Researchers have developed the first blood test that can accurately detect more than 50 types of cancer and identify in which tissue the cancer originated, often before there are any clinical signs or symptoms of the disease.
The blood test reported in this study analyzes methylation of cell-free DNA (cfDNA), targeting approximately one million of the 30 million methylation sites in the human genome. A machine learning classifier (an algorithm) was used to predict the presence of cancer and the type of cancer based on the patterns of methylation in the cfDNA shed by tumours. The classifier analysed blood samples from 4316 participants—3,052 in the training set (1531 with cancer, 1,521 without cancer) and 1,264 in the validation set (654 with cancer and 610 without cancer)—to identify methylation changes, classify the samples as cancer or non-cancer, and identify the tissue of origin.
The classifier's performance was consistent in both the training and validation sets, with a false positive rate of 0.7 percent in the validation set, the researchers reported on March 31, 2020 in Annals of Oncology. In 12 types of cancer that are often the most deadly (anal, bladder, bowel, oesophageal, stomach, head and neck, liver and bile duct, lung, ovarian and pancreatic cancers, lymphoma, and cancers of white blood cells such as multiple myeloma), the true positive rate was 67.3 percent across clinical stages I, II and III. Detection improved with each cancer stage. Across more than 50 cancer types, the corresponding true positive rates were 18 percent in stage I, 43 percent in stage II, 81 percent in stage III, and 93 percent in stage IV.
The researchers say that the targeted methylation test meets the fundamental requirements for a multi-cancer early detection blood test for population-level screening: the ability to detect multiple deadly cancer types with a single test that has a very low false positive rate, and the ability to identify where in the body the cancer is located with high accuracy.