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eFORGE: A Tool for Identifying Cell Type-Specific Signal in Epigenomic Data

View Article: PubMed Central - PubMed

ABSTRACT

Epigenome-wide association studies (EWAS) provide an alternative approach for studying human disease through consideration of non-genetic variants such as altered DNA methylation. To advance the complex interpretation of EWAS, we developed eFORGE (http://eforge.cs.ucl.ac.uk/), a new standalone and web-based tool for the analysis and interpretation of EWAS data. eFORGE determines the cell type-specific regulatory component of a set of EWAS-identified differentially methylated positions. This is achieved by detecting enrichment of overlap with DNase I hypersensitive sites across 454 samples (tissues, primary cell types, and cell lines) from the ENCODE, Roadmap Epigenomics, and BLUEPRINT projects. Application of eFORGE to 20 publicly available EWAS datasets identified disease-relevant cell types for several common diseases, a stem cell-like signature in cancer, and demonstrated the ability to detect cell-composition effects for EWAS performed on heterogeneous tissues. Our approach bridges the gap between large-scale epigenomics data and EWAS-derived target selection to yield insight into disease etiology.

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Analysis of Cancer EWASThis heatmap shows a stem cell-like signature for regions from five cancer EWAS, through color-coded enrichment –log10(q value). The left column depicts results for 330 top probes from a breast cancer metastatic behavior EWAS (Fang et al., 2011), the second column from the left shows results for 450 probes from a colorectal carcinoma EWAS (Kibriya et al., 2011), and the central column shows results for 240 probes from a sporadic colorectal cancer EWAS (Laczmanska et al., 2013). The next column on the right shows results for 801 probes from an adrenocortical carcinoma EWAS (Barreau et al., 2013), and the last column on the right shows results for 362 probes from a clear cell renal cell carcinoma EWAS (Arai et al., 2012). All five studies showed intermediate enrichment (q value <0.05) of at least one eFORGE “ES cell” or “iPSC” category. Aside from this stem cell-like signature, no other shared tissue category is enriched across the five probe lists.
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fig7: Analysis of Cancer EWASThis heatmap shows a stem cell-like signature for regions from five cancer EWAS, through color-coded enrichment –log10(q value). The left column depicts results for 330 top probes from a breast cancer metastatic behavior EWAS (Fang et al., 2011), the second column from the left shows results for 450 probes from a colorectal carcinoma EWAS (Kibriya et al., 2011), and the central column shows results for 240 probes from a sporadic colorectal cancer EWAS (Laczmanska et al., 2013). The next column on the right shows results for 801 probes from an adrenocortical carcinoma EWAS (Barreau et al., 2013), and the last column on the right shows results for 362 probes from a clear cell renal cell carcinoma EWAS (Arai et al., 2012). All five studies showed intermediate enrichment (q value <0.05) of at least one eFORGE “ES cell” or “iPSC” category. Aside from this stem cell-like signature, no other shared tissue category is enriched across the five probe lists.

Mentions: Finally, we showed that eFORGE detects tissue-specific patterns in cancer EWAS data. We analyzed five cancer EWAS: breast cancer (Fang et al., 2011), colorectal cancer (Kibriya et al., 2011), sporadic colorectal cancer (Laczmanska et al., 2013), clear cell renal cell carcinoma (Arai et al., 2012), and adrenocortical carcinoma (Barreau et al., 2013). Using the top 330, 450, 240, 801, and 362 EWAS hits, respectively, we performed eFORGE analysis for each DMP set, and identified enrichment in stem cells but not in breast, intestine, or renal tissues across the five studies (Figure 7). This suggests that many regulatory elements affected by cancer epigenetic reprogramming may be stem cell like. This is consistent with previous findings that DNAm changes in cancer tissue aid the emergence of a possible stem cell phenotype (Widschwendter et al., 2007). In conclusion, application of eFORGE to cancer EWAS data provided evidence for a stem cell-like enrichment across all five studies, which warrants further investigation.


