Gene Expression Analysis for Chemotherapy Effectiveness Prediction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for predicting the effectiveness of chemotherapy in breast cancer patients are inadequate, as they do not accurately differentiate between patients who will benefit from chemotherapy and those who may experience unnecessary side effects without therapeutic benefit.
Innovation Solution
A method involving the measurement and normalization of mRNA expression levels of specific genes (UBE2C, TOP2A, RRM2, FOXM1, MKI67, and BTN3A2) from breast cancer patients, combined with tumor size and lymph node metastasis staging, to calculate a BCT score that predicts chemotherapy effectiveness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If chemotherapy is administered to all breast cancer patients, then some patients may benefit from the treatment, but patients who do not respond to chemotherapy experience unnecessary side effects and pain
Solution Approach 1:
The patent applies preliminary action by measuring mRNA expression levels of specific genes (UBE2C, TOP2A, RRM2, FOXM1, MKI67, and BTN3A2) before chemotherapy administration to predict treatment response. This pre-assessment allows clinicians to identify patients likely to benefit from chemotherapy versus those who would experience side effects without therapeutic benefit, enabling informed treatment decisions before exposing patients to harmful effects
Solution Approach 2:
The patent uses gene expression profiles as an intermediary biomarker system to mediate between the patient's cancer characteristics and the chemotherapy treatment decision. The BCT score, calculated from normalized mRNA expression levels of proliferation-related genes and immune-related genes, serves as an intermediary indicator that predicts chemotherapy effectiveness without requiring actual treatment administration, thus avoiding unnecessary side effects
2Measurement precision
If gene expression analysis is performed to predict chemotherapy effectiveness, then treatment decisions can be personalized, but the complexity of the diagnostic method increases
Solution Approach 1:
The patent applies segmentation by dividing the gene expression analysis into distinct functional categories: proliferation-related genes (UBE2C, TOP2A, RRM2, FOXM1, MKI67) and immune-related genes (BTN3A2). This segmentation allows for systematic measurement and normalization of each gene's mRNA expression level, making the complex diagnostic process more manageable and interpretable while maintaining high prediction accuracy through the calculated BCT score
Data Source
Figure 1
Figure 2
Figure 3
AI summary
The present invention relates to a method of predicting the effectiveness of chemotherapy in a breast cancer patient, and more particularly, to a method for predicting the effectiveness of chemotherapy by measuring the expression levels of genes for predicting prognosis of breast cancer and a standard gene in a biological sample obtained from the breast cancer patient, and a method for predicting the difference between a patient group having a high effectiveness of chemotherapy and a patient group having a low effectiveness of chemotherapy. Therefore, the method of the present invention can accurately predict the effectiveness of chemotherapy for the breast cancer patient, and can be used for the purpose of presenting clues about the direction of breast cancer treatment in the future.