Skip to content

SERS-Based Serum Molecular Spectral Detection of Invasive Lung Cancer

SERS-Based Serum Molecular Spectral Detection of Lung Cancer Microinvasion Versus Invasion Screening: A Multicenter, Open-Label, Double-Blind, Independent Data Analysis Clinical Trial

Status
Not yet recruiting
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT06775015
Enrollment
200
Registered
2025-01-14
Start date
2026-04-04
Completion date
2026-12-31
Last updated
2025-03-31

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Lung Cancer Patients

Keywords

SERS,Raman,Early screening for lung cancer,Pulmonary nodule,diagnostic model

Brief summary

Surgery is the main treatment for early lung cancer. It is worth noting that there are significant differences in postoperative prognosis and surgical methods between microinvasive cancer and early-stage invasive cancer. Micro invasive lung cancer can achieve 100% long-term survival through surgical resection, without the need for postoperative adjuvant radiotherapy. There is no need to remove lung lobes during surgery, only segmental or wedge resection is required, and systematic lymph node dissection is not recommended. Therefore, accurate prediction of preoperative and intraoperative microinvasive cancer and invasive cancer in pulmonary nodules is crucial for patients to choose surgical methods, which can significantly affect postoperative lung function retention and overall survival. Raman spectroscopy (RS), as a non-invasive and highly specific molecular detection technique, can be obtained at the molecular level to sensitively detect changes in biomolecules composed of proteins, nucleic acids, lipids, and sugars related to tumor metabolism in biological samples. The surface enhanced Raman spectroscopy (SERS) developed based on this technology is one of the feasible methods for high-sensitivity biomolecule analysis. We collected serum Raman spectroscopy data from a cohort of 138 early lung cancer patients in our preliminary research. Based on a machine learning model, we constructed an early lung microinvasive cancer and invasive cancer Raman intelligent diagnosis system, which achieved an accuracy rate of 89.4%. To obtain the highest level of clinical evidence and truly achieve clinical translation, this prospective, multicenter clinical study aims to validate the use of this intelligent diagnostic system for early diagnosis of lung cancer and the discrimination between microinvasive cancer and invasive cancer.

Detailed description

1. 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. Completion of baseline procedures, participants were assessed for 30 days and completed all safety monitoring. 4. After completing the baseline assessment and confirming enrollment, participants will be given 2ml of fasting venous blood.

Interventions

Serum Raman spectroscopy intelligent diagnostic system Description: 1. 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.

Sponsors

Fuzhou General Hospital
Lead SponsorOTHER

Study design

Observational model
COHORT
Time perspective
PROSPECTIVE

Eligibility

Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No

Inclusion criteria

1. Participants confirmed by chest CT to have pulmonary nodules 2. The diagnosis of participants with malignant pulmonary nodules must meet the TNM diagnostic criteria (Ninth Edition); 3. Participants are willing to participate in this study and follow the research plan; 4. Participants or legally authorized representatives can give written informed consent approved by the Ethics Review Committee that manages the website;

Exclusion criteria

1. Participants with concomitant other malignant tumors; 2. Participants with missing baseline clinical data; 3. 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; 4. Participants who do not cooperate or refuse to participate in clinical trials at a later stage.

Design outcomes

Primary

MeasureTime frameDescription
Diagnostic accuracythrough study completion, an average of 1 yearDetermine whether there is hematogenous metastasis in enrolled lung cancer patients through RAMAN intelligent diagnostic system
Time to RAMAN diagnosisup to 30 daysThe time to perform RAMAN testing and obtain diagnostic results after obtaining serum

Secondary

MeasureTime frameDescription
Safety assessment Resultsup to 30 daysAEs and SAEs through Day 30

Countries

China

Contacts

Primary ContactZongyang Yu, Ph.D
yuzy527@sina.com13509327806

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026