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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

DHS and RF occupancy at UC DMRs. Aggregation plots of DHS and RF occupancy are shown for five ENCODE cell types across UC subgroup-specific DMRs stratified into patterns 1 to 3 (left to right for each DHS/RF and cell type combination). Plots are based on 10 kb for each DMR centered on the DMR midpoint. DHS/occupancy across each DMR (rows) is pseudo-colored (red) and DMRs are sorted (vertically, for each DMR pattern separately) according to the number of DHS bases within the 10 kb region. Patterns of DNaseI hypersensitive sites (A), EZH2 (B), POLR2A (C), as well as binding patterns of selected RFs (D) pseudo-colored (red) with aggregation plots on top across the different cell lines are shown across the three UC DMR methylation patterns (1 to 3). (E, F) Aggregation plots of CGI positions (E) and CGI-shore positions (F) in UC DMRs stratified into patterns 1 to 3. For aggregation plots, tic marks indicate 5%, 10%, 20%, 40%, and 60% basewise occupancy, respectively.
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Fig5: DHS and RF occupancy at UC DMRs. Aggregation plots of DHS and RF occupancy are shown for five ENCODE cell types across UC subgroup-specific DMRs stratified into patterns 1 to 3 (left to right for each DHS/RF and cell type combination). Plots are based on 10 kb for each DMR centered on the DMR midpoint. DHS/occupancy across each DMR (rows) is pseudo-colored (red) and DMRs are sorted (vertically, for each DMR pattern separately) according to the number of DHS bases within the 10 kb region. Patterns of DNaseI hypersensitive sites (A), EZH2 (B), POLR2A (C), as well as binding patterns of selected RFs (D) pseudo-colored (red) with aggregation plots on top across the different cell lines are shown across the three UC DMR methylation patterns (1 to 3). (E, F) Aggregation plots of CGI positions (E) and CGI-shore positions (F) in UC DMRs stratified into patterns 1 to 3. For aggregation plots, tic marks indicate 5%, 10%, 20%, 40%, and 60% basewise occupancy, respectively.

Mentions: DNaseI hypersensitive sites (DHSs) define regions of open chromatin and are frequently associated with regulatory factor binding. We mapped DHS-peak bases locally in a 10 kb window centered on UC DMRs and explored the spatial patterns of ENCODE ChIP-seq RF binding in relation to DMR positioning. Chromatin accessibility, as measured by DHS, increased towards DMR midpoints and the most frequent UC DMR-DHS overlaps were observed in the H1ESC cell line (Figure 5A). A general trend of decreasing DHS levels across all UC DMR patterns was observed in the more differentiated and cancer-derived-cell lines compared to H1ESC, however this was most accentuated among pattern 2 DMRs (Figure 5A). While pattern 1 DMRs did not exhibit specificity in DHS peak distributions when assessed by aggregation plots (APs), pattern 2 DMRs were centered on DHS sites, and pattern 3 DMRs showed a consistent tendency towards a local depletion of DHSs towards the DMR midpoints. EZH2 binding was strongly associated with DHSs in H1ESC and exhibited a sharp peak centered on pattern 2 DMR midpoints, a feature seen to a lesser extent in GM12878 and HepG2 but lacking entirely in K562 and HeLa-S3 cells (Figure 5B). The observed patterns are consistent with H3K27-trimethylation-mediated repressive/poised state as ‘default’ for pattern 2 DMRs in ESC with a successive transition to stable modes of repression in response to differentiation cues or immortality (Figure 4A). POLR2A binding across pattern 2 DMRs was associated with local DHS density in all cell lines except H1ESC, indicating a decoupling of open chromatin status and gene transcription in ESCs (Figure 5C).Figure 5


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)

DHS and RF occupancy at UC DMRs. Aggregation plots of DHS and RF occupancy are shown for five ENCODE cell types across UC subgroup-specific DMRs stratified into patterns 1 to 3 (left to right for each DHS/RF and cell type combination). Plots are based on 10 kb for each DMR centered on the DMR midpoint. DHS/occupancy across each DMR (rows) is pseudo-colored (red) and DMRs are sorted (vertically, for each DMR pattern separately) according to the number of DHS bases within the 10 kb region. Patterns of DNaseI hypersensitive sites (A), EZH2 (B), POLR2A (C), as well as binding patterns of selected RFs (D) pseudo-colored (red) with aggregation plots on top across the different cell lines are shown across the three UC DMR methylation patterns (1 to 3). (E, F) Aggregation plots of CGI positions (E) and CGI-shore positions (F) in UC DMRs stratified into patterns 1 to 3. For aggregation plots, tic marks indicate 5%, 10%, 20%, 40%, and 60% basewise occupancy, respectively.
© Copyright Policy - open-access
Related In: Results  -  Collection

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getmorefigures.php?uid=PMC4373102&req=5

Fig5: DHS and RF occupancy at UC DMRs. Aggregation plots of DHS and RF occupancy are shown for five ENCODE cell types across UC subgroup-specific DMRs stratified into patterns 1 to 3 (left to right for each DHS/RF and cell type combination). Plots are based on 10 kb for each DMR centered on the DMR midpoint. DHS/occupancy across each DMR (rows) is pseudo-colored (red) and DMRs are sorted (vertically, for each DMR pattern separately) according to the number of DHS bases within the 10 kb region. Patterns of DNaseI hypersensitive sites (A), EZH2 (B), POLR2A (C), as well as binding patterns of selected RFs (D) pseudo-colored (red) with aggregation plots on top across the different cell lines are shown across the three UC DMR methylation patterns (1 to 3). (E, F) Aggregation plots of CGI positions (E) and CGI-shore positions (F) in UC DMRs stratified into patterns 1 to 3. For aggregation plots, tic marks indicate 5%, 10%, 20%, 40%, and 60% basewise occupancy, respectively.
Mentions: DNaseI hypersensitive sites (DHSs) define regions of open chromatin and are frequently associated with regulatory factor binding. We mapped DHS-peak bases locally in a 10 kb window centered on UC DMRs and explored the spatial patterns of ENCODE ChIP-seq RF binding in relation to DMR positioning. Chromatin accessibility, as measured by DHS, increased towards DMR midpoints and the most frequent UC DMR-DHS overlaps were observed in the H1ESC cell line (Figure 5A). A general trend of decreasing DHS levels across all UC DMR patterns was observed in the more differentiated and cancer-derived-cell lines compared to H1ESC, however this was most accentuated among pattern 2 DMRs (Figure 5A). While pattern 1 DMRs did not exhibit specificity in DHS peak distributions when assessed by aggregation plots (APs), pattern 2 DMRs were centered on DHS sites, and pattern 3 DMRs showed a consistent tendency towards a local depletion of DHSs towards the DMR midpoints. EZH2 binding was strongly associated with DHSs in H1ESC and exhibited a sharp peak centered on pattern 2 DMR midpoints, a feature seen to a lesser extent in GM12878 and HepG2 but lacking entirely in K562 and HeLa-S3 cells (Figure 5B). The observed patterns are consistent with H3K27-trimethylation-mediated repressive/poised state as ‘default’ for pattern 2 DMRs in ESC with a successive transition to stable modes of repression in response to differentiation cues or immortality (Figure 4A). POLR2A binding across pattern 2 DMRs was associated with local DHS density in all cell lines except H1ESC, indicating a decoupling of open chromatin status and gene transcription in ESCs (Figure 5C).Figure 5

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