B Cell Subset Frequency Biomarkers for Kinase Inhibitor Response Prediction
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Solution Overview
Problem
Current treatments for B cell lymphomas, particularly for chronic lymphocytic leukemia and other types of B cell lymphomas, often fail to effectively target specific patient populations, leading to limited treatment options and adverse responses in some patients.
Innovation Solution
A method involving kinase inhibitors, such as cerdulatinib, is developed to treat B cell lymphomas, where patient suitability is predicted based on baseline circulating peripheral blood B cell subset frequency distributions, identifying specific B cell subset patterns that correlate with treatment response.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If standard kinase inhibitor therapy is administered to B cell lymphoma patients, then treatment coverage is provided, but treatment efficacy varies significantly across different patient populations with limited response in some groups
Solution Approach 1:
The patent segments B cell lymphoma patients into distinct subpopulations based on circulating B cell subset frequency distributions (naïve, transitional, memory B cells). This segmentation allows identification of specific patient groups (e.g., those with elevated transitional B cells) who are more likely to respond to kinase inhibitor therapy, thereby improving treatment efficacy while acknowledging variability across different patient populations.
2Object-affected harmful factors
If kinase inhibitor treatment is provided without patient selection, then all patients receive therapy, but adverse events occur in patients unlikely to respond
Solution Approach 1:
The patent implements preliminary action by assessing circulating B cell subset frequency distributions before initiating kinase inhibitor therapy. This pre-treatment evaluation identifies patients with specific B cell profiles (e.g., elevated transitional B cell frequencies) who are more likely to benefit, allowing clinicians to select appropriate candidates and avoid adverse events in non-responders before treatment begins.
3Reliability
If treatment is tailored to specific B cell subset patterns, then treatment efficacy improves for selected patients, but complexity of treatment decision-making increases
Solution Approach 1:
The patent utilizes parameter changes by measuring frequency distributions of circulating B cell subsets (naïve, transitional, memory) as biomarkers. These quantitative parameters provide objective criteria for predicting treatment response, transforming complex biological variability into measurable indicators that guide treatment decisions with improved reliability.
Data Source
AI summary
Methods for treating B cell lymphomas are provided. B cell lymphomas patients suitable for treatments can be identified based on the baseline B cell subset frequencies. For instance, increased frequency of transitional (CD10+) B cells within total nave B cells or within total B cells predicts poor response to kinase inhibitors. By contrast, having an increased nave B cells to total B cells frequency without an increased transitional (CD10+) B cell frequency predicts good response to the kinase inhibitors. Having a decreased frequency of nave B cells of the total B cell population with a corresponding increase in frequency of memory switched and double negative B cells of the total B cell population also predicts good response to the kinase inhibitors. Once the patients are identified, the patients can be suitably treated with the kinase inhibitors such as cerdulatinib.