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The Interactions of microRNA and Epigenetic Modifications in Prostate Cancer.

Singh PK, Campbell MJ - Cancers (Basel) (2013)

Bottom Line: Any imbalance in these processes may lead to abnormal transcriptional activity and thus result in disease state.Changes in DNA methylation, altered histone modifications and miRNA expression are functionally associated with CaP initiation and progression.Given the importance and prevalence of these epigenetic events in CaP biology it is timely to understand further how different epigenetic components interact and influence each other.

View Article: PubMed Central - PubMed

Affiliation: Department of Pharmacology & Therapeutics, Roswell Park Cancer Institute, Elm and Carlton Streets, Buffalo, NY 14263, USA. Prashant.singh@roswellpark.org.

ABSTRACT
Epigenetic modifiers play important roles in fine-tuning the cellular transcriptome. Any imbalance in these processes may lead to abnormal transcriptional activity and thus result in disease state. Distortions of the epigenome have been reported in cancer initiation and progression. DNA methylation and histone modifications are principle components of this epigenome, but more recently it has become clear that microRNAs (miRNAs) are another major component of the epigenome. Interactions of these components are apparent in prostate cancer (CaP), which is the most common non-cutaneous cancer and second leading cause of death from cancer in the USA. Changes in DNA methylation, altered histone modifications and miRNA expression are functionally associated with CaP initiation and progression. Various aspects of the epigenome have also been investigated as biomarkers for different stages of CaP detection, though with limited success. This review aims to summarize key aspects of these mechanistic interactions within the epigenome and to highlight their translational potential as functional biomarkers. To this end, exploration of TCGA prostate cancer data revealed that expression of key CaP miRNAs inversely associate with DNA methylation. Given the importance and prevalence of these epigenetic events in CaP biology it is timely to understand further how different epigenetic components interact and influence each other.

No MeSH data available.


Related in: MedlinePlus

Significant negative correlation between altered miRNA expression and DNA methylation pattern in primary prostate cancer tumors from the TCGA data-set. Circos plot showing miRNAs where there is a significant correlation with CpGs near miRNA gene locations. Outer ring represents all the chromosomes. MiRNA genes are represented by purple lines near their chromosomal locations. Green lines represent CpGs in the region. Lines connecting two dots represent the statistically significant correlation between two features selected, miRNA expression and CpG methylation in this case. (Figures generated from [125] using latest version of data release for Prostate cancer “PRAD-13-March-2013”).
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cancers-05-00998-f002: Significant negative correlation between altered miRNA expression and DNA methylation pattern in primary prostate cancer tumors from the TCGA data-set. Circos plot showing miRNAs where there is a significant correlation with CpGs near miRNA gene locations. Outer ring represents all the chromosomes. MiRNA genes are represented by purple lines near their chromosomal locations. Green lines represent CpGs in the region. Lines connecting two dots represent the statistically significant correlation between two features selected, miRNA expression and CpG methylation in this case. (Figures generated from [125] using latest version of data release for Prostate cancer “PRAD-13-March-2013”).

Mentions: We explored TCGA data for associations between DNA methylation and miRNA expression in CaP tumors. An integrated tool of all the data types generated by TCGA have been developed to understand the systems level interaction between different data features. Statistically significant association can be identified and visualized using Regulome Explorer [125]. Regulome Explorer has been used for integrated analysis in colon, rectal and breast cancers [126,127]. We used Regulome Explorer to identify statistically significant correlations between miRNA expression (RNA-seq) and status of DNA methylation (Illumina 450k methylation arrays). We specifically searched for CpG sites showing negative correlation with miRNA expression on the same chromosome (using “cis” setting in distance filter and p-value cutoff of −log10(p) ≥ 6). This analysis identified a total of 27 CpGs negatively correlated with expression of 17 miRNAs from 5 different chromosomes (Figure 2). Notably corroborating the discussion above, all five miRNAs of miR-200 family (miR-200a/b/429, miR-200c/141) and miR-205 showed strong negative correlation between miRNA expression and CpG methylation [89,90]. Many of miRNAs with important function in CaP did not show significant correlation in this analysis which can be partially because of the allocation of CpGs to miRNAs in Illumina 450K array annotation. This preliminary exploration of TCGA data strengthens the observation that miRNAs are epigenetically silenced in CaP. It will be interesting to interrogate this resource in further detail to identify how other genomic data from TCGA correlates with miRNA expression and DNA methylation.


