MENLO PARK, Calif.—GRAIL, Inc., a company focused on early cancer detection, has announced validation data for its multi-cancer early detection blood test. The article was published in Annals of Oncology.
According to the data, GRAIL’s technology can detect more than 50 cancer types across all stages, through a single blood draw — with a very low false positive rate of less than one percent. When a cancer signal is detected, the test can also identify the tissue of origin with 93% accuracy.
At present, the majority of deadly cancers lack guideline-recommended screening tests. As a result, most cancers are detected after they have progressed to late stages when chances of survival are much lower. When cancer is diagnosed after it has spread, the five-year cancer-specific survival rate is 21%, compared to 89% when the cancer is diagnosed early and still localized.
“At GRAIL, we believe that multi-cancer early detection has the potential to significantly reduce cancer mortality,” said Alex Aravanis, M.D., Ph.D., chief scientific officer and head of R&D, as well as a co-founder of GRAIL. “This is a seminal moment in the field of cancer detection. We’ve built what we believe to be one of the largest clinical study programs ever conducted in genomic medicine, and the data published in Annals of Oncology further support GRAIL’s approach and commitment to clinical and scientific rigor.”
The publication includes data from GRAIL’s foundational Circulating Cell-free Genome Atlas (CCGA) study, which included more than 15,000 participants with or without a diagnosis of cancer. In the sub-study reported in today’s publication (N=6,689), results from the validation set (N=1,969) showed that GRAIL’s proprietary targeted methylation technology achieved high specificity (99.3%), across more than 50 cancer types.
The detection rate for a pre-specified set of 12 deadly cancer types was 67.3% across stages I-III (95% confidence interval [CI]: 60.7-73.3%). The overall detection rate for all cancer types was 43.9% across stages I-III (95% CI: 39.4-48.5%). When a cancer signal was detected, a tissue of origin result was provided for 96% of the samples. Of these, the test correctly identified the tissue of origin in 93% of cases. Performance of the test was consistent across training and validation sets.
“The promising results from this independent validation data set demonstrate the robustness of the test performance, including its ability to detect multiple cancer types, and its generalizability to broader populations due to a low false positive rate. In addition, the high accuracy in identifying the anatomic origin of the primary cancer, in conjunction with detection of a positive cancer signal in the blood, will allow providers to efficiently direct next steps for each individual’s diagnostic work-up and subsequent clinical care,” noted Minetta Liu, M.D., research chair and professor in the department of Oncology at the Mayo Clinic, co-lead author and investigator in the CCGA study.
“Despite the scale of and care in developing and validating this targeted methylation approach, the study has limitations. Participants with cancer were not all asymptomatic; to understand performance in an asymptomatic screening population will require additional studies, which are ongoing. Establishing a mortality benefit will also require additional studies as the CCGA study was not designed to examine all-cause mortality outcomes,” the article explains. “Until such longer-term studies are completed, a multi-cancer test that shifts detection to earlier stages may function as a proxy for mortality, given that cancer-specific mortality is improved when cancer is diagnosed at earlier stages.”
The impact of early detection on cancer mortality can be modeled using data from the National Cancer Institute’s Surveillance, Epidemiology, and End Results (SEER) Program. GRAIL also published new data modeling the most recent SEER statistics today in Cancer Epidemiology, Biomarkers & Prevention, showing that if all cancers currently diagnosed at stage IV could be diagnosed earlier, evenly distributed across stages I-III, cancer deaths could fall by 24%.
“The Human Genome Project ushered in the era of precision medicine, but the benefits have largely impacted patients with specific mutations or genetic diseases. GRAIL has combined the advances in human genomics with machine-learning data science to develop a multi-cancer early detection test that can maximize overall population detection while minimizing potential harms,” added Joshua Ofman, M.D., MSHS, chief medical officer and external affairs at GRAIL. “These validation data suggest that GRAIL’s test could be one of the first examples of a technology derived from insights from the Human Genome Project to have an impact at the broader population level, and could facilitate an important transition from screening for individual cancers, to screening individuals for all cancer types.”
“One strength of this analysis is the use of SEER data, which documents real-world cancer incidence and death in a large and representative U.S. population, reflecting contemporary patterns of utilization of cancer screening and treatment,” the study says. “Another strength involves the breadth of our assessment, which included 15 of the largest single-cancer contributors to the U.S. cancer burden. In addition, our estimates of deaths avertable accounted for the influence of uncommon, unstaged, and non-AJCC–staged cancers (e.g., brain or leukemia), which resulted in more conservative estimates.”
The CCGA data from the second sub-study were previously presented at the European Society for Medical Oncology (ESMO) 2019 Congress and American Society of Clinical Oncology (ASCO) 2019 Breakthrough, and are available on GRAIL’s website. The CCGA study is ongoing; GRAIL states that additional findings will be made publicly available at future medical meetings and/or in peer-reviewed publications.
