PD-L1+ EV Assessment for CAR T Cell Treatment Selection
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Solution Overview
Problem
Existing cancer immunotherapies, such as CAR T cell therapies, are ineffective in 60-70% of patients due to T cell exhaustion induced by PD-L1+ extracellular vesicles (EVs) secreted by blood cancer cells, leading to relapse within 1-2 years.
Innovation Solution
Assessing the presence or absence of a PD-L1high EV population in a cancer patient's sample to determine responsiveness to CAR T cell therapy, and administering appropriate treatments based on the assessment, including CAR T cell therapy for PD-L1low populations and alternative therapies for PD-L1high populations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If CAR T cell therapy is administered to all cancer patients, then initial response rates are achieved (70%-80% in CLL), but durable remission is only obtained in 20%-40% of patients due to T cell exhaustion induced by PD-L1+ EVs
Solution Approach 1:
The patent performs preliminary assessment of PD-L1+ EV population in patient samples before administering CAR T cell therapy. This preliminary action identifies patients at risk of T cell exhaustion, allowing for preventive measures to be taken before treatment begins, thereby improving durable remission rates by avoiding ineffective treatments.
Solution Approach 2:
The patent establishes a feedback mechanism by measuring PD-L1+ EV population levels in patient samples and using this information to guide treatment decisions. This feedback loop allows clinicians to adjust treatment strategies based on individual patient characteristics, preventing T cell exhaustion in patients with high PD-L1+ EV populations.
2Loss of information
If PD-L1+ EV population is assessed in patient samples, then treatment effectiveness can be predicted, but additional diagnostic steps and treatment complexity increase
Solution Approach 1:
The patent extracts the specific information about PD-L1+ EV population from complex patient samples using targeted detection methods. By focusing only on the relevant PD-L1+ EV population rather than analyzing all cellular components, the method obtains critical treatment responsiveness information while minimizing unnecessary diagnostic complexity.
Data Source
AI summary
This document provides methods and materials for assessing cancer. For example, methods and materials that can be used to determine if a mammal (e.g., a human) having cancer is likely to be responsive to a cancer immunotherapy (e.g., a chimeric T cell therapy) are provided. In some cases, methods and materials for treating a mammal having cancer and identified as being likely to respond to a cancer immunotherapy (e.g., a chimeric T cell therapy) are also provided.