Liver cancer Hepatocellular Carcinoma (HCC) is the fifth most common cancer world-wide. It is particularly prevalent in Asia, and its occurrence is highest in areas where hepatitis B is prevalent. Hundreds of millions of people in Asia are at risk for developing liver cancer particularly people who suffer from liver disease, chronic liver inflammation high alcohol uptake. Follow up of high-risk populations such as chronic hepatitis patients and early diagnosis of transitions from chronic hepatitis to HCC would improve cure rates. However, current diagnostic methods, which include imaging and immunoassays with single proteins such as alpha-fetoprotein often fail to diagnose HCC early (Flores & Marrero, 2014). The main challenge is that solid tumors hide in internal organs andevolve long before they exhibit clinical symptoms.Many studies showed that it is possible to find tumor DNA in one of the most accessible and commonly used biological sample in clinical medicine, blood..


It is widely established by now that tumor DNA is shed into the bodyand could be found in the plasma portion of whole blood even beforethe onset of clinical symptoms (Warton & Samimi, 2015). Isolatingplasma from blood is a simple procedure that could be performed byany clinical lab in almost any hospital or nurse/doctor clinic. Themain challenge is how to tell apart tumor DNA from all other normalDNA that finds itself in plasma. And moreover, how do we know if wedetect cancer whether it is a liver cancer or some other cancer. It islike finding a needle in a haystack. Although screening for sequencemutations has held high promise, it appears now that it is not ahighly effective way for detecting tumor DNA in blood.


However, there is a very unique and novel way to detect fewmolecules of cancer DNA on the background of normal DNA, it is notby examining the genetic sequence but rather by examining the“epigenetic” profile of DNA. Research pioneered by Moshe Szyf aprofessor at McGill University and a fellow of the Royal Society ofCanada has taken almost three decades to establish the uniqueepigenetic characteristics of cancer cells and their DNA. The fruit ofthis research is a robust test for early detection of liver cancer thatrequires just 5 ml of blood (2 ml of plasma) and could be used forearly detection of liver cancer in healthy people and people who areat a higher risk for liver cancer. The test does not only detect cancerbut can determine that the cancer originates in the liver. This is aproprietary invention that is under patent protection process acrossthe world (PCT/IB2019/055855).

The novel epiLiver test: Robust binary categorical differentiation between liver cancer and normal DNA (BCD)

Our scientists investigated DNA methylation results from normal tissues,blood and cancer from dozens of people and used proprietary methods todiscover methylation profiles that are categorically different betweenliver cancer, blood and normal tissues. We called this new method BCD:Binary Categorical Differentiation. The method identifies Black and whitedifferences between cancer and normal.Our test has two components.The first component is called “detect”, it detects cancer.The second component is called “spec” and it determines that the cancer is liver cancer {HCC}.


Using our proprietary BCD method, we discovered HCC methylation profiles that are so unique that even if we have only 5 copies of DNA from cancer mixed with tens of thousand of copies from other cells we could detect it using our method of analysis called next generation sequencing. We then verified that these DNA methylation profiles that we discovered would indeed discover cancer when we examined DNA methylation profiles from more than 10000 people. The figure below shows that the methylation score that we developed detects HCC in789 HCC patients (in purple) but not in a variety of normal liver tissue and blood from 1442 people (each spot represents one person). The specificity and sensitivity are above 95% and area under the curve is 0.9926


However, what makes our test truly unique in the field is that we have also discovered DNA methylation profiles that can tell that the DNA is not just cancer DNA but liver cancer DNA with a potential specificity of close to 95%. Most available test don’t differentiate between liver and other cancers. The figure below shows the scores for the Spec test across DNA methylation results from close to 8000 different tumors. Each spot represent a sample from a single person. The test clearly differentiates between liver cancer and other 17 cancers (the liver cancers are in blue in the far right. Each spot is one sample, other 17cancers are in different colors).

Clinical validation of BCD-next generationSpec and Detect for liver cancer detection in plasma from 401 people.

In summary, we validated that our detect and spec markers reveal a profile that is highly accurate for liver cancer DNA at any stage on thousands of samples and tissues using DNA methylation. In HKG epitherapeutics we developed a lab test using a proprietary next generation sequencing based method that can reveal the profiles ofDNA methylation of thousands of copies of DNA in people plasma and then searches for the few copies that have cancer-specific and liver specific profiles. Our method counts copies that have cancer-specific and liver -cancer specific profiles and issues a result. We validated that the background of other DNA in blood is very low as we had predicted, providing a “black and white” difference between cancer and normal DNA. The “heatmap below shows the results of a study on401 people from Dhaka Bangladesh. 49 healthy controls, 50 chronic hepatitis B and 302 cancers from stages A to D. Each column is a different patient. For each patient we sequence 5 genes. The level of methylation is indicated by the color, red is most methylated and blue is not methylated. You can see a clear red and blue difference between the samples. All the control and chronic hepatitis are almost totally blue while a lot of red is seen in the cancer patients. The boundary between cancer and non cancer is sharp and clear.

Clinical validation of BCD-next generationSpec and Detect for liver cancer detection in plasma from 401 people.

We developed a combined score that The chart below shows that the number of methylated copies (MCR) in cancer patient plasma in ourBangladesh trial is dramatically different than in healthy and chronic hepatitis B patients, most people have between 2 and 10 methylated copies while in cancer patients it could reach more than 10000.

The 5 gene M score predicts HCC

Our team developed a proprietary equation to quantify the methylation levels across the 5 genes for each patient, which we callM score. We then calculated the M scores of 285 healthy and cancer patients from our Bangladesh clinical trial. The chart below shows that the M scores for liver cancer (HCC) patients is much higher than in controls. In the chart A (below) each spot is the M score for a different patient from the Bangladesh study (red spots are people with HCC and blue are healthy people with no known tumors). In chartB we present the median M score for the cancer (red bar) and healthy group (blue bar) (+/ confidence intervals). You can see the large difference between the cancer and healthy groups. In chart C we examined how well the M score can differentiate between the cancer and healthy people. The ROC curve measures sensitivity and specificity of the test. The area under the curve (AUC) defines the accuracy of the test integrating both specificity and sensitivity where1 is a perfect score, the AUC of the epiliver test in this study was0.9437.

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