Multicenter Clinical Research for Early Diagnosis of Lung Cancer Using Blood Plasma Derived Exosome
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|ClinicalTrials.gov Identifier: NCT04529915|
Recruitment Status : Active, not recruiting
First Posted : August 28, 2020
Last Update Posted : August 28, 2020
Lung cancer is a leading cause of cancer death worldwide. Early diagnosis is linked to a better prognosis. Further, surgical resection at the early stages of non-small cell lung cancer (NSCLC) results in markedly improved survival rates. Computed tomography (CT)- or bronchoscopy-guided needle biopsies are standard definitive diagnostic procedures for lung cancer and are used to obtain tissue for pathological examination. However, these procedures are invasive, difficult to repeat, expensive, and risk exposure to radiation. Conversely, liquid biopsies, such as circulating tumor cells (CTCs), circulating tumor DNA (ctDNA), and extracellular vesicles (EVs), are simple and less invasive procedures that can be repeated more frequently than tissue biopsies.
To analyze the exosomes abundantly present in the blood and to conduct clinical studies to determine whether it is possible to diagnose lung cancer. To this end, blood samples from normal people (n = 150) and lung cancer patients (n = 420) are obtained from the Human biobank of five hospitals participating in the study.
|Condition or disease||Intervention/treatment|
|Lung Cancer||Diagnostic Test: Exosome sampling|
|Study Type :||Observational|
|Estimated Enrollment :||470 participants|
|Official Title:||Multicenter Clinical Research for Early Diagnosis of Lung Cancer Using Blood Plasma|
|Actual Study Start Date :||April 9, 2020|
|Estimated Primary Completion Date :||December 29, 2023|
|Estimated Study Completion Date :||December 29, 2023|
Diagnostic Test: Exosome sampling
Diagnostic Test: Exosome sampling
- Evaluation of the distinction between healthy controls and lung cancer patients through deep-learning analysis of exosomes [ Time Frame: 3 years ]Comparative evaluation of whether it is possible to distinguish between healthy controls and lung cancer patients through deep-learning analysis of exosomes
- Evaluating the possibility of distinguishing between normal and lung cancer patients through the analysis of lung cancer-specific exosomal protein [ Time Frame: 3 years ]Quantitative analysis using lung cancer-specific exosomal protein evaluated the possibility of distinguishing between healthy controls and lung cancer patients.
- Evaluation of the possibility of distinguishing the early pathological stages in lung cancer patients through deep-learning analysis of exosomes [ Time Frame: 3 years ]Evaluating whether the early stages of lung cancer patients can be distinguished using deep-learning analysis of exosomes
- Evaluation of the possibility of distinguishing the early pathological stages in lung cancer patients through quantitative analysis of lung cancer specific exosomal proteins [ Time Frame: 3 years ]Evaluating whether the early stages of lung cancer patients can be distinguished using quantitative analysis of lung cancer specific exosomal proteins
Biospecimen Retention: Samples Without DNA
To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.
Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT04529915
|Korea, Republic of|
|Korea University Guro Hospital|
|Seoul, Guro-gu, Korea, Republic of, 08308|
|Principal Investigator:||Hyun Koo MD, PhD, MD, PhD||Professor|