About DNA Methylation

DNA methylation is a type of chemical modification of DNA that can be inherited without changing the DNA sequence. Aberrant DNA methylation is mainly found in 5’-CpG-3’dinucleotides within promoters or in the first exon of genes, which is an important pathway for the repression of gene transcription in diseased cells. It is well demonstrated that DNA methylation plays an important role in the regulation of gene expression, tumorigenesis, and other genetic and epigenetic diseases. Thus, detection of methylation in some genes of diseased cells could provide very useful information for discrimination of this disease.

About USGMAT

Ultra-Sensitive Gene Methylation Amplification Technology (USGMAT) is BioCangen’s proprietary specific gene methylation detection technology. The USGMAT can quantitatively detect methylation alterations in the promotor regions in a real time, multiplex format. Compared to the current quantitative MS-PCR or other methylation-based gene amplification methods, USGMAT is much more rapid, simple, inexpensive and accurate in the quantification of gene methylation change and only needs extremely tiny amounts of starting DNA. Thus USGMAT can allow both high sensitivity and specificity to be achieved in detection of early-stage cancer.

About BioCangen

BioCangen Inc. as subsidiary company of Epigentek Group Inc. focuses on the development of methylation-based novel products for early cancer detection and therapeutic response prediction. With proprietary technology called Ultra-Sensitive Gene Methylation Amplification Technology (USGMAT), Biocangen has developed a highly sensitive and specific non-invasive test for detecting early-stage cancer, and is developing the new class of tests for predicting cancer therapy response.

By using proprietary technology called Methylation Specific-Signal Amplification Microarray (MS-SAM), Biocangen is also able to rapidly and reliably identify epigenetic biomarkers that can be used for developing more tests to detect specific type of cancer and predicting individualized response to single drug and drug regimes in cancer treatment.