Research

Deciphering the Immunogenomic Landscape of Lung Cancer

Our laboratory conducts cutting-edge research at the intersection of genomics and immunology, with a primary focus on lung cancer. We utilize high-throughput sequencing, bioinformatics, and advanced experimental models to unravel the molecular mechanisms driving tumorigenesis and immune evasion. Our goal is to translate these fundamental discoveries into novel diagnostic, preventive, and therapeutic strategies, aiming to significantly improve patient outcomes.

Specific Research Directions:

1. Early Oncogenesis and Immunoprevention: We investigate the genomic and immunological events that drive the initiation and progression of lung precancers. By characterizing the dynamic interplay between evolving precancerous cells and the host immune response, we aim to identify mechanisms of cancer progression, biomarkers for risk stratification, and actionable vulnerabilities for cancer interception. Our research has led to the development and implementation of clinical trials evaluating immune- and inflammation-targeted approaches, including IMPRINT-Lung with pembrolizumab and Can-Prevent-Lung with canakinumab. Building on these studies, we are developing Isu-Prevent-Lung, a clinical trial evaluating IL-1R1 blockade with isunakinra in individuals with high-risk pulmonary nodules. These efforts aim to translate mechanistic discoveries into novel strategies for lung cancer prevention and interception.
2. Intratumor Heterogeneity (ITH) and Therapeutic Resistance: We investigate the complex landscape of ITH at the genomic, epigenetic, transcriptomic and immunological levels and its impact on tumor evolution, treatment response and clinical outcomes. Using bulk and single-cell sequencing, spatial profiling and integrative computational approaches, we characterize the spatial and temporal evolution of heterogeneous tumor ecosystems and investigate how ITH contributes to therapeutic resistance. Our goal is to identify mechanisms and predictive biomarkers that can guide more effective and personalized treatment strategies.
3. Immune Evasion and Immunotherapy Response: We investigate the mechanisms by which tumor cells evade immune surveillance and suppress anti-tumor immunity. By integrating genomic, transcriptomic, single-cell, spatial and immune profiling with clinical data, we characterize the dynamic interactions between tumor cells and the immune microenvironment and identify mechanisms and biomarkers associated with response and resistance to immunotherapy. We also apply advanced computational approaches, including machine learning, to integrate multidimensional data and uncover clinically relevant patterns that may inform more effective therapeutic strategies.