TKI resistance | Resistance mechanisms to tyrosine kinase inhibitors in solid tumors

Summary
Over the past 10 years, the chemotherapeutic arsenal has been expanded to include molecular-targeted therapies based on the principle that cancer cells become addicted to a single driver oncogene. However, use of these new therapies is limited due to development of acquired resistance. To fully understand how resistance develops, patient-derived models are an absolute pre-requisite, but establishing them remains extremely challenging. Few groups worldwide have successfully implemented a systematic standardized approach to facilitate translational cancer research discovery. My project aims to provide rational therapeutic guidance for combinatorial or adaptive designs to overcome acquired resistance to tyrosine kinase inhibitors (TKIs) in patients with oncogene-addiction. By establishing new laboratory models of resistance directly from patient biopsies (patient derived cell lines and xenografts) I will elucidate the molecular mechanisms whereby cancer cells escape targeted treatments. I will then implement innovative approaches to overcome resistance using TKI combinatorial screens, apoptosis sensitizers and by screening for epigenetic modifiers.
Additionally, I will scrutinize the emergence of resistance acquisition in vitro. Current working models involve “persistor” cellular populations able to tolerate the TKI and, in a subsequent step, to become fully resistant to the drug. This drug tolerant persistor stage most probably involves epigenetic reprogrammation. An epigenetic inhibitor screen will be performed to identify agents able to interfere with the emergence of persistors and ultimately with the acquisition of TKI resistance. These results should provide an alternative strategy to validate innovative combinatorial drug strategies to avoid emergence of resistance in patients.
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More information & hyperlinks
Web resources: https://cordis.europa.eu/project/id/717034
Start date: 01-12-2016
End date: 30-11-2021
Total budget - Public funding: 1 500 000,00 Euro - 1 500 000,00 Euro
Cordis data

Original description

Over the past 10 years, the chemotherapeutic arsenal has been expanded to include molecular-targeted therapies based on the principle that cancer cells become addicted to a single driver oncogene. However, use of these new therapies is limited due to development of acquired resistance. To fully understand how resistance develops, patient-derived models are an absolute pre-requisite, but establishing them remains extremely challenging. Few groups worldwide have successfully implemented a systematic standardized approach to facilitate translational cancer research discovery. My project aims to provide rational therapeutic guidance for combinatorial or adaptive designs to overcome acquired resistance to tyrosine kinase inhibitors (TKIs) in patients with oncogene-addiction. By establishing new laboratory models of resistance directly from patient biopsies (patient derived cell lines and xenografts) I will elucidate the molecular mechanisms whereby cancer cells escape targeted treatments. I will then implement innovative approaches to overcome resistance using TKI combinatorial screens, apoptosis sensitizers and by screening for epigenetic modifiers.
Additionally, I will scrutinize the emergence of resistance acquisition in vitro. Current working models involve “persistor” cellular populations able to tolerate the TKI and, in a subsequent step, to become fully resistant to the drug. This drug tolerant persistor stage most probably involves epigenetic reprogrammation. An epigenetic inhibitor screen will be performed to identify agents able to interfere with the emergence of persistors and ultimately with the acquisition of TKI resistance. These results should provide an alternative strategy to validate innovative combinatorial drug strategies to avoid emergence of resistance in patients.

Status

CLOSED

Call topic

ERC-2016-STG

Update Date

27-04-2024
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Horizon 2020
H2020-EU.1. EXCELLENT SCIENCE
H2020-EU.1.1. EXCELLENT SCIENCE - European Research Council (ERC)
ERC-2016
ERC-2016-STG