Supplementary Table 6a: Spearman correlation values between drug sensitivity and target expression for 86 drugs common between GDSC and CTRP. Supplementary Table 6b: Correlation matrix comparing gene expression values. There are 558 cell lines and 15,934 genes common between both the datasets. Calculated 558x 558 - Correlation matrix comparing gene expression values for 15,934 genes in one cell line from GDSC compared to 15,934 genes in CTRP. Correlation method used was Spearman. Supplementary Table 6c: Spearman correlation values comparing Area under the curve (AUC) values across common cell lines in the GDSC and CTRP datasets for the 86 drugs common between them. Supplementary Table 6d: List of the cell lines where a better gene expression correlation was observed with a different cell line.
ARTICLE ABSTRACT
Cancer precision medicine aims to predict the drug likely to yield the best response for a patient. Genomic sequencing of tumors is currently being used to better inform treatment options; however, this approach has had a limited clinical impact due to the paucity of actionable mutations. An alternative to mutation status is the use of gene expression signatures to predict response. Using data from two large-scale studies, The Genomics of Drug Sensitivity of Cancer (GDSC) and The Cancer Therapeutics Response Portal (CTRP), we investigated the relationship between the sensitivity of hundreds of cell lines to hundreds of drugs, and the relative expression levels of the targets these drugs are directed against. For approximately one third of the drugs considered (73/222 in GDSC and 131/360 in CTRP), sensitivity was significantly correlated with the expression of at least one of the known targets. Surprisingly, for 8% of the annotated targets, there was a significant anticorrelation between target expression and sensitivity. For several cases, this corresponded to drugs targeting multiple genes in the same family, with the expression of one target significantly correlated with sensitivity and another significantly anticorrelated suggesting a possible role in resistance. Furthermore, we identified nontarget genes that are significantly correlated or anticorrelated with drug sensitivity, and find literature linking several to sensitization and resistance. Our analyses provide novel and important insights into both potential mechanisms of resistance and relative efficacy of drugs against the same target.
