Fig. 4: Multi Cancer Early Detection using AACS.

a AACS signature measured from N = 77 cancer patients (blue squares) or N = 20 healthy donors (grey circles), plotted in N-dimensional space. 3/5 measured AACS dimensions shown for visual clarity, selected by choosing the 3 dimensions with the highest feature importance in the ANOVA analysis presented in Supplementary Fig. 5. b Receiver Operating Characteristic (ROC) Curve examining the accuracy of ensemble subspace discriminant classifier performance on unseen validation data. Area Under the ROC Curve was 0.95. c Cross-validation approach scheme. d Average normalised SHAP values with standard errors for a linear Support Vector Machine (SVM) model trained and validated on the N = 97 datapoints using 5X cross validation. e AACS measured and plotted in N-dimensional space, with patients labelled according to tumour location: breast (pink squares), prostate (blue squares), colorectal (green squares), pancreatic (black squares), and cancer-negative controls (grey circles). f K-nearest neighbour classifier performance on a held-back, unseen validation set trained and validated using cross-validation as in panel (c) to identify tumour origin. Cancers are localised to either abdominal (colorectal, pancreatic) or hormonal (breast, prostate) origin. Abdominal cancers could be identified via abdominal CT scan, and hormonal cancers could be triangulated for further imaging or biopsy, considering patient biological sex. g AACS measured and plotted for N = 77 cancer patients (blue squares) and N = 20 cancer-negative controls (red circles), with the addition of AACS signatures for N = 20 patients with autoimmune disease (green diamond) and N = 20 patients with infection (black plus), providing controls of non-cancer heightened immune surveillance. 2/5 measured AACS dimensions shown for visual clarity and were selected using the ANOVA analysis in Supplementary Fig. 10. An Additional 3 dimensions provide required specificity, and UMAP representations are shown in Supplementary Fig. 8 and 9. h Healthy (black diamond) and pancreatic cancer (red circles) AACS, with the clinical stage of each pancreatic cancer patient shown numerically next to its data point. Patients with metastatic cancer cluster towards the healthy distribution, highlighted schematically with a shadow, whereas patients with earlier stages of cancer have signals further from the healthy distribution.