylation landscape of multiple myeloma shows extensive inter- and intrapatient heterogeneity that fuels transcriptomic variability 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Background Cancer evolution depends on epigenetic and genetic diversity. Historically, in multiple myeloma (MM), subclonal diversity and tumor evolution have been investigated mostly from a genetic perspective. Methods Here, we performed an analysis of 42 MM samples from 21 patients by using enhanced reduced representation bisulfite sequencing (eRRBS). We combined several metrics of epigenetic heterogeneity to analyze DNA methylation heterogeneity in MM patients. Results We show that MM is characterized by the continuous accumulation of stochastic methylation at the promoters of development-related genes. High combinatorial entropy change is associated with poor outcomes in our pilot study and depends predominantly on partially methylated domains (PMDs). These PMDs, which represent the major source of inter- and intrapatient DNA methylation heterogeneity in MM, are linked to other key epigenetic aberrations, such as CpG island (CGI)/transcription start site (TSS) hypermethylation and H3K27me3 redistribution as well as 3D organization alterations. In addition, transcriptome analysis revealed that intratumor methylation heterogeneity was associated with low-level expression and high variability. Conclusions We propose that disrupted DNA methylation in MM is responsible for high epigenetic and transcriptomic instability allowing tumor cells to adapt to environmental changes by tapping into a pool of evolutionary trajectories. Multiple myeloma Disordered DNA methylation Epipolymorphism Epiallele switching Inter- and intrapatient heterogeneity Transcriptomic variability Medicine R Genetics Catherine Guérin-Charbonnel verfasserin aut Victor Gaborit verfasserin aut Loïc Campion verfasserin aut Magali Devic verfasserin aut Elise Douillard verfasserin aut Nathalie Roi verfasserin aut Hervé Avet-Loiseau verfasserin aut Olivier Decaux verfasserin aut Thierry Facon verfasserin aut Jan-Philipp Mallm verfasserin aut Roland Eils verfasserin aut Nikhil C. Munshi verfasserin aut Philippe Moreau verfasserin aut Carl Herrmann verfasserin aut Florence Magrangeas verfasserin aut Stéphane Minvielle verfasserin aut In Genome Medicine BMC, 2016 13(2021), 1, Seite 21 (DE-627)594424275 (DE-600)2484394-5 1756994X nnns volume:13 year:2021 number:1 pages:21 https://doi.org/10.1186/s13073-021-00938-3 kostenfrei https://doaj.org/article/4a911b1129d149468316660d33d6e2e4 kostenfrei https://doi.org/10.1186/s13073-021-00938-3 kostenfrei https://doaj.org/toc/1756-994X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 13 2021 1 21
allfieldsGer	10.1186/s13073-021-00938-3 doi (DE-627)DOAJ055476376 (DE-599)DOAJ4a911b1129d149468316660d33d6e2e4 DE-627 ger DE-627 rakwb eng QH426-470 Jennifer Derrien verfasserin aut The DNA methylation landscape of multiple myeloma shows extensive inter- and intrapatient heterogeneity that fuels transcriptomic variability 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Background Cancer evolution depends on epigenetic and genetic diversity. Historically, in multiple myeloma (MM), subclonal diversity and tumor evolution have been investigated mostly from a genetic perspective. Methods Here, we performed an analysis of 42 MM samples from 21 patients by using enhanced reduced representation bisulfite sequencing (eRRBS). We combined several metrics of epigenetic heterogeneity to analyze DNA methylation heterogeneity in MM patients. Results We show that MM is characterized by the continuous accumulation of stochastic methylation at the promoters of development-related genes. High combinatorial entropy change is associated with poor outcomes in our pilot study and depends predominantly on partially methylated domains (PMDs). These PMDs, which represent the major source of inter- and intrapatient DNA methylation heterogeneity in MM, are linked to other key epigenetic aberrations, such as CpG island (CGI)/transcription start site (TSS) hypermethylation and H3K27me3 redistribution as well as 3D organization alterations. In addition, transcriptome analysis revealed that intratumor methylation heterogeneity was associated with low-level expression and high variability. Conclusions We propose that disrupted DNA methylation in MM is responsible for high epigenetic and transcriptomic instability allowing tumor cells to adapt to environmental changes by tapping into a pool of evolutionary trajectories. Multiple myeloma Disordered DNA methylation