NSCLC Biomarkers to Predict Response to Immunotherapy with Checkpoint Inhibitors (ICI): From the Cells to In Vivo Images

SIMPLE SUMMARY: Lung cancer and in particular non-small cell lung cancer (NSCLC) remains the leading cause of cancer-related death. The development of new therapeutic approaches, including immunotherapy, has led to substantial improvement in survival time and quality of life. However, the clinical benefit of immunotherapy-based strategies is still limited to a minority of patients, reflecting the need to identify predictive biomarkers of response, which are any substance, structure, or process or its products that can be measured in the body and that can influence or predict clinical response. In this work, we provide an overview of the approved and the most promising investigational biomarkers, which have been assessed in vitro/ex vivo and in vivo, to identify patients who could benefit the most from immunotherapy-based treatment. ABSTRACT: Lung cancer remains the leading cause of cancer-related death, and it is usually diagnosed in advanced stages (stage III or IV). Recently, the availability of targeted strategies and of immunotherapy with checkpoint inhibitors (ICI) has favorably changed patient prognosis. Treatment outcome is closely related to tumor biology and interaction with the tumor immune microenvironment (TME). While the response in molecular targeted therapies relies on the presence of specific genetic alterations in tumor cells, accurate ICI biomarkers of response are lacking, and clinical outcome likely depends on multiple factors that are both host and tumor-related. This paper is an overview of the ongoing research on predictive factors both from in vitro/ex vivo analysis (ranging from conventional pathology to molecular biology) and in vivo analysis, where molecular imaging is showing an exponential growth and use due to technological advancements and to the new bioinformatics approaches applied to image analyses that allow the recovery of specific features in specific tumor subclones.