Cross-platform pathway-based analysis identifies markers of response to the PARP inhibitor olaparib

Abstract

Poly(ADP-ribose) polymerase (PARP) is an enzyme involved in DNA repair. PARP inhibitors can act as chemosensitizers, or operate on the principle of synthetic lethality when used as single agent. Clinical trials have shown drugs in this class to be promising for BRCA mutation carriers. We postulated that inability to demonstrate response in non-BRCA carriers in which BRCA is inactivated by other mechanisms or with deficiency in homologous recombination for DNA repair is due to lack of molecular markers that define a responding subpopulation. We identified candidate markers for this purpose for olaparib (AstraZeneca) by measuring inhibitory effects of nine concentrations of olaparib in 22 breast cancer cell lines and identifying features in transcriptional and genome copy number profiles that were significantly correlated with response. We emphasized in this discovery process genes involved in DNA repair. We found that the cell lines that were sensitive to olaparib had a significant lower copy number of BRCA1 compared to the resistant cell lines (p value 0.012). In addition, we discovered seven genes from DNA repair pathways whose transcriptional levels were associated with response. These included five genes (BRCA1, MRE11A, NBS1, TDG, and XPA) whose transcript levels were associated with resistance and two genes (CHEK2 and MK2) whose transcript levels were associated with sensitivity. We developed an algorithm to predict response using the seven-gene transcription levels and applied it to 1,846 invasive breast cancer samples from 8 U133A/plus 2 (Affymetrix) data sets and found that 8-21 % of patients would be predicted to be responsive to olaparib. A similar response frequency was predicted in 536 samples analyzed on an Agilent platform. Importantly, tumors predicted to respond were enriched in basal subtype tumors. Our studies support clinical evaluation of the utility of our seven-gene signature as a predictor of response to olaparib.

Fig. 1

Approach for the development of a predictor of olaparib response in a breast cancer cell line panel with inclusion of prior knowledge of DNA repair pathways. For 22 breast cancer cell lines, growth inhibition assays were used to measure their sensitivity to olaparib, expressed as the surviving fraction at 50 % (SF50). For these cell lines, expression data were obtained with three different platforms (Affymetrix U133A, Affymetrix Exon 1.0 ST, and whole transcriptome shotgun sequencing). The bottom-up approach was used for biomarker selection, incorporating prior knowledge of the principal DNA repair pathways BER, NER, MMR, HR/FA, NHEJ, and DDR. Biomarkers from [31] were systematically expanded with genes assigned to any of these pathways in the KEGG database, resulting in 118 genes. For each DNA repair pathway and expression data set the most important markers were obtained with LR in combination with forward feature selection, followed by reduction to those selected with consistent pattern of sensitivity for all three platforms

Fig. 2

Waterfall plot of the response to olaparib (expressed as SF50 in µM) for 22 breast cancer cell lines, ordered from most resistant at the left to most sensitive at the right, with bars colored according to subtype (luminal in light grey, basal in black, claudin-low in dark grey, and ERBB2 amplified in white). The threshold of 1 µM used to divide the cell lines into a group of 15 resistant cell lines (indicated with R) and a group of 7 sensitive cell lines (indicated with S) is represented with a horizontal dashed line

Fig. 3

Boxplot of SF50 for the cell lines divided according to breast cancer subtype (9 luminal, 7 claudin-low, and 6 basal lines). No association was found between breast cancer subtype and response to olaparib in the cell line panel (Fisher’s exact test for basal vs. luminal, p value 0.136)

Fig. 4

Overview of individual DNA repair-associated markers that are significantly associated with or do trend towards an association with response to olaparib in the 22 breast cancer cell lines, based on mutation, copy number, and expression data (see Supplementary Table 1 for the complete list of markers). The four boxplots at the top show the association results for BRCA1. The BRCA1-mutated cell lines MDAMB436 and SUM149PT tend to be more sensitive to olaparib compared to the wild-type cell lines (p value 0.091). The sensitive cell lines are also characterized by a significant lower copy number of BRCA1 (p value 0.012) and by BRCA1 down-regulation (RNA-seq, p value 0.055). Cell lines with a deficiency in BRCA1 and/or PTEN tend to be more sensitive to olaparib than cell lines with functional BRCA1 and PTEN (p value 0.052). The boxplots at the bottom show the association for genes NBS1 and XRCC5 that are significantly down-regulated and for genes CHEK2 and MK2 that are significantly up-regulated in the sensitive compared to the resistant cell lines