HR Positive/HER-2 Negative Breast CancerNCT07692230
MRI-Driven Precision Typing and Response Prediction in Luminal Breast Cancer
An observational study of HR Positive/HER-2 Negative Breast Cancer, run by Fudan University at 1 site in China.
Trial summary
Luminal breast cancer is characterized by marked heterogeneity, resulting in diverse treatment responses and long-term outcomes. This project aims to integrate MRI and multiomics data to achieve non-invasive molecular typing and precise response prediction. Read more about this study
- Who is it for?
- Any age, women only
- Conditions the study is for
- HR Positive/HER-2 Negative Breast Cancer
- How many people
- 2,000 participants
- Where
- 1 siteChina
- Study dates
- 6 Jan 2026to 31 Dec 2029
- How long will I take part?
- 3 Years
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages Any age
- Women only
- No healthy volunteers
- Child, Adult, Older adult
Study population: Patients with invasive luminal breast cancer (HR+/HER2-)
Who may be able to join
- Histopathologically confirmed invasive luminal breast cancer (HR+/HER2-);
- Patients who underwent breast MRI examination.
Who cannot join
- Pathological biopsy performed prior to the baseline MRI examination;
- Patients have received any form of prior treatment for the breast cancer;
- History of other malignancies;
- Incomplete or poor-quality MRI and/or pathological images;
- Missing clinical data.
Trial locations and contacts
1 site in 1 country.
China1 site
Fudan university Shanghai Cancer Center
Shanghai, Shanghai Municipality, 200032
About this study
Official title: MRI-driven Multiomics Research on Precise Typing and Response Prediction of Luminal Breast Cancer
Luminal breast cancer is characterized by marked heterogeneity, resulting in diverse treatment responses and long-term outcomes. This project aims to integrate MRI and multiomics data to achieve non-invasive molecular typing and precise response prediction. By linking imaging phenotypes with underlying molecular and pathological characteristics, the investigators will develop predictive models for treatment resistance, recurrence, and metastasis, ultimately supporting personalized treatment strategies and precision oncology.
Read the detailed description
Luminal breast cancer represents the most common type of breast cancer, characterized by its intricate tumor heterogeneity that poses a significant challenge in clinical management due to resistance to endocrine therapy and high risk of long-term recurrence. It is significant for the accurate prediction of molecular subtypes and treatment response for luminal breast cancer. Our team has previously identified four molecular subtypes and seven pivotal molecules associated with luminal breast cancer utilizing multiomics techniques. The investigators posit that the integration of MRI-driven multiomics studies holds promise in achieving precise typing and response prediction for luminal breast cancer. This project intends to use multiomics molecular subtypes and key molecules as the gold standard to extract comprehensive quantitative features from diverse regions and levels utilizing MRI, thus facilitating non-invasive diagnosis. Additionally, our approach involves correlating MRI data with multiomics information to unveil the biological significance of imaging models at both pathological and molecular levels. Finally, the investigators aim to construct response prediction models through the fusion of multi-temporal MRI features and multiomics data across various scales, enabling precise forecasts of treatment resistance, recurrence, and metastasis. This initiative aims to enhance treatment decision-making and promote application transformation. This study will include a large-scale real-world retrospective and prospective population to validate and improve the effectiveness of model.
- Conditions
- HR Positive/HER-2 Negative Breast Cancer
- Keywords
- HR positive/HER-2 negative breast cancer, Magnetic resonance imaging, Multiomics, Precise typing, Response prediction
What is being measured
The primary outcome is the main question the study is designed to answer.
Diagnostic performance of breast MRI for molecular subtyping of luminal breast cancer, with comparison to multiomics
The primary outcome is the diagnostic performance of AI-assisted analysis for molecular subtyping of luminal breast cancer on contrast-enhanced breast MRI. Quantitative radiomic features and deep learning features are extracted from DCE-MRI, followed by classification into multiomics-defined molecular subtypes. Performance metrics include sensitivity, specificity, positive predictive value, negative predictive value, accuracy, and area under the receiver operating characteristic curve (AUC). Participants must have undergone both breast MRI and multiomics profiling of tumor tissue. Performance metrics will be compared with those obtained from multiomics classification within the same participants to evaluate the relative diagnostic performance.
Measured: 1 year
Secondary outcomes (1)
Predictive Performance of Multiomics Model for Pathological Complete Response (pCR) in Luminal Breast Cancer
The model integrates multiomics data, including breast MRI, pathological features, and other relevant molecular and clinical variables, to predict pathological complete response (ypT0/is ypN0) following neoadjuvant therapy in patients with luminal breast cancer. Performance metrics include sensitivity, specificity, positive predictive value, negative predictive value, accuracy, area under the receiver operating characteristic curve (AUC), C-index, and time-dependent AUC. Participants must have undergone neoadjuvant therapy with available pathological response assessment.
Measured: 1 years
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted9 Jul 2026
- Study start6 Jan 2026
- Primary completion31 Dec 2027 (estimated)
- Study completion31 Dec 2029 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for HR Positive/HER-2 Negative Breast CancerStudies of the same condition, open and under way.
