Gene Expression Marker System for Cancer Sensitivity Prediction
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Solution Overview
Problem
Current cancer chemotherapy lacks an effective method to predict individual patient sensitivity to anti-cancer agents like oxaliplatin, fluorouracil, and levofolinate, leading to ineffective treatments and adverse events, as existing biomarkers fail to reliably determine therapeutic response.
Innovation Solution
A marker system utilizing specific gene expression levels, particularly from genes such as ALAD, C20orf43, GDA, TMEM18, and UGT2B10, to predict sensitivity to anti-cancer agents, allowing for the calculation of best tumor response and selection of sensitivity-enhancing agents.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional biomarkers are used to predict patient sensitivity to anti-cancer agents, then treatment decisions can be made, but the prediction accuracy is insufficient leading to ineffective treatments
Solution Approach 1:
The patent segments the prediction system into multiple independent gene markers (ALAD, C20orf43, CABLES1, CDC14B, GDA, HOXB6, RPL7AP27, TMEM18, UGT2B10) that can be measured separately and then integrated. Each gene serves as an independent predictive marker, allowing for modular assessment of patient sensitivity to triplet combination anti-cancer agents.
Solution Approach 2:
The patent creates a composite biomarker system by combining multiple gene expression markers into an integrated prediction model. This composite approach uses the collective information from nine specific genes to achieve higher prediction accuracy and reliability than any single marker could provide alone.
2Measurement precision
If gene expression levels of multiple genes are measured to determine sensitivity, then prediction accuracy improves, but measurement complexity and cost increase
Solution Approach 1:
The complex measurement task is segmented into nine discrete gene targets that can be measured using standard molecular biology techniques. This segmentation allows the use of established methods like qRT-PCR or microarray analysis for each gene, making the overall complex system manageable through standardized components.
Solution Approach 2:
The patent employs universal measurement approaches that can detect multiple gene expressions simultaneously. By using multi-functional assays and standardized protocols that work across all nine gene markers, the system reduces operational complexity despite measuring multiple parameters.
3Measurement precision
If comprehensive gene expression analysis is performed, then therapeutic response can be accurately determined, but treatment time and cost increase
Solution Approach 1:
The patent performs preliminary gene expression analysis on tumor samples obtained before chemotherapy initiation. By measuring the expression levels of nine specific genes in advance, the system predicts patient sensitivity to triplet combination agents before treatment begins, eliminating the need for time-consuming trial-and-error treatment approaches.
Solution Approach 2:
The system uses readily available clinical tumor samples and established gene expression measurement techniques that are already part of routine diagnostic workflows. This self-service approach leverages existing infrastructure and samples, minimizing additional time requirements beyond standard diagnostic procedures.
Data Source
AI summary
To provide a marker for determining sensitivity of a patient to an anti-cancer agent, which marker can determine whether or not the patient has a therapeutic response to the anti-cancer agent, and novel cancer therapeutic means employing the marker.The marker for determining the sensitivity of a subject to an anti-cancer agent including oxaliplatin or a salt thereof, fluorouracil or a salt thereof, and levofolinate or a salt thereof, the marker containing one or more genes selected from the group consisting of ALAD gene, C20orf43 gene, CABLES1 gene, CDC14B gene, GDA gene, HOXB6 gene, RPL7AP27 gene, TMEM18 gene, and UGT2B10 gene.