Summary
Immunotherapy has revolutionised clinical oncology, with the use of immune checkpoint inhibitors (ICIs). These agents are in clinical use for almost a decade, treating over 20 types of cancers. They have shown a remarkable therapeutic benefit even in patients with advanced disease. Yet, only a small proportion of patients benefit from this therapy, leaving the rest resistant, for reasons that are still not clear. While there are certain clinical biomarkers to predict ICI therapy outcome, their prevalence and prediction power is rather limited. Therefore, there is a clinical unmet need to develop more powerful biomarkers to predict response to immunotherapy. In our ongoing ERC consolidator grant we discovered a unique sub-population of neutrophils, present in peripheral blood, that predicts response to immunotherapy in a very high probability. We designated these cells as immunotherapy-responsiveness cells (IRCs). Using various mouse models, we demonstrate that the levels of circulating IRCs measured at baseline are significantly higher in responding tumours to ICI therapy. These results were confirmed in a limited number of non-small cell lung cancer (NSCLC) and melanoma patients. Hence, our aim is to further test IRC levels in clinical samples, to evaluate their predictive power for ICI therapy, and to develop a clinical liquid biopsy-based predictive biomarker using flow cytometry test. The development of clinical IRC detection based on flow cytometry (BioFlow®) can serve two markets: (1) Clinicians – enabling oncologists to easily predict response to ICI therapy, thus improving personalised immunotherapy treatment; and (2) Pharmaceutical companies - developing immunotherapies - that can use IRC detection in development stages and through clinical studies, enabling tight regulative assessment of R&D success rates. The BioFlow goal is to technically validate and develop a predictive biomarker platform for both markets that will lead to its commercialisation.
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| Web resources: | https://cordis.europa.eu/project/id/101081690 |
| Start date: | 01-09-2022 |
| End date: | 29-02-2024 |
| Total budget - Public funding: | - 150 000,00 Euro |
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Original description
Immunotherapy has revolutionised clinical oncology, with the use of immune checkpoint inhibitors (ICIs). These agents are in clinical use for almost a decade, treating over 20 types of cancers. They have shown a remarkable therapeutic benefit even in patients with advanced disease. Yet, only a small proportion of patients benefit from this therapy, leaving the rest resistant, for reasons that are still not clear. While there are certain clinical biomarkers to predict ICI therapy outcome, their prevalence and prediction power is rather limited. Therefore, there is a clinical unmet need to develop more powerful biomarkers to predict response to immunotherapy. In our ongoing ERC consolidator grant we discovered a unique sub-population of neutrophils, present in peripheral blood, that predicts response to immunotherapy in a very high probability. We designated these cells as immunotherapy-responsiveness cells (IRCs). Using various mouse models, we demonstrate that the levels of circulating IRCs measured at baseline are significantly higher in responding tumours to ICI therapy. These results were confirmed in a limited number of non-small cell lung cancer (NSCLC) and melanoma patients. Hence, our aim is to further test IRC levels in clinical samples, to evaluate their predictive power for ICI therapy, and to develop a clinical liquid biopsy-based predictive biomarker using flow cytometry test. The development of clinical IRC detection based on flow cytometry (BioFlow®) can serve two markets: (1) Clinicians – enabling oncologists to easily predict response to ICI therapy, thus improving personalised immunotherapy treatment; and (2) Pharmaceutical companies - developing immunotherapies - that can use IRC detection in development stages and through clinical studies, enabling tight regulative assessment of R&D success rates. The BioFlow goal is to technically validate and develop a predictive biomarker platform for both markets that will lead to its commercialisation.Status
SIGNEDCall topic
ERC-2022-POC2Update Date
09-02-2023
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