Novel blood testing technology being developed by researchers at the Johns Hopkins Kimmel Cancer Center that combines genomewide sequencing of single molecules of DNA shed from tumors and machine learning may allow earlier detection of lung and other cancers.

The test, called GEMINI (Genome-wide Mutational Incidence for Non-Invasive detection of cancer), looks for changes to DNA throughout the genome. First, a blood sample is collected from a person at risk of developing cancer. Then, cell-free DNA
(cfDNA) shed by tumors is extracted from the plasma and sequenced using cost-efficient whole-genome sequencing. Single molecules of DNA are analyzed for sequence alterations and used to obtain mutation profiles across the genome. Finally, a machine learning model trained to identify changes in cancer and noncancer mutation frequencies in different regions of the genome is used to distinguish people who have cancer from those who do not have cancer. The classifier generates a score ranging from 0 to 1, with a higher score reflecting a higher probability of having cancer.

In a series of laboratory tests of GEMINI, investigators found that the approach, when followed by computerized tomography imaging, detected over 90% of lung cancers, including among patients with stage 1 and 2 disease. A description of the work, a proof-of-concept study, appeared in Nature Genetics.

“This study shows for the first time that a test like GEMINI, incorporating genomewide mutation profiles from single molecules of cfDNA, in combination with other cancer detection approaches, may be used for early detection of cancers, as well as for monitoring patients during therapy,” says senior study author Victor Velculescu, professor of oncology and co-director of the Cancer Genetics and Epigenetics Program at the Kimmel Cancer Center.

The study mostly focused on detection of lung cancer in high-risk populations, says Daniel Bruhm, lead study author and graduate student in the human genetics program at the Johns Hopkins University School of Medicine. “However, we detected altered mutational profiles in cfDNA from patients with other cancers, including liver cancer, melanoma or lymphoma, suggesting it may be used more broadly,” Bruhm says.