Exploring Novel Biomarkers for Predicting Response to Combination Immunotherapy and Chemotherapy in Lung Cancer

Abstract

Background: Lung cancer remains one of the most prevalent causes of cancer-related mortality, with a high demand for accurate biomarkers to predict treatment responses to combination immunotherapy and chemotherapy. Objective: To explore novel biomarkers that can predict responses to combination therapy involving immunotherapy and chemotherapy in lung cancer patients, thereby improving personalized treatment strategies. Methods: A total of 188 patients with non-small cell lung cancer (NSCLC) were enrolled in a prospective study at the Department of Pathology & Immunology, Washington University in St. Louis. Patients were treated with a combination of chemotherapy and immune checkpoint inhibitors. Tumor samples were collected before and after treatment. Biomarkers related to tumor mutational burden (TMB), PD-L1 expression, and immune cell infiltration were analyzed using next-generation sequencing (NGS), immunohistochemistry (IHC), and flow cytometry. Statistical analysis included paired t-tests and regression analysis. Results: The study found a significant correlation between high TMB and improved response to combination therapy, with 72% of patients exhibiting positive outcomes in the high TMB group compared to 42% in the low TMB group (p-value = 0.002). PD-L1 expression above 50% correlated with a 67% response rate (p-value = 0.03). Immune cell infiltration, particularly CD8+ T cells, was significantly associated with better treatment response (p-value = 0.005). Standard deviation for treatment response across all biomarkers was calculated as ±14.2%, indicating variability in patient responses. Conclusion: Novel biomarkers, including TMB and PD-L1, significantly predict responses to combination therapies in lung cancer, with immune cell infiltration being a key determinant of therapeutic efficacy.