c-MAF Gene Expression Analysis for Bone Metastasis Prediction
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Solution Overview
Problem
Current methods for predicting bone metastasis in triple-negative and ER+ breast cancers lack effective markers, leading to inadequate treatment strategies, as they do not accurately assess the risk of bone metastasis or guide personalized therapies.
Innovation Solution
The method involves determining the expression level of the c-MAF gene in breast cancer samples, comparing it to a reference value, and using c-MAF inhibitors to prevent or treat bone metastasis, with increased c-MAF expression levels indicating a higher risk of bone metastasis and poor clinical outcome.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current methods are used for predicting bone metastasis, then treatment strategies can be implemented, but the prediction accuracy and treatment personalization are insufficient
Solution Approach 1:
The patent changes the parameter being measured from general cancer markers to specifically the c-MAF gene expression level. This parameter change enables more accurate prediction of bone metastasis risk, directly resolving the contradiction between measurement precision and treatment reliability by providing a specific molecular marker that correlates with bone metastasis propensity
2Adaptability or versatility
If general treatment strategies are applied to all breast cancer patients, then treatment can be provided, but personalized therapy for bone metastasis prevention is not achieved
Solution Approach 1:
The patent applies local quality by identifying a specific molecular characteristic (c-MAF expression level) within the broader breast cancer population. This allows treatment strategies to be tailored to patients with high c-MAF expression who are at risk for bone metastasis, rather than applying uniform treatment to all patients, thereby achieving both personalization and improved prevention efficacy
3Measurement precision
If c-MAF gene expression level is determined and used for prediction, then accurate bone metastasis risk assessment is achieved, but additional testing requirements increase
Solution Approach 1:
The patent extracts the specific c-MAF gene expression measurement from the complex array of potential cancer markers. By focusing on this single extracted parameter rather than analyzing multiple markers simultaneously, the method achieves high prediction accuracy while simplifying the testing procedure and reducing complexity
Data Source
AI summary
The present invention relates to a method for the prognosis of bone metastasis in triple negative (including basal-like) breast cancer or, alternatively, ER+ breast cancer (including luminal A and B) which comprises determining if the c-MAF gene is amplified in a primary tumor sample. Likewise, the invention also relates to a method for determining the tendency to develop bone metastasis with respect to metastasis in other organs, which comprise determining the c-MAF gene expression level, amplification or translocation. The invention also relates to a method for predicting early bone metastasis in a subject suffering breast cancer. The invention also relates to a c-MAF inhibitor as therapeutic agent for use in the treatment of triple negative (including basal-like) breast cancer metastasis or, alternatively, ER+ breast cancer (including luminal A and B) metastasis. The invention relates to kits for predicting bone metastasis and predicting the clinical outcome of a subject suffering from bone metastasis. Finally, the invention relates to a method for typing of a subject suffering breast cancer and for classifying a subject from breast cancer into a cohort.