eFORGE: A Tool for Identifying Cell Type-Specific Signal in Epigenomic Data
Analysis of Cancer EWASThis heatmap shows a stem cell-like signature for regions from five cancer EWAS, through color-coded enrichment –log10(q value). The left column depicts results for 330 top probes from a breast cancer metastatic behavior EWAS (Fang et al., 2011), the second column from the left shows results for 450 probes from a colorectal carcinoma EWAS (Kibriya et al., 2011), and the central column shows results for 240 probes from a sporadic colorectal cancer EWAS (Laczmanska et al., 2013). The next column on the right shows results for 801 probes from an adrenocortical carcinoma EWAS (Barreau et al., 2013), and the last column on the right shows results for 362 probes from a clear cell renal cell carcinoma EWAS (Arai et al., 2012). All five studies showed intermediate enrichment (q value <0.05) of at least one eFORGE “ES cell” or “iPSC” category. Aside from this stem cell-like signature, no other shared tissue category is enriched across the five probe lists.
© Copyright Policy - CC BY
Related In: Results  -  Collection

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Show All Figures
getmorefigures.php?uid=PMC5120369&req=5

fig7: Analysis of Cancer EWASThis heatmap shows a stem cell-like signature for regions from five cancer EWAS, through color-coded enrichment –log10(q value). The left column depicts results for 330 top probes from a breast cancer metastatic behavior EWAS (Fang et al., 2011), the second column from the left shows results for 450 probes from a colorectal carcinoma EWAS (Kibriya et al., 2011), and the central column shows results for 240 probes from a sporadic colorectal cancer EWAS (Laczmanska et al., 2013). The next column on the right shows results for 801 probes from an adrenocortical carcinoma EWAS (Barreau et al., 2013), and the last column on the right shows results for 362 probes from a clear cell renal cell carcinoma EWAS (Arai et al., 2012). All five studies showed intermediate enrichment (q value <0.05) of at least one eFORGE “ES cell” or “iPSC” category. Aside from this stem cell-like signature, no other shared tissue category is enriched across the five probe lists.
Mentions: Finally, we showed that eFORGE detects tissue-specific patterns in cancer EWAS data. We analyzed five cancer EWAS: breast cancer (Fang et al., 2011), colorectal cancer (Kibriya et al., 2011), sporadic colorectal cancer (Laczmanska et al., 2013), clear cell renal cell carcinoma (Arai et al., 2012), and adrenocortical carcinoma (Barreau et al., 2013). Using the top 330, 450, 240, 801, and 362 EWAS hits, respectively, we performed eFORGE analysis for each DMP set, and identified enrichment in stem cells but not in breast, intestine, or renal tissues across the five studies (Figure 7). This suggests that many regulatory elements affected by cancer epigenetic reprogramming may be stem cell like. This is consistent with previous findings that DNAm changes in cancer tissue aid the emergence of a possible stem cell phenotype (Widschwendter et al., 2007). In conclusion, application of eFORGE to cancer EWAS data provided evidence for a stem cell-like enrichment across all five studies, which warrants further investigation.

View Article: PubMed Central - PubMed

ABSTRACT

Epigenome-wide association studies (EWAS) provide an alternative approach for studying human disease through consideration of non-genetic variants such as altered DNA methylation. To advance the complex interpretation of EWAS, we developed eFORGE (http://eforge.cs.ucl.ac.uk/), a new standalone and web-based tool for the analysis and interpretation of EWAS data. eFORGE determines the cell&nbsp;type-specific regulatory component of a set of&nbsp;EWAS-identified differentially methylated positions. This is achieved by detecting enrichment of overlap with DNase I hypersensitive sites across 454 samples (tissues, primary cell types, and cell lines) from&nbsp;the ENCODE, Roadmap Epigenomics, and BLUEPRINT projects. Application of eFORGE to&nbsp;20&nbsp;publicly available EWAS datasets identified disease-relevant cell types for several common diseases, a stem cell-like signature in cancer, and demonstrated the ability to detect cell-composition effects for EWAS performed on heterogeneous tissues. Our approach bridges the gap between large-scale epigenomics data and EWAS-derived target selection to yield insight into disease etiology.

No MeSH data available.


Related in: MedlinePlus