Epipolymorphism Epiallele switching Inter- and intrapatient heterogeneity Transcriptomic variability Medicine R Genetics Catherine Guérin-Charbonnel verfasserin aut Victor Gaborit verfasserin aut Loïc Campion verfasserin aut Magali Devic verfasserin aut Elise Douillard verfasserin aut Nathalie Roi verfasserin aut Hervé Avet-Loiseau verfasserin aut Olivier Decaux verfasserin aut Thierry Facon verfasserin aut Jan-Philipp Mallm verfasserin aut Roland Eils verfasserin aut Nikhil C. Munshi verfasserin aut Philippe Moreau verfasserin aut Carl Herrmann verfasserin aut Florence Magrangeas verfasserin aut Stéphane Minvielle verfasserin aut In Genome Medicine BMC, 2016 13(2021), 1, Seite 21 (DE-627)594424275 (DE-600)2484394-5 1756994X nnns volume:13 year:2021 number:1 pages:21 https://doi.org/10.1186/s13073-021-00938-3 kostenfrei https://doaj.org/article/4a911b1129d149468316660d33d6e2e4 kostenfrei https://doi.org/10.1186/s13073-021-00938-3 kostenfrei https://doaj.org/toc/1756-994X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 13 2021 1 21
allfieldsSound	10.1186/s13073-021-00938-3 doi (DE-627)DOAJ055476376 (DE-599)DOAJ4a911b1129d149468316660d33d6e2e4 DE-627 ger DE-627 rakwb eng QH426-470 Jennifer Derrien verfasserin aut The DNA methylation landscape of multiple myeloma shows extensive inter- and intrapatient heterogeneity that fuels transcriptomic variability 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Background Cancer evolution depends on epigenetic and genetic diversity. Historically, in multiple myeloma (MM), subclonal diversity and tumor evolution have been investigated mostly from a genetic perspective. Methods Here, we performed an analysis of 42 MM samples from 21 patients by using enhanced reduced representation bisulfite sequencing (eRRBS). We combined several metrics of epigenetic heterogeneity to analyze DNA methylation heterogeneity in MM patients. Results We show that MM is characterized by the continuous accumulation of stochastic methylation at the promoters of development-related genes. High combinatorial entropy change is associated with poor outcomes in our pilot study and depends predominantly on partially methylated domains (PMDs). These PMDs, which represent the major source of inter- and intrapatient DNA methylation heterogeneity in MM, are linked to other key epigenetic aberrations, such as CpG island (CGI)/transcription start site (TSS) hypermethylation and H3K27me3 redistribution as well as 3D organization alterations. In addition, transcriptome analysis revealed that intratumor methylation heterogeneity was associated with low-level expression and high variability. Conclusions We propose that disrupted DNA methylation in MM is responsible for high epigenetic and transcriptomic instability allowing tumor cells to adapt to environmental changes by tapping into a pool of evolutionary trajectories. Multiple myeloma Disordered DNA methylation Epipolymorphism Epiallele switching Inter- and intrapatient heterogeneity Transcriptomic variability Medicine R Genetics Catherine Guérin-Charbonnel verfasserin aut Victor Gaborit verfasserin aut Loïc Campion verfasserin aut Magali Devic verfasserin aut Elise Douillard verfasserin aut Nathalie Roi verfasserin aut Hervé Avet-Loiseau verfasserin aut Olivier Decaux verfasserin aut Thierry Facon verfasserin aut Jan-Philipp Mallm verfasserin aut Roland Eils verfasserin aut Nikhil C. Munshi verfasserin aut Philippe Moreau verfasserin aut Carl Herrmann verfasserin aut Florence Magrangeas verfasserin aut Stéphane Minvielle verfasserin aut In Genome Medicine BMC, 2016 13(2021), 1, Seite 21 (DE-627)594424275 (DE-600)2484394-5 1756994X nnns volume:13 year:2021 number:1 pages:21 https://doi.org/10.1186/s13073-021-00938-3 kostenfrei https://doaj.org/article/4a911b1129d149468316660d33d6e2e4 kostenfrei https://doi.org/10.1186/s13073-021-00938-3 kostenfrei https://doaj.org/toc/1756-994X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 13 2021 1 21
language	English
source	In Genome Medicine 13(2021), 1, Seite 21 volume:13 year:2021 number:1 pages:21
sourceStr	In Genome Medicine 13(2021), 1, Seite 21 volume:13 year:2021 number:1 pages:21
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Multiple myeloma Disordered DNA methylation Epipolymorphism Epiallele switching Inter- and intrapatient heterogeneity Transcriptomic variability Medicine R Genetics
isfreeaccess_bool	true
container_title	Genome Medicine
