Predicting and affecting response to cancer therapy based on pathway-level biomarkers

摘要

Euclidean distance (ED) distribution of genes and pathways calculated from microarray data from two different institutions (CCLE and GDSC) across 438 cell lines. Blue line: ED distribution between the pathways in the two datasets; red line: ED distribution between the genes. values were generated using Mann–Whitney -test. ED distribution of genes and pathways between RNA-seq and microarray data across 294 ovarian cancer patients. Blue line: ED between the pathways; red line: ED between the genes. -values were generated using Mann–Whitney -test. tSNE plot of the gene-expression levels in three tumor types and their adjacent normal tissue. Samples are colored by tissue type and state (tumorormal). tSNE plot of the pathway activity levels in three tumor types and their adjacent normal tissue. Samples are colored by tissue type and state (tumorormal). Workflow pipeline depicting the data flow from the (i) Input data to (ii) the drug-based Classification step to (iii) the final Results output. The quantile–quantile (QQ) plots are colored by tissue type. See also Supplementary Figs.  – .