Identification of a Molecularly-Defined Subset of Breast and Ovarian Cancer Models that Respond to WEE1 or ATR Inhibition, Overcoming PARP Inhibitor Resistance

Abstract

Purpose: PARP inhibitors (PARPi) induce synthetic lethality in homologous recombination repair (HRR)-deficient tumors and are used to treat breast, ovarian, pancreatic, and prostate cancers. Multiple PARPi resistance mechanisms exist, most resulting in restoration of HRR and protection of stalled replication forks. ATR inhibition was highlighted as a unique approach to reverse both aspects of resistance. Recently, however, a PARPi/WEE1 inhibitor (WEE1i) combination demonstrated enhanced antitumor activity associated with the induction of replication stress, suggesting another approach to tackling PARPi resistance.

Experimental design: We analyzed breast and ovarian patient-derived xenoimplant models resistant to PARPi to quantify WEE1i and ATR inhibitor (ATRi) responses as single agents and in combination with PARPi. Biomarker analysis was conducted at the genetic and protein level. Metabolite analysis by mass spectrometry and nucleoside rescue experiments ex vivo were also conducted in patient-derived models.

Results: Although WEE1i response was linked to markers of replication stress, including STK11/RB1 and phospho-RPA, ATRi response associated with ATM mutation. When combined with olaparib, WEE1i could be differentiated from the ATRi/olaparib combination, providing distinct therapeutic strategies to overcome PARPi resistance by targeting the replication stress response. Mechanistically, WEE1i sensitivity was associated with shortage of the dNTP pool and a concomitant increase in replication stress.

Conclusions: Targeting the replication stress response is a valid therapeutic option to overcome PARPi resistance including tumors without an underlying HRR deficiency. These preclinical insights are now being tested in several clinical trials where the PARPi is administered with either the WEE1i or the ATRi.

Figure 1.

Screening of patient-derived tumor xenografts identifies a subset of WEE1- inhibitor intrinsically sensitive tumors. A, Waterfall plot showing the best response to AZD1775, plotted as the percentage of tumor volume change compared with the tumor volume on day 1 after at least approximately 21 days of treatment using the 120 mg/kg schedule summarized in Supplementary Table S2 (n = 29). +20% and −30% are marked by dashed lines to indicate the range of PR, SD, and PD. Bars represent means of an average of six individual tumors and error bars represent SEM. B, Time response to AZD1775 for the PDX models shown in A. The percentage of tumor volume change during AZD1775 treatment is plotted. Shades of blue are used to label PDX models with PD, SD, PR, or CR response to the treatment.

Figure 2.

Response biomarkers to AZD1775. A, Summary of selected DDR genetic alterations (see Materials and Methods, for the complete gene list) identified by exome sequencing in the PDX cohort from Fig. 1A. Sensitivity (CR+PR) or resistance (SD+PD) to AZD1775 is indicated, as well as the cancer subtype. The frequency of each mutation within the PDX cohort and the P value for the association of each alteration with AZD1775 response is shown. Different colors indicate the specific type of mutation. B, Forest plot and odds ratio analysis of the response to AZD1775 according to the IHC/genetic markers LKB1, pRb/RB1 and PTEN (n = 28). mut, mutant; null, no expression by IHC. C, Sensitivity to AZD1775 of MCF10A p53^−/− Rb^−/− cells upon LKB1 knockdown using two independent siRNAs separately and pooled. Bars indicate the AUC relative to the control siRNA (siCON). Error bars indicate SD of three independent experiments. P values are shown. D, Metabolite data annotation to KEGG metabolic pathways for PDX098 and PDX060 (AZD1775 sensitive), compared with PDX102 (AZD1775 resistant). Nodes represent metabolic pathways and the depicted color indicates the number of significant changes following treatment with AZD1775 for 8 or 24 hours compared with vehicle [|log₂(fold change)|>0.5, P value < 0.05]. E, REVEALER analysis for AZD1775 antitumor response in the PDX cohort. The nonlinear information coefficient (IC) and conditional information coefficient (CIC) values are provided.

Figure 3.

WEE1 inhibition results in activation of CDK2 and subsequent DNA damage and replication stress response in breast cancer cell lines. A, Immunoblot analysis showing CDK2 and CDK1 activation 24 hours after treatment with different doses of AZD1775 in MDA-MB-231 and MDA-MB436 cells. To assess CDK2 tyrosine phosphorylation (pY15) level, total CDK2 was first immunoprecipitated (IP) and the bound fraction were eluted and analyzed. IP, immunoprecipitation; WCL, whole cell lysate. B, Immunoblot analysis of TNBC cell lines treated with DMSO (U) or AZD1775 0.5 μmol/L during different time periods. Biomarkers of target engagement, DNA damage response (DDR) and replication stress response (RSR) or mitosis were analyzed. C, Immunoblot analysis of target engagement and DDR biomarker in MDA-MB-231 cells treated with DMSO (−) or 0.5 μmol/L AZD1775 for 6 hours in the presence (+) or absence (−) of diluted EmbryoMax nucleoside solution. D, Immunoblot analysis of MDA-MB-231 cells from S-phase culture synchronized by double thymidine block treated with DMSO (−) or AZD1775 0.5 μmol/L in the presence (+) or absence (−) of RO-3306 (CDK1 inhibitor, CDK1i) or CVT-313 (CDK2 inhibitor, CDK2i). Protein samples were collected at indicated time points and the indicated biomarkers were analyzed.

Figure 4.

Shortage of dNTP induces sensitivity to AZD1775 in PDXs. A, Bright field images and quantification of the organoid area from PDCs treated for 72 hours with DMSO or 1 μmol/L AZD1775, in the presence (+) or absence (−) of nucleosides (Embryomax, 1:12.5 dilution). B, Immunoblot analysis of DDR and RSR biomarkers in two AZD1775-sensitive models, PDC098 and PDC236, treated with 1 μmol/L AZD1775 in the presence (+) or absence (−) of nucleosides at the indicated dilution for 6 hours. C, Representative immunofluorescence images of two AZD1775-sensitive PDX models (PDX098 and PDX236) and quantification of the percentage of cells exhibiting pan-nuclear γH2AX staining in seven AZD1775-sensitive and 19 AZD1775-resistant PDXs. D, Representative immunofluorescence images of two AZD1775-sensitive PDX models (PDX098 and PDX236) and quantification of the percentage of cells in S–G2-phase (geminin-positive) with pRPA nuclear foci in seven AZD1775-sensitive and 19 AZD1775-resistant PDXs. Each dot represents the mean of at least two independent tumors per PDX model. All pictures were taken at 600× magnification. E and F, show quantifications of pan-nuclear γH2AX staining and pRPA nuclear foci in four models with acquired resistance to AZD1775.

Figure 5.

WEE1 inhibition sensitizes PARPi-resistant tumors. A, Waterfall plots showing the best response to the indicated drugs as percentage of tumor volume change after at least 21 days of treatment, compared with the tumor volumes on day 1 (n = 29). +20% and −30% are marked by dashed lines to indicate the range of PR, SD, and PD. Bars represent means and error bars SEM. B, Radar plot comparatively showing the percentage of tumor volume change upon treatment with AZD1775, olaparib, and the combination as in Figs. 1A and 5A. C, Relative tumor volume during treatment with vehicle, AZD1775, olaparib, or combination in PDX252. D, Comparative analysis of the antitumor activity of AZD1775 plus olaparib versus cisplatin (n = 32). AZD1775 was administered at 120 mg/kg (5 days on / 9 days off) or at 60 mg/kg (5 days on / 2 days off, **). When both doses were tested in the same model, we observed that: *, the model exhibited a reduction of antitumor response when treated with the low dose of AZD1775, compared with the high dose, or #, the model exhibited the same antitumor response upon treatment with the low dose of AZD1775, compared with the high dose. E, REVEALER analysis for AZD1775 plus olaparib antitumor response in the PDX cohort. The nonlinear information coefficient (IC) and conditional information coefficient (CIC) values are provided. F, Quantification of cells with pan-nuclear γH2AX staining (top) and cells in S–G₂-phase of the cell cycle (geminin positive) with pRPA nuclear foci (bottom) following treatment with vehicle, olaparib, AZD1775, or the combination (Olap+1775) in PDXs showing (n = 5) or not (n = 10) antitumor response upon combination (Combo) treatment. Each dot represents the mean of at least two independent tumors per PDX model. P values, Tukey multiple comparison test.

Figure 6.

ATR inhibition sensitizes PARPi-resistant tumors. A, Waterfall plots showing the best response to the indicated drugs as percentage of tumor volume change after at least 21 days of treatment, compared with the tumor volumes on day 1 (n = 31). +20% and −30% are marked by dashed lines to indicate the range of PR, SD, and PD. Bars represent means and error bars SEM. B, Summary of selected DDR genetic alterations identified by exome sequencing in the PDX cohort from A. Sensitivity (tumor regression) or resistance (tumor progression) to AZD6738 is indicated, as well as the cancer subtype. The frequency of each mutation within the PDX cohort and the P value for the association of each alteration with AZD6738 response is shown. *, To perform this statistical analysis and given the low number of CR/PR AZD6738 responders, the two models that exhibited SD with AZD6738 were also considered responders. Different colors indicate the specific type of mutation. C, Comparative analysis of the antitumor activity of olaparib plus AZD1775 versus olaparib plus AZD6738 (n = 31). AZD1775 was administered at 120 mg/kg (5 days on / 9 days off) or at 60 mg/kg (5 days on / 2 days off, **). When both doses were tested in the same model, we observed that: *, the model exhibited a reduction of antitumor response when treated with the low dose of AZD1775, compared with the high dose, or #, the model exhibited the same antitumor response upon treatment with the low dose of AZD1775, compared with the high dose. D, REVEALER analysis for AZD6738 plus olaparib antitumor response in the PDX cohort. The nonlinear information coefficient (IC) and conditional information coefficient (CIC) values are provided. E, Expression levels of the indicated proteins by immunoblot. Each dot represents individual tumors. Bars represent means and error bars SEM. P values, Tukey multiple comparison test.