Figure S5_2 from Integrative Kinome Profiling Identifies mTORC1/2 Inhibition as Treatment Strategy in Ovarian Clear Cell Carcinoma

Supplementary Figure 5 | Clustering (n=106) and survival analysis (n=70) on kinome mutations and CNA. (A) Disease-specific survival of patients (n=70) grouped on ARID1A status, (B) PIK3CA status and (C) ARID1A + PIK3CA status. (D) Consensus clustering, with maximum group count set to 10 and clustering optimization with 1000 repetitions maximum, shows adding of tumors (n=106) as consensus index (horizontally) and empirical cumulative distribution (vertically) for 1-10 clusters. (E) Area under the curve plot of decrease in friction from 1-10 clusters. (F) Heatmap distribution of tumors in 8 clusters. (G) Disease-specific survival of patients (n=70) in 8 clusters, (H) cluster 3 vs. other clusters. (I) Disease-specific survival in advanced stage OCCC patients (FIGO 2C-4), Log rank (Mantel-Cox) was used for statistical analysis. (J) Nonsynonymous mutation distribution in genes involved in the frequently mutated PI3K/AKT/mTOR (blue) and MAPK pathway (yellow), ERBB family of receptor tyrosine kinases (green) and DNA repair pathway (red) as well as ARID1A and PALB2 are shown with OncoPrint. CNA in each mutated gene are added. The 106 OCCC tumors that were both kinome sequenced and SNP arrayed are shown on the horizontal axis grouped on tumor clusters and ordered on total event frequency in the subsequently altered pathways. (K) Oncoprint from advanced stage patients in cluster 3 vs. other clusters, shown on the horizontal axis grouped on tumor clusters and ordered on total event frequency in the subsequent altered pathways, ordered as aforementioned.