Lung CancersNCT06772363
SERS-Based Serum Molecular Spectral Screening for Hematogenous Metastasis
An observational study of Lung Cancers, run by Fuzhou General Hospital at 1 site in China.
Trial summary
Although modern medicine has made significant progress in the diagnosis and treatment of lung cancer, most patients are diagnosed at locally advanced stage or with distant metastases, especially in the late stages where the cancer has spread to other organs through hematogenous metastasis. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Lung Cancers
- What is being tested?
- Serum Raman spectroscopy intelligent diagnostic system
- How many people
- 200 participants
- Where
- 1 siteChina
- Study dates
- 9 Apr 2026to 1 Jun 2026
- 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 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: The participants were diagnosed with lung malignancy through pathological examination and were able to undergo clinical staging based on TNM.
Who may be able to join
- Participants with Lung cancer meeting the criteria of TNM (Ninth Edition);
- Participants are willing to participate in this study and follow the research plan;
- Participants or legally authorized representatives can give written informed consent approved by the Ethics Review Committee that manages the website;
Who cannot join
- Participants with concomitant other malignant tumors;
- Participants with missing baseline clinical data;
- Participants with severe underlying lung diseases (such as bronchiectasis, bronchial asthma or COPD, etc.), or those with a history of occupational or environmental exposure to dust, mines or asbestos;
- Participants who do not cooperate or refuse to participate in clinical trials at a later stage.
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
About this study
Official title: SERS-Based Serum Molecular Spectral Screening for Hematogenous Metastasis vs. Non-Metastasis in Non-Small Cell Lung Cancer: A Multicenter, Open-Label, Double-Blind, Independent Data Analysis Clinical Trial
Although modern medicine has made significant progress in the diagnosis and treatment of lung cancer, most patients are diagnosed at locally advanced stage or with distant metastases, especially in the late stages where the cancer has spread to other organs through hematogenous metastasis. This not only significantly the survival rate of patients but also increases the complexity and difficulty of treatment. Hematogenous metastasis plays an important role in the clinical progression of lung cancer, its complex biological processes pose a huge challenge for clinical management. Early detection of hematogenous metastasis is difficult, and traditional imaging methods have limited sensitivity in detecting small metastatic lesions. The emerging technology of circulating tumor cells (CTCs) has been limited in clinical application due to its high detection costs and technical requirements. Therefore researching and developing high-sensitivity, high-specificity, simple, easy-to-popularize, and low-cost technologies to predict the risk of hematogenous metastasis lung cancer is crucial for early diagnosis and more precise treatment. Raman spectroscopy (RS), a non-invasive and highly specific molecular detection technology, can detect in biomolecules such as proteins, nucleic acids, lipids, and sugars related to tumor metabolism in biological samples at the molecular level. Surface-enhanced R spectroscopy (SERS), developed based on this technology, is one of the feasible methods for high-sensitivity biomolecular analysis. Although SERS technology has shown diagnostic results in numerous preclinical studies of various tumors, it is limited by small sample sizes and lacks external validation. Therefore, clinical studies on the diagnosis of tumors Raman spectroscopy are needed, with the following requirements: 1. Objective, rapid, and practical Raman spectroscopy data processing methods are needed, and and deep learning methods may be the best classification methods; 2. Multicenter, large-sample clinical samples are needed to train deep learning diagnostic models, and real-world performance should be validated through external data from prospective studies. In previous study, the investigators collected serum Raman spectroscopy data from a cohort of 23 patients with lung malignancies and developed an intelligent Raman diagnostic system for hematogenous metastasis in non-small cell lung cancer (NSCLC) based on learning models, with an accuracy rate of 95%. To obtain the highest level of clinical evidence and truly achieve clinical translation, this prospective, multicenter clinical aims to validate the use of this intelligent diagnostic system for early diagnosis of hematogenous metastasis in NSCLC.
Read the detailed description
This study used a confocal Raman microspectrometer produced by Renishaw, Britain, purchased by the Key Laboratory of the School of Optoelectronics and Engineering of Fujian Normal University. The spectral resolution was 2 cm-1, the excitation wavelength was 785 nm, and a 20x objective Leica microscope was used to collect SERS spectra in the range of 400-1800 cm-1. The excitation irradiation time of each spectrum was 1 s, and the laser power was 30 mW. The measured SERS spectra were collected using the WIRE3.4 (Renishaw) software package. In order to reduce the interference of fluorescence background signals between different spectral lines, the Vancouver Raman Algorithm software (multi-order polynomial fitting algorithm) was used to remove the fluorescence background, remove the baseline and smooth the results. At the same time, in order to avoid changes in peak spectrum intensity caused by instrument performance problems, the spectrum after background subtraction was normalized using NILabVIEW2014 software. Then, the obtained spectral data was analyzed for mean spectrum and charts using Origin, and multivariate statistical analysis was performed.
