Lung NeoplasmsNCT07291921
To Conduct Multi-omics Integrated Studies in Peripheral Blood, Such as Fragment Omics, Metabolomics and Epigenetics, and Establish Non-invasive Dynamic Follow-up Monitoring Programs During Perioperative and Postoperative Periods (Observational Study)
An observational study of Lung Neoplasms and Neoadjuvant Therapy, run by Peking University People's Hospital at 1 site in China.
Trial summary
This project aims to innovatively integrate multi-omics data, including plasma metabolomics, radiomics, and cfDNA multi-level information, combined with survival data (e.g., RFS), to establish a novel multidimensional approach for noninvasive postoperative recurrence monitoring in lung cancer using artificial… Read more about this study
- Who is it for?
- Ages 18 to 85 years
- Conditions the study is for
- Lung Neoplasms, Neoadjuvant Therapy, Immunotherapy
- How many people
- 100 participants
- Where
- 1 siteChina
- Study dates
- 8 May 2025to 31 Oct 2027
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
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 18 to 85 years
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: Patients with pulmonary nodules who underwent radical treatment at our center between May 2025 and October 2027, met all eligibility criteria, and provided informed consent.
Who may be able to join
- Signed written informed consent.
- Male or female, aged ≥ 18 and < 85 years.
- Radical resection performed, pathologic stage IB-IIIA (8th TNM) non-small-cell lung cancer.
- Tumor tissue and blood samples obtainable at all protocol-specified time-points.
- No pure ground-glass nodule on imaging.
- Completed standard neoadjuvant immunotherapy combined with platinum-based chemotherapy.
Who cannot join
- Postoperative pathology shows other than NSCLC, including but not limited to benign lesions, small-cell carcinoma, metastasis, or indeterminate/inadequate histology.
- Insufficient or poor-quality blood or tissue samples.
- Pure ground-glass nodule on imaging.
- History of any malignancy within the past 5 years.
- Contraindication to surgery preventing radical resection.
- Non-radical (R2) resection.
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- Pathologic stage IIIB-N3, IIIC, or IV on paraffin sections.
- Refusal or withdrawal of informed consent.
- Any condition deemed unsuitable by the investigator (e.g., perioperative blood transfusion, severe psychiatric disorder precluding follow-up).
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
China1 site, 1 recruiting
- Recruiting
Peking University People's Hospital
Beijing, Beijing Municipality, 100044
Yue He, +86-010-88325983, hy771999@163.com
About this study
This project aims to innovatively integrate multi-omics data, including plasma metabolomics, radiomics, and cfDNA multi-level information, combined with survival data (e.g., RFS), to establish a novel multidimensional approach for noninvasive postoperative recurrence monitoring in lung cancer using artificial intelligence algorithms. The goal is to develop a new noninvasive recurrence monitoring system for lung cancer.
Read the detailed description
This project is a prospective observational study designed to comprehensively integrate plasma metabolomic, radiomic, and epigenomic data to develop a predictive model for postoperative recurrence risk in lung cancer. The study will retrospectively enroll 200 patients who underwent radical surgery after neoadjuvant therapy, and prospectively enroll 100 additional post-radical-surgery lung cancer patients who received neoadjuvant treatment as a validation cohort. Peripheral blood samples will be collected at multiple timepoints for metabolomic profiling. Unsupervised clustering, random forest algorithms, and Wilcoxon tests will be applied to identify recurrence-related features and construct a recurrence prediction model.Additionally, using preoperative and first postoperative follow-up CT imaging data, a deep learning-based 3D ResNet will be employed to generate radiomic recurrence risk scores for each patient. Plasma cfDNA will undergo low-pass whole-genome sequencing and methylation analysis to extract multi-dimensional recurrence-associated features. Finally, the study will innovatively utilize the DeepProg deep learning framework to integrate radiomic, cfDNA, and plasma metabolomic data into a non-invasive multi-omics model. Combined with survival data, this model will predict recurrence risk, ultimately achieving high-accuracy stratification of patients' postoperative recurrence probability.
- Keywords
- NSCLC, Neoadjuvant immunotherapy, Perioperative monitoring, Liquid biopsy, MRD, Minimal residual disease, Multiple omics
- Medical subject headings
- Lung Neoplasms, Neoplasm, Residual
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| High-risk group | High-risk recurrence groups identified by the multi-omics model | |
| Low-risk group | Low-risk recurrence groups identified by the multi-omics model |
What is being measured
The primary outcome is the main question the study is designed to answer.
Two-year recurrence-free survival rate
Measured: Time from curative surgery to confirmation of clinical progression (recurrence or metastasis) within two years
Secondary outcomes (2)
Overall survival
Measured: Time from curative surgery to confirmation of death (any cause)，assessed up to 60 months.
Timely diagnosis rate by the novel MRD monitoring technique
The proportion of patients with recurrence signals detected by non-invasive methods prior to clinical confirmation of recurrence/metastasis, and quantify the mean lead time.
