Multigene Expression Scoring for Chemotherapy Benefit Prediction

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Solution Overview

Problem

Current methods for predicting chemotherapy benefit in breast cancer patients, particularly those with luminal tumors, lack clear indicators due to incomplete validation studies and reliance on clinical factors alone, leading to uncertainty in treatment decisions and potential overuse of chemotherapy.

Innovation Solution

A method involving the determination of RNA expression levels of specific genes (UBE2C, BIRC5, DHCR7, STC2, AZGP1, RBBP8, IL6ST, and MGP) combined with clinical values such as tumor size and nodal status to generate a combined score, which predicts chemotherapy response and benefit, using techniques like PCR, microarray, or next-generation sequencing.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If clinical factors alone (grading, tumor size, lymph node involvement) are used to predict chemotherapy benefit, then the treatment decision process is simple, but the prediction accuracy is insufficient leading to uncertainty in treatment decisions

Engineering Contradiction:

Improveprediction accuracyVSAvoidtest complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The patent combines gene expression data from multigene assays with clinical factors (tumor size, nodal status, grading) to create a composite predictive model. This merging of molecular and clinical information resolves the contradiction by achieving high prediction accuracy through integrated analysis while maintaining clinical applicability through a structured scoring system.

Inventive Principle:

Principle #5Merging (Combining)

Solution Approach 2:

The patent transforms gene expression levels into standardized scores that can be mathematically combined with clinical parameters. By changing the parameter representation from raw gene expression values to normalized scores, the system achieves precise predictions while keeping the computational process manageable for clinical use.

Inventive Principle:

Principle #35Parameter changes

2Measurement precision

If multigene assays are used to predict chemotherapy response, then prediction accuracy improves, but the ability to generalize across different tumor subtypes (especially ER-positive tumors) is limited

Engineering Contradiction:

Improvechemosensitivity predictionVSAvoidapplicability across tumor subtypes

Core Design Contradiction:

Measurement precisionVSAdaptability or versatility

Solution Approach 1:

The patent develops a predictive model that functions universally across different breast cancer subtypes by integrating both molecular (gene expression) and clinical parameters. The combined score system is designed to be applicable to ER-positive, ER-negative, and HER2-positive tumors, making the test multi-functional rather than subtype-specific.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Solution Approach 2:

The patent allows the predictive model to adapt to local characteristics of different tumor subtypes through the interaction between gene expression profiles and clinical factors. The gene expression data captures subtype-specific molecular features while clinical parameters provide context-specific information, creating a tailored prediction for each patient's tumor characteristics.

Inventive Principle:

Principle #3Local quality

3Reliability

If chemotherapy is applied to luminal tumors based on clinical factors alone, then treatment coverage is broad, but unnecessary chemotherapy exposure increases due to lack of clear predictive indicators

Engineering Contradiction:

Improvetreatment benefit identificationVSAvoidchemotherapy side effects

Core Design Contradiction:

ReliabilityVSObject-affected harmful factors

Solution Approach 1:

The patent uses gene expression data as molecular feedback to refine chemotherapy decision-making. By measuring the expression levels of specific genes and combining them with clinical factors, the system provides feedback on the likelihood of chemotherapy benefit, enabling more reliable identification of patients who will truly benefit from treatment while avoiding unnecessary exposure for those who won't respond.

Inventive Principle:

Principle #23Feedback

Applied Scientific Principles

This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.

Function Achieved in This Case

This approach provides a more accurate prediction of chemotherapy benefit, allowing for tailored treatment strategies by identifying patients who will benefit from chemotherapy, reducing unnecessary side effects and improving treatment outcomes.

Implementation Method 1

using techniques like PCR, microarray, or next-generation sequencing

Methodology Applied

Scientific EffectPCR (Polymerase Chain Reaction):

Implementation Method 2

using techniques like PCR, microarray, or next-generation sequencing

Methodology Applied

Scientific EffectMicroarray hybridization:

Implementation Method 3

using techniques like PCR, microarray, or next-generation sequencing

Methodology Applied

Scientific EffectNext-generation sequencing:

Data Source

PatentUS12180551B2Method of using biomarkers and clinical variables for predicting chemotherapy benefit

Publication Date: 2024.12.31 EUROBIO SCIENTIFIC GMBH

AI summary

Provided herein are methods for predicting chemotherapy benefit. The invention predicts chemotherapy benefit based on the expression analysis of biomarkers, e.g., RNA biomarker transcription analysis, taken from a tumor sample. The biomarker expression data can be combined with clinical variables, e.g., tumor size and nodal status, to generate a profile that predicts the benefit of including chemotherapy as a treatment decision.