NCT06833723

Development of a Multi-omics Prediction Model for Immunotherapy Response in Triple-Negative Breast Cancer Subtypes

Construction and Validation of a Multi-omics Prediction Model to Assess Immunotherapy Efficacy in Patients With Triple-Negative Breast Cancer Subtypes Based on Genomic, Transcriptomic, Proteomic, and Immune Profiling Data

• Status: Active Not Recruiting
• Phase: —
• Study type: Observational
• Enrollment: 1,000 (estimated)
• Sponsor: Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences · Academic / Other
• Sex: Female
• Age: 18 Years
• Healthy volunteers: Not accepted

Summary

This study aims to collect clinical samples from breast cancer patients who have undergone or are expected to undergo immunotherapy at our institution. The samples, including fresh tissue from diagnostic punctures, residual tumor tissue post-surgery, blood samples, and imaging data, will be used to build a predictive model for immunotherapy efficacy. The research will employ proteomics, transcriptomics, metabolomics sequencing, imaging mass cytometry (IMC), and spatial transcriptomics to construct a multi-omics, multi-dimensional (temporal and spatial) model to predict the effectiveness of immunotherapy.

Detailed description

This research will utilize a comprehensive approach by analyzing various types of clinical samples from breast cancer patients treated with immunotherapy. The integration of proteomic, transcriptomic, and metabolomic data, along with advanced imaging techniques like IMC and spatial transcriptomics, will allow for a detailed understanding of the tumor microenvironment and its response to immunotherapy. This multi-dimensional analysis aims to enhance the accuracy of predicting immunotherapy outcomes, thereby aiding in personalized treatment strategies for breast cancer patients. The study adheres strictly to ethical guidelines, ensuring patient confidentiality and welfare are maintained throughout the research process.

Conditions

• Breast Neoplasms

Interventions

Type	Name	Description
OTHER	Retrospective Data Collection and Analysis	This is a retrospective study involving the collection and analysis of existing clinical data from breast cancer patients who received immunotherapy or neoadjuvant immunotherapy between January 1, 2015, and September 30, 2023. No new interventions are administered as part of this study. The data includes diagnostic puncture tissue, residual tumor tissue post-surgery, blood samples, and imaging data. These samples are analyzed using multi-omics approaches (proteomics, transcriptomics, metabolomics) and advanced imaging techniques (imaging mass cytometry and spatial transcriptomics) to build a predictive model for immunotherapy efficacy.

Timeline

• Start date: 2025-04-17
• Primary completion: 2025-12-17
• Completion: 2027-11-17
• First posted: 2025-02-19
• Last updated: 2026-01-15

Locations

1 site across 1 country: China