CHICAGO–(BUSINESS WIRE)–GRAIL, Inc., a life sciences company focused on the early detection of cancer, today announced initial results from its Circulating Cell-Free Genome Atlas (CCGA) Study. Data from three prototype genome sequencing assays showed it may be feasible to develop a blood test for early detection of multiple cancer types with greater than 99 percent specificity.
“We are excited that early results with our prototype assays suggest we can develop blood tests for early detection of cancer with a very low rate of false-positive results,” said Alexander Aravanis, MD, PhD, Vice President of Research and Development at GRAIL. “These data will be used to inform development of a blood test for early detection of multiple cancer types. Our next steps are to analyze additional data sets from CCGA, including validating these results in an independent data set, and to continue optimizing our assays.”
The data were presented today by Dr. Aravanis in a late-breaking research minisymposium at the American Association for Cancer Research (AACR) Annual Meeting 2018 in Chicago (Abstract LB-343).
Specificity Analyses
When developing early detection tests, high specificity is important to minimize false-positive results. Across all three of the assays evaluated, a “cancer-like” signal was found in less than one percent of participants who entered the study without a cancer diagnosis (5 of 580), suggesting a test with a specificity greater than 99 percent is feasible. Through longitudinal follow-up in the study, it has since been confirmed that two of the five participants who had a cancer-like signal have been diagnosed with cancer. This suggests the signal indicated presence of undiagnosed cancer. Follow-up of the other three participants continues.
Clonal hematopoiesis of indeterminate potential (CHIP) is a known confounding signal present in cell-free DNA (cfDNA) of white blood cells that could increase false-positive results. This CHIP signal is likely due to natural aging processes. Therefore, in this study, paired sequencing of white blood cells and cfDNA was performed to identify these non-cancer mutations. Somatic (non-inherited) mutations from the white blood cells accounted for 66 and 78 percent of all mutations identified in participants with and without cancer, respectively.
Sensitivity Analyses
Initial analyses showed all three prototype assays detected a strong biological signal in cancer types that are typically not screened for and have low survival rates (five-year cancer-specific mortality rate of greater than 50 percent1). These included lung, ovarian, pancreatic, liver, and esophageal cancers. The signal was detected across all stages of cancer, and increased with stage across all three of the assays. The assays evaluating the whole genome performed best, and the whole-genome bisulfite assay showed the strongest detection rates. Additional data showing detection rates for specific cancer types will be presented at an upcoming medical meeting.
Combined Detection Rates (Sensitivity) for Lung, Ovarian, Pancreatic, Liver, and Esophageal Cancers at 95% Specificity*
| Stages I/II/III (95% Confidence Interval) |
Stage IV (95% Confidence Interval) |
|
| Whole-Genome Bisulfite Assay | 65% (56%, 74%) |
95% (88%, 99%) |
| Whole-Genome Assay | 61% (51%, 70%) |
89% (79%, 95%) |
| Targeted Assay | 50% (41%, 60%) |
80% (69%, 88%) |
*95% specificity cut-off used for initial sensitivity analyses
About the First CCGA Sub-Study
In this pre-planned sub-study of CCGA, three prototype sequencing assays were evaluated as potential methods for a blood-based test for early cancer detection. Blood samples from 878 participants with newly diagnosed cancer who had not yet received treatment and 580 participants without diagnosed cancer were sequenced with all three prototype assays. Twenty different cancer types across all stages were included in the sub-study.
The prototype sequencing assays included:
- Targeted sequencing of paired cfDNA and white blood cells to detect somatic mutations such as single nucleotide variants and small insertions and/or deletions;
- Whole-genome sequencing of paired cfDNA and white blood cells to detect somatic copy number changes; and
- Whole-genome bisulfite sequencing of cfDNA to detect abnormal cfDNA methylation patterns.
About CCGA
CCGA is a prospective, observational, longitudinal study designed to characterize the landscape of cell-free nucleic acid (cfNA) profiles in people with and without cancer. The planned enrollment for the study is more than 15,000 participants across 141 sites in the United States and Canada. Approximately 70 percent of participants will have cancer at the time of enrollment (newly diagnosed, have not yet received treatment) and 30 percent will not have a known cancer diagnosis. The groups are demographically similar and representative of a real-world population. The group of participants without cancer includes individuals with conditions that are known to increase cfNA signal, such as inflammatory or autoimmune diseases. Planned follow-up for all participants is at least five years to collect clinical outcomes.
Presentation Details
Abstract LB-343
Development of plasma cell-free DNA (cfDNA) assays for early cancer detection: first insights from the Circulating Cell-Free Genome Atlas (CCGA)
Alexander M. Aravanis et al. Tuesday, April 17, 2018: 4:20-4:35pm CDT, Session LBMS01 – Minisymposium: Late-Breaking Research, Room S101 – McCormick Place South (Level 1).
About GRAIL
GRAIL is a life sciences company whose mission is to detect cancer early, when it can be cured. GRAIL is using the power of high-intensity sequencing, population-scale clinical studies, and state-of-the-art computer science and data science to enhance the scientific understanding of cancer biology and develop blood tests for early cancer detection. The company’s funding was led by ARCH Venture Partners and includes Amazon, Bezos Expeditions, Bill Gates, Bristol-Myers Squibb, Celgene, Decheng Capital, GV, Illumina, Johnson & Johnson Innovation, Merck, McKesson Ventures, Sutter Hill Ventures, Tencent, Varian Medical Systems, and other financial partners. For more information, please visit www.grail.com.
1 Surveillance Research Program, National Cancer Institute SEER*Stat software, version 8.3.4. 5-year cancer-specific mortality rates for persons aged 50-79; SEER18, 2010-2014.
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