CTC Fluorescence Classification With RNA-Preserving Fixation
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Solution Overview
Problem
Current methods for identifying and analyzing circulating tumor cells (CTCs) are limited by high false positives, damage to cells, loss of RNA, and difficulty in staining multiple biomarkers, leading to inaccurate cancer screening and therapy.
Innovation Solution
A reagent system using specific hydrophilic polymers, detergents, and chrome alum in fixing buffers, applied at low temperatures, combined with a blocking buffer to preserve cell integrity and reduce non-specific staining, followed by machine-learning analysis for accurate CTC identification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional fixatives (formaldehyde, paraformaldehyde, ethanol, methanol) are used to prepare cells for analysis, then cell fixation is achieved, but cell damage occurs, artifacts appear, autofluorescent debris is generated, ribonucleic acid is lost, and cellular membranes are disrupted
Solution Approach 1:
The patent changes the chemical parameters of the fixation process by using a novel fixative composition containing specific concentrations of formaldehyde (0.1-10%), paraformaldehyde (0.1-10%), and a blocking agent (0.1-10%) in a buffered solution at controlled pH (7.0-9.0). This parameter optimization reduces cell damage and preserves RNA while achieving reliable fixation.
Solution Approach 2:
The patent introduces a blocking agent as an intermediary substance that prevents non-specific binding of antibodies and reduces background staining. This blocking agent acts as a mediator between the fixation process and subsequent staining, reducing artifacts and improving signal-to-noise ratio without compromising cell integrity.
2Measurement precision
If conventional blocking buffers (milk, normal serum, highly purified proteins) are used to improve staining specificity, then non-specific binding is reduced, but the buffers are inadequate for rare cells, multi-antibody stains, and stains requiring greater than four fluorophores
Solution Approach 1:
The patent creates a composite blocking buffer system combining multiple components: a primary blocking agent (protein or peptide), secondary blocking agents (synthetic polymers or small molecules), and optimized salt concentrations. This composite formulation provides enhanced blocking capability that works effectively with rare cells, multiple antibodies, and high-fluorophore stains simultaneously.
Solution Approach 2:
The patent develops a universal blocking buffer formulation that serves multiple functions: blocking non-specific binding, reducing background staining, maintaining cell membrane integrity, and being compatible with various fluorophores and antibody combinations. This multi-functional buffer is specifically optimized for rare cell analysis and multi-antibody staining applications.
3Productivity
If traditional methods are used to identify CTCs using physical properties and cell-surface markers, then identification is achieved, but false positives increase and relevant pathogenic CTCs are missed
Solution Approach 1:
The patent replaces traditional mechanical/physical identification methods with advanced fluorescent imaging and machine learning algorithms. The system uses fluorescence-activated cell sorting (FACS) combined with deep learning neural networks to analyze cell images, replacing conventional physical property-based identification with computational analysis that achieves higher accuracy in detecting pathogenic CTCs.
Solution Approach 2:
The patent creates digital copies of cell images and uses machine learning models to analyze and classify CTCs. The system generates and processes numerous image copies through computational algorithms, allowing sophisticated pattern recognition and classification that exceeds human capability in identifying rare and pathogenic CTCs with high precision.
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 the ability to analyze CTCs at a molecular level, improving cancer screening and reducing the need for invasive procedures by preserving RNA and enabling clear distinction of stained features.
Implementation Method 1
A reagent system using specific hydrophilic polymers, detergents, and chrome alum in fixing buffers, applied at low temperatures
Implementation Method 2
followed by machine-learning analysis for accurate CTC identification
Implementation Method 3
fixing buffers, applied at low temperatures
Data Source
AI summary
Disclosed herein are compositions and methods of fixing and staining rare cells. Further, disclosed herein are methods of identifying circulating tumor cells (CTC). In some embodiments, the method includes: imaging a cell sample to identify a cell of interest; determining a first pixel intensity of a stained nuclear area; determining a second pixel intensity of a background area; calculating a ploidy status of the cell of interest by subtracting the second pixel intensity from the first pixel intensity; and determining whether the cell of interest is a CTC based on the ploidy status. The method may be computer implemented, such that the method uses a machine learning algorithm to identify a feature; process the feature to extract a parameter of interest; analyze the parameter of interest; and when the parameter of interest is greater than or less than a pre-determined threshold, classify the cell of interest as a CTC.