Researchers at the Johns Hopkins Kimmel Cancer Center are developing novel blood testing technology that combines genome-wide sequencing of single molecules of DNA shed from tumors with machine learning. This technology has the potential to enable earlier detection of lung and other cancers.
The test, called GEMINI (Genome-wide Mutational Incidence for Non-Invasive detection of cancer), focuses on identifying changes to DNA throughout the genome. The process involves collecting a blood sample from individuals at risk of developing cancer. The cell-free DNA (cfDNA) shed by tumors is then extracted from the plasma and subjected to cost-efficient whole genome sequencing. The DNA molecules are analyzed for sequence alterations, and mutation profiles across the genome are obtained. A machine learning model is then used to differentiate individuals with cancer from those without by identifying changes in cancer and non-cancer mutation frequencies in various parts of the genome. The model generates a score ranging from 0 to 1, with a higher score indicating a higher likelihood of having cancer.
In laboratory tests of GEMINI, the approach successfully detected over 90% of lung cancers, including stage I and II cases, when combined with computerized tomography imaging. The findings of this proof-of-concept study were published online on July 27 in the journal Nature Genetics.
Victor Velculescu, M.D., Ph.D., professor of oncology and co-director of the cancer genetics and epigenetics program at the Kimmel Cancer Center, the senior study author, stated, “This study demonstrates, 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 techniques, may be used for early cancer detection and for monitoring patients during treatment.”
The study primarily focused on detecting lung cancer in high-risk populations. However, altered mutational profiles were also detected in cfDNA from patients with other cancers, such as liver cancer, melanoma, and lymphoma, suggesting that the technology could have broader applications.
During the development of GEMINI, researchers examined whole-genome sequences of cancers from 2,511 individuals across 25 different cancer types. They identified distinct mutation frequencies across the genome in different tumor types, such as lung cancers having an average of 52,209 somatic mutations per genome. The investigators also discovered genomic regions with the highest mutation rates and observed that the frequency of mutations in these regions was similar between tumor tissue and blood-derived cfDNA from lung cancer, melanoma, and B cell non-Hodgkin lymphoma patients.
Researchers evaluated the ability of GEMINI to detect sequence alterations in cfDNA from 365 individuals in the Longitudinal Urban Cohort Ageing Study (LUCAS), a cohort known to be at high risk for lung cancer. The study found that GEMINI scores were higher in people with cancer compared to those without. Additionally, GEMINI was combined with DELFI (DNA evaluation of fragments for early interception), a previously developed test that detects changes in the size and distribution of cfDNA fragments across the genome, to enhance detection of early-stage lung cancer. The combined approach successfully detected several cancer samples that GEMINI alone missed. In a group of 89 samples from the LUCAS cohort, GEMINI combined with DELFI accurately detected lung cancers 91% of the time, and similar results were obtained in a separate validation cohort of 57 individuals, mostly with early-stage lung cancer.
The researchers also investigated the use of GEMINI in other study samples, including seven patients without any detectable tumors at the time of blood collection. These patients had a median GEMINI score of 0.78, higher than that of individuals without cancer. Six of them tested positive using GEMINI and were later diagnosed with lung cancer between 231 and 1,868 days after the blood samples were obtained, implying that mutations in cfDNA profiles can be detected years before standard diagnoses.
Furthermore, GEMINI was shown to be able to differentiate between subtypes of lung cancer and detect early liver cancers. In a group of patients receiving lung cancer drug treatment, GEMINI scores decreased during the initial response to therapy, indicating that the test could be used to monitor patients during treatment.
Based on the results, Rob Scharpf, Ph.D., associate professor of oncology at the Kimmel Cancer Center, stated that the combination of genome-wide GEMINI mutation analysis and DELFI fragmentation analysis of cfDNA “may offer an opportunity for cost-effective and scalable cancer detection.” However, larger clinical trials are necessary to validate the usefulness of this tool before it can be used in a clinical setting.
Other contributors to the study include Dimitrios Mathios, Zachariah Foda, Akshaya Annapragada, Jamie Medina, Vilmos Adleff, Elaine Jiayuee Chiao, Leonardo Ferreira, Stephen Cristiano, James White, Amy Kim, Valsamo Anagnostou, and Jillian Phallen from Johns Hopkins. Additional authors are from Boston University and the Allegheny Health Network Cancer Institute in Pittsburgh.
The research received support from the Dr. Miriam and Sheldon G. Adelson Medical Research Foundation, the Stand Up to Cancer (SU2C) InTime Lung Cancer Interception Dream Team Grant, the SU2C-Dutch Cancer Society International Translational Cancer Research Dream Team Grant (SU2C-AACR-DT1415), the Gray Foundation, the Commonwealth Foundation, the Mark Foundation for Cancer Research, the Cole Foundation, a research grant from Delfi Diagnostics, and several U.S. National Institutes of Health grants.
Some of the authors, including Daniel Bruhm, Dimitrios Mathios, Stephen Cristiano, Jillian Phallen, Rob Scharpf, and Victor Velculescu, have submitted patent applications related to the use of cfDNA for cancer detection. Cristiano, Phallen, Adleff, Scharpf, and Velculescu are also founders of Delfi Diagnostics and consultants for the organization. Velculescu serves on the board of directors and is an officer for Delfi Diagnostics, as well as holds stock in the company. James White is the founder and owner of Resphera Biosciences. Additionally, The Johns Hopkins University owns equity in Delfi Diagnostics. Velculescu is an adviser to Viron Therapeutics and Epitope. These relationships have been reviewed and approved by The Johns Hopkins University in accordance with its conflict-of-interest policies.