Extended Data Fig. 3: Biclusters of patients based on similar changes (δ) in somatic alteration.

Biclustering of four δ matrices, reflecting changes in CCF of mutations or copy number in known cancer genes or genesets, yielded significant biclusters (all empirical P values < 0.0001; Methods). The biclusters from all four δ matrices included at least one bicluster with patient TPS130 (a patient with an unknown mechanism of resistance). Patient TPS130 consistently biclustered together with TPS021 and TPS037 (patients with known mechanisms of resistance) across all matrices, highlighting the possibility that additional genomic alterations contribute to resistance beyond the identified resistance alterations. a, The change in somatic alterations, δ, was calculated based on WES data of the samples closest to the start and end of therapy. We biclustered four δ matrices (\(\delta _{{\rm{cancer}}\;{\rm{gene}}}^{{\rm{copy}}\,{\rm{number}}}\), \(\delta _{{\rm{geneset}}}^{{\rm{mutation}}}\), \(\delta _{{\rm{geneset}}}^{{\rm{copy}}\,{\rm{number}}}\) and \(\delta _{{\rm{geneset}}}^{{\rm{copy}}\,{\rm{number}}\;{\rm{and}}\;{\rm{mutation}}}\)) and assessed their significance by comparing the size of biclusters against n = 10,000 permuted matrices with a two-sided t-test (Methods). b–e, Illustration of the biclustering results (using BiMax) of the four δ matrices (biclusters are listed in Supplementary Table 6). Outlined in red are biclusters containing TPS130 observed in all four δ matrices.