NF-kB Pathway Classifiers for Lymphoma Therapy Precision
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Solution Overview
Problem
Current treatments for lymphomas, such as rituximab, often result in toxicity and systemic immunosuppression, and patients respond differently to therapies, necessitating improved diagnostic and therapeutic methods to effectively manage NF-κB pathway activation in lymphomas.
Innovation Solution
Developing classifiers for NF-κB pathway activation by measuring gene expression patterns of p105 and p100 pathways, using specific genes like EXD3, BIRC7, and NIP7, and detecting Rel A/Rel B nuclear intensity to predict pathway activation and tailor therapies like rituximab administration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional treatments like rituximab are used for lymphomas, then therapeutic effect is achieved, but toxicity and systemic immunosuppression occur
Solution Approach 1:
The invention segments the NF-κB pathway into two distinct classification systems: p105 canonical pathway classifiers and p100 noncanonical pathway classifiers. This segmentation allows for pathway-specific treatment strategies, enabling targeted therapy that addresses the specific activated pathway while minimizing off-target effects and systemic toxicity associated with conventional non-specific treatments like rituximab.
2Ease of manufacture
If conventional treatments are applied to all lymphoma patients, then standard therapy is provided, but patient response varies due to different NF-κB pathway activations
Solution Approach 1:
The invention implements a dynamic treatment approach where the therapy is adapted based on the patient's specific NF-κB pathway activation status. By using gene expression classifiers to determine which pathway (p105 canonical or p100 noncanonical) is activated, the treatment can be dynamically adjusted to match the patient's molecular profile, thereby improving response rates compared to static conventional therapy.
Solution Approach 2:
The invention changes the therapeutic parameter from non-specific immunosuppression to pathway-specific targeted therapy. By identifying the activated pathway through gene expression profiling and administering corresponding targeted agents, the treatment parameters are optimized for each patient's specific molecular characteristics, improving overall response rates and reducing variability in patient outcomes.
3Measurement precision
If gene expression classifiers are developed for NF-κB pathways, then accurate pathway prediction is achieved, but diagnostic complexity increases
Solution Approach 1:
The diagnostic system is segmented into two separate, pathway-specific classifier sets: one for detecting p105 canonical pathway activation and another for p100 noncanonical pathway activation. This segmentation simplifies the diagnostic process by allowing clinicians to use the appropriate classifier based on the suspected pathway, rather than requiring a single complex system that attempts to detect all pathways simultaneously.
Data Source
AI summary
This disclosure relates to classifiers of NF-κB pathway activation, devices, and methods of use thereof. In certain embodiments, the disclosure relates to methods comprising measuring changes in expression of genes controlled by p105 in a sample providing a detected p105 controlled gene expression pattern. In certain embodiments, the methods further comprise measuring changes in expression of genes controlled by p100 in a sample providing a detected p100 controlled gene expression pattern. In certain embodiments, the methods further comprise the step of comparing the detected p105 controlled gene expression patterns to a predetermined gene pattern and/or the detected p100 controlled gene expression patterns to a predetermined pattern.