Phase I Study of Autologous Tumor-Draining Lymph Node-Derived Lymphocytes as Neoadjuvant Therapy for HER2-Negative Breast Cancer
- Disease/Condition
- Breast Neoplasms
- Drug/Device/Intervention
- Sentinel Lymph Node Biopsy (SLNB)
- Study type
- Interventional
- Intervention type
- procedure
- Primary sponsor
- Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University
- Location
- Guangzhou, China
- Phase
- Phase 1
- Start date
- Nov 01, 2023
- End date
- Aug 31, 2031
- Enrollment
- 24 participants
Incidence of Dose-Limiting Toxicity (DLT),Incidence of Grade≥3 Treatment-Emergent Adverse Event (TEAE)
RATIONALE: Patients with HER2-negative breast cancer not responding to initial neoadjuvant
 chemotherapy might have lower chances for a pathologic complete response (pCR) at definitive
 surgery, indicating worse prognosis. Adoptive cell therapy has demonstrated efficacy in
 advanced breast cancer, but whether the addition of adoptive cell therapy to neoadjuvant
 chemotherapy could increase the pCR rate remains unclear. Tumor-draining lymph node-derived
 lymphocytes (LNLs) that have abundant tumor-reactive T cells, but not exhausted T cells, are
 easy to produce. It is not yet known whether LNL treatment is safe and effective in patients
 with HER2-negative breast cancer not responding to neoadjuvant chemotherapy.
 
 PURPOSE: This phase I trial is mainly to investigate the safety of autologous LNL in patients
 with HER2-negative breast cancer not responding to neoadjuvant chemotherapy.
- Registry
- ClinicalTrials.gov
- Trial ID
- NCT06121570
- Type
- Non-Device Trial
Access comprehensive clinical trial information for NCT06121570 through Pure Global AI's free database. This Phase 1 trial is sponsored by Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University and is currently Recruiting. The study focuses on Breast Neoplasms. Target enrollment is 24 participants.
This page provides complete trial specifications, intervention details, outcomes, and location information. Pure Global AI offers free access to ClinicalTrials.gov data, helping medical device and pharmaceutical companies navigate clinical research efficiently.