Clinical trial NCT06833723: Development of a Multi-omics Prediction Model for Immunotherapy Response in Triple-Negative Breast Cancer Subtypes
Official title: 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
Study type: OBSERVATIONAL
Overall status: ACTIVE_NOT_RECRUITING
Conditions: Breast Neoplasms
Lead sponsor: Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences
Sponsor class: OTHER
First posted: 2025-02-19
Enrollment: 1000
Sex: FEMALE
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: COHORT
Time perspective: RETROSPECTIVE
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.

Brief 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.

Eligibility criteria: 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).

Primary outcomes:
measure: Predictive Accuracy of Immunotherapy Efficacy Model
timeFrame: 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 outcomes:
measure: Correlation Between Multi-Omics Profiles and Immunotherapy Response
timeFrame: From the date of sample collection until the end of follow-up (up to 5 years post-treatment).
Other outcomes:
Locations:
city: Hangzhou
country: China
facility: Zhejiang Cancer Hospital
state: Zhejiang
Study officials:
affiliation: Hangzhou Institute of Medicine (HIM), Chinese Academy
name: Zhewei Xu
role: PRINCIPAL_INVESTIGATOR
References: