Functional Genome Analysis  (B070)
Deutsches Krebsforschungszentrum, Im Neuenheimer Feld 580
D-69120 Heidelberg, Germany.
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  Epigenetics
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DNA Methylation 
microRNA-Based Regulation
Archive
   - microRNA miR-192 promoter    - Correction of experimental bias




   - Common cancer biomarker GHSR





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DNA-methylation studies

Changes in genomic DNA methylation patterns are one of the earliest and most consistent features of tumourigenesis. It has been demonstrated that aberrant DNA methylation profiles can be used as a valuable markers for clinical tumour characterisation. Technically, we initially applied microarray technology toward a genome-wide and high-resolution analysis of DNA methylation patterns. Meanwhile, next-generation sequencing and other techniques have replaced the arrays entirely.
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The detection of methylation variations is mostly performed by using bisulfite treatment to uncover the methylation status. Sodium bisulfite induces methylation-dependent single-nucleotide polymorphisms by converting unmethylated cytosine to uracil and, upon PCR amplification, to thymine (see figure below). 5-Methylcytosine is not affected by sodium bisulfite treatment and thus amplified as cytosine. The conversion can be identified by any means of sequence analysis.

scheme of bisulfite treatment

The data are evaluated in combination with available clinical data and information from other analyses, such as transcript profiling. This could allow fundamental insights into the role of DNA methylation during tumourigenesis. We study in some detail the functional consequences of variations of particularly promoter methylation, with a focus on promoters of microRNA genes, and have been successful with uncovering relevant functional mechanisms in several cancer entities.



Methylation pattern at particular CpG dimers in the promoters of cancer-relevant genes. The type of pancreas tissue analysed is shown at the top; the degree of methylation is indicated by a colour-code as shown at the bottom, ranging from green (no methylation) to red (hypermethylation).










Dutruel et al. (2014) Oncogene 33, 3401. pdf icon
Moskalev et al. (2012) Genes Chrom. Cancer 51, 105. pdf icon



Botla et al. (2016) Cancer Res. 76, 4149.  pdf icon
Haas et al. (2013) EMBO Mol. Med. 5, 413. pdf icon
Moskalev et al. (2011) Nucleic Acids Res. 39, e77. pdf icon



Moskalev et al. (2015) Oncotarget 6, 4418.

Bubnov et al. (2012) Exp. Oncol. 34, 370. pdf icon
de Souza Rocha Simonini et al. (2010) Cancer Res. 70, 9175. pdf icon



Jandaghi et al. (2015) Cell Cycle 14, 689.

Botla et al. (2012) Breast Canc. Res. Treat. 135, 705. pdf icon
Böttcher et al. (2010) PloS ONE 5, e11002. pdf icon



Haller et al. (2014) Int. J. Cancer 136, 1013. pdf icon
Moskalev et al. (2012) BMC Cancer 12, 213. pdf icon
Riazalhosseini & Hoheisel (2008) Genome Biol. 9, 405. pdf icon





 







 

Early epigenetic down-regulation of microRNA-192 expression promotes pancreatic cancer progression logo NGFN

Pancreatic ductal adenocarcinoma (PDAC) is characterized by very early metastasis, suggesting the hypothesis that metastasis-associated changes may occur prior to actual tumor formation. We identified miR-192 as an epigenetically regulated suppressor gene with predictive value in this disease. miR-192 was downregulated by promoter methylation in both PDAC and chronic pancreatitis (CP), the latter of which is a major risk factor for development of PDAC. Functional studies in vitro and in vivo in mouse models of PDAC showed that overexpression of miR-192 was sufficient to reduce cell proliferation and invasion. Mechanistic analyses correlated changes in miR-192 promoter methylation and expression with epithelial-mesenchymal transition (EMT). Cell proliferation and invasion were linked to altered expression of the miR-192 target gene SERPINE1 that is encoding the protein plasminogen activator inhibitor-1 (PAI-1), an established regulator of these properties in PDAC cells. Notably, our data suggested that invasive capacity was altered even before neoplastic transformation occurred, as triggered by miR-192 downregulation. Overall, our results highlighted a role for miR-192 in explaining the early metastatic behavior of PDAC and suggested its relevance as a target to develop for early diagnostics and therapy.
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Botla et al. (2016) Cancer Res. 76, 4149. 
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Methylation patterns of miR-192 promoter

