Current research suggests that a new technique to determine tumor methylation status can be used in archived tissue samples.
DNA in tumors is often altered compared with DNA in normal tissues. One common DNA alteration in cancerous tissue is hypermethylation, which results in loss of gene expression. The difference in methylation between normal and cancerous tissues can be used as a biomarker for early cancer diagnosis, risk assessment, and response to therapy.
Archival tissues, or tissues that are formalin-fixed and paraffin-embedded for long-term storage, are difficult to screen for cancer biomarkers due to the low quality of their DNA. It is therefore important to develop new techniques to screen for DNA methylation that can be used in archival tissues.
Balic and colleagues examined the ability of high-resolution melting analysis (HRM) to detect methylation on archival tissues from colorectal cancer patients. They found that HRM provided similar results between archival and fresh tissues. In addition, they validated the results using the widely used MethyLight assay.
The results by Balic et al "add substantial information on the HRM-based DNA methylation analysis and demonstrate its applicability for analysis of archival tissues." This assay can be used to establish risk stratification of patients based on methylation status of specific markers and, due to its high sensitivity may have the potential to detect low amounts of methylated cells within the tumor, or even to detect low numbers of tumor cells in the background of non-tumor cells in lymph nodes and other organs. Most importantly, because formalin fixation and paraffin embedding are the most common means of tissue storage, the reported method has the potential to make DNA methylation analysis possible on this vast tissue resource.
Balic and colleagues will now evaluate the ability of HRM-based DNA methylation analysis to predict the presence of lymph node metastases and to detect very small tumor deposits in lymph nodes with known micrometastatic disease in a well defined cohort of prostate cancer samples. This may lead to new and better predictive and staging methods for prostate cancer patients.
This study was supported partly by the Austrian National Bank Fund.
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