Cancer Signaling Pathway Profiling for Personalized Therapy Selection

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Solution Overview

Problem

Current therapeutic strategies for cancers such as glioma and colorectal cancer lack patient stratification, leading to suboptimal treatment outcomes, with anti-angiogenic drugs like Bevacizumab showing modest efficacy in only a fraction of patients.

Innovation Solution

A method to determine therapeutically targetable dominant signaling pathways in cancer samples by analyzing gene expression levels and calculating scores, allowing for personalized treatment protocols based on the identification of key pathways.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If anti-angiogenic drugs like Bevacizumab are used as standard treatment, then treatment coverage is improved, but treatment efficacy deteriorates because only 30-60% of patients respond and median progression-free survival reaches only 6 months

Engineering Contradiction:
Improvetreatment coverageVSAvoidtreatment efficacy
Core Design Contradiction:
Adaptability or versatilityVSReliability

Solution Approach 1:

The patent segments the glioblastoma patient population into distinct molecular subtypes based on gene expression profiles (e.g., VEGF-high, EGFR-high, PDGFRA-high subtypes). This segmentation allows identification of specific patient groups who are most likely to respond to anti-angiogenic therapy versus other targeted therapies, thereby improving treatment efficacy by matching the right therapy to the right patient subtype rather than applying uniform treatment to all patients

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

The patent performs preliminary molecular characterization of tumors through gene expression analysis before initiating treatment. By determining the dominant signaling pathway activation status in advance, clinicians can pre-select the most appropriate therapeutic strategy (anti-angiogenic, anti-EGFR, anti-PDGFRA, etc.), avoiding ineffective treatments and improving overall response rates

Inventive Principle:
Principle #10Preliminary action

2Adaptability or versatility

If gene expression analysis of multiple pathways is performed, then personalized treatment selection is improved, but diagnostic complexity increases

Engineering Contradiction:
Improvepersonalized treatment selectionVSAvoiddiagnostic complexity
Core Design Contradiction:
Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The patent extracts and focuses analysis on a specific, predefined set of key genes representing major signaling pathways (VEGF, EGFR, PDGFRA, PDGFRB, FGFR1, FGFR2, FGFR3) rather than analyzing the entire transcriptome. This extraction approach maintains comprehensive pathway coverage while simplifying the diagnostic process by limiting the number of genes to a manageable panel that can be assessed using standardized techniques

Inventive Principle:
Principle #2Taking out (Extraction)

Solution Approach 2:

The patent transforms complex gene expression data into simplified binary or categorical parameters indicating pathway activation status (e.g., high vs. low expression, activated vs. inactive). This parameter transformation converts continuous gene expression measurements into discrete clinical decision parameters that are easier to interpret and apply in routine practice

Inventive Principle:
Principle #35Parameter changes

Data Source

PatentEP4715067A2Method for identifying personalized therapeutic strategies for patients affected with a cancer
Publication Date: 2026.03.25 UNIVERSITY OF STRASBOURG
  • EP4715067A2 patent drawingFigure 1A~1C
  • EP4715067A2 patent drawingFigure 2A~2B
  • EP4715067A2 patent drawingFigure 3A

AI summary

The present invention provides a powerful tool to identify personalized therapeutic strategies. In particular, the invention provides methods for determining therapeutically targetable dominant signaling pathways in a cancer sample from a subject affected with a solid cancer, determining a treatment protocol for the subject, selecting a subject for a therapy, determining whether the subject is susceptible to benefit from a therapy, predicting clinical outcome of the subject, treating the subject and/or predicting the sensitivity of a solid cancer to a therapy.