Description

Today lung cancer patients are treated with conventional therapies like surgery, targeted, chemo- and radiotherapy. Except for surgery, the problem with these therapies is that most patients show tumor regression at first, but that resistance against the therapies is induced over time. More recently a novel treatment option has been added as first- or second-line treatment option for advanced lung cancer patients: immunotherapy. This therapy relies on the patient’s own immune system to fight his or her cancer cells. In contrast with conventional therapies, only ±20% of lung cancer patients respond.
However, many of them remain progression-free with some exceptional cases of complete cure. The fact that the other 80% of patients is not responding to immunotherapy today, suggests that we need to obtain more insights on the resistance mechanisms that are present at onset or installed during disease progression against immunotherapy.
The reason why it is not straightforward to evaluate the Resistance Mechanisms against Immunotherapy (RMI), is because immunotherapy does not involve just one drug to which cancer cells can become resistant; but a whole immune system which comprises several types of immune and nonimmune cells. With this project we want to mimic the 3D architecture and dynamic interactions found within a lung cancer patients’ tumor, by culturing several key players of an antitumor immune response together in lung tumor spheroids. Hence with this project application, we want to design and apply an innovative ‘3D CRiMe scene platform’ to unravel new RMIs installed by lung cancer cells. Moreover, we will apply topnotch technologies to decipher and validate the potential RMIs. The knowledge gained from this project will foster more scientifically based clinical development of biomarkers and drugs that could tip the overall survival balance of lung cancer patients treated with immunotherapy.
AcronymAIIFUND64
StatusActive
Effective start/end date1/04/2031/03/21

ID: 54103745