Fig. 3. Growth patterns and growth associations using 993 linear tumors.

Across 993 linear tumors from PCAWG consortium we expect an under-selection mutation to be associated with periods of positive growth. We compared several mutation types (driver mutation, mutation within geneX, within GO categoryX), to a random distribution from their respective sample for association with positive growth. a, b The averaged growth progression, mutational growth, and mutational effect, for a single low-coverage CNS-oligo tumor and a single low-coverage thyroid adenocarcinoma tumor without any PCAWG-identified drivers. Green asterisks denote the ordered position of a PCAWG-predicted driver within the sample. Yellow asterisks denote a growth peak and putative driver presence. In c, we derived three main growth patterns (steady growth, sigmoid growth, and stagnation/shrinkage) for 993 linear tumors, as they were grouped using a k-means clustering algorithm. Various cancer types showed specific enrichment or depletion for the three clusters (levels of significance for Fisher’s tests for enrichment noted as *, **, and *** for p < 0.05, 0.01, and 0.001). In d, PCAWG drivers and Vogelstein genes show significant positive growth enrichment compared to a list of random highly mutated genes. Boxplots represent 2 × σ deviation, lines represent the mean, while violin plots are trimmed to data range. e We show the GO enrichment for the 20 most affected biological processes, when we use 293 genes, significantly associated with periods of positive growth.