Predicting Immunotherapy Response in MSS Solid Tumors
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Solution Overview
Problem
There is a need to refine the prediction of response to immunotherapy in patients with solid tumors of microsatellite stability (MSS) status, as current methods are not effective in predicting the prognosis and treatment response for these patients.
Innovation Solution
A method for predicting the response to a treatment with a PD1 or PD-L1 inhibitor in patients with MSS status solid tumors, involving the quantification of CD8 and PD-L1 biological markers in a tumor sample, potentially combined with VEGF inhibitors and chemotherapeutic agents like 5-FU and oxaliplatin.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If molecular diagnosis of MSI is used to predict response to immunotherapy, then prognosis and treatment response can be predicted for MSI patients, but the method does not work effectively for MSS status patients
Solution Approach 1:
The patent changes the prediction parameters from MSI status (binary) to a multi-parameter immune profile including CD8+ T cell density, PD-L1 expression level, and their spatial relationship. This parameter transformation enables the method to work effectively for MSS patients who were previously unpredictable, thereby improving both reliability and adaptability simultaneously.
Solution Approach 2:
The patent adds new dimensions to the prediction model by incorporating spatial information (distance between CD8+ cells and PD-L1+ cells) and quantitative immune marker profiles. This dimensional expansion allows the method to capture complex tumor-immune interactions that traditional MSI testing missed, enabling accurate prediction across all patient types including MSS patients.
2Measurement precision
If traditional MSI testing is used, then the testing process is simple, but the measurement precision for predicting response in MSS patients is insufficient
Solution Approach 1:
The patent segments the immune profile into distinct measurable components: CD8+ T cell density, PD-L1 expression level, and spatial distance between these markers. By breaking down the complex immune-tumor interaction into separable, quantifiable parameters, the method achieves high measurement precision while maintaining a systematic and manageable testing framework.
Solution Approach 2:
The patent uses quantitative immunohistochemistry as an intermediary measurement tool that bridges the gap between simple tissue sampling and complex response prediction. This intermediary method provides precise, objective measurements of immune marker expression and spatial relationships, enabling accurate prediction without requiring complex multi-omics approaches.
3Reliability
If personalized treatment adjustment is made based on immune markers, then treatment effectiveness improves, but the treatment protocol complexity increases
Solution Approach 1:
The patent introduces dynamic treatment adjustment based on quantified immune marker levels and spatial relationships. Instead of a static one-size-fits-all protocol, the treatment plan adapts to each patient's specific immune profile (e.g., adjusting PD-L1 inhibitor dosage or combination therapy based on measured CD8+ and PD-L1 levels), thereby improving effectiveness while managing complexity through data-driven decision making.
Data Source
AI summary
The present invention relates to methods for predicting response to an immunotherapeutic treatment in a patient with a cancer.