Marker Discovery

With the sequencing data from MeD-seq on (cell population enriched) laser capture microdissected (LCM) formalin-fixed and paraffin-embedded tissue samples we construct genome-wide DNA methylation profiles for normal and diseased tissue types (Figure 1). Samples are grouped together based on their tissue type, for example normal cervix and cervical squamous cell carcinoma (SCC) and, in this example, all other cancers/control types from the urogenital zone. For marker discovery only DNA samples that have passed our quality standards are used.

Figure 1. female urogenital zone, methylations profiles are generated for both control and cancer tissue samples.

Comparison of cancer and control methylation profiles by an in house developed bioinformatics pipeline Mimir facilitates the identification of specific or general Differentially Methylated Regions (DMR) in a genome wide fashion
(Figure 2).

Mimir is capable of detecting the following types of DMR’s

  • Specific region, methylated in one specific
    cancer type
  • General region, methylated in 2 or more cancer
  • Pan region, methylated in all cancer types of
    the female genital area

Figure 2, Illustration of DMR detection for the 3 types of DMR's. Only endometrial and cervix are depicted, other tissue types and carcinoma are also used in the same anayslis.

Primer and probe selection:

From the DMR regions we can develop specific, general and pan region markers. However, not all DMR’s are suitable to create powerful cancer detection markers. To determine if a DMR is discriminating enough and suitable to create a powerful markers, we use quality scores, predictive scores and visualizations to select our top DMR’s. After determination of our top DMR’s, primers and probe covering the most powerful methylated CpG’s in the selected DMR are designed.

Visualization of these selected DMR’s in grouped DNA methylation profiles through an Integrative Genomics Viewer (IGV) facilitates the identification of promising target sequences for the development of quantitative Methylation-Specific PCR (qMSP) assays (Figure 3).

Figure 3, IGV caption of the 3 DMR types. Specific DMR for cervical adenocarcinoma (AdC), general DMR for AdC and squamous cell carcinoma (SCC) and last a regional pan DMR  covering AdC, SCC and endometrial endometrioid and serous adenocarcinoma.

During the design of primers and probes we also look at the possibility of combining several markers in one multiplex assay. To assess the potential of the newly discovered markers the developed assays are tested on bisulfite-converted DNA of relevant samples.

Publications about our techniques

Genome-wide DNA methylation profiling using the methylation-dependent restriction enzyme LpnPI Genome Res. 2018 28(1):88-99

MicroRNA expression and DNA methylation profiles do not distinguish between primary and recurrent well-differentiated liposarcoma

Methylation markers FAM19A4 and miR124-2 as triage strategy for primary human papillomavirus screen positive women: A large European multicenter study.

Expression of p16 and HPV E4 on biopsy samples and methylation of FAM19A4 and miR124-2 on cervical cytology samples in the classification of cervical squamous intraepithelial lesions.

Cancer risk stratification of anal intraepithelial neoplasia in HIV-positive men by validated methylation markers associated with progression to cancer.

CADM1 and MAL methylation status in cervical scrapes is representative of the most severe underlying lesion in women with multiple cervical biopsies.

Host Cell Deoxyribonucleic Acid Methylation Markers for the Detection of High-grade Anal Intraepithelial Neoplasia and Anal Cancer.

Reliable identification of women with CIN3+ using hrHPV genotyping and methylation markers in a cytology-screened referral population.

Intra- and inter-laboratory agreement of the FAM19A4/mir124-2 methylation test: Results from an international study.

FAM19A4/miR124-2 methylation in invasive cervical cancer: A retrospective cross-sectional worldwide study.

Defining hrHPV genotypes in cervical intraepithelial neoplasia by laser capture microdissection supports reflex triage of self-samples using HPV16/18 and FAM19A4/miR124-2 methylation.

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