Flow Cytometry Gating for Heterogeneous Tumor Cell Analysis
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Solution Overview
Problem
Flow cytometry analysis of heterogeneous tumor samples is complex due to the presence of multiple cell types, making it difficult to discern specific sub-populations like CD8 positive cells, which are often obscured in density plots, and current methods lack efficient strategies for data simplification.
Innovation Solution
A method involving homogenization, dissociation, and digital sorting or gating of tumor samples to create well-defined homogeneous populations, utilizing biomarker staining and scattering properties for efficient data analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If flow cytometry is used to analyze heterogeneous tumor samples, then comprehensive information about multiple cell types is obtained, but data complexity increases and specific sub-populations become difficult to detect
Solution Approach 1:
The patent applies segmentation by dividing the heterogeneous tumor sample into distinct cell population segments through flow cytometry analysis. Different cell types (tumor cells, immune cells, stromal cells) are segmented based on their unique characteristics detected by the flow cytometer, allowing comprehensive analysis while maintaining data organization and reducing complexity through structured categorization.
2Quantity of substance
If heterogeneous cell populations are analyzed together, then complete tumor composition is captured, but detection precision of specific sub-populations decreases
Solution Approach 1:
The patent segments the complete tumor composition into distinct cell populations based on their physical and chemical characteristics. By analyzing each segment separately with appropriate gating strategies, the detection precision of specific sub-populations is maintained while still capturing the complete tumor composition through comprehensive multi-parameter analysis.
Solution Approach 2:
The patent applies local quality by using different analysis parameters and gating strategies tailored to specific cell populations within the heterogeneous sample. Each cell type is analyzed with optimized detection parameters that enhance the measurement precision for that particular population while contributing to the overall composition analysis.
3Quantity of substance
If traditional flow cytometry methods are used for heterogeneous samples, then all cell types are detected, but data interpretation becomes difficult and time-consuming
Solution Approach 1:
The patent applies preliminary action by pre-establishing gating strategies and analysis protocols before examining the heterogeneous tumor sample. Reference ranges and population definitions are predetermined based on known cell type characteristics, which streamlines the data interpretation process and reduces the time required to analyze all detected cell types.
Solution Approach 2:
The patent uses copying by creating standardized data representations and templates for different cell populations. Once population characteristics are established for one sample type, these can be copied and adapted for similar samples, significantly reducing interpretation time while maintaining detection of all cell types.
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
Enhances data quality and simplifies the interpretation of flow cytometry data from heterogeneous tumor samples by separating immune and tumor cells, allowing for accurate quantification of biomarker-expressing cell populations and improved treatment decision-making.
Implementation Method 1
Current optical detection systems monitor changes in light scatter and fluorescence
Implementation Method 2
When a particle passes through the aperture, the resistance across the orifice increases. The increase in resistance at constant current results in an increase in voltage across the orifice
Data Source
AI summary
Disclosed herein is a method of analyzing flow cytometry data for cells derived from homogenized whole tumor samples.