Characterization of Immune Modulatory Signal Pathway Activation for Functional Diagnostics to Optimize Immunotherapy in Lung Cancer Patients

• Grant number: 24/10032-1
• Support Opportunities: Scholarships abroad - Research Internship - Doctorate (Direct)
• Start date: December 01, 2024
• End date: November 30, 2025
• Field of knowledge: Health Sciences - Medicine - Surgery
• Principal Investigator: Lidia Maria Rebolho Batista Arantes
• Grantee: Katiane Tostes
• Supervisor: Patrick Micke
• Host Institution: Hospital do Câncer de Barretos. Fundação Pio XII (FP). Barretos , SP, Brazil
• Institution abroad: Uppsala University (UU), Sweden
• Associated to the scholarship: 21/08352-0 - Immune-checkpoint inhibitors: biomarkers to predict response in non-small cell Lung Cancer patients, BP.DD

Abstract

Lung cancer causes 1.8 million deaths annually, representing the highest cancer mortality rate, with 85% of patients falling under non-small cell lung cancer (NSCLC). Immunotherapy targeting immune checkpoint inhibitors (ICI) has shown significant advances, employing monoclonal antibodies to modulate co-stimulatory and co-inhibitory signals crucial for immune tolerance maintenance. Despite its progress, immunotherapy in NSCLC still faces challenges that must be overcome to benefit a larger patient population. Characterizing the immune landscape of the tumor microenvironment (TME) is crucial for advancing and expanding immunotherapy. Identifying immune markers capable of distinguishing responders from non-responders to ICI therapy in NSCLC patients is essential. Through multiplex immunohistochemistry with lineage markers (CD4, CD8, CD20, FoxP3, CD168, CD168, CD38), checkpoint inhibitors (PD1, PD-L1, LAG3, LAM3, CD40, ICOS) as well as potentially relevant signal pathways (pSMAD, pSTAT3, activated YAP), this study aims to evaluate complex cellular interactions and spatial organization in the TME of forty NSCLC patients treated with anti-PD1 and/or anti-PD-L1 ICIs. Additionally, proximity ligation assays (PLA) will investigate subcellular interactions among key immune checkpoints including PD1-PD-L1, TIGIT-CD155, CTLA4-B7, TIM3-GAL9 and LAG3-MHCII. The study hypothesizes that insights into immune infiltrate distribution and its correlation with treatment response will reveal predictive biomarkers for patient stratification. Through thorough analysis and interpretation, this research aims to advance understanding of the NSCLC TME, potentially guiding improved therapeutic strategies tailored to individual patient profiles.