Serum Peptide Multi-Marker Models for Breast Cancer Metastasis Detection ID: 2017-046

A novel, minimally invasive serum-based method for accurately predicting breast cancer metastasis.

Technology Overview

This technology encompasses the development of serum peptide multi-marker models that correlate with the presence of breast cancer metastasis. By evaluating serum samples from breast cancer patients, it enables the prediction of metastatic disease, thereby optimizing patient care by potentially negating the need for further treatment in certain cases. Utilizing mass spectrometry for the identification of serum biomarkers, this method offers a significant improvement over traditional diagnostic approaches.

Key Advantages

• Minimally invasive compared to tissue biopsies and imaging techniques
• Enhanced predictive power through the use of mass spectrometry and m/z properties of serum biomarkers
• Superior diagnostic power with multi-marker models over single biomarker assessments
• Potential to reduce unnecessary treatments for patients with non-metastatic breast cancer

Problems Addressed

• Need for invasive tissue biopsies and extensive imaging for metastasis detection
• Challenges in accurately predicting metastatic breast cancer through single biomarkers
• Risk of overtreatment in early-stage breast cancer patients due to lack of precise diagnostics

Market Applications

• Diagnostic laboratories and clinics specializing in cancer detection and management
• Development of diagnostic kits for breast cancer metastasis prediction
• Research institutions focusing on cancer biomarker discovery and validation
• Pharmaceutical and biotechnology companies aiming to develop personalized cancer treatment strategies

Additional Information

Technology ID: 2017-046
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Date Published: 28 March, 2025