authorswithroles_txt_mv	Jennifer Derrien @@aut@@ Catherine Guérin-Charbonnel @@aut@@ Victor Gaborit @@aut@@ Loïc Campion @@aut@@ Magali Devic @@aut@@ Elise Douillard @@aut@@ Nathalie Roi @@aut@@ Hervé Avet-Loiseau @@aut@@ Olivier Decaux @@aut@@ Thierry Facon @@aut@@ Jan-Philipp Mallm @@aut@@ Roland Eils @@aut@@ Nikhil C. Munshi @@aut@@ Philippe Moreau @@aut@@ Carl Herrmann @@aut@@ Florence Magrangeas @@aut@@ Stéphane Minvielle @@aut@@
publishDateDaySort_date	2021-01-01T00:00:00Z
hierarchy_top_id	594424275
id	DOAJ055476376
language_de	englisch
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callnumber-first	Q - Science
author	Jennifer Derrien
spellingShingle	Jennifer Derrien misc QH426-470 misc Multiple myeloma misc Disordered DNA methylation misc Epipolymorphism misc Epiallele switching misc Inter- and intrapatient heterogeneity misc Transcriptomic variability misc Medicine misc R misc Genetics The DNA methylation landscape of multiple myeloma shows extensive inter- and intrapatient heterogeneity that fuels transcriptomic variability
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topic_title	QH426-470 The DNA methylation landscape of multiple myeloma shows extensive inter- and intrapatient heterogeneity that fuels transcriptomic variability Multiple myeloma Disordered DNA methylation Epipolymorphism Epiallele switching Inter- and intrapatient heterogeneity Transcriptomic variability
topic	misc QH426-470 misc Multiple myeloma misc Disordered DNA methylation misc Epipolymorphism misc Epiallele switching misc Inter- and intrapatient heterogeneity misc Transcriptomic variability misc Medicine misc R misc Genetics
topic_unstemmed	misc QH426-470 misc Multiple myeloma misc Disordered DNA methylation misc Epipolymorphism misc Epiallele switching misc Inter- and intrapatient heterogeneity misc Transcriptomic variability misc Medicine misc R misc Genetics
topic_browse	misc QH426-470 misc Multiple myeloma misc Disordered DNA methylation misc Epipolymorphism misc Epiallele switching misc Inter- and intrapatient heterogeneity misc Transcriptomic variability misc Medicine misc R misc Genetics
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title	The DNA methylation landscape of multiple myeloma shows extensive inter- and intrapatient heterogeneity that fuels transcriptomic variability
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title_full	The DNA methylation landscape of multiple myeloma shows extensive inter- and intrapatient heterogeneity that fuels transcriptomic variability
author_sort	Jennifer Derrien
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author_browse	Jennifer Derrien Catherine Guérin-Charbonnel Victor Gaborit Loïc Campion Magali Devic Elise Douillard Nathalie Roi Hervé Avet-Loiseau Olivier Decaux Thierry Facon Jan-Philipp Mallm Roland Eils Nikhil C. Munshi Philippe Moreau Carl Herrmann Florence Magrangeas Stéphane Minvielle
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title_sort	dna methylation landscape of multiple myeloma shows extensive inter- and intrapatient heterogeneity that fuels transcriptomic variability
callnumber	QH426-470
title_auth	The DNA methylation landscape of multiple myeloma shows extensive inter- and intrapatient heterogeneity that fuels transcriptomic variability
abstract	Abstract Background Cancer evolution depends on epigenetic and genetic diversity. Historically, in multiple myeloma (MM), subclonal diversity and tumor evolution have been investigated mostly from a genetic perspective. Methods Here, we performed an analysis of 42 MM samples from 21 patients by using enhanced reduced representation bisulfite sequencing (eRRBS). We combined several metrics of epigenetic heterogeneity to analyze DNA methylation heterogeneity in MM patients. Results We show that MM is characterized by the continuous accumulation of stochastic methylation at the promoters of development-related genes. High combinatorial entropy change is associated with poor outcomes in our pilot study and depends predominantly on partially methylated domains (PMDs). These PMDs, which represent the major source of inter- and intrapatient DNA methylation heterogeneity in MM, are linked to other key epigenetic aberrations, such as CpG island (CGI)/transcription start site (TSS) hypermethylation and H3K27me3 redistribution as well as 3D organization alterations. In addition, transcriptome analysis revealed that intratumor methylation heterogeneity was associated with low-level expression and high variability. Conclusions We propose that disrupted DNA methylation in MM is responsible for high epigenetic and transcriptomic instability allowing tumor cells to adapt to environmental changes by tapping into a pool of evolutionary trajectories.
abstractGer	Abstract Background Cancer evolution depends on epigenetic and genetic diversity. Historically, in multiple myeloma (MM), subclonal diversity and tumor evolution have been investigated mostly from a genetic perspective. Methods Here, we performed an analysis of 42 MM samples from 21 patients by using enhanced reduced representation bisulfite sequencing (eRRBS). We combined several metrics of epigenetic heterogeneity to analyze DNA methylation heterogeneity in MM patients. Results We show that MM is characterized by the continuous accumulation of stochastic methylation at the promoters of development-related genes. High combinatorial entropy change is associated with poor outcomes in our pilot study and depends predominantly on partially methylated domains (PMDs). These PMDs, which represent the major source of inter- and intrapatient DNA methylation heterogeneity in MM, are linked to other key epigenetic aberrations, such as CpG island (CGI)/transcription start site (TSS) hypermethylation and H3K27me3 redistribution as well as 3D organization alterations. In addition, transcriptome analysis revealed that intratumor methylation heterogeneity was associated with low-level expression and high variability. Conclusions We propose that disrupted DNA methylation in MM is responsible for high epigenetic and transcriptomic instability allowing tumor cells to adapt to environmental changes by tapping into a pool of evolutionary trajectories.
abstract_unstemmed	Abstract Background Cancer evolution depends on epigenetic and genetic diversity. Historically, in multiple myeloma (MM), subclonal diversity and tumor evolution have been investigated mostly from a genetic perspective. Methods Here, we performed an analysis of 42 MM samples from 21 patients by using enhanced reduced representation bisulfite sequencing (eRRBS). We combined several metrics of epigenetic heterogeneity to analyze DNA methylation heterogeneity in MM patients. Results We show that MM is characterized by the continuous accumulation of stochastic methylation at the promoters of development-related genes. High combinatorial entropy change is associated with poor outcomes in our pilot study and depends predominantly on partially methylated domains (PMDs). These PMDs, which represent the major source of inter- and intrapatient DNA methylation heterogeneity in MM, are linked to other key epigenetic aberrations, such as CpG island (CGI)/transcription start site (TSS) hypermethylation and H3K27me3 redistribution as well as 3D organization alterations. In addition, transcriptome analysis revealed that intratumor methylation heterogeneity was associated with low-level expression and high variability. Conclusions We propose that disrupted DNA methylation in MM is responsible for high epigenetic and transcriptomic instability allowing tumor cells to adapt to environmental changes by tapping into a pool of evolutionary trajectories.
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title_short	The DNA methylation landscape of multiple myeloma shows extensive inter- and intrapatient heterogeneity that fuels transcriptomic variability
url	https://doi.org/10.1186/s13073-021-00938-3 https://doaj.org/article/4a911b1129d149468316660d33d6e2e4 https://doaj.org/toc/1756-994X
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author2	Catherine Guérin-Charbonnel Victor Gaborit Loïc Campion Magali Devic Elise Douillard Nathalie Roi Hervé Avet-Loiseau Olivier Decaux Thierry Facon Jan-Philipp Mallm Roland Eils Nikhil C. Munshi Philippe Moreau Carl Herrmann Florence Magrangeas Stéphane Minvielle
author2Str	Catherine Guérin-Charbonnel Victor Gaborit Loïc Campion Magali Devic Elise Douillard Nathalie Roi Hervé Avet-Loiseau Olivier Decaux Thierry Facon Jan-Philipp Mallm Roland Eils Nikhil C. Munshi Philippe Moreau Carl Herrmann Florence Magrangeas Stéphane Minvielle
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The DNA methylation landscape of multiple myeloma shows extensive inter- and intrapatient heterogeneity that fuels transcriptomic variability

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