Flow Cytometry Platform for Tumor Heterogeneity Analysis
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Solution Overview
Problem
Current methods for identifying and quantifying intratumoral heterogeneity in tumors are limited by their inability to accurately resolve discrete cell sub-populations, genetic instability, and differential cell cycling, leading to challenges in developing effective cancer therapies due to late detection, drug resistance, and immune evasion.
Innovation Solution
A method involving flow cytometry that concurrently analyzes tumor regenerative hierarchies, DNA content, and cell cycle phases using vital membrane fluorophores, DNA and RNA binding dyes, and specific antibodies to resolve discrete cell fractions and quantify genetic instability and differential cycling, enabling a structured population model for tumor analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional methods (H&E staining, IHC) are used for tumor analysis, then the analysis is quick and inexpensive, but the resolution of discrete cell sub-populations is insufficient due to all-or-none analysis limitations
Solution Approach 1:
The patent segments the tumor cell population into discrete hierarchical sub-populations (cancer stem cells, progenitor cells, differentiated cells) based on DNA content and cell cycle phase. Flow cytometry enables separate quantification of each segment, resolving the heterogeneity that conventional all-or-none methods cannot detect.
Solution Approach 2:
The patent adds dimensional resolution by analyzing tumors across multiple parameters simultaneously: DNA content (ploidy), cell cycle phase (G0/G1/S/G2M), and marker expression. This multi-dimensional approach transforms the analysis from two-dimensional (present/absent) to multi-parameter resolution, enabling discrete sub-population identification.
2Reliability
If manual counting is used for IHC analysis, then reliability is improved, but subjectivity and discordance increase
Solution Approach 1:
The patent replaces manual mechanical counting with automated flow cytometry analysis. The flow cytometer automatically detects, quantifies, and analyzes thousands of cells based on fluorescent markers, eliminating human subjectivity while maintaining or improving reliability through consistent, objective measurement across large cell populations.
Solution Approach 2:
The patent creates digital copies of cell characteristics through fluorescent labeling and optical detection. Instead of manually observing and counting cells, the system creates measurable signals (fluorescence intensity, DNA content) that can be automatically analyzed by computational algorithms, ensuring reproducibility and eliminating observer bias.
3Measurement precision
If flow cytometry is used for marker quantification, then cell population quantification is improved, but cell cycle phase resolution is insufficient due to lack of G0 phase markers
Solution Approach 1:
The patent segments the cell cycle analysis by combining DNA content measurement with cell cycle-specific markers. This segmentation allows distinct identification of G0/G1 cells (2N DNA, Ki-67 negative), S-phase cells (increasing DNA, Ki-67 positive), and G2M cells (4N DNA, cyclin B1 positive), resolving the previously elusive G0 phase.
Solution Approach 2:
The patent employs a multi-functional analytical approach where flow cytometry simultaneously measures DNA content, cell cycle phase markers, and tumor-specific markers in a single assay. This universal method resolves multiple parameters (ploidy, cell cycle, heterogeneity) that previously required separate experiments, enabling comprehensive cell cycle phase resolution including G0.
4Loss of information
If single-parameter analysis is used, then the analysis is simple, but intratumor heterogeneity cannot be fully characterized
Solution Approach 1:
The patent transitions from single-parameter to multi-parameter analysis by simultaneously measuring DNA content (ploidy), cell cycle phase markers (Ki-67, cyclin B1), and tumor cell surface markers. This adds multiple dimensions to the analysis, enabling full characterization of intratumor heterogeneity across hierarchical sub-populations without losing information about genetic instability or cell cycle dynamics.
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 provides a high-resolution, quantifiable method for identifying and quantifying tumor heterogeneity, improving the understanding of tumor behavior and potential therapeutic targets, enhancing drug screening and prognosis prediction by resolving interdependent populations and their responses to treatments.
Implementation Method 1
staining or labelling a fixed and permeabilized tumour-derived single cell suspension sample with a vital membrane fluorophore
Implementation Method 2
DNA binding dye
Implementation Method 3
RNA binding dyes
Implementation Method 4
antibodies that recognize a marker expressed in G1 but not GO cell cycle phases, and antibodies recognizing a marker expressed by G2M cell cycle phase
Data Source
Figure 1~4
Figure 5~6b
Figure 7a~8b
AI summary
The present invention provides a method for concurrent resolution of the cancer stem cell (CSC) derived hierarchy, genetic instability, differentially cycling cells and host cells recruited for performing tumor growth supporting functions; and (ii) quantification, monitoring and analysis of these populations. The first level of analysis can be carried out using either CSC- and progenitor-specific markers or a marker-free approach based on label-chase to resolve the tumor regenerative hierarchy. The next level involves combinatorial quantification of differential DNA- RNA contents to identify recruited host and tumor cell variants resulted from genetic instability and differential cycling within the tumor.