Multi-Omics Prediction of Radiation Lung Injury in Immunotherapy-Treated Lung Cancer Patients

Официальное название

Multi-Omics Prediction of Radiation Pneumonitis Risk in Lung Cancer Patients After Immunotherapy and Thoracic Radiotherapy

Обзор

This prospective study aims to develop a multi-omics-based predictive model for radiation pneumonitis in lung cancer patients receiving sequential immunotherapy and thoracic radiotherapy.

Подробное описание

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.

Вмешательства

• Другое No Intervention: Observational Cohort
  This study involves collection of peripheral blood, urine, and stool samples from lung cancer patients who have received immunotherapy followed by thoracic radiotherapy. Samples are obtained at baseline prior to the initiation of radiotherapy for comprehensive multi-omics profiling, including genomic, transcriptomic, proteomic, and metabolomic analyses. No therapeutic intervention is administered as part of this study.

Первичные конечные точки

• Area Under the Receiver Operating Characteristic Curve (AUC) of the Multi-Omics Prediction Model for Radiation Pneumonitis [Срок оценки: At 6 months post-radiotherapy]

Критерии участия

Критерии включения

Patients aged 18 or older years with a life expectancy of at least 6 months. Additional inclusion criteria were a Zubrod performance status of 0-1, documentation of baseline chest computed tomography (CT) scans prior to the initiation of immunotherapy, receipt of at least 2 cycles of systemic therapy (PD-1) as either monotherapy or combination therapy within the past six months, voluntary participation with written informed consent, and appropriate baseline biochemical tests. The radiation dose for thoracic radiotherapy was ≥30Gy for all eligible patients in this study. No use of antibiotics within 1 week prior to the initiation of thoracic radiotherapy.

Exclusion Criteria:Participation in other interventional clinical studies or treatments, having received investigational drugs or treatments within 4 weeks prior to the first dose, or prior receipt of a solid organ or hematopoietic stem cell transplant, having an active infection, or pre-existing/active ICI-induced pneumonitis.

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Критерии приведены из реестра в оригинале (на английском). Окончательную оценку соответствия проводит исследовательский центр.

Здоровые добровольцы: Нет

Дизайн исследования

Модель наблюдения

Когортное

Центры проведения

Китай · 1 центр

• Union Hospital, Tongji Medical College, Huazhong University of Science and Technology — Ухань

Идентификаторы

NCT: NCT07742800 · HBCH-RT-2026-06

Первоисточники (государственные реестры)

• ClinicalTrials.gov (NIH, США)

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