The combination of immune checkpoint inhibitors with thoracic radiotherapy has yielded substantial survival gains in lung cancer, yet this dual-modality strategy confers a markedly elevated risk of radiation pneumonitis, particularly when radiotherapy follows immunotherapy. To date, no validated biomarkers exist to stratify patients by this risk, constraining both individualized treatment planning and proactive surveillance. This prospective study addresses this unmet need by systematically collecting blood, urine, and stool samples from patients receiving sequential immunotherapy and thoracic radiotherapy. Employing integrative multi-omics platforms, including genomics, transcriptomics, proteomics, and metabolomics, we aim to discover novel molecular signatures capable of accurately predicting radiation pneumonitis susceptibility. Ultimately, by correlating multi-omic profiles with clinical outcomes, we seek to construct a clinically actionable prediction model to inform risk-adapted monitoring, facilitate patient-clinician shared decision-making, and enhance therapeutic safety and quality of life in this expanding patient population.
