Murine Tumor Immune Gene Panel for Immunotherapy Response Prediction
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Solution Overview
Problem
Current preclinical murine models lack a robust and cost-effective assay to characterize tumor-immune interactions at a gene expression level, limiting the ability to predict which cancer patients will benefit from immunotherapies and causing unnecessary treatment costs and health risks.
Innovation Solution
A method and kit for assessing immune response in murine models by detecting the expression of a panel of at least 50 genes, using next-generation sequencing, amplification assays, hybridization assays, or microarrays, and comparing the results to a reference level to evaluate immune cell activation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a robust assay is developed to characterize tumor-immune interactions at gene expression level, then measurement precision and reliability are improved, but device complexity and cost increase
Solution Approach 1:
The assay is divided into distinct functional modules: (1) sample preparation module for isolating tumor tissue and immune cells, (2) gene expression detection module using targeted gene panels, (3) data analysis module for comparing expression levels to reference ranges. This segmentation allows each module to be optimized independently while maintaining overall system reliability.
Solution Approach 2:
The invention changes the parameter of gene expression measurement from traditional bulk tissue analysis to single-cell or micro-dissected tumor cell analysis. This parameter change enables precise characterization of tumor-immune interactions at the cellular level while using targeted gene panels to control complexity.
2Reliability
If comprehensive gene expression profiling is performed to predict immunotherapy response, then prediction accuracy is improved, but loss of time and cost increase
Solution Approach 1:
The invention extracts only the most relevant genes involved in immune response pathways from the complete genome for analysis. By focusing on a curated panel of immune-related genes rather than performing whole-transcriptome sequencing, the assay achieves reliable prediction of immunotherapy response while significantly reducing analysis time and cost.
Solution Approach 2:
Reference gene expression profiles for different immune response patterns are pre-established and stored in a database. During actual patient assessment, detected gene expression levels are rapidly compared against these pre-computed references, enabling quick prediction of immunotherapy response without requiring de novo analysis.
3Ease of operation
If traditional bulk tissue analysis is used, then ease of operation is maintained, but measurement precision of tumor-immune interactions deteriorates
Solution Approach 1:
The invention introduces micro-dissection or FACS sorting as an intermediary step between bulk tissue collection and gene expression analysis. This intermediary process separates tumor cells from immune cells and stromal components, enabling precise measurement of tumor-immune interactions while maintaining operational simplicity through standardized protocols.
Data Source
AI summary
The disclosure provides methods and compositions, e.g., kits and microarray, for assessing the immune response in a murine tumor model based on the expression of a gene panel that characterizes tumor immune interactions.