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Updated: Jul 26, 2025
Monitoring PD-1-Blocking Antibodies Bound to T Cells Derived from a Drop of Peripheral Blood
Published on: February 5, 2020
Development and Validation of Blood-Based Predictive Biomarkers for Response to PD-1/PD-L1 Checkpoint Inhibitors:
Ewan Hunter1, Matthew Salter1, Ryan Powell1
1Oxford BioDynamics Plc., Oxford OX4 2WB, UK.
Background:
Unprecedented advantages in cancer treatment with immune checkpoint inhibitors (ICIs) remain limited to only a subset of patients. Systemic analyses of the regulatory 3D genome architecture linked to individual epigenetic and immunogenetic controls associated with tumour immune evasion mechanisms and immune checkpoint pathways reveal a highly prevalent molecular profile predictive of response to PD-1/PD-L1 ICIs. A clinical blood test based on a set of eight (8) 3D genomic biomarkers has been developed and validated on the basis of an observational trial to predict response to ICI therapy.
Methods:
The predictive eight biomarker set is derived from prospective observational clinical trials, representing 280 treatments with Pembrolizumab, Atezolizumab, Durvalumab, Nivolumab, and Avelumab in a broad range of indications: melanoma, lung, hepatocellular, renal, breast, bladder, colon, head and neck, bone, brain, lymphoma, prostate, vulvar, and cervical cancers.
Results:
The 3D genomic eight biomarker panel for response to immune checkpoint therapy achieved a high accuracy of 85%, sensitivity of 93%, and specificity of 82%.
Conclusions:
This study demonstrates that a 3D genomic approach can be used to develop a predictive clinical assay for response to PD-1/PD-L1 checkpoint inhibition in cancer patients.
Insights
A new blood test using eight 3D genomic biomarkers accurately predicts response to immune checkpoint inhibitors (ICIs) in cancer patients. This 3D genomic approach offers a promising tool for personalized cancer therapy selection.
Area of Science:
- Oncology
- Genomics
- Immunotherapy
Background:
- Immune checkpoint inhibitors (ICIs) offer significant cancer treatment benefits but benefit only a subset of patients.
- Tumor immune evasion and checkpoint pathways are influenced by 3D genome architecture, epigenetics, and immunogenetics.
- A specific molecular profile predicts response to PD-1/PD-L1 ICIs.
Purpose of the Study:
- To develop and validate a clinical blood test for predicting response to ICI therapy.
- To identify a set of 3D genomic biomarkers associated with ICI treatment efficacy.
Main Methods:
- A predictive panel of eight (8) 3D genomic biomarkers was identified.
- The biomarker set was derived from prospective observational clinical trials.
- The study included 280 treatments across various cancers and multiple ICIs (Pembrolizumab, Atezolizumab, Durvalumab, Nivolumab, Avelumab).
Main Results:
- The 3D genomic biomarker panel demonstrated high predictive accuracy (85%).
- The panel achieved a sensitivity of 93% and a specificity of 82% for predicting response to immune checkpoint therapy.
Conclusions:
- A 3D genomic approach can effectively develop a predictive clinical assay.
- This assay can identify cancer patients likely to respond to PD-1/PD-L1 checkpoint inhibition therapy.
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