PD-L1 Biomarker Selection for Anti-SEMA4D and Checkpoint Inhibitor Therapy
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Solution Overview
Problem
Current methods for treating cancer with immunotherapy are limited by the immunosuppressive environment in tumor microenvironments, particularly due to high PD-L1 expression, which reduces the effectiveness of immune checkpoint inhibitors.
Innovation Solution
Utilizing PD-L1 status as a biomarker to select cancer patients with low PD-L1 expression for treatment with a combination of an anti-SEMA4D antibody, such as pepinemab, and an immune checkpoint inhibitor, thereby enhancing the therapeutic efficacy of immunotherapy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If immune checkpoint inhibitors are used to treat cancer, then immune response is enhanced, but effectiveness is reduced by high PD-L1 expression in tumor microenvironment
Solution Approach 1:
The patent segments the patient population based on PD-L1 expression levels (low vs. high), identifying that low PD-L1 expression patients respond better to combination therapy. This segmentation allows for targeted treatment selection, applying the combination of anti-SEMA4D antibody and immune checkpoint inhibitor specifically to the subgroup most likely to benefit, thereby improving overall treatment effectiveness while accounting for the harmful immunosuppressive environment.
2Reliability
If combination therapy with anti-SEMA4D antibody and immune checkpoint inhibitor is administered, then objective response rate and progression-free survival improve, but patient selection complexity increases
Solution Approach 1:
The patent applies preliminary action by determining PD-L1 expression status before administering the combination therapy. This pre-treatment assessment identifies suitable candidates (low PD-L1 expression patients) who are most likely to respond to the combination of anti-SEMA4D antibody and immune checkpoint inhibitor. By performing this selection step in advance, the patent simplifies the overall treatment decision-making process and ensures that the complex combination therapy is reserved for patients with the highest probability of benefit.
Data Source
AI summary
The disclosure relates to methods for treating cancer or selecting subjects for cancer treatment using low PD-L1 expression as a patient biomarker prior to treatment.