- Conditions
- Lung Cancers
- Being tested
- Serum Raman spectroscopy intelligent diagnostic system
- Keywords
- SERS, NSCLC, Raman, diagnostic model
- Medical subject headings
- Lung Neoplasms
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Serum Raman spectroscopy intelligent diagnostic systemDiagnostic test
- Screening interested participants should sign the appropriate informed consent (ICF) prior to completion any study procedures. 2. The investigator will review symptoms, risk factors, and other non-invasive inclusion and exclusion criteria. 3. The following is the general sequence of events during the 3 months evaluation period: 4. Completion of baseline procedures Participants were assessed for 3 months and completed all safety monitoring.
| Study group | Role | What they receive |
|---|---|---|
| Patients who underwent chest CT scans and were found to have lung nodules | Patients who underwent chest CT scans and were found to have lung nodules and underwent surgical resection Receives: Diagnostic Test: Serum Raman spectroscopy intelligent diagnostic system |
What is being measured
The primary outcome is the main question the study is designed to answer.
Diagnostic accuracy
Determine whether there is hematogenous metastasis in enrolled lung cancer patients through RAMAN intelligent diagnostic system
Measured: through study completion, an average of 1 year
Time to RAMAN diagnosis
The time to perform RAMAN testing and obtain diagnostic results after obtaining serum
Measured: up to 30 days
Secondary outcomes (1)
Safety assessment Results
AEs and SAEs through Day 30
Measured: up to 30 days
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted13 Jan 2025
- Study start9 Apr 2026 (estimated)
- Primary completion1 Jun 2026 (estimated)
- Study completion1 Jun 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Lung CancersStudies 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
- 200 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Fuzhou General Hospital
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06772363
- Sponsor's protocol ID
- 2024-044
- Status last verified
- Mar 2025
- First submitted
- 4 Jan 2025
- Last updated
- 31 Mar 2025
- Results posted
- No
- Data monitoring committee
- Yes
- 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 31 Mar 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- SERS-Based Serum Molecular Spectral Screening for Hematogenous Metastasis vs. Non-Metastasis in Non-Small Cell Lung Cancer: A Multicenter, Open-Label, Double-Blind, Independent Data Analysis Clinical Trial
- ClinicalTrials.gov ID
- NCT06772363
- Acronym / sponsor ID
- 2024-044
- Conditions
- Lung Cancers
- Keywords
- SERS, NSCLC, Raman, diagnostic model
- Study type
- Observational
- Recruitment status
- Not yet recruiting
- Enrolment
- 200 participants (estimated)
- Lead sponsor
- Fuzhou General HospitalUniversity, hospital or other
- Study start
- 9 Apr 2026 (estimated)
- Primary completion
- 1 Jun 2026 (estimated)
- Study completion
- 1 Jun 2026 (estimated)
- First posted
- 13 Jan 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.
Although modern medicine has made significant progress in the diagnosis and treatment of lung cancer, most patients are diagnosed at locally advanced stage or with distant metastases, especially in the late stages where the cancer has spread to other organs through hematogenous metastasis. This not only significantly the survival rate of patients but also increases the complexity and difficulty of treatment. Hematogenous metastasis plays an important role in the clinical progression of lung cancer, its complex biological processes pose a huge challenge for clinical management. Early detection of hematogenous metastasis is difficult, and traditional imaging methods have limited sensitivity in detecting small metastatic lesions. The emerging technology of circulating tumor cells (CTCs) has been limited in clinical application due to its high detection costs and technical requirements. Therefore researching and developing high-sensitivity, high-specificity, simple, easy-to-popularize, and low-cost technologies to predict the risk of hematogenous metastasis lung cancer is crucial for early diagnosis and more precise treatment. Raman spectroscopy (RS), a non-invasive and highly specific molecular detection technology, can detect in biomolecules such as proteins, nucleic acids, lipids, and sugars related to tumor metabolism in biological samples at the molecular level. Surface-enhanced R spectroscopy (SERS), developed based on this technology, is one of the feasible methods for high-sensitivity biomolecular analysis. Although SERS technology has shown diagnostic results in numerous preclinical studies of various tumors, it is limited by small sample sizes and lacks external validation. Therefore, clinical studies on the diagnosis of tumors Raman spectroscopy are needed, with the following requirements: 1. Objective, rapid, and practical Raman spectroscopy data processing methods are needed, and and deep learning methods may be the best classification methods; 2. Multicenter, large-sample clinical samples are needed to train deep learning diagnostic models, and real-world performance should be validated through external data from prospective studies. In previous study, the investigators collected serum Raman spectroscopy data from a cohort of 23 patients with lung malignancies and developed an intelligent Raman diagnostic system for hematogenous metastasis in non-small cell lung cancer (NSCLC) based on learning models, with an accuracy rate of 95%. To obtain the highest level of clinical evidence and truly achieve clinical translation, this prospective, multicenter clinical aims to validate the use of this intelligent diagnostic system for early diagnosis of hematogenous metastasis in NSCLC.
