ViRP Score Predicts VEGF-A Drug Response
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Solution Overview
Problem
Current methods for predicting the clinical response of patients to VEGF-A inhibitory drugs, such as bevacizumab, are inefficient and costly, as they require initial treatment dosing to assess effectiveness and can result in adverse side effects due to non-selective treatment approaches.
Innovation Solution
An in vitro method involving the analysis of gene expression levels of SYK, NOTCH1, ACACA/ACACB, TP53BP1, CDKN1A, CHEK1, BCL2, MYH9, FN1, and NDRG1 to calculate a ViRP score, which predicts responsiveness to VEGF-A inhibitory drugs before treatment, allowing for more targeted and efficient drug administration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If initial treatment dosing is administered to assess effectiveness, then clinical response prediction is achieved, but treatment costs increase and adverse side effects occur
Solution Approach 1:
The patent applies preliminary action by measuring gene expression levels (SYK, NOTCH1, ACACA, TP53BP1, CDKN1A, CHEK1, BCL2, MYH9, FN1, NDRG1) in tumor tissue samples obtained through biopsy before treatment begins. This allows the ViRP score to be calculated in advance, predicting which patients will respond to VEGF-A inhibitory drugs without requiring initial treatment dosing. The preliminary biomarker assessment eliminates the need for trial-and-error treatment approaches, thereby reducing both treatment costs and adverse side effects while maintaining reliable clinical response prediction.
2Adaptability or versatility
If non-selective treatment approaches are used, then all patients receive therapy, but adverse side effects increase due to lack of patient selection
Solution Approach 1:
The patent applies local quality by using the ViRP score to identify specific patient subgroups with particular gene expression profiles that predict responsiveness to VEGF-A inhibitory drugs. Instead of uniform treatment for all patients, the biomarker panel enables tailored selection: patients with specific expression patterns (e.g., high SYK, low NDRG1) are identified as likely responders and receive therapy, while others receive alternative treatments. This localized, precision-medicine approach maintains treatment accessibility for appropriate candidates while eliminating unnecessary exposure to adverse side effects for non-responders.
3Measurement precision
If biomarker analysis is performed before treatment, then patient selection is improved, but measurement complexity increases
Solution Approach 1:
The patent applies segmentation by dividing the complex task of predicting treatment response into a focused panel of 10 specific genes (SYK, NOTCH1, ACACA, TP53BP1, CDKN1A, CHEK1, BCL2, MYH9, FN1, NDRG1) with predetermined weights. Rather than analyzing the entire genome or proteome, the method segments the biomarker search space to only those genes with known relevance to VEGF-A pathway and cancer response. This segmented approach, implemented through the ViRP scoring system, achieves high measurement precision for patient selection while keeping the analytical system manageable and clinically feasible.
Data Source
AI summary
The present disclosure relates to biomarkers for predicting clinical response of a VEGF-A (vascular endothelial growth factor A) inhibitory drug in cancer therapy. In particular, the disclosure provides a multi-gene expression signature score named ViRP (VEGF inhibitory Response Predictor) able to predict response to a VEGF-A inhibitory drug in a patient being diagnosed with a solid cancerous tumor.