DELFI Diagnostics Licenses GEMINI Technology from Johns Hopkins University

DELFI Diagnostics, a pioneering developer of a new class of high-performance, accessible liquid biopsy tests for early cancer detection and monitoring, has exclusively licensed a new, highly accurate method for identifying somatic genomic alterations in cell-free DNA (cfDNA) known as GEMINI, or GEnome-wide Mutational Incidence for Non Invasive detection of cancer

Until now, first-generation liquid biopsy technologies relied on expensive, deep, targeted sequencing to detect mutations associated with cancer. Now, for the first time, researchers have achieved genome-wide detection of tumor-specific mutations from the same low-coverage whole genome sequencing methods that form the basis of the DELFI Diagnostics platform.

In a study published in Nature Genetics, researchers showed that GEMINI, combined with the approach used by DELFI Diagnostics, could successfully identify early stage lung cancers – those cancers that are most critical to detect to change patient outcome. In a cohort of lung cancer cases and non-cancer controls (n=163), combining the GEMINI analysis with DELFI's fragmentomics approach yielded an area under the receiver operator curve (AUC), a common measure of diagnostic accuracy, of 0.93¹. The combined technology also showed high performance in other applications including monitoring response to therapy, and distinguishing small-cell lung cancer from non-small cell lung cancer.

"We founded DELFI Diagnostics to address population-health needs in cancer detection with low-cost, flexibly deployable technology," said Nicholas Dracopoli, PhD, DELFI Diagnostics's Chief Scientific Officer and Co-Founder. "Whenever we evaluate new technology, it must meet multiple criteria: It must help boost early stage cancer detection, and it must be able to be applied to the sequencing data generated from our low-cost platform. GEMINI fulfills both those requirements and shows how we can further refine the performance of our platform without changing our lab processes."

DELFI Diagnostics's fragmentomics-based approach applies machine learning-based algorithms to low-coverage, whole genome sequencing data from cfDNA. Beyond the genome-wide analysis of fragment length profiles that reflect the aberrant packaging of DNA in cancer cells, the whole-genome sequencing approach also reveals many other changes in DNA features including somatic genomic alterations, amplifications, deletions, and more.

"We have already shown that this platform can detect lung cancer with very high sensitivity," said Peter Bach, MD, DELFI Diagnostics's Chief Medical Officer. "This new study shows that what was a first-generation approach to cancer detection -- looking for genomic mutations -- can now be extended genome-wide and enhanced with the DELFI platform, improving early stage cancer detection with no additional sequencing or lab prep cost."