- More trials run by Fudan UniversityThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Other
- Enrolment
- 2,000 participants (estimated)
- Target duration
- 3 Years
Sponsor and investigators
- Lead sponsor
- Fudan University
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Yajia Gu, MD, Fudan University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07692230
- Sponsor's protocol ID
- 2410-Exp103-KY
- Other IDs
- 82430061
- Status last verified
- Jul 2026
- First submitted
- 26 Jun 2026
- Last updated
- 21 Jul 2026
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided
Study at a glance
From the registry record, last updated by the sponsor on 21 Jul 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- MRI-driven Multiomics Research on Precise Typing and Response Prediction of Luminal Breast Cancer
- ClinicalTrials.gov ID
- NCT07692230
- Acronym / sponsor ID
- 2410-Exp103-KY
- Conditions
- HR Positive/HER-2 Negative Breast Cancer
- Keywords
- HR positive/HER-2 negative breast cancer, Magnetic resonance imaging, Multiomics, Precise typing, Response prediction
- Study type
- Observational
- Recruitment status
- Active, not recruiting
- Enrolment
- 2,000 participants (estimated)
- Lead sponsor
- Fudan UniversityUniversity, hospital or other
- Study start
- 6 Jan 2026 (actual)
- Primary completion
- 31 Dec 2027 (estimated)
- Study completion
- 31 Dec 2029 (estimated)
- First posted
- 9 Jul 2026 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
Luminal breast cancer is characterized by marked heterogeneity, resulting in diverse treatment responses and long-term outcomes. This project aims to integrate MRI and multiomics data to achieve non-invasive molecular typing and precise response prediction. By linking imaging phenotypes with underlying molecular and pathological characteristics, the investigators will develop predictive models for treatment resistance, recurrence, and metastasis, ultimately supporting personalized treatment strategies and precision oncology.
Detailed description
Luminal breast cancer represents the most common type of breast cancer, characterized by its intricate tumor heterogeneity that poses a significant challenge in clinical management due to resistance to endocrine therapy and high risk of long-term recurrence. It is significant for the accurate prediction of molecular subtypes and treatment response for luminal breast cancer. Our team has previously identified four molecular subtypes and seven pivotal molecules associated with luminal breast cancer utilizing multiomics techniques. The investigators posit that the integration of MRI-driven multiomics studies holds promise in achieving precise typing and response prediction for luminal breast cancer. This project intends to use multiomics molecular subtypes and key molecules as the gold standard to extract comprehensive quantitative features from diverse regions and levels utilizing MRI, thus facilitating non-invasive diagnosis. Additionally, our approach involves correlating MRI data with multiomics information to unveil the biological significance of imaging models at both pathological and molecular levels. Finally, the investigators aim to construct response prediction models through the fusion of multi-temporal MRI features and multiomics data across various scales, enabling precise forecasts of treatment resistance, recurrence, and metastasis. This initiative aims to enhance treatment decision-making and promote application transformation. This study will include a large-scale real-world retrospective and prospective population to validate and improve the effectiveness of model.
Study design
- Observational model
- Cohort
- Time perspective
- Other
- Target follow-up
- 3 Years
Who may qualify
- Sex
- Female only
- Healthy volunteers
- Not accepted
- Age groups
- Child, Adult, Older adult
- Study population
- Patients with invasive luminal breast cancer (HR+/HER2-)
Key inclusion criteria (2 listed)
- Histopathologically confirmed invasive luminal breast cancer (HR+/HER2-);
- Patients who underwent breast MRI examination.
Key exclusion criteria (5 listed)
- Pathological biopsy performed prior to the baseline MRI examination;
- Patients have received any form of prior treatment for the breast cancer;
- History of other malignancies;
- Incomplete or poor-quality MRI and/or pathological images;
- Missing clinical data.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Diagnostic performance of breast MRI for molecular subtyping of luminal breast cancer, with comparison to multiomics
Time frame: 1 year
The primary outcome is the diagnostic performance of AI-assisted analysis for molecular subtyping of luminal breast cancer on contrast-enhanced breast MRI. Quantitative radiomic features and deep learning features are extracted from DCE-MRI, followed by classification into multiomics-defined molecular subtypes. Performance metrics include sensitivity, specificity, positive predictive value, negative predictive value, accuracy, and area under the receiver operating characteristic curve (AUC). Participants must have undergone both breast MRI and multiomics profiling of tumor tissue. Performance metrics will be compared with those obtained from multiomics classification within the same participants to evaluate the relative diagnostic performance.
1 secondary outcome
Predictive Performance of Multiomics Model for Pathological Complete Response (pCR) in Luminal Breast Cancer
Time frame: 1 years
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 21 Jul 2026.
- Individual participant dataSharing planned: Undecided
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
The record lists no contact. Use the official record to reach the sponsor.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of HR Positive/HER-2 Negative Breast Cancer, run by Fudan University at 1 site in China.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 2 inclusion and 5 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: under way, not looking for participants, as of the sponsor's last update on 21 Jul 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in China. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Diagnostic performance of breast MRI for molecular subtyping of luminal breast cancer, with comparison to multiomics (time frame: 1 year). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 21 Jul 2026.