ME-Score Prediction of Immunotherapy Response in mCRC Metastases
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Solution Overview
Problem
Current immunotherapies for metastatic colorectal cancer (mCRC) are largely unresponsive due to the unique immune microenvironment of liver metastases, and there is a need to develop a method for predicting the potential of mCRC patients to respond to immunotherapy.
Innovation Solution
A method involving the determination of the MicroEnvironment (ME) score, calculated based on the ratio of CD8+ T cells, dendritic cells, and macrophages, and optionally B cells and NK cells, to predict the responsiveness of metastases to immunotherapy, using techniques like flow cytometry and RNA-Seq to assess cell densities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If immunotherapy is administered to metastatic colorectal cancer patients, then treatment options are expanded, but response efficacy remains low due to the unique immune microenvironment of liver metastases
Solution Approach 1:
The patent applies preliminary action by calculating the ME-score using immune cell densities (CD8+ T cells, dendritic cells, macrophages, B cells, and NK cells) from biopsy samples before administering immunotherapy. This pre-treatment assessment identifies patients with favorable immune microenvironments who are more likely to respond to immunotherapy, thereby improving response efficacy while accounting for microenvironmental differences in liver metastases
2Reliability
If standard immunotherapy protocols are used, then treatment consistency is maintained, but patient response rates remain low due to heterogeneous immune microenvironments
Solution Approach 1:
The patent applies parameter changes by using the ME-score, which quantifies the immune microenvironment through specific cellular parameters (densities of CD8+ T cells, dendritic cells, macrophages, B cells, and NK cells). This scoring system transforms qualitative microenvironmental differences into measurable parameters, enabling precise prediction of immunotherapy response while maintaining consistent treatment protocols across diverse patient populations
Data Source
AI summary
The present disclosure relates to a method for predicting the response of a metastasis to immunotherapy in a metastatic colorectal cancer patient. The present disclosure also encompasses an immunotherapy for use in the treatment of a metastatic colorectal cancer in a patient in need thereof previously identified as having a metastasis responsive to immunotherapy and an immune-stimulating agent for use in the treatment of a metastatic colorectal cancer in a patient in need thereof previously identified as having a metastasis non-responsive to immunotherapy. The present disclosure also relates to a pharmaceutical composition comprising an immune-stimulating agent and retinoic acid for use in the treatment of a metastatic colorectal cancer in a patient in need thereof.