The Interactions of microRNA and Epigenetic Modifications in Prostate Cancer.

Singh PK, Campbell MJ - Cancers (Basel) (2013)

Significant negative correlation between altered miRNA expression and DNA methylation pattern in primary prostate cancer tumors from the TCGA data-set. Circos plot showing miRNAs where there is a significant correlation with CpGs near miRNA gene locations. Outer ring represents all the chromosomes. MiRNA genes are represented by purple lines near their chromosomal locations. Green lines represent CpGs in the region. Lines connecting two dots represent the statistically significant correlation between two features selected, miRNA expression and CpG methylation in this case. (Figures generated from [125] using latest version of data release for Prostate cancer “PRAD-13-March-2013”).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3795376&req=5

cancers-05-00998-f002: Significant negative correlation between altered miRNA expression and DNA methylation pattern in primary prostate cancer tumors from the TCGA data-set. Circos plot showing miRNAs where there is a significant correlation with CpGs near miRNA gene locations. Outer ring represents all the chromosomes. MiRNA genes are represented by purple lines near their chromosomal locations. Green lines represent CpGs in the region. Lines connecting two dots represent the statistically significant correlation between two features selected, miRNA expression and CpG methylation in this case. (Figures generated from [125] using latest version of data release for Prostate cancer “PRAD-13-March-2013”).
Mentions: We explored TCGA data for associations between DNA methylation and miRNA expression in CaP tumors. An integrated tool of all the data types generated by TCGA have been developed to understand the systems level interaction between different data features. Statistically significant association can be identified and visualized using Regulome Explorer [125]. Regulome Explorer has been used for integrated analysis in colon, rectal and breast cancers [126,127]. We used Regulome Explorer to identify statistically significant correlations between miRNA expression (RNA-seq) and status of DNA methylation (Illumina 450k methylation arrays). We specifically searched for CpG sites showing negative correlation with miRNA expression on the same chromosome (using “cis” setting in distance filter and p-value cutoff of −log10(p) ≥ 6). This analysis identified a total of 27 CpGs negatively correlated with expression of 17 miRNAs from 5 different chromosomes (Figure 2). Notably corroborating the discussion above, all five miRNAs of miR-200 family (miR-200a/b/429, miR-200c/141) and miR-205 showed strong negative correlation between miRNA expression and CpG methylation [89,90]. Many of miRNAs with important function in CaP did not show significant correlation in this analysis which can be partially because of the allocation of CpGs to miRNAs in Illumina 450K array annotation. This preliminary exploration of TCGA data strengthens the observation that miRNAs are epigenetically silenced in CaP. It will be interesting to interrogate this resource in further detail to identify how other genomic data from TCGA correlates with miRNA expression and DNA methylation.

Bottom Line: Any imbalance in these processes may lead to abnormal transcriptional activity and thus result in disease state.Changes in DNA methylation, altered histone modifications and miRNA expression are functionally associated with CaP initiation and progression.Given the importance and prevalence of these epigenetic events in CaP biology it is timely to understand further how different epigenetic components interact and influence each other.

View Article: PubMed Central - PubMed

Affiliation: Department of Pharmacology & Therapeutics, Roswell Park Cancer Institute, Elm and Carlton Streets, Buffalo, NY 14263, USA. Prashant.singh@roswellpark.org.

ABSTRACT
Epigenetic modifiers play important roles in fine-tuning the cellular transcriptome. Any imbalance in these processes may lead to abnormal transcriptional activity and thus result in disease state. Distortions of the epigenome have been reported in cancer initiation and progression. DNA methylation and histone modifications are principle components of this epigenome, but more recently it has become clear that microRNAs (miRNAs) are another major component of the epigenome. Interactions of these components are apparent in prostate cancer (CaP), which is the most common non-cutaneous cancer and second leading cause of death from cancer in the USA. Changes in DNA methylation, altered histone modifications and miRNA expression are functionally associated with CaP initiation and progression. Various aspects of the epigenome have also been investigated as biomarkers for different stages of CaP detection, though with limited success. This review aims to summarize key aspects of these mechanistic interactions within the epigenome and to highlight their translational potential as functional biomarkers. To this end, exploration of TCGA prostate cancer data revealed that expression of key CaP miRNAs inversely associate with DNA methylation. Given the importance and prevalence of these epigenetic events in CaP biology it is timely to understand further how different epigenetic components interact and influence each other.

No MeSH data available.


Related in: MedlinePlus