Fig. 5: Predictive value of pangenomic markers derived from WGS data. | Nature Medicine

Fig. 5: Predictive value of pangenomic markers derived from WGS data.

From: Insights for precision oncology from the integration of genomic and clinical data of 13,880 tumors from the 100,000 Genomes Cancer Programme

Fig. 5

a, Distribution of TMB and mutational signatures across six tumor types. (Samples that underwent PCR amplification during library preparation were excluded and the dataset for each tumor type was downsampled to 100 samples.) The horizontal red bar indicates the median TMB for each cancer type. Etiology definitions based on COSMIC (v.3) single-base substitution signatures: APOBEC activity, signatures 2 and 13; aging, signature 1; HRD, signature 3; MMR deficiency, signatures 6, 15, 20, 21, 26 and 44; POLE mutations, signatures 10a, 10b and 14; smoking, signatures 4 and 92; ultraviolet exposure, signatures 7a–d. Only signatures with more than 20% contribution are shown. Homologous recombination status is indicated in the bars below the signature plots. b,c, Kaplan–Meier estimates of overall survival with P values calculated using a stratified log-rank test. The numbers of patients at risk at different time points are indicated below the survival curves. The points and error bars on the embedded forest plots indicate the hazard ratios (HRs) with 95% confidence intervals (CIs), correspondingly. HRs, CIs and P values were calculated from Cox proportional-hazards models corrected according to cancer stage. Patients were stratified according to HRD status in cancers treated with platinum chemotherapy (n = 1,737, left, b); according to MMR signatures in cancers treated with immunotherapies (n = 764, right, b); according to high and low TMB in skin cutaneous melanoma (n = 98, left, c); and according to lung adenocarcinoma (n = 162, right, c). Exact P values can be found in Supplementary Table 2.

Back to article page