Multi-cancer early detection with a spectroscopic liquid biopsy platform

A rapid, low-cost, sensitive, multi-cancer early detection (MCED) test would be transformational in the diagnostics field. Earlier cancer detection can increase survival rates and quality of life of patients. An effective test must accurately identify the small proportion of patients with typically non-specific symptoms who have cancer. Such symptoms do not easily segregate by organ system, necessitating a multi-cancer approach. In this large-scale study (n = 2094 patients) we applied the Dxcover® Cancer Liquid Biopsy to differentiate cancer against non-cancer patients, as well as organ specific tests to identify cancers of the brain, breast, colorectal, kidney, lung, ovary, pancreas, and prostate. The test uses Fourier transform infrared (FTIR) spectroscopy to analyze all macromolecules in a minute volume of patient serum, and machine learning algorithms to build a classifier of the resultant spectral profiles to detect cancer. This approach can be fine-tuned to maximize either sensitivity or specificity depending on the requirements from different healthcare systems and cancer diagnostic pathways. The cancer v asymptomatic non-cancer classification detected 64% of stage I cancers when specificity was 99% (overall sensitivity 56%). When tuned for higher sensitivity, this model identified 99% of stage I cancers (while specificity was 58%). When examining cancer against all non-cancer (including symptomatic patients), the sensitivity-tuned model enabled 90% sensitivity with 61% specificity, with detection rates of 93% for stage I, 84% for stage II, 92% for stage III and 95% for stage IV. For organ specific cancer classifiers, area under the receiver operating characteristic (ROC) curve values were calculated for all cancers: brain (0.90), breast (0.75), colorectal (0.91), kidney (0.91), lung (0.91), ovarian (0.86), pancreatic (0.85) and prostate (0.86). Cancer treatment is more effective when given earlier and this low-cost strategy can facilitate the requisite earlier diagnosis.