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Fig. 5 | Genome Medicine

Fig. 5

From: Modeling clonal structure over narrow time frames via circulating tumor DNA in metastatic breast cancer

Fig. 5

Whole exome sequencing uncovers driver mutations and allows neoantigen prediction. Whole exome sequencing results from 31 total samples with tumor fraction ≥10% using short variant and INDEL calling tools from gatk-Mutect2 pipelines (McKenna et al., 2010), with subsequent neoantigen binding predictions for known MHC molecules from NetMHCpan 4.0 (Reynisson et al., 2020). a Driver mutations found via whole exome sequencing across time points. Variant data visualized are those whose genes have been previously annotated in literature as breast cancer drivers or pan cancer drivers. b Trends in predicted neoantigens among cohort members. Strong binders are denoted as those peptide sequences with NetMHCpan ranks <0.5%, and weak binders are those with ranks <2%. Neoantigen Generating sSNV are alterations whose changes to peptide structure are predicted to produce neoantigens capable of strong or weak binding to known MHC molecules. c, d Neoantigen dynamics from patient RP-527 and RP-535, showing proportions of detected neoantigens and dropout over time. Strong, weak, and ND labels correspond to binding affinity of predicted neoantigens, as well as a non-detected category to capture dropout. Threads are colored by their state at the final sequencing time point

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