Gene Expression Panel Predicts Chemotherapy Response
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Solution Overview
Problem
Current methods for predicting the response of breast cancer tumors to chemotherapy lack robustness and specificity, particularly for estrogen receptor-positive and HER2-negative tumors, leading to unnecessary treatments and inadequate response assessment.
Innovation Solution
A method involving the determination of gene expression levels of specific genes such as UBE2C, BIRC5, DHCR7, STC2, AZGP1, RBBP8, IL6ST, and MGP in tumor samples, followed by mathematical combination of these levels to yield a predictive score for chemotherapy response, using techniques like PCR-based methods, microarrays, or sequencing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If classical clinical factors (grading, tumor size, lymph node involvement) are used to predict chemotherapy response, then the treatment decision process is simple, but the prediction accuracy is insufficient leading to unnecessary treatments
Solution Approach 1:
The patent transitions from using classical clinical parameters (grading, tumor size, lymph node status) to measuring gene expression levels of specific markers (Ki-67, BIRC5, UBE2C, STC2, AZGP1, RBBP8, IL6ST, MGP) to predict chemotherapy response. This parameter change enables more accurate predictions while the standardized assay protocol keeps the implementation complexity manageable.
2Reliability
If gene expression analysis is performed to improve prediction accuracy, then chemotherapy response prediction improves, but the cost and complexity of testing increases
Solution Approach 1:
The patent divides the prediction task into discrete measurable components - specific gene markers (Ki-67, BIRC5, UBE2C, STC2, AZGP1, RBBP8, IL6ST, MGP) are selected and measured individually, then combined through a standardized algorithm. This segmentation makes the complex gene expression analysis manageable and reproducible in clinical settings.
Solution Approach 2:
The invention specifies exact gene expression markers and their measurement methods (qRT-PCR, RNA in-situ hybridization, or immunohistochemistry) to transform the abstract concept of gene expression analysis into a concrete, standardized protocol that improves reliability while controlling complexity.
3Adaptability or versatility
If multigene assays are used to predict chemotherapy response, then predictive capability improves, but the applicability to specific subtypes (ER-positive, HER2-negative) is limited
Solution Approach 1:
The patent tailors the gene expression panel specifically for luminal (ER-positive, HER2-negative) breast cancer subtypes, selecting markers that are particularly relevant to this population. The assay can be adapted to other subtypes by adjusting the gene panel, demonstrating local optimization for specific clinical scenarios while maintaining overall versatility.
Data Source
AI summary
A method for predicting a response to and/or benefit of chemotherapy, including neoadjuvant chemotherapy, in a patient suffering from or at risk of developing recurrent neoplastic disease, in particular breast cancer, said method comprising the steps of:(a) determining in a tumor sample from said patient the RNA expression levels of the following 8 genes: UBE2C, RACGAP1, DHCR7, STC2, AZGP1, RBBP8, IL6ST, and MGP, indicative of a response to chemotherapy for a tumor, or(b) determining in a tumor sample from said patient the RNA expression levels of the following 8 genes: UBE2C, BIRC5, DHCR7, STC2, AZGP1, RBBP8, IL6ST, and MGP; indicative of a response to chemotherapy for a tumor(c) mathematically combining expression level values for the genes of the said set which values were determined in the tumor sample to yield a combined score, wherein said combined score is predicting said response and/or benefit of chemotherapy.