Cancer Prognosis Prediction Using Marker-Negative Cell Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for predicting cancer patient prognosis are not accurate due to the limitations of detecting circulating tumor cells (CTCs) that express high levels of epithelial markers, as they do not adequately reflect the pathological state of patients, especially those with low expression of leukocyte and epithelial markers.
Innovation Solution
A method involving the concentration and optical detection of target cells with minimal leukocyte and epithelial marker expression from biological samples, using specific gravity separation and optical detection techniques to determine overall survival prognosis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If circulating tumor cells (CTCs) expressing high levels of epithelial markers are detected, then the detection method is simple and well-established, but the prediction accuracy of patient prognosis is insufficient
Solution Approach 1:
Instead of detecting cells that express epithelial markers (conventional approach), the invention inverts the detection strategy by specifically identifying cells that do not express epithelial markers and do not express leukocyte markers. This inversion allows detection of a previously overlooked cell population (mesenchymal-type CTCs) that correlates better with patient prognosis, thereby improving measurement precision without excessive complexity increase
Solution Approach 2:
The invention applies local quality by differentiating cell detection based on specific marker expression patterns. Rather than using a uniform detection approach for all tumor cells, the method specifically targets cells with low epithelial marker expression and low leukocyte marker expression, creating a localized detection strategy that improves prognosis prediction accuracy for specific cell subpopulations
2Reliability
If only epithelial marker expression is used for CTC identification, then the detection process is straightforward, but cells with low epithelial marker expression are missed
Solution Approach 1:
The invention segments the CTC detection process into multiple marker evaluation steps. Instead of relying on a single epithelial marker criterion, the method divides detection into: (1) epithelial marker expression level assessment, (2) leukocyte marker expression level assessment, and (3) combined analysis. This segmentation enables identification of diverse cell types including those with low epithelial marker expression, improving both reliability and quantity of detected cells
Solution Approach 2:
The detection method achieves universality by using multiple marker systems (epithelial markers and leukocyte markers) that can identify different cell populations. This multi-functional approach allows the same detection platform to capture various CTC subtypes with different marker profiles, increasing the quantity and diversity of detected cells while maintaining reliability
3Measurement precision
If soluble tumor antigens are used for diagnosis, then the detection method is simple, but the results do not accurately reflect patient prognosis
Solution Approach 1:
The invention replaces the biochemical detection method (soluble tumor antigen measurement) with a cellular detection approach (direct visualization and counting of marker-negative cells). This substitution transitions from measuring dissolved molecules to detecting intact cells with specific phenotypic characteristics, thereby improving prognosis correlation while managing device complexity through standardized imaging and analysis protocols
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 method allows for high-accuracy prediction of cancer patient prognosis by counting target cells that do not substantially express CD45 and epithelial markers, reflecting the pathological state and aiding in optimal treatment selection.
Implementation Method 1
the concentration step is a concentration method based on a specific gravity difference of a biological sample
Implementation Method 2
optically detecting and counting cells contained in the concentrated liquid, the cells each having cell nucleus
Data Source
AI summary
The purpose of the present invention is to provide a method for accurately predicting a cancer patient prognosis based on a count of desired cells for which expression of a leukocyte marker and an epithelial marker is hardly exhibited by detecting those cells. Provided is a method for diagnosing an overall survival prognosis for a patient suffering from cancer, the method including: a step of obtaining a concentrated solution containing desired cells by pre-treating a biological sample obtained from the patient; a step of optically detecting the concentrated cells; and a step of detecting the desired cells from the detected image, wherein an association is made with the overall survival prognosis diagnosis by counting the detected desired cells, and wherein the desired cells are cells confirmed by the existence of a cell nucleus and in which expression of a leukocyte marker and an epithelial marker is hardly exhibited.