Value Proposition:
· Uses methylation-based epigenetic instability as a biomarker for cancer detection
· Target specific and/or target agnostic capabilities to detect cancer
· Outperforms existing technologies of DNA methylation-based cancer diagnostics
· Can be used in combination with current approaches/diagnostics to increase sensitivity
Technology Description
Researchers at Johns Hopkins have developed computational technology for evaluating the presence of unique methylation drift signatures that predict and indicate the presence of disease for diagnostic purposes. Biomarkers are identified using a method for measuring epigenetic drift within genomic elements as opposed to single site methylation. These biomarkers can then be related to the DNA sequence, predicted transcription factor binding sites, and regulatory DNA. The described technology exhibits increased sensitivity by employing sequencing and methylation analysis techniques that increase the amount of cfDNA that can be successfully used to detect the presence of cancer.
Unmet Need
Disease diagnostics can improve the effectiveness of treatments and reduce long-term complications. Current procedures to diagnose and identify the presence of disease like cancer are invasive, have high inter-person variation, or expensive and offer few details about the specifics of the cancer. Therefore, there is a strong need for sensitive, non-invasive diagnostics to be developed to help identify the presence of disease and decrease variability and discomfort in obtaining the results.
Stage of Development: Preclinical proof of principle
Publications:
