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Identification of Mediators of T-cell Receptor Signaling via the Screening of Chemical Inhibitor Libraries
Published on: January 22, 2019
Caspase-8 activation by TRAIL monotherapy predicts responses to IAPi and TRAIL combination treatment in breast cancer
R Polanski1, J Vincent1, U M Polanska1
1AstraZeneca, Oncology Bioscience iMed, Alderley Park, Macclesfield, UK.
Abstract:
The discovery of cancer cell-selective tumour necrosis factor-related apoptosis inducing ligand (TRAIL)-induced apoptosis generated broad excitement and development of TRAIL receptor agonists (TRA) as potential cancer therapy. Studies demonstrating the synergistic combination effect of SMAC mimetics and TRA further suggested potentially effective treatment in multiple tumour settings. However, predictive biomarkers allowing identification of patients that could respond to treatment are lacking. Here, we described a high throughput combination screen conducted across a panel of 31 breast cancer cell lines in which we observed highly synergistic activity between TRAIL and the inhibitors of apoptosis proteins (IAP) inhibitor (IAPi) AZD5582 in ~30% of cell lines. We detected no difference in the expression levels of the IAPi or TRAIL-targeted proteins or common modulators of the apoptotic pathway between the sensitive and resistant cell lines. Synergistic combination effect of AZD5582 and TRAIL correlated with sensitivity to TRAIL, but not to AZD5582 as a single agent. TRAIL treatment led to significantly greater activity of Caspase-8 in sensitive than in resistant cell lines (P=0.002). The majority (12/14) of AZD5582+TRAIL-resistant cell lines retained a functional cell death pathway, as they were sensitive to AZD5582+TNFα combination treatment. This suggested that failure of the TRAIL receptor complex to transduce the death signal to Caspase-8 underlies AZD5582+TRAIL resistance. We developed a 3D spheroid assay and demonstrated its suitability for the ex vivo analysis of the Caspase-8 activity as a predictive biomarker. Altogether, our study demonstrated a link between the functionality of the TRAIL receptor pathway and the synergistic activity of the IAPi+TRA combination treatment. It also provided a rationale for development of the Caspase-8 activity assay as a functional predictive biomarker that could allow better prediction of the response to IAPi+TRA-based therapies than the analysis of expression levels of protein biomarkers.
Insights
Predictive biomarkers are needed for cancer therapies combining TRAIL receptor agonists (TRA) and IAP inhibitors (IAPi). This study found Caspase-8 activity predicts response to AZD5582+TRAIL, suggesting a functional assay for patient selection.
Area of Science:
- Oncology
- Molecular Biology
- Drug Discovery
Background:
- Tumour necrosis factor-related apoptosis inducing ligand (TRAIL) and SMAC mimetics show promise in cancer therapy.
- Predictive biomarkers for combination therapies involving TRAIL receptor agonists (TRA) and inhibitors of apoptosis proteins (IAP) inhibitors (IAPi) are lacking.
Purpose of the Study:
- To identify predictive biomarkers for the synergistic combination of TRAIL and the IAPi AZD5582 in breast cancer.
- To investigate the mechanisms of resistance to this combination therapy.
Main Methods:
- High-throughput screening of 31 breast cancer cell lines for synergy between TRAIL and AZD5582.
- Analysis of protein expression levels and functional assays including Caspase-8 activity.
- Development and validation of a 3D spheroid assay for ex vivo biomarker analysis.
Main Results:
- Approximately 30% of cell lines exhibited synergistic activity with AZD5582 and TRAIL.
- Resistance to the combination was linked to impaired Caspase-8 activation downstream of the TRAIL receptor, not protein expression levels.
- A 3D spheroid assay effectively measured Caspase-8 activity as a predictive biomarker.
Conclusions:
- The functionality of the TRAIL receptor pathway, specifically Caspase-8 activation, is critical for predicting response to IAPi+TRA combination therapy.
- Caspase-8 activity assays offer a superior predictive biomarker approach compared to protein expression analysis for patient stratification.
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