Fig. 3: Cancer detection in stage IV colorectal cancer (CRC). | Nature Communications

Fig. 3: Cancer detection in stage IV colorectal cancer (CRC).

From: Genome-wide mutational signatures in low-coverage whole genome sequencing of cell-free DNA

Fig. 3

a SNP-subtracted mutation profiles from 0.3Ɨ WGS of plasma from healthy individuals (n = 19) and patients with stage IV CRC (n = 16) were used as input for Principal Component Analysis (PCA). Healthy and cancer samples are shown in red and blue, respectively. PC principal component. b PC1 and PC2 were correlated against ctDNA fraction determined by ichorCNA. Both PCs showed significant correlation (PC1, p = 0.0043; PC2, p = 0.0076, two-sided Pearson correlation). Healthy and cancer samples are shown in red and blue, respectively. The gray shaded area indicates the 95% confidence interval of the fitted linear model. c The signature contributions to PC1 and PC2 were assessed by fitting signatures to the SBS profile of each PC. Signature contributions to each PC are shown as proportions. SBSnĀ“ indicates SNP-subtracted mutation data fitted to SBSn, where n is an integer. PC1 is shown in red, PC2 is shown in blue. d In samples from healthy individuals (n = 19) and patients with stage IV CRC (n = 16), SBS1 contribution was significantly correlated with SBS8Ā“ (p = 5.6 Ɨ 10āˆ’5, two-sided Pearson correlation). Healthy and cancer samples are shown in red and blue, respectively. The gray shaded area indicates the 95% confidence interval of the fitted linear model. e A random forest model was used to classify cancer samples (n = 16) vs. healthy (n = 19) using SNP-subtracted mutation profiles. Ten-fold nested cross-validation repeated 500 times was used. Each iteration is shown.Ā A Receiver Operating Characteristic curve is shown (AUC 0.99, 95% CI 0.95–1.00). Source data are provided as a Source data file. AUC area under the curve, CV cross-validation.

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