Down-regulation of miR-192 in chronic pancreatitis (CP) and PDAC patient samples compared to normal pancreas (NP) is epigenetically regulated. (left) Pooled bisulfite sequencing of the CpG island located 3.5 kb upstream of miR-192  revealed an increase in its methylation status in PDAC and CP samples compared to NP (boxed region in the heatmap). (right) Hypermethylation inversely correlated with expression of miR-192 in CP and PDAC.
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GHSR DNA hypermethylation:
a common epigenetic alteration of high diagnostic value in many cancers

           logo NGFN                logo DAAD

Diagnosis
Identification of a single molecular trait that is determinant of common malignancies may serve as a powerful diagnostic supplement to cancer type-specific markers. Substantial hypermethylation at the promoter and first exon of growth hormone secretagouge receptor (GHSR) was found to be characteristic of seven studied malignancies with very high sensitivity and specificity. Discrimination of breast or pancreatic cancer from healthy tissue samples exhibited 100% specificity and sensitivity, for example.
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Figure to the right: Typical ROC diagrames are shown for five particular cancer entities. Also the overall accuracy for all studied cancers is presented. The AUC value indicates the respetive degree of diagnostic accuracy.

Early detection
Moreover, differential methylation was observed for ductal carcinoma in situ (DCIS), for instance, which is considered an early stage breast cancer that may progress to invasive cancer. GHSR gene methylation could therefore be particularly attractive for early detection, which is a key factor in cancer control.








Field defect in sporadic cancers
The increased methylation of the signature CpGs was also present in normal-appearing tissues collected from cancer patients, but not in samples obtained from healthy donors. This suggests the involvement of DNA methylation in a “field defect”. Field defect (or field cancerization) refers clinically to the existence of pre-neoplastic alterations in cells of a tissue that are associated with local recurrences. From a molecular point of view, this phenomenon has been explained by genetic abnormalities in patients with familial cancers. However, our data propose a contribution of epigenetic alterations to the field defect in sporadic cancers. GHSR methylation could thus possibly act as a marker of treatment success and recurrence.
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Figure to the left: To visualise differences in the degree of methylation in breast samples, correspondence analysis (CA) was used. In the projection plot, each sample is depicted as a coloured square and CpG sites that exhibited the most significant differential methylation levels are represented as black dots. All co-localise with the cancer samples at the right side of the plot, indicating that the highest methylation level is found in cancer. In contrast, the healthy samples are located to the left, in the opposite direction off the centroid, indicating that the CpGs are at the lowest level of methylation in these samples. Likewise, based on the localisation of normal-appearing tissues of cancer patients and benign samples along the horizontal axis (first principal component; i.e., the direction along which the samples show the largest variation), it can be seen that an intermediate methylation load existed in these samples



Jandaghi et al. (2015) Cell Cycle 14, 689.

Moskalev et al. (2015) Oncotarget 6, 4418.
Botla et al. (2012) Breat Cancer Res. Treat. 136, 705.  pdf icon









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FINISHED PROJECT:
Correction of PCR-bias in quantitative DNA-methylation studies

          logo NGFN                logo DAAD

PCR amplification of bisulfite-treated DNA is a processing step that is common to many currently used methods of quantitative methylation analysis. Preferential amplification of unmethylated alleles – known as PCR-bias – may significantly affect the accuracy of quantification. To date, reported processes for avoiding PCR-bias relied on an optimisation of PCR conditions. Although shown to be effective for particular genes, the implementation is time-consuming and labour-intensive, especially if multiple loci are analysed, thus the usefulness remains contradictory.
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We developed an effective method of correcting biased methylation data. As opposed to refining experimental conditions, we approached the correction of amplification bias by accepting its occurrence during experimentation but adjusting the initial amplification result by a comparison to calibration data and the application of regression curves for deriving correction factors. As few as three calibration samples (0, 50, 100% methylation) are sufficient to define methylation degrees accurately. Two types of regression – hyperbolic and cubic polynomial – were checked. The correction process based on cubic polynomial regression was found to be superior overall.
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The method is applicable irrespective of the locus that is interrogated or the number of sites analysed. Based on curve-fitting, the method is not influenced by the type of bias – preferential recovery of methylated or unmethylated alleles – and works equally well for both. Furthermore, any bias that was additionally introduced by the analysis procedure, for example a sequencing readout, could be compensated by the very process. The method is also automatable for high-throughput analyses.

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Figure legend: The degree of bias introduced by PCR-amplification is shown for three gene promoters.The apparent degree of methylation observed after amplification (y axis) was plotted as a function of the actual methylation (x axis). The red line indicates the regression curve fitted to the data. Without correction (left) there was partly a substantial deviation between real and observed methylation, as indicated by the distance between the red line and the expected diagonal. The deviation basically disappeared upon correction (right).

Moskalev et al. (2011) Nucleic Acids Res. 39, e77.   pdf icon
  










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