Detailed description
This study used a confocal Raman microspectrometer produced by Renishaw, Britain, purchased by the Key Laboratory of the School of Optoelectronics and Engineering of Fujian Normal University. The spectral resolution was 2 cm-1, the excitation wavelength was 785 nm, and a 20x objective Leica microscope was used to collect SERS spectra in the range of 400-1800 cm-1. The excitation irradiation time of each spectrum was 1 s, and the laser power was 30 mW. The measured SERS spectra were collected using the WIRE3.4 (Renishaw) software package. In order to reduce the interference of fluorescence background signals between different spectral lines, the Vancouver Raman Algorithm software (multi-order polynomial fitting algorithm) was used to remove the fluorescence background, remove the baseline and smooth the results. At the same time, in order to avoid changes in peak spectrum intensity caused by instrument performance problems, the spectrum after background subtraction was normalized using NILabVIEW2014 software. Then, the obtained spectral data was analyzed for mean spectrum and charts using Origin, and multivariate statistical analysis was performed.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Patients who underwent chest CT scans and were found to have lung nodules | – | Diagnostic Test: Serum Raman spectroscopy intelligent diagnostic systemPatients who underwent chest CT scans and were found to have lung nodules and underwent surgical resection |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- The participants were diagnosed with lung malignancy through pathological examination and were able to undergo clinical staging based on TNM.
Key inclusion criteria (3 listed)
- Participants with Lung cancer meeting the criteria of TNM (Ninth Edition);
- Participants are willing to participate in this study and follow the research plan;
- Participants or legally authorized representatives can give written informed consent approved by the Ethics Review Committee that manages the website;
Key exclusion criteria (4 listed)
- Participants with concomitant other malignant tumors;
- Participants with missing baseline clinical data;
- Participants with severe underlying lung diseases (such as bronchiectasis, bronchial asthma or COPD, etc.), or those with a history of occupational or environmental exposure to dust, mines or asbestos;
- Participants who do not cooperate or refuse to participate in clinical trials at a later stage.
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 |
|---|---|---|
| Serum Raman spectroscopy intelligent diagnostic system1. Screening interested participants should sign the appropriate informed consent (ICF) prior to completion any study procedures. 2. The investigator will review symptoms, risk factors, and other non-invasive inclusion and exclusion criteria. 3. The following is the general sequence of events during the 3 months evaluation period: 4. Completion of baseline procedures Participants were assessed for 3 months and completed all safety monitoring. | Diagnostic test | Patients who underwent chest CT scans and were found to have lung nodules |
Primary outcome
Diagnostic accuracy
Time frame: through study completion, an average of 1 year
Determine whether there is hematogenous metastasis in enrolled lung cancer patients through RAMAN intelligent diagnostic system
Time to RAMAN diagnosis
Time frame: up to 30 days
The time to perform RAMAN testing and obtain diagnostic results after obtaining serum
1 secondary outcome
Safety assessment Results
Time frame: up to 30 days
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 31 Mar 2025.
- Individual participant dataSharing planned: Undecided
Related trials for Lung Cancers
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.
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 Cancers, run by Fuzhou General 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 3 inclusion and 4 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: opening soon, as of the sponsor's last update on 31 Mar 2025. 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 Zongyang Yu, Ph.D (13509327806 ext. 22859650, yuzy527@sina.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Diagnostic accuracy (time frame: through study completion, an average of 1 year). 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?
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 31 Mar 2025.