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Laboratory for Advanced Medicine Shares New Data on IvyGene Test Performance in Liver Cancer

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NEW YORK (GenomeWeb) – The Laboratory for Advanced Medicine's methylation-based liquid biopsy test IvyGene has high specificity and sensitivity for detecting liver cancer, according to early data presented by the company last week.

Investigators presented the work at the Society for Immunotherapy of Cancer's annual meeting in Washington DC, where they reported on the performance of the test in a set of blinded samples from patients with stage I-IV hepatocellular carcinoma, normal controls, and individuals with potentially confounding diseases, including benign liver disease and a handful of other cancer types.

According to the company, IvyGene, which was commercially launched this spring, had an overall sensitivity of 95 percent in distinguishing liver cancer cases from controls, with relatively little loss of power in the early-stage cancer cases compared to  later-stage patients (89 percent versus 100 percent).

Based on the test's calls in the normal controls and the subjects with benign liver disease, investigators calculated the specificity of the test to be 97.5 percent.

The data is the first that IvyGene has presented formally on the test, relying up to this point on earlier studies conducted by an academic team at the University of California, San Diego, whose work is at the heart of the epigenetic methodology used in the company's commercial assay.

Members of the UCSD group published a study in late 2017 in Nature Materials describing a classifier that could distinguish patients with liver cancer from healthy controls as well as quantify disease stage or progression.

In another report, published in the Proceedings of the National Academy of Sciences, the same team showed they could use epigenetic features to distinguish cancer samples from normal tissue with more than 95 percent accuracy and locate colorectal cancer metastases accurately that were specific to either the liver or the lung.

David Taggart, Laboratory Director for LAM's West Lafayette, Indiana CLIA lab and first author of a poster presented at SITC, said that as opposed to data from the bisulfite sequencing method used by the UCSD team, the newer IvyGene data reflects the narrower approach that the company has adopted in its clinical testing, in which unique methylation panels or signatures are developed for different cancer types.

So far, the company is marketing the test for lung, colorectal, breast, and liver cancers in the US. Taggart said that the team has also developed a discriminator for nasopharyngeal cancers, which it plans to launch in Asia.

Hepatocellular carcinoma represents about 75 percent of liver cancers in the US and already has well-established screening criteria – focused largely on individuals with cirrhosis, are screened every six months using ultrasound with or without blood testing for alpha- fetoprotein, according to guidelines.

Taggart said that neither of those available tools has great performance. Ultrasound is about 73 percent sensitive on average, he said, but varies widely from user to user, which leaves significant room for DNA-based tools that might work better.

In the company's study presented at the SITC meeting, investigators tested samples from 130 subjects in total, including 60 HCC patients (34 with stage III, 10 with stage II, nine with stage I, and seven with stage IV), 30 control subjects without liver disease, 10 controls with benign liver disease, and another 30 individuals diagnosed with breast, colorectal, or lung cancer.

LAM technicians were blinded to the nature of the samples, which they processed using the IvyGene platform.

Overall, the test correctly classified 57 of the 60 samples drawn from subjects with hepatocellular carcinoma, for an overall calculated sensitivity of 95 percent, ranging from 89 percent in the stage I subset to 100 percent in stage IV patients. One stage I patient and two stage III patients were called negative.

The test correctly identified 29 of the 30 samples drawn from subjects without liver disease and all10 samples from benign liver disease patients, for a combined specificity of 97.5 percent.

The test seems to have lower specificity in terms of distinguishing liver cancer from other tumors, though. Of the samples drawn from subjects with cancer other than liver cancer, 90 percent of the breast cancer samples, 80 percent of the colorectal cancer samples, and 90 percent of the lung cancer samples were correctly identified as not liver cancer — an 87 percent specificity on average.

Taggart and colleagues concluded that the results support the idea that methylation analysis of circulating DNA can offer more sensitive and specific detection of these types of liver cancers than currently used technologies.

"I feel the data are very strong," he said, adding that the company sees the combination of its newly-presented results with the earlier UCSD bisulfite sequencing data as even more persuasive of the technology's promise.

The next step is to confirm the ability of the test to identify cancers in at-risk individuals in a prospective manner, something LAM has already started with a trial that was registered in October but is not yet recruiting.

LAM faces numerous competitors in what has become a crowded field of genetic early cancer detection pioneers. Blood-based approaches have propagated rapidly in the last few years, with multiple companies and academic groups now naming DNA methylation either as an aspect of their approach, in the cases of firms like Grail and Freenome, or as their central tenet.

Researchers from UCLA published a study this summer, for example, describing a method they call CancerDetector, which proved highly sensitive in detecting early-stage liver cancers in a small proof-of-principle study. The authors said they hope to commercialize a clinical test through a company called Early Diagnostics.

Investigators from UCSD, meanwhile, have launched a firm called Singlera, which is advancing a methylation haplotype method for the detection of a range of tumor types.

UCSD's Kang Zhang, whose work underlies the IvyGene test, was at one point a co-author on methylation-based cancer detection research with UCSD professor Kun Zhang, who has led the team developing the Singlera strategy. But LAM CFO Richard Brand said that the technologies the two companies are commercializing are not connected.

According to Taggart, as LAM moves forward with prospective validation in liver cancer, it is also continuing to generate retrospective data for the other tumor types it has targeted.

"Liver cancer happened to be first," he said. "There is a really clear clinical need, and we were able to get to a very sensitive and specific [signal] earlier … but we also have data for breast cancer, colorectal cancer, and lung cancer that are on the way."