Measured: two years
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted18 Dec 2025
- Study start8 May 2025
- Primary completion31 Oct 2027 (estimated)
- Study completion31 Oct 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Lung NeoplasmsStudies 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
- Cohort
- Time perspective
- Prospective
- Enrolment
- 100 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Peking University People's Hospital
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Chen KeZhong, Peking University People's Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07291921
- Sponsor's protocol ID
- BRWEP2024W034080204-1
- Status last verified
- Dec 2025
- First submitted
- 6 Dec 2025
- Last updated
- 3 Mar 2026
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided
Study at a glance
From the registry record, last updated by the sponsor on 3 Mar 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- To Conduct Multi-omics Integrated Studies in Peripheral Blood, Such as Fragment Omics, Metabolomics and Epigenetics, and Establish Non-invasive Dynamic Follow-up Monitoring Programs During Perioperative and Postoperative Periods (Observational Study)
- ClinicalTrials.gov ID
- NCT07291921
- Acronym / sponsor ID
- BRWEP2024W034080204-1
- Keywords
- NSCLC, Neoadjuvant immunotherapy, Perioperative monitoring, Liquid biopsy, MRD, Minimal residual disease, Multiple omics
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 100 participants (estimated)
- Lead sponsor
- Peking University People's HospitalUniversity, hospital or other
- Study start
- 8 May 2025 (actual)
- Primary completion
- 31 Oct 2027 (estimated)
- Study completion
- 31 Oct 2027 (estimated)
- First posted
- 18 Dec 2025 (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.
This project aims to innovatively integrate multi-omics data, including plasma metabolomics, radiomics, and cfDNA multi-level information, combined with survival data (e.g., RFS), to establish a novel multidimensional approach for noninvasive postoperative recurrence monitoring in lung cancer using artificial intelligence algorithms. The goal is to develop a new noninvasive recurrence monitoring system for lung cancer.
Detailed description
This project is a prospective observational study designed to comprehensively integrate plasma metabolomic, radiomic, and epigenomic data to develop a predictive model for postoperative recurrence risk in lung cancer. The study will retrospectively enroll 200 patients who underwent radical surgery after neoadjuvant therapy, and prospectively enroll 100 additional post-radical-surgery lung cancer patients who received neoadjuvant treatment as a validation cohort. Peripheral blood samples will be collected at multiple timepoints for metabolomic profiling. Unsupervised clustering, random forest algorithms, and Wilcoxon tests will be applied to identify recurrence-related features and construct a recurrence prediction model.Additionally, using preoperative and first postoperative follow-up CT imaging data, a deep learning-based 3D ResNet will be employed to generate radiomic recurrence risk scores for each patient. Plasma cfDNA will undergo low-pass whole-genome sequencing and methylation analysis to extract multi-dimensional recurrence-associated features. Finally, the study will innovatively utilize the DeepProg deep learning framework to integrate radiomic, cfDNA, and plasma metabolomic data into a non-invasive multi-omics model. Combined with survival data, this model will predict recurrence risk, ultimately achieving high-accuracy stratification of patients' postoperative recurrence probability.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| High-risk group | – | –High-risk recurrence groups identified by the multi-omics model |
| Low-risk group | – | –Low-risk recurrence groups identified by the multi-omics model |
Who may qualify
- Ages
- 18 to 85 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Patients with pulmonary nodules who underwent radical treatment at our center between May 2025 and October 2027, met all eligibility criteria, and provided informed consent.
Key inclusion criteria (6 listed)
- Signed written informed consent.
- Male or female, aged ≥ 18 and < 85 years.
- Radical resection performed, pathologic stage IB-IIIA (8th TNM) non-small-cell lung cancer.
- Tumor tissue and blood samples obtainable at all protocol-specified time-points.
- No pure ground-glass nodule on imaging.
Key exclusion criteria (9 listed)
- Postoperative pathology shows other than NSCLC, including but not limited to benign lesions, small-cell carcinoma, metastasis, or indeterminate/inadequate histology.
- Insufficient or poor-quality blood or tissue samples.
- Pure ground-glass nodule on imaging.
- History of any malignancy within the past 5 years.
- Contraindication to surgery preventing radical resection.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Two-year recurrence-free survival rate
Time frame: Time from curative surgery to confirmation of clinical progression (recurrence or metastasis) within two years
2 secondary outcomes
Overall survival
Time frame: Time from curative surgery to confirmation of death (any cause)，assessed up to 60 months.
Timely diagnosis rate by the novel MRD monitoring technique
Time frame: two years
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 3 Mar 2026.
- Individual participant dataSharing planned: Undecided
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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.
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 Neoplasms and Neoadjuvant Therapy, run by Peking University People's Hospital at 1 site in China.
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 6 inclusion and 9 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: looking for participants now, as of the sponsor's last update on 3 Mar 2026. 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 China. 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?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Kezhong Chen (+86-010-88325983, mdkzchen@163.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Two-year recurrence-free survival rate (time frame: Time from curative surgery to confirmation of clinical progression (recurrence or metastasis) within two years). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
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 3 Mar 2026.