HLA-I Evolutionary Divergence Predicts Immunotherapy Response

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Solution Overview

Problem

Current cancer immunotherapy approaches, such as checkpoint inhibitors, often provide durable benefits to only a minority of patients, and there is a need for predictive methods to identify which patients will respond favorably to these treatments.

Innovation Solution

Determining a patient's HLA-I evolutionary divergence (HED) through quantifying sequence divergence between HLA class I alleles, particularly using the Grantham distance metric, to identify candidates for immunotherapy, and administering checkpoint inhibitor therapies like PD-1 or CTLA-4 blockade therapies.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If checkpoint inhibitor therapy is administered to all cancer patients, then more patients may potentially benefit from immunotherapy, but treatment costs and side effects increase for patients who will not respond

Engineering Contradiction:

Improveresponse rate to immunotherapyVSAvoidnumber of patients treated

Core Design Contradiction:

ReliabilityVSQuantity of substance

Solution Approach 1:

The patent applies preliminary action by determining HLA-I evolutionary divergence (HED) before administering checkpoint inhibitor therapy. This pre-treatment genetic assessment identifies patients with high HED who are more likely to respond favorably to immunotherapy, allowing clinicians to predict treatment outcomes in advance and avoid unnecessary treatments for patients with low HED who are unlikely to benefit.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent employs self-service by using the patient's own HLA genotype information to predict their response to immunotherapy. The HLA-I alleles are naturally present in every individual's genome, and by analyzing the evolutionary divergence between these alleles, the system enables self-prediction of treatment response without requiring external trial-and-error approaches.

Inventive Principle:

Principle #25Self-service

2Reliability

If HLA-I evolutionary divergence analysis is performed to identify suitable candidates, then treatment effectiveness improves, but diagnostic complexity and time increase

Engineering Contradiction:

Improvepredictive accuracy of immunotherapy responseVSAvoidgenotyping and analysis system

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The patent applies universality by using a single HLA genotyping approach that serves multiple purposes: it determines the patient's HLA-I alleles, calculates evolutionary divergence between alleles, predicts immunotherapy response, and can potentially inform other aspects of cancer treatment planning. This multi-functional use of the genetic analysis reduces the need for separate diagnostic tests.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Solution Approach 2:

The patent employs parameter changes by transforming raw HLA allele sequence data into a meaningful predictive parameter—evolutionary divergence (HED) score. By quantifying the genetic distance between HLA-I alleles using established metrics, the system converts complex genomic information into a simple binary classification (high vs. low HED) that directly predicts treatment response.

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS20220389102A1HLA class i sequence divergence and cancer therