Systematic identification of genomic markers of drug sensitivity in cancer cells

Abstract

Clinical responses to anticancer therapies are often restricted to a subset of patients. In some cases, mutated cancer genes are potent biomarkers for responses to targeted agents. Here, to uncover new biomarkers of sensitivity and resistance to cancer therapeutics, we screened a panel of several hundred cancer cell lines--which represent much of the tissue-type and genetic diversity of human cancers--with 130 drugs under clinical and preclinical investigation. In aggregate, we found that mutated cancer genes were associated with cellular response to most currently available cancer drugs. Classic oncogene addiction paradigms were modified by additional tissue-specific or expression biomarkers, and some frequently mutated genes were associated with sensitivity to a broad range of therapeutic agents. Unexpected relationships were revealed, including the marked sensitivity of Ewing's sarcoma cells harbouring the EWS (also known as EWSR1)-FLI1 gene translocation to poly(ADP-ribose) polymerase (PARP) inhibitors. By linking drug activity to the functional complexity of cancer genomes, systematic pharmacogenomic profiling in cancer cell lines provides a powerful biomarker discovery platform to guide rational cancer therapeutic strategies.

Figures

Figure 1. A systematic screen in cancer cell lines identifies therapeutic biomarkers

a, The number of tumour-derived cell lines used for screening classified according to tissue type (n = 639 in total). b, The panel of 130 screening drugs classified according to their therapeutic targets, primary effector pathways, and cellular functions. A single drug may be included in multiple categories. The inset indicates the number of drugs screened against a selection of prototype cancer targets. c, A volcano plot representation of MANOVA results showing the magnitude (effect; x-axis) and significance (p-value; inverted y-axis) of all drug-gene associations. Each circle represents a single drug-gene interaction and the size is proportional to the number of mutant cell lines screened (range 1 – 334). The horizontal dashed line indicates the threshold of statistical significance (0.2 FDR, P < 0.0099). Insets I and II are magnified views of selected highly significant associations and the drug name, therapeutically relevant target(s) (in superscript), and cancer gene (in brackets) are given for each. The p-values for nilotinibABL(BCR-ABL), P = 2.54 × 10−65, and nutlin-3aMDM2(TP53), P= 2.78 × 10−37, have been capped at 1 × 10−28 in this representation.

Figure 2. Biomarkers of drug sensitivity and resistance

a, Gene-specific volcano plots of drug sensitivity associated with BRAF mutations in cancer cell lines (n = 54). b-k, Scatter plots of cell line IC50 (uM) values from selected drug-gene associations. IC50 values are on a log scale comparing mutated or non-mutated (WT) cell lines. Each circle represents the IC50 of one cell line and the red bar is the geometric mean. The drug name is indicated above each plot and therapeutic drug target(s) are bracketed.

Figure 3. Multi-feature genomic signatures of drug response

a, The top drug-feature associations identified by the EN are plotted for their frequency and effect size. Associations are colored black for expression features, red for mutations, blue for copy number, and green for tissue. b-c. Heatmaps of highly significant EN features associated with response to b, dasatinib (inhibitor of SRC,ABL) and c, 17-AAG (HSP90 inhibitor) for the 14 most sensitive (purple) and resistant (yellow) cell lines. For each cell line mutation features are at the top of the heatmap shown in black (present) or gray (absent), followed by expression features (blue corresponds to lower expression, red to higher expression). To the left of each feature is a bar indicating the absolute value of the effect size. Bars in purple are negative effects, indicating features associated with sensitivity, and bars in yellow are positive effects, indicating features associated with resistance. The natural log IC50 values are represented at the bottom. For clarity, only the top 4 features associated with sensitivity and resistance to 17-AAG are shown.

Figure 4. Ewing’s sarcoma cell lines are sensitive to PARP inhibition

a, The IC50 values of WT and EWS-FLI1 fusion positive cell lines to olaparib and AG-014699. b, Dose response curves to olaparib following 6-days constant drug exposure. Cell lines are classified according to tissue sub-type. c, Colony formation assays were performed for 7-21 days over a range of olaparib concentrations (0.1, 0.32, 1, 3.2 or 10 uM) and the concentration at which the number of colonies is reduced >90% for each cell line is indicated. d, Olaparib induced apoptosis in Ewing’s sarcoma cell lines following 72 hours treatment. e, Sensitivity to olaparib of EWS-FLI1 and FUS-CHOP transformed mouse mesenchymal cells compared to the SK-N-MC cell line (which harbors the EWS-FLI1 fusion). f, Sensitivity to olaparib of A673 cells transiently transfected with (siEF1) and without (siCT) EWS-FLI1 specific siRNA. All error bars are s.d from triplicate measurements except for b where error bars have been removed for clarity.

METHODS REFERENCES