Researchers have come up with a new blood testing technology called GEMINI (Genome-wide Mutational Incidence for Non-Invasive Detection of Cancer). This technology utilizes genome-wide sequencing of single molecules of DNA along with machine learning.
This test works by collecting blood sample from individuals at risk of cancer. Then, cell-free DNA shed by tumors is sequenced. The single molecules are analyzed for sequence alterations to provide mutation profiles across the genome. A machine learning model was trained to identify changes in cancer and non-cancer mutation frequencies in different regions of genome was used to identify people who have cancer from those who do not have. The model generated a score between 0 to 1; with higher scores indicating higher likelihood of cancer.
The GEMINI test in combination with computerized tomography imaging was able to detect over 90% of lung cancer including early stage diseases. The potential was further demonstrated in a study with seven participants without detectable tumors, who later received lung cancer diagnosis. The median GEMINI score of the group was 0.78, which was higher than individuals without cancer. The test was also able to identify altered mutation profiles from patients with other cancers as well including liver cancer, lymphoma etc. In the group of patients receiving lung cancer drug treatment, GEMINI scores decreased during initial response and thus, suggested the testing could be used to monitor patients.
The senior study author, Victor Velculescu, professor of Oncology and co-director of the cancer genetics and epigenetics program at the Kimmel Cancer Center said, “This study shows for the first time that a test like GEMINI, incorporating genome-wide 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.”
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