On December 1, 2016, GRAIL, a life sciences company created in large part by Illumina, announced the "CCGA" - the Circulating Cell-free Genome Atlas.
- The full press release is here or here.
- Webpage at ClinicalTrials.gov, here.
- Subscription coverage and interviews at Genomeweb, here.
- See the company's website at GrailBio.com.
The project has some similarities to the NIH-sponsored Cancer Genome Atlas (TCGA, here) but transfers the genomics from solid tumor tissue to circulating DNA in blood.
Besides Illumina, other investors include ARCH Ventures, Jeff Bezos, Bill Gates, GV (Google Ventures), and Sutter Hill Ventures.
Additional quotes directly from GRAIL's press release:
About the Circulating Cell-free Genome Atlas (CCGA) StudyThe purpose of the CCGA study is to characterize the landscape of cell-free DNA profiles in individuals with and without cancer. The observational CCGA study will enroll at least 7,000 cancer patients and 3,000 healthy individuals, interrogating the biology of both tumor biopsy tissue samples and the circulating, tumor-derived nucleic acids in blood. Circulating tumor nucleic acids (ctNAs) in the blood are an emerging biomarker for earlier cancer detection. GRAIL and its collaborators will collect clinical outcomes on the enrolled participants for at least 5 years. The result will be a detailed atlas of cancer genetics that GRAIL will use to support its product development goals. The database, upon analysis, may be expanded to additional enrollment in specific cancers or healthy individuals. More information about the CCGA study can be found at NCT02889978.
About GRAIL’s High-intensity Sequencing ApproachGRAIL’s approach is to sequence circulating nucleic acids at unprecedented breadth and depth to optimize the detection of early-stage cancer. Combined with one of the largest clinical trial programs ever pursued in genomic medicine, GRAIL will be creating datasets of unprecedented scale to enable the deepest and most comprehensive understanding of cancer biology. GRAIL’s technology infrastructure teams are at the forefront of modern practice in developing and deploying scalable, cloud-based databases and analysis engines. Further, GRAIL is utilizing, at scale, the latest tools of data science, including powerful approaches from machine learning such as hierarchical neural networks. GRAIL will apply such methods to all steps of the Company’s data-generating pipeline including the ultimate challenge of classifying patients according to the presence, type, and severity of cancer. From the laboratory to the clinic, GRAIL’s goal is to produce the highest quality data and transform them into clinically actionable insights to save lives.