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

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.

Study Overview

• Status: Active, not recruiting
• Conditions: Breast Neoplasms
• Intervention / Treatment: Other: Retrospective Data Collection and Analysis

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.

• Study Type: Observational
• Enrollment (Estimated): 1000

Contacts and Locations

Study Locations

• China
  • Zhejiang
    • Hangzhou, Zhejiang, China
      • Zhejiang Cancer Hospital

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: No

• Sampling Method: Non-Probability Sample

Study Population

Study Population Description:

The study population consists of female breast cancer patients who received or are expected to receive immunotherapy/neoadjuvant immunotherapy at our institution. The study is divided into two cohorts:

Retrospective Cohort (2015-2023): Includes patients who received immunotherapy/neoadjuvant immunotherapy between January 1, 2015, and September 30, 2023.

Prospective Cohort (2023-Present): Includes patients who may receive immunotherapy/neoadjuvant immunotherapy starting from October 1, 2023.

All participants are female, aged ≥ 18 years, and able to provide sufficient tumor tissue samples, blood samples, and imaging data.

Description

Inclusion Criteria:

- Female, aged ≥ 18 years.

Pathologically confirmed diagnosis of breast cancer.

Patients who received immunotherapy/neoadjuvant immunotherapy at our institution between January 1, 2015, and September 30, 2023 (retrospective cohort), or patients who may receive immunotherapy/neoadjuvant immunotherapy starting from October 1, 2023 (prospective cohort).

Availability of sufficient tumor tissue samples (e.g., fresh biopsy tissue, residual tumor tissue post-surgery).

Availability of blood samples and imaging data.

Signed informed consent (for the prospective cohort).

Exclusion Criteria:

• Male breast cancer patients.

Inability to provide sufficient tumor tissue samples or other clinical data.

Presence of severe comorbidities (e.g., active infections, severe cardiac, hepatic, or renal dysfunction) that may affect the safety assessment of immunotherapy.

Lack of signed informed consent (for the prospective cohort).

Study Plan

How is the study designed?

Number of groups / cohorts

2

Cohorts and Interventions

Group / Cohort	Intervention / Treatment
Cohort (2015-2023); This group includes breast cancer patients who were treated at our institution from January 1, 2015, to September 30, 2023, and received immunotherapy or neoadjuvant immunotherapy. Clinical samples (e.g., fresh tissue from diagnostic punctures, residual tumor tissue post-surgery, blood samples, and imaging data) from these patients will be retrospectively collected and analyzed. The data will be used to build and validate the predictive model for immunotherapy efficacy.	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.
Cohort (2023-Present); This group includes breast cancer patients treated at our institution starting from October 1, 2023, who are potential candidates for immunotherapy or neoadjuvant immunotherapy. Clinical samples (e.g., fresh tissue from diagnostic punctures, residual tumor tissue post-surgery, blood samples, and imaging data) will be prospectively collected. These samples will undergo multi-omics analysis (proteomics, transcriptomics, metabolomics) and advanced imaging techniques (imaging mass cytometry and spatial transcriptomics) to further refine and validate the predictive model for immunotherapy efficacy.	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.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Predictive Accuracy of Immunotherapy Efficacy Model	The primary outcome is the predictive accuracy of the multi-omics and multi-dimensional model in determining the efficacy of immunotherapy in breast cancer patients. The model will be evaluated based on its ability to correctly classify patients as responders or non-responders to immunotherapy using clinical outcomes (e.g., progression-free survival, overall survival) as the gold standard.	From the date of sample collection (retrospective cohort: 2015-2023; prospective cohort: 2023-present) until the end of follow-up (up to 5 years post-treatment).

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Correlation Between Multi-Omics Profiles and Immunotherapy Response	To assess the relationship between proteomic, transcriptomic, and metabolomic profiles of tumor tissue and the clinical response to immunotherapy.	From the date of sample collection until the end of follow-up (up to 5 years post-treatment).

Collaborators and Investigators

• Sponsor: Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences
• Investigators: Principal Investigator: Qin Wu, Hangzhou Institute of Medicine (HIM), Chinese Academy

Study record dates

Study Major Dates

• Study Start (Actual): April 17, 2025
• Primary Completion (Actual): December 17, 2025
• Study Completion (Estimated): November 17, 2027

Study Registration Dates

• First Submitted: February 13, 2025
• First Submitted That Met QC Criteria: February 13, 2025
• First Posted (Actual): February 19, 2025

Study Record Updates

• Last Update Posted (Actual): January 15, 2026
• Last Update Submitted That Met QC Criteria: January 14, 2026
• Last Verified: January 1, 2026

More Information

Terms related to this study

• Additional Relevant MeSH Terms: Neoplasms by Site; Neoplasms; Skin Diseases; Breast Diseases; Skin and Connective Tissue Diseases; Breast Neoplasms
• Other Study ID Numbers: HIM-1

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO
• IPD Plan Description: Due to ethical and privacy concerns, the individual participant data will not be shared outside the research team.

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No
• product manufactured in and exported from the U.S.: No