Lung Cancer Clinical Trial
Official title:
Plasma Biomarkers as a Non-invasive Approach for Early Diagnosis of Lung Cancer
Lung cancer is the most common cancer with the highest morbidity and mortality in the world.
Stagement is closely related to the 5 years of survival rate of patients. The postoperative
5-year survival rate is above 90% for stage ⅠA lung cancer patients, while the 5-year
survival rate of stage IV lung cancer patients is less than 5%. Therefore, early screening
and diagnosis for lung cancer is a key method to reduce lung cancer mortality and prolong
survival for patients.
At present, low-dose computed tomography (LDCT) is the most effective method for early
detection of lung cancer. In addition to imaging examination, plasma tumor markers detection
is also a common clinical detection method for tumor screening and postoperative monitoring.
Liquid biopsy is a non-invasive or minimally invasive method for testing blood or other
liquid samples to analyze tumor-related markers including nucleic acids and proteins. Several
studies have explored the detection of hot spot gene mutations, methylation and methylation
changes of DNA, protein markers and autoantibodies in peripheral blood in lung cancer
patients. Liquid biopsy has generally become the most popular field for early diagnosis of
lung cancer.
Based above, it is necessary to combine multi-omics methods to improve the detection of early
stage lung cancer. In our study, we intend to integrate molecular features obtained through
liquid biopsy and clinical data of lung cancer patients, and develop and prospectively
validate a machine-learning method which can robustly discriminate early-stage lung cancer
patients from controls.
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