The ANswer within the microEnvironment: Malignant pleural mesothelioma resistance to Old and NEw drugs
BACKGROUND AND RATIONALE: Pleural mesothelioma (PM) is an intrathoracic neoplasia with an unfavourable prognosis. Although rare, a high peak incidence is expected in 2020-2025. The most important risk factor is asbestos exposure that leads to a protracted immune response, making PM a candidate for immunotherapeutic approaches. However, to date the overall response rates to treatment with immune checkpoint inhibitors (ICI) are only 10-20%. HYPOTHESIS: The hypothesis is that the tumour microenvironment (TME), particularly tumour immune microenvironment (TIM), plays a crucial role in the development/progression of PM, affecting survival of mesothelial cells and escape from immunosurveillance. AIM: The main goal of the project is the identification of predictive biomarkers of ICI response. METHODS: The research will be done on 360 chemo naïve pleural biopsies from PM patients that will undergo neoadjuvant chemotherapy followed by surgery or palliative systemic treatment (platinum-based chemotherapy or ICI). A subset of PM tissues from patients undergoing surgery will be investigated before and after treatment. The research will be based on a multidisciplinary and interdisciplinary approach. Through advanced statistical methods (machine learning algorithms), clinical data, and findings from immunofluorescence, high-throughput molecular assays, radiomics, and magnetic resonance will be integrated to identify the most discriminative predictive features for the ICI treatment response. Experimental models (in vitro and in vivo) for functional studies will also be considered. EXPECTED RESULTS AND POTENTIAL IMPACT: ANEMONE is built upon the strong belief that there are specific key pathways and TME/TIM markers capable of predicting the prognosis and the response to ICI in PM patients. The identification of these pathways could have a strong impact on PM patient management allowing a better treatment response and outcome.
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This project has received funding from the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement No. 964264.