Immunotherapy, Lung Neoplasms, Minimal Residual Disease, Neoadjuvant Therapy
Conditions
Keywords
NSCLC, Neoadjuvant immunotherapy, Perioperative monitoring, Liquid biopsy, MRD, Minimal residual disease, Multiple omics
Brief 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 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.
Interventions
None listed
Sponsors
Peking University People's Hospital
Study design
Observational model
COHORT
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to 85 Years
Healthy volunteers
No
Inclusion criteria
1. Signed written informed consent. 2. Male or female, aged ≥ 18 and \< 85 years. 3. Radical resection performed, pathologic stage IB-IIIA (8th TNM) non-small-cell lung cancer. 4. Tumor tissue and blood samples obtainable at all protocol-specified time-points. 5. No pure ground-glass nodule on imaging. 6. Completed standard neoadjuvant immunotherapy combined with platinum-based chemotherapy.
Exclusion criteria
1. Postoperative pathology shows other than NSCLC, including but not limited to benign lesions, small-cell carcinoma, metastasis, or indeterminate/inadequate histology. 2. Insufficient or poor-quality blood or tissue samples. 3. Pure ground-glass nodule on imaging. 4. History of any malignancy within the past 5 years. 5. Contraindication to surgery preventing radical resection. 6. Non-radical (R2) resection. 7. Pathologic stage IIIB-N3, IIIC, or IV on paraffin sections. 8. Refusal or withdrawal of informed consent. 9. Any condition deemed unsuitable by the investigator (e.g., perioperative blood transfusion, severe psychiatric disorder precluding follow-up).
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| Two-year recurrence-free survival rate | Time from curative surgery to confirmation of clinical progression (recurrence or metastasis) within two years |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Overall survival | Time from curative surgery to confirmation of death (any cause)，assessed up to 60 months. | — |
| Timely diagnosis rate by the novel MRD monitoring technique | two years | 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. |
Countries
China
Contacts
CONTACTKezhong Chen
CONTACTYue He
Outcome results
None listed