Size-Based Flow Cytometry Gating for Minority Cell Detection
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Solution Overview
Problem
Flow cytometry analysis of heterogeneous tumor samples is complex due to the presence of multiple cell types, leading to obscured detection of minority populations and difficulty in data interpretation.
Innovation Solution
A method of digital sorting and gating is developed to analyze heterogeneous tumor samples by homogenizing, dissociating cells, staining for biomarkers, and performing primary and secondary gatings based on scattering and marker presence, allowing for the quantification of cell populations without physical sorting.
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 interpretation becomes complex and minority cell populations are obscured
Solution Approach 1:
The patent applies segmentation by dividing the heterogeneous tumor sample analysis into distinct sequential gating steps. First, a primary gate identifies a specific cell population (e.g., immune cells) based on scattering properties. Then, within this gated population, secondary gates further segment the cells based on biomarker expression. This multi-level segmentation transforms the complex heterogeneous data into manageable, interpretable subsets while preserving comprehensive information about all cell types present in the original sample.
2Quantity of substance
If heterogeneous tumor samples are analyzed by flow cytometry, then representative information about tumor composition is provided, but detection of minority cell populations is obscured
Solution Approach 1:
The gating strategy segments the analysis into hierarchical levels, where each gate narrows down to a specific population of interest. This segmentation allows minority cell populations to be detected with high precision because the analysis focuses on enriched subsets rather than attempting to detect all populations simultaneously in the heterogeneous mixture.
Solution Approach 2:
The patent employs another dimension by using scattering properties (forward scatter and side scatter) as an additional parameter space for cell population identification. By gating on scattering characteristics first, the method creates a dimensional separation that enriches for specific cell types before biomarker analysis, thereby enhancing the detectability of minority populations that would otherwise be obscured in the heterogeneous sample.
3Manufacturing precision
If physical sorting is performed to separate cell populations, then homogeneous populations are obtained, but processing time and complexity increase
Solution Approach 1:
The patent replaces the mechanical physical sorting system with a digital/gating-based selection system. Instead of physically separating cells through sorting machinery, the invention uses software-based gating to virtually select and analyze specific cell populations from the flow cytometry data. This substitution achieves homogeneous population analysis without the time loss and complexity associated with physical sorting operations.
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
This approach enhances data quality and efficiency by providing well-defined, homogeneous cell populations for improved research and analysis, enabling accurate determination of biomarker expression and correlations between subsets.
Implementation Method 1
Current optical detection systems monitor changes in light scatter and fluorescence
Implementation Method 2
Current optical detection systems monitor changes in light scatter and fluorescence
Implementation Method 3
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Data Source
AI summary
Disclosed herein is a method of analyzing flow cytometry data for cells derived from homogenized whole tumor samples.