Antifolate Response Prediction via Gene Expression Signatures
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Solution Overview
Problem
Current antifolate treatments, such as pemetrexed, face challenges in identifying patient subpopulations that respond better to the therapy due to sensitivity to thymidylate synthase levels and variability in patient responses across approved indications.
Innovation Solution
A method involving the measurement of nucleic acid expression levels of specific biomarkers using amplification, hybridization, and sequencing assays to detect an anti-folate gene expression signature and proliferation in cancer samples, enabling the determination of an anti-folate predictive response signature for personalized treatment selection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If antifolate treatments are administered to all patients, then treatment coverage is maximized, but treatment effectiveness decreases due to variability in patient response
Solution Approach 1:
The patent segments the patient population into distinct subgroups based on gene expression profiles (e.g., high vs. low thymidylate synthase expression). This segmentation allows identification of specific patient subsets who are more likely to respond to antifolate therapy, thereby improving treatment effectiveness while accounting for response variability.
Solution Approach 2:
The patent performs preliminary gene expression analysis before administering antifolate treatment. By measuring biomarker levels (such as thymidylate synthase, dihydrofolate reductase, and other folate pathway enzymes) in advance, the method predicts which patients will respond well to therapy, allowing for personalized treatment decisions prior to drug administration.
2Measurement precision
If gene expression analysis is performed on multiple biomarkers, then prediction accuracy improves, but test complexity increases
Solution Approach 1:
The patent employs a multi-functional gene expression analysis system that can simultaneously evaluate multiple biomarkers (thymidylate synthase, dihydrofolate reductase, thymidine phosphorylase, and other folate pathway genes) using a single comprehensive assay platform. This approach maintains high prediction accuracy by analyzing multiple markers while managing test complexity through integrated methodology.
Solution Approach 2:
The patent combines multiple individual biomarker assessments into a unified gene expression signature analysis. By merging the evaluation of several biomarkers into a single composite predictive model, the method achieves improved prediction accuracy without proportionally increasing test complexity, as the combined signature provides synergistic predictive power.
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 allows for the identification of patients likely to respond to antifolate agents, optimizing treatment outcomes by tailoring therapy based on individual biomarker profiles and proliferation signatures.
Implementation Method 1
performing quantitative real time reverse transcriptase polymerase chain reaction (qRT-PCR)
Implementation Method 2
amplification, hybridization and/or sequencing assay
Data Source
AI summary
Provided herein is an antifolate predictive response signature for use in determining the response of a subject suffering from cancer to antifolate therapy. Also provided are methods and compositions for determining proliferation in a sample obtained from a subject suffering from cancer through the use of a proliferation gene signature as well as methods for predicting response of a subject suffering from cancer based on an assessment of proliferation in a sample obtained from the subject.