Better Predicting Breast Cancer Recurrence and Chemotherapy Needs
Official title: Integrating Clinical, Pathologic, and Immune Features to Predict Breast Cancer Recurrence and Chemotherapy Benefit
Funded at University of Chicago · NIH-11115736 · Data updated 2026-11-12
This project uses artificial intelligence to help predict which breast cancer patients might benefit most from chemotherapy and who is at risk for their cancer returning.
Quick facts
| Grant type | Career grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Chicago NIH-funded |
| Lab location | 1 site (Chicago, United States) |
| Project start | July 7, 2023 |
| Project end | June 30, 2028 |
| Funding year | 2025 |
| Award (this year) | $201,055 |
| NIH project number | 5K08CA283261-03 |
| Project ID | NIH-11115736 on NIH RePORTER |
Who could benefit from this research
✓Could help
Patients with hormone receptor-positive breast cancer who are considering chemotherapy would be the focus of this research.
✕Less likely to help
Patients with breast cancer types other than hormone receptor-positive may not directly benefit from this specific prediction tool.
What this research studies
Breast cancer is a common disease, and while many patients respond well to anti-estrogen therapy, some face aggressive forms that require chemotherapy to prevent recurrence. Current tests to guide chemotherapy decisions can be expensive and slow, leading to delays in treatment or limited access. This project aims to develop a new, faster, and more affordable method using artificial intelligence to analyze routine biopsy images. By looking at these images, the AI can help doctors understand a patient's risk of recurrence and whether chemotherapy would be truly beneficial. This could lead to more personalized and timely treatment plans for breast cancer patients.
Why it matters
Potential benefit: If successful, this could provide a faster, more affordable, and more accurate way to decide if chemotherapy is needed for breast cancer patients, potentially reducing treatment delays and costs.
How similar studies have gone: While existing gene expression tests predict recurrence, this approach uses deep learning on pathology images to offer a novel, potentially more accessible, and refined prediction method.
Where this research is happening
-
University of Chicago
Chicago, United States Active
Researchers
- Principal investigator: Howard, Frederick Matthew — University of Chicago
- Study coordinator: Howard, Frederick Matthew
Related research
Other NIH-funded projects on the same topics.
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Predicting breast cancer recurrence and chemotherapy need using pathology images and AI
A doctor-scientist at a major university is developing an AI-based tool that uses pathology slides to predict which breast cancer patients will benefit from chemotherapy.
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Using advanced technology to predict breast cancer recurrence and chemotherapy benefits
This study is looking to help doctors better predict if breast cancer might come back and how well chemotherapy will work by using advanced computer techniques to analyze tissue samples, making it easier and more affordable for patients to understand their treatment options.
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A 3D ultrasound scanner to see early chemotherapy response in breast cancer
A new 3D ultrasound imaging method will be tested to see if it can quickly show whether breast cancer is responding to chemotherapy.
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Gene expression marks high risk for very late breast cancer return
A patient-focused study aims to find gene patterns that identify women with early breast cancer who are most likely to have cancer come back more than a decade later.
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Using gene expression to identify patients at high risk for late breast cancer recurrence
Researchers are studying breast cancer patients to find gene patterns that predict who might have cancer come back many years later, so doctors can tailor care for those at highest risk.
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Gene tests to find women at high risk of breast cancer returning many years later
This project looks for patterns in tumor gene activity to spot women with ER-positive breast cancer who are more likely to have the cancer come back more than 10 years after initial treatment.
About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page.