epiPancancer – multiple cancer blood test

Early Detection of Cancer Can Save Life and Prevent the Suffering and Cost of Treating Disease

Many cancers are detected late. And late detection of cancer results in increased morbidity and death. Current biomarkers lack sensitivity and specificity to detect cancer early. Available biomarkers and diagnostic methods are invasive; can’t be used for follow-up of healthy population.

Our scientists multiple cancer blood test, by investigating DNA methylation results from normal tissues, blood and cancer from thousands of people and used proprietary methods to discover methylation profiles that are categorically different between cancer, blood and normal tissues. We called this new method BCD: Binary Categorical Differentiation. The method identifies black and white differences between cancer and normal.

Discovery of epiPanCancer Markers

Using our proprietary BCD method, we discovered methylation profiles that are so unique that are totally unmethylated in healthy blood and methylated in many cancers by examining publicly available DNA methylation data from 169 Healthy blood Samples and 130 Cancer (13 Cancer type, 10 each).  In  Figure A below each sample received an average pancancer methylation score; the cancer samples methylation scores are much higher than the healthy controls which are close to 0. In Figure B, we present the methylation scores for each of the samples for the 4 genes that together form the epi PanCancer marker. Red indicates high methylation and blue no methylation. While all healthy are blue many reds are seen in the cancer samples. In Figure C is a list of the different cancers that were examined here.

Validation of Pancancer Markers on 18,752 Individuals From Public Data

We then verified that these DNA methylation profiles that we discovered in the 130 cancer samples using DNA methylation profiles from more than 18,000 people. These DNA methylation profiles are publicly available. The figure below shows that the methylation score that we developed detects cancer in numerous cancer patients (Figure A) (in orange) but not in blood from healthy people (blue) and very few healthy tissues (red) and other diseases (green) (each spot represents one person). There is some detection in tissues which are adjacent to the tumor (purple NAT).  The specificity is above 95% (only 5% false positives) and area under the curve is 0.9581 (95% specificity and 87% sensitivity across 31 different cancers).

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