Fig. 6

Comparison of somatic genomic and transcriptomic profiles between JAX PDX resource and TCGA tumor cohorts. a Distribution of mutational load of non-silent coding somatic mutations for genes on the CTP panel based on exome sequence data for TCGA samples and CTP panel-based sequence data for JAX PDX models (all filters included). (LUAD: lung adenocarcinoma, LUSC: lung squamous cell carcinoma, COADREAD: colorectal adenocarcinoma, Colorectal: colon and rectal cancer, TNBC: triple-negative breast cancer, BLCA: urothelial bladder carcinoma, BLCA invasive: muscle invasive bladder cancer, SKCM: skin cutaneous melanoma, GBM: glioblastoma multiforme). b Overlap of CTP panel genes that have non-silent coding somatic mutations with > 5% mutation frequency in TCGA data with genes that have at least one non-silent coding somatic mutation in PDX CTP data (all filters and rescue of clinically relevant variants included) for each tumor type. Fisher’s exact test (Additional file 1: Table S9) was used to compute the significance of the overlap. c Hierarchical clustering of z-score of expression (log₂(TPM + 1)) of top 1000 most varying genes of TCGA RNA-Seq samples across different tumor types. The same set of genes (omitting non-expressed genes) was used as input for unsupervised hierarchical clustering of PDX models for all tumor types represented in the JAX resource. Gene sets identified as having high expression in specific tumor types had significant overlap between TCGA and PDX samples. d Correlation between PDX models and TCGA samples of over-expressed (z-score of log₂(TPM + 1) > 1, green) or under-expressed (z-score of log₂(TPM + 1) < − 1, orange) genes across multiple tumor types. e Correlation between PDX and TCGA tumors for the frequency of copy number gain (red) or loss (blue) of selected genes frequently amplified or deleted in TCGA tumors as predicted by GISTIC