Finding biomarkers for immunotherapy in lung cancer patients by cell-type specific expression

Lung cancer is the number one cause of cancer-related death worldwide. Most cases are diagnosed at an advanced stage of disease when the treatment goal is essentially palliative. The most common type of lung cancer is non-small cell lung cancer (NSCLC). The major advances in the treatment of advanced NSCLC are the advent of targeted agents for tumors with driver mutations and immunotherapy. Immune checkpoint inhibitors (ICI) have been proven to be of benefit for advanced NSCLC and are currently part of the standard of care for these patients. However, it isn`t clear if ICI works better as a prior treatment to surgery (neoadjuvant treatment) or a consolidative treatment. In order to give better treatment we need to find the best way to administer it, identify biological markers that could predict treatment success, and understand the biological mechanisms of immunotherapy. By treating patients with immune checkpoint blockade prior to surgery (neoadjuvant treatment) with different intervals until the surgery, using Nanostring`s GeoMX digital spatial profiler, we obtained gene and protein expression of cancer cells or immune cell regions from the biopsy of each patient. Using bioinformatics analysis, we identified potential biological markers for immunotherapy and assessed the effectiveness of different schedules of neoadjuvant treatment