Lung CancerNCT04529915
Multicenter Clinical Research for Early Diagnosis of Lung Cancer Using Blood Plasma Derived Exosome
An observational study of Lung Cancer, run by Korea University Guro Hospital at 1 site in South Korea.
Trial summary
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. Read more about this study
- Who is it for?
- Ages 40 years and olderHealthy volunteers can take part
- Conditions the study is for
- Lung Cancer
- What is being tested?
- Exosome sampling
- How many people
- 470 participants
- Where
- 1 siteSouth Korea
- Study dates
- 9 Apr 2020to 29 Dec 2023
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 40 years and older
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Study population: For this study, Koreans, regardless of gender, were studied for adults over 40 years of age. Participating institutions for this clinical research are Korea University Guro Hospital, Gangnam Severance Hospital, Bundang Seoul National University Hospital, Seoul Asan Hospital, and Samsung Seoul Hospital. Blood plasma samples is taken from stored in the biobank of each hospital.
Who may be able to join
- Patients with primary adenocarcinoma of lung with permanent pathology of N0 or N1
- Patients with T1mi, Tsi, T1a, T1b, T1c, T2a, and T2b stage
- An adult of Korean nationality
- Patients without prior chemo/radiation treatment prior to lung cancer surgery
- Patients who have not been diagnosed with other cancers prior to lung cancer surgery
Who cannot join
- Patients who do not meet the inclusion criteria
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Multicenter Clinical Research for Early Diagnosis of Lung Cancer Using Blood Plasma
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 = 320) are obtained from the Human biobank of five hospitals participating in the study.
- Conditions
- Lung Cancer
- Being tested
- Exosome sampling
- Keywords
- Blood plasma, Exosome, Liquid biopsy, Lung cancer, Biomarker, Deep-learning analysis
- Medical subject headings
- Lung Neoplasms
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Exosome samplingDiagnostic test
- Centrifugation of blood plasma
- Size exclusion chromatography
- ELISA assay, Western blotting
- Deep-learning analysis
| Study group | Role | What they receive |
|---|---|---|
| Lung cancer | Not described Receives: Diagnostic Test: Exosome sampling | |
| Healthy | Not described Receives: Diagnostic Test: Exosome sampling |
What is being measured
The primary outcome is the main question the study is designed to answer.
Evaluation of the distinction between healthy controls and lung cancer patients through deep-learning analysis of exosomes
Comparative evaluation of whether it is possible to distinguish between healthy controls and lung cancer patients through deep-learning analysis of exosomes
Measured: 3 years
Evaluating the possibility of distinguishing between normal and lung cancer patients through the analysis of lung cancer-specific exosomal protein
Quantitative analysis using lung cancer-specific exosomal protein evaluated the possibility of distinguishing between healthy controls and lung cancer patients.
Measured: 3 years
Secondary outcomes (2)
Evaluation of the possibility of distinguishing the early pathological stages in lung cancer patients through deep-learning analysis of exosomes
Evaluating whether the early stages of lung cancer patients can be distinguished using deep-learning analysis of exosomes
Measured: 3 years
Evaluation of the possibility of distinguishing the early pathological stages in lung cancer patients through quantitative analysis of lung cancer specific exosomal proteins
Evaluating whether the early stages of lung cancer patients can be distinguished using quantitative analysis of lung cancer specific exosomal proteins
Measured: 3 years
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted28 Aug 2020
- Study start9 Apr 2020
- Primary completion29 Dec 2023 (estimated)
- Study completion29 Dec 2023 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (7)Papers the sponsor has linked to this study.
- Other trials for Lung CancerStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Other
- Time perspective
- Retrospective
- Enrolment
- 470 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Korea University Guro Hospital
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Hyun Koo Kim, Korea University Guro Hospital
- Investigators
- Hyun Koo MD, PhD, MD, PhD, Principal investigator, Professor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04529915
- Sponsor's protocol ID
- 2020GR0176
- Status last verified
- Dec 2021
- First submitted
- 2 Aug 2020
- Last updated
- 30 Dec 2021
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided
Publications
Kaplan RN, Rafii S, Lyden D. Preparing the "soil": the premetastatic niche. Cancer Res. 2006 Dec 1;66(23):11089-93. doi: 10.1158/0008-5472.CAN-06-2407.
