Clinical validation of a targeted methylation-based multi-cancer early detection test

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Published: 13 Apr 2021
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Dr Eric Klein - Cleveland Clinic, Cleveland, USA

Dr Eric Klein speaks to ecancer about the clinical validation of a targeted methylation-based multi-cancer early detection test.

He says this study aimed at early cancer detection which could identify tumours at a time when outcomes are superior and treatment is less morbid. It assessed the performance of targeted methylation analysis of circulating cell-free DNA (cfDNA) to detect and localise multiple cancer types across all stages at high specificity.

Dr Klein then mentions the methodology used in this study. He further discusses the key results obtained from this research. In conclusion, he talks about the future impact of this research on the treatment and diagnosis of cancer.

 

Clinical validation of a targeted methylation-based multi-cancer early detection test

Dr Eric Klein - Cleveland Clinic, Cleveland, USA

Our study was about the continued validation of a multi-cancer early detection test in preparation for offering a test in the marketplace. The background on this is that the data that we’re presenting is the third sub-study of something called the CCGA, the Circulating Cell Genome Atlas study, which was 15,000 individuals divided into three phases. The first phase was a discovery study so that we could develop a blood-based assay in patients who were mostly known to have cancer and determine which assay whole genome sequencing targeted mutations or a whole genome methylation assay best predicted the presence of cancer at a very, very high specificity. So the algorithm that we used was set as a specificity of about 99.5% with the idea being that for a widely available screening test we would not want a high false positive rate and, in fact, we achieved that.

So what we found in the first sub-study was that the methylation assay performed best. CCGA2 was a second sub-study to validate the algorithm and further refine it and develop a targeted methylation assay. The data that we’re showing is from CCGA3 which was an additional validation study with the optimised targeted methylation assay.

What was the methodology used in this study?

The methodology was what I described which was using a next generation sequencing platform we again started out with 15,000 individuals to do a discovery study to determine which assay worked best for predicting the presence of cancer in patients with known cancer with a very high specificity, again a very low false positive rate. So the methodology was to compare whole genome sequencing to a targeted mutation assay to initially a whole genome bisulphate methylation assay and then finally to a targeted methylation assay. The population was drawn from 142 different sites in the United States and 70% of these 15,000 people were known to have cancer and 30% were thought to be cancer free, at least by self-report and medical history and so forth. So we compared the results of all of these assays in both populations.

What were the key results of your study?

The key results were that the targeted methylation assay in this third sub-study, which included a total of a little over 4,000 individuals, had a very high specificity – 99.5%, again meaning a false positive rate in patients who were not known to have cancer or not thought to have cancer of only 0.5%. Very, very important were we to roll out this multi-cancer early detection test in the population we need a test that doesn’t tell people who don’t have cancer that they might, that’s a key critical piece of data that came from this study.

The second important observation was that in the patients who were known to have cancer the sensitivity of the test was a little over 51%. So we detected the presence of cancer in patients known to have cancer in a little more than half. Really impressively in addition to that when we looked at the signal and tried to predict in those who had a positive signal who were known to have cancer did the signal tell us what organ system the cancer came from, we were able to do that with an accuracy of almost 89%. So the advantages of this particular assay are very high specificity, very low false positive rate, a much broader sensitivity than individual screening tests that are used currently for screening breast cancer, prostate cancer, colon cancer and so forth, and we were able to detect these cancers, about half of them, in cancer subtypes that do not have established screening paradigms. Then, really impressively, when someone had a positive signal we could predict the tissue of origin or the clinical site of origin, the organ system of origin, in 89% of patients.

How might these results impact the research and treatment of cancer?

The impact is really huge. Again, to get back to a point I just made, there are only five cancers for which there is a screening paradigm – that’s breast, cervical, lung in high risk people, prostate and colorectal cancer. They detect a certain number of cancers, they’ve all been shown to reduce mortality but there’s a whole slew of other cancers that account for most of the mortality from cancer in the United States for which there is no standard screening paradigm. Those are cancers that are detected at late stages where the burden of cure is higher, meaning patients need more treatments, and the cure rate is a lot lower.

So the potential impact of this sort of test with these sorts of results that I’ve commented on already is that we now will be able to screen for multiple cancers all at the same time with a single blood test for which there is no available screening currently. When you model that data out we think that we can cause a stage shift to detection of these lethal cancers at much earlier stages and therefore be able to impact the cure rate. That’s the clinical implication of this and I’m really excited by it.