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Integrative epigenomic analysis of differential DNA methylation in urothelial carcinoma.

Aine M, Sjödahl G, Eriksson P, Veerla S, Lindgren D, Ringnér M, Höglund M - Genome Med (2015)

Bottom Line: We identify 5,453 between-tumor DMRs and derive four DNA methylation subgroups of UC with distinct associations to clinicopathological features and gene expression subtypes.Genome-wide DMR methylation patterns are reflected in the gene expression subtypes of UC.UC DMRs display three distinct methylation patterns, each associated with intrinsic features of the genome and differential regulatory factor binding preferences.

View Article: PubMed Central - PubMed

Affiliation: Division of Oncology and Pathology, Department of Clinical Sciences Lund, Lund University, Lund, Sweden.

ABSTRACT

Background: Urothelial carcinoma of the bladder (UC) is a common malignancy. Although extensive transcriptome analysis has provided insights into the gene expression patterns of this tumor type, the mechanistic underpinnings of differential methylation remain poorly understood. Multi-level genomic data may be used to profile the regulatory potential and landscape of differential methylation in cancer and gain understanding of the processes underlying epigenetic and phenotypic characteristics of tumors.

Methods: We perform genome-wide DNA methylation profiling of 98 gene-expression subtyped tumors to identify between-tumor differentially methylated regions (DMRs). We integrate multi-level publically available genomic data generated by the ENCODE consortium to characterize the regulatory potential of UC DMRs.

Results: We identify 5,453 between-tumor DMRs and derive four DNA methylation subgroups of UC with distinct associations to clinicopathological features and gene expression subtypes. We characterize three distinct patterns of differential methylation and use ENCODE data to show that tumor subgroup-defining DMRs display differential chromatin state, and regulatory factor binding preferences. Finally, we characterize an epigenetic switch involving the HOXA-genes with associations to tumor differentiation states and patient prognosis.

Conclusions: Genome-wide DMR methylation patterns are reflected in the gene expression subtypes of UC. UC DMRs display three distinct methylation patterns, each associated with intrinsic features of the genome and differential regulatory factor binding preferences. Epigenetic inactivation of HOX-genes correlates with tumor differentiation states and may present an actionable epigenetic alteration in UC.

No MeSH data available.


Related in: MedlinePlus

Chromatin state characterization of UC DMRs. (A) Frequency of H1ESC chromatin states for all UC DMRs (N = 5,453) calculated per base across 4 kb windows centered on each DMR midpoint. (B) Frequency of H1ESC chromatin states for all human RefSeq promoters calculated per base across 4 kb windows centered on each RefSeq TSS (N = 27,397). The corresponding frequency of UC DMR overlaps is also shown (solid black line). (C) Frequency of H1ESC chromatin states from RefSeqs having a UC DMR in the 4 kb window centered on its TSS (N = 5,290). (D) Chromatin states for H1ESC and eight additional cell lines (listed in panel E; Ernst et al. [17]). For UC DMRs in a H1ESC chromatin state, the frequencies of the typical chromatin state in the eight other cell types are shown. (E) For UC DMRs in the ‘Inactive/poised promoter’ state in H1ESC, the frequencies of other chromatin states are shown for the eight additional cell types. The 15 Chromatin states are color coded as in Figure 1 (chromatin states 13 to 15 are represented by a dashed line in panels A to C).
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Fig3: Chromatin state characterization of UC DMRs. (A) Frequency of H1ESC chromatin states for all UC DMRs (N = 5,453) calculated per base across 4 kb windows centered on each DMR midpoint. (B) Frequency of H1ESC chromatin states for all human RefSeq promoters calculated per base across 4 kb windows centered on each RefSeq TSS (N = 27,397). The corresponding frequency of UC DMR overlaps is also shown (solid black line). (C) Frequency of H1ESC chromatin states from RefSeqs having a UC DMR in the 4 kb window centered on its TSS (N = 5,290). (D) Chromatin states for H1ESC and eight additional cell lines (listed in panel E; Ernst et al. [17]). For UC DMRs in a H1ESC chromatin state, the frequencies of the typical chromatin state in the eight other cell types are shown. (E) For UC DMRs in the ‘Inactive/poised promoter’ state in H1ESC, the frequencies of other chromatin states are shown for the eight additional cell types. The 15 Chromatin states are color coded as in Figure 1 (chromatin states 13 to 15 are represented by a dashed line in panels A to C).

Mentions: To further characterize the regulatory potential associated with UC DMRs, we mapped the overlaps of H1ESC chromatin states UC DMRs. The distribution of chromatin states at UC DMRs exhibited a clear pattern of decreasing ‘Heterochromatin/low signal’ marks and a corresponding increase in states associated with promoter and gene regulatory regions towards DMR midpoints (Figure 3A). The ‘Inactive/poised promoter’ as well as ‘Weak promoter’ and ‘Weak enhancer’ states showed increased frequencies towards the midpoint of DMRs while the ‘Weak transcription’, ‘Polycomb repressed’, and ‘Active promoter’ state overlaps exhibited decreases.Figure 3


Integrative epigenomic analysis of differential DNA methylation in urothelial carcinoma.

Aine M, Sjödahl G, Eriksson P, Veerla S, Lindgren D, Ringnér M, Höglund M - Genome Med (2015)

Chromatin state characterization of UC DMRs. (A) Frequency of H1ESC chromatin states for all UC DMRs (N = 5,453) calculated per base across 4 kb windows centered on each DMR midpoint. (B) Frequency of H1ESC chromatin states for all human RefSeq promoters calculated per base across 4 kb windows centered on each RefSeq TSS (N = 27,397). The corresponding frequency of UC DMR overlaps is also shown (solid black line). (C) Frequency of H1ESC chromatin states from RefSeqs having a UC DMR in the 4 kb window centered on its TSS (N = 5,290). (D) Chromatin states for H1ESC and eight additional cell lines (listed in panel E; Ernst et al. [17]). For UC DMRs in a H1ESC chromatin state, the frequencies of the typical chromatin state in the eight other cell types are shown. (E) For UC DMRs in the ‘Inactive/poised promoter’ state in H1ESC, the frequencies of other chromatin states are shown for the eight additional cell types. The 15 Chromatin states are color coded as in Figure 1 (chromatin states 13 to 15 are represented by a dashed line in panels A to C).
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4373102&req=5

Fig3: Chromatin state characterization of UC DMRs. (A) Frequency of H1ESC chromatin states for all UC DMRs (N = 5,453) calculated per base across 4 kb windows centered on each DMR midpoint. (B) Frequency of H1ESC chromatin states for all human RefSeq promoters calculated per base across 4 kb windows centered on each RefSeq TSS (N = 27,397). The corresponding frequency of UC DMR overlaps is also shown (solid black line). (C) Frequency of H1ESC chromatin states from RefSeqs having a UC DMR in the 4 kb window centered on its TSS (N = 5,290). (D) Chromatin states for H1ESC and eight additional cell lines (listed in panel E; Ernst et al. [17]). For UC DMRs in a H1ESC chromatin state, the frequencies of the typical chromatin state in the eight other cell types are shown. (E) For UC DMRs in the ‘Inactive/poised promoter’ state in H1ESC, the frequencies of other chromatin states are shown for the eight additional cell types. The 15 Chromatin states are color coded as in Figure 1 (chromatin states 13 to 15 are represented by a dashed line in panels A to C).
Mentions: To further characterize the regulatory potential associated with UC DMRs, we mapped the overlaps of H1ESC chromatin states UC DMRs. The distribution of chromatin states at UC DMRs exhibited a clear pattern of decreasing ‘Heterochromatin/low signal’ marks and a corresponding increase in states associated with promoter and gene regulatory regions towards DMR midpoints (Figure 3A). The ‘Inactive/poised promoter’ as well as ‘Weak promoter’ and ‘Weak enhancer’ states showed increased frequencies towards the midpoint of DMRs while the ‘Weak transcription’, ‘Polycomb repressed’, and ‘Active promoter’ state overlaps exhibited decreases.Figure 3

Bottom Line: We identify 5,453 between-tumor DMRs and derive four DNA methylation subgroups of UC with distinct associations to clinicopathological features and gene expression subtypes.Genome-wide DMR methylation patterns are reflected in the gene expression subtypes of UC.UC DMRs display three distinct methylation patterns, each associated with intrinsic features of the genome and differential regulatory factor binding preferences.

View Article: PubMed Central - PubMed

Affiliation: Division of Oncology and Pathology, Department of Clinical Sciences Lund, Lund University, Lund, Sweden.

ABSTRACT

Background: Urothelial carcinoma of the bladder (UC) is a common malignancy. Although extensive transcriptome analysis has provided insights into the gene expression patterns of this tumor type, the mechanistic underpinnings of differential methylation remain poorly understood. Multi-level genomic data may be used to profile the regulatory potential and landscape of differential methylation in cancer and gain understanding of the processes underlying epigenetic and phenotypic characteristics of tumors.

Methods: We perform genome-wide DNA methylation profiling of 98 gene-expression subtyped tumors to identify between-tumor differentially methylated regions (DMRs). We integrate multi-level publically available genomic data generated by the ENCODE consortium to characterize the regulatory potential of UC DMRs.

Results: We identify 5,453 between-tumor DMRs and derive four DNA methylation subgroups of UC with distinct associations to clinicopathological features and gene expression subtypes. We characterize three distinct patterns of differential methylation and use ENCODE data to show that tumor subgroup-defining DMRs display differential chromatin state, and regulatory factor binding preferences. Finally, we characterize an epigenetic switch involving the HOXA-genes with associations to tumor differentiation states and patient prognosis.

Conclusions: Genome-wide DMR methylation patterns are reflected in the gene expression subtypes of UC. UC DMRs display three distinct methylation patterns, each associated with intrinsic features of the genome and differential regulatory factor binding preferences. Epigenetic inactivation of HOX-genes correlates with tumor differentiation states and may present an actionable epigenetic alteration in UC.

No MeSH data available.


Related in: MedlinePlus