Artificial intelligence (AI) has the potential to transform biomarker testing in early-stage NSCLC by streamlining data analysis, improving interpretation of complex genomic profiles, and predicting actionable mutations from imaging or pathology data.
Liquid biopsy using circulating tumor DNA (ctDNA) is emerging as a valuable tool in early-stage NSCLC, with the potential to complement or, in some cases, substitute for tissue-based testing.
Current NCCN guidelines for early-stage NSCLC recommend testing for key biomarkers to guide decisions regarding adjuvant targeted therapy or immunotherapy.
Comprehensive biomarker testing at the time of early NSCLC diagnosis is critical because it ensures that clinicians identify actionable molecular alterations before definitive treatment plans are set.
Comprehensive biomarker testing in early-stage NSCLC requires coordination across multiple specialties, including thoracic surgery, medical oncology, pathology, pulmonology, and radiology.