APM Gene Panels for Predicting Immune Checkpoint Therapy Response
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Solution Overview
Problem
There is a significant unmet need for molecular diagnostic tools to detect and predict response or resistance to immune checkpoint inhibitors, a promising class of cancer therapeutics, as existing treatments vary in severity of side effects and lack effective predictive methods.
Innovation Solution
Development of gene panels comprising antigen processing machinery (APM) genes, particularly HLA class II activation-related genes (HLAGs), for predicting response to cancer therapies, including immune checkpoint inhibitors, through mutation detection and expression analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If immune checkpoint inhibitors are used as cancer therapy, then treatment effectiveness is improved, but prediction of response or resistance is insufficient
Solution Approach 1:
The patent performs mutation detection in APM genes before administering immune checkpoint inhibitors to predict treatment response. This preliminary molecular diagnostic action enables clinicians to anticipate whether a patient will respond to or resist the therapy, allowing for informed treatment decisions before the actual therapy begins.
Solution Approach 2:
The patent introduces APM gene mutation status as an intermediary biomarker that mediates between the immune checkpoint inhibitor treatment and the clinical outcome. By detecting mutations in genes like HLA-A, HLA-B, HLA-C, B2M, and TAP1, the system creates a molecular intermediary that provides predictive information about treatment response, bridging the gap between treatment administration and observed efficacy.
2Ease of operation
If existing cancer treatments are used, then treatment coverage is provided, but side effect severity varies and predictive methods are lacking
Solution Approach 1:
The patent implements a feedback mechanism where APM gene mutation detection results feed back into treatment selection decisions. The molecular diagnostic information about a patient's genetic profile is used to adjust and personalize the treatment regimen, selecting immune checkpoint inhibitors for patients with wild-type APM genes while avoiding them in patients with mutations, thereby optimizing the benefit-risk ratio.
Solution Approach 2:
The patent applies local quality by tailoring the treatment approach to each patient's specific APM gene mutation status. Instead of a uniform treatment strategy, the therapy selection is customized based on the individual's molecular characteristics, with patients having wild-type APM genes receiving immune checkpoint inhibitors and those with mutations receiving alternative treatments.
3Measurement precision
If gene panels for APM genes are developed, then prediction accuracy is improved, but diagnostic complexity increases
Solution Approach 1:
The patent segments the complex diagnostic task into a focused gene panel targeting specific APM genes (HLA-A, HLA-B, HLA-C, B2M, TAP1) rather than analyzing the entire genome. This segmentation concentrates the diagnostic effort on the most clinically relevant genes associated with immune checkpoint inhibitor response, making the complex task of genomic analysis more manageable and clinically feasible.
Solution Approach 2:
The patent extracts and isolates the specific APM genes that are most predictive of immune checkpoint inhibitor response from the vast genomic landscape. By focusing only on these key genes involved in antigen presentation and immune recognition, the patent simplifies the diagnostic process while maintaining high predictive accuracy, removing unnecessary complexity from the gene panel.
Data Source
AI summary
This disclosure generally relates to a molecular classification of cancer and particularly to molecular markers for predicting response to cancer therapy, including cancer immune therapy, and methods of use thereof.