PubMed 17145848Psaila B, Lyden D. The metastatic niche: adapting the foreign soil. Nat Rev Cancer. 2009 Apr;9(4):285-93. doi: 10.1038/nrc2621.
PubMed 19308068Talmadge JE, Fidler IJ. AACR centennial series: the biology of cancer metastasis: historical perspective. Cancer Res. 2010 Jul 15;70(14):5649-69. doi: 10.1158/0008-5472.CAN-10-1040. Epub 2010 Jul 7.
PubMed 20610625Bidard FC, Pierga JY, Vincent-Salomon A, Poupon MF. A "class action" against the microenvironment: do cancer cells cooperate in metastasis? Cancer Metastasis Rev. 2008 Mar;27(1):5-10. doi: 10.1007/s10555-007-9103-x.
PubMed 18066649van Akkooi AC, Verhoef C, Eggermont AM. Importance of tumor load in the sentinel node in melanoma: clinical dilemmas. Nat Rev Clin Oncol. 2010 Aug;7(8):446-54. doi: 10.1038/nrclinonc.2010.100. Epub 2010 Jun 22.
PubMed 20567244Choi BH, An H, Cho S, Lee S, Kim HR, Cho JH, Lee JH, Kim GY, Jeon OH, Shin H, Choi Y, Kim HK. GCC2 in Small Extracellular Vesicles as a Diagnostic and Prognostic Biomarker of Early-Stage Lung Adenocarcinoma. J Extracell Vesicles. 2026 May;15(5):e70264. doi: 10.1002/jev2.70264.
PubMed 42087680Lamorte D, De Luca L, Tartarone A, Trino S, Giulivo I, De Stradis A, Maietti M, Caivano A, Laurenzana I. Serum extracellular vesicle microRNAs as potential biomarkers to predict pembrolizumab response and prognosis in metastatic non-small cell lung cancer patients. Front Immunol. 2025 Jun 4;16:1540906. doi: 10.3389/fimmu.2025.1540906. eCollection 2025.
PubMed 40534853
Study at a glance
From the registry record, last updated by the sponsor on 30 Dec 2021. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Multicenter Clinical Research for Early Diagnosis of Lung Cancer Using Blood Plasma
- ClinicalTrials.gov ID
- NCT04529915
- Acronym / sponsor ID
- 2020GR0176
- Conditions
- Lung Cancer
- Keywords
- Blood plasma, Exosome, Liquid biopsy, Lung cancer, Biomarker, Deep-learning analysis
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 470 participants (estimated)
- Lead sponsor
- Korea University Guro HospitalUniversity, hospital or other
- Study start
- 9 Apr 2020 (actual)
- Primary completion
- 29 Dec 2023 (estimated)
- Study completion
- 29 Dec 2023 (estimated)
- First posted
- 28 Aug 2020 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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 = 320) are obtained from the Human biobank of five hospitals participating in the study.
Study design
- Observational model
- Other
- Time perspective
- Retrospective
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Lung cancer | – | Diagnostic Test: Exosome sampling |
| Healthy | – | Diagnostic Test: Exosome sampling |
Who may qualify
- Ages
- 40 years and older
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
- Study population
- For this study, Koreans, regardless of gender, were studied for adults over 40 years of age. Participating institutions for this clinical research are Korea University Guro Hospital, Gangnam Severance Hospital, Bundang Seoul National University Hospital, Seoul Asan Hospital, and Samsung Seoul Hospital. Blood plasma samples is taken from stored in the biobank of each hospital.
Key inclusion criteria (5 listed)
- Patients with primary adenocarcinoma of lung with permanent pathology of N0 or N1
- Patients with T1mi, Tsi, T1a, T1b, T1c, T2a, and T2b stage
- An adult of Korean nationality
- Patients without prior chemo/radiation treatment prior to lung cancer surgery
- Patients who have not been diagnosed with other cancers prior to lung cancer surgery
Key exclusion criteria (1 listed)
- Patients who do not meet the inclusion criteria
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Exosome sampling* Centrifugation of blood plasma * Size exclusion chromatography * ELISA assay, Western blotting * Deep-learning analysis | Diagnostic test | Healthy, Lung cancer |
Primary outcome
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.
2 secondary outcomes
Evaluation of the possibility of distinguishing the early pathological stages in lung cancer patients through deep-learning analysis of exosomes
Time frame: 3 years
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
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 30 Dec 2021.
- Background: PubMed 17145848Kaplan RN, Rafii S, Lyden D. Preparing the "soil": the premetastatic niche. Cancer Res. 2006 Dec 1;66(23):11089-93. doi: 10.1158/0008-5472.CAN-06-2407.
- Background: PubMed 19308068Psaila B, Lyden D. The metastatic niche: adapting the foreign soil. Nat Rev Cancer. 2009 Apr;9(4):285-93. doi: 10.1038/nrc2621.
- Background: PubMed 20610625Talmadge JE, Fidler IJ. AACR centennial series: the biology of cancer metastasis: historical perspective. Cancer Res. 2010 Jul 15;70(14):5649-69. doi: 10.1158/0008-5472.CAN-10-1040. Epub 2010 Jul 7.
- Background: PubMed 18066649Bidard FC, Pierga JY, Vincent-Salomon A, Poupon MF. A "class action" against the microenvironment: do cancer cells cooperate in metastasis? Cancer Metastasis Rev. 2008 Mar;27(1):5-10. doi: 10.1007/s10555-007-9103-x.
- Background: PubMed 20567244van Akkooi AC, Verhoef C, Eggermont AM. Importance of tumor load in the sentinel node in melanoma: clinical dilemmas. Nat Rev Clin Oncol. 2010 Aug;7(8):446-54. doi: 10.1038/nrclinonc.2010.100. Epub 2010 Jun 22.
- Derived from this study: PubMed 42087680Choi BH, An H, Cho S, Lee S, Kim HR, Cho JH, Lee JH, Kim GY, Jeon OH, Shin H, Choi Y, Kim HK. GCC2 in Small Extracellular Vesicles as a Diagnostic and Prognostic Biomarker of Early-Stage Lung Adenocarcinoma. J Extracell Vesicles. 2026 May;15(5):e70264. doi: 10.1002/jev2.70264.
- Derived from this study: PubMed 40534853Lamorte D, De Luca L, Tartarone A, Trino S, Giulivo I, De Stradis A, Maietti M, Caivano A, Laurenzana I. Serum extracellular vesicle microRNAs as potential biomarkers to predict pembrolizumab response and prognosis in metastatic non-small cell lung cancer patients. Front Immunol. 2025 Jun 4;16:1540906. doi: 10.3389/fimmu.2025.1540906. eCollection 2025.
- Individual participant dataSharing planned: Undecided
Related trials for Lung Cancer
RecruitingPhase 1/2
Study of INBRX-106 and INBRX-106 in Combination With Pembrolizumab (Keytruda®) in Subjects With Locally Advanced or Metastatic Solid Tumors (Hexavalent OX40 Agonist)
Solid Tumor, Non-Small Cell Lung Cancer
RecruitingObservational study
A Prospective ,Multicenter ,Non-interventional ,Real-world Study Observing Changes in Molecular Markers Osimertinib Targeted Therapy in EGFRm NSCLC
Non Small Cell Lung Cancer
Active, not recruiting
Streamlined Geriatric and Oncological Evaluation Based On IC Technology
Breast Cancer, Comorbidities and Coexisting Conditions
RecruitingPhase 3
A Study Evaluating Sotorasib Platinum Doublet Combination Versus Pembrolizumab Platinum Doublet Combination as a Front-Line Therapy in Participants With Stage IV or Advanced Stage IIIB/C Nonsquamous Non-Small Cell Lung Cancers (CodeBreaK 202)
Non-Small Cell Lung Cancer (NSCLC)
Active, not recruitingPhase 2
Datopotamab Deruxtecan (Dato-DXd, DS-1062a) in Advanced and/or Unresectable Non-Small Cell Lung Cancer
Metastatic Lung Cancer, Advanced Non Small Cell Lung Cancer
Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Hyun Koo MD, PhD, MD, PhD principal investigator
Professor
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Lung Cancer, run by Korea University Guro Hospital at 1 site in South Korea.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 5 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 30 Dec 2021. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in South Korea. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Evaluation of the distinction between healthy controls and lung cancer patients through deep-learning analysis of exosomes (time frame: 3 years). The study lists 2 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT04529915, which also lists 7 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 30 Dec 2021.