Adaptive responses in a PARP inhibitor window of opportunity trial illustrate limited functional interlesional heterogeneity and potential combination therapy options

Abstract

Poly (ADP-ribose) polymerase inhibitor (PARPi)-based combination therapies are demonstrating efficacy in patients, however, identifying the right combination for the right patient remains a critical challenge. Thus, it is urgent to develop approaches able to identify patients likely to benefit from specific combination therapies. Several groups, including ours, have demonstrated that targeting adaptive responses induced by PARPi increases depth and duration of response. In this study, we instituted a talazoparib (PARPi) monotherapy window of opportunity trial to identify informative adaptive responses in high grade serous ovarian cancer patients (HGSOC). Patients were treated for 7 to 14 days with PARPi monotherapy prior to surgery with tissue samples from multiple sites being collected pre- and post-treatment in each patient. Analysis of these samples demonstrated that individual patients displayed different adaptive responses with limited interlesional heterogeneity. Ability of combination therapies designed to interdict adaptive responses to decrease viability was validated using model systems. Thus, assessment of adaptive responses to PARPi provides an opportunity for patient-specific selection of combination therapies designed to interdict patient-specific adaptive responses to maximize patient benefit.

Keywords: adaptive response; combination therapy; ovarian cancer; poly (ADP-ribose) polymerase inhibitor; targeted therapy.

Figure 1. HGSOC response to PARP inhibitor.

Patients were treated for 7 to 14 days with talazoparib. Blood and tumor samples were collected before and after treatment. (A) Plasma CA125 concentration was measured before and after treatment as well as after tumor reductive surgery. (B) PARP enzymatic activity was assessed in all pre- and post-treatment tumor samples by measuring the level of PARylation using RPPA analysis. (C) Heat map representing the unsupervised clustering of protein samples analyzed by RPPA. Red and blue colors represent higher and lower expression, respectively.

Figure 2. Patient-specific adaptive response to PARP inhibitor.

(A) The heat map represents unsupervised clustering of post-treatment samples normalized with the average of pre-treatment samples from that patient. Proteins were rank ordered according to the ratio of expression across patients. Samples P3-P5 are from patient 1, P8-P10 from patient 2 and P14-P16 from patient 3. (B) Pathway activity was assessed using pathway scores. The histogram represents the change of each post-treatment sample compared to the average of pre-treatment samples. (C) Histograms representing the change of protein expression (Z-score) in each post-treatment samples compared to the average of pre-treatment samples. Samples P3-P5 are from patient 1, P8-P10 from patient 2 and P14-P16 from patient 3.

Figure 3. Adaptive response of ovarian cancer cell lines treated with PARP inhibitor.

(A) Viability of cell lines treated with increasing concentration of talazoparib for 6 days. Viability was measured using Prestoblue assay. (B) IC50 was measured and cells were treated for 72 hours with or without IC50 doses of talazoparib determined experimentally for each line. PARP enzymatic activity was assessed by measuring the level of PARylation using RPPA analysis. (C) The heat map represents unsupervised clustering of post-treatment samples normalized with pre-treatment samples and rank sum ordering of the protein expression. The red and blue colors represent upregulated and downregulated proteins, respectively. (D) Pathway activity was assessed using pathway scores. The histogram represents the change of each treated sample compared to control. (E) Histograms representing the change of protein expression (Z-score) in each PARPi treated cell lines compared to untreated.

Figure 4. Synergism between PARP and DNA damage checkpoint inhibitors.

(A) Cancer cell lines were treated with or without talazoparib, AZD6738/AZD1775 and their combination for 6 days. Viability was measured using Prestoblue assay. (B) 3D cell viability assay of OVCAR8 and HEYA8 treated with or without talazoparib, AZD6738 or their combination for 7 days. (C) After 7 days of treatment, drugs were washed out and cells were allowed to grow for an additional 7 days before a Prestoblue viability assay. CI: Chou-Talalay combination index. CI = 1 represents additivity, CI < 1 indicates synergism and CI > 1 indicates antagonism. A CI < 0.4 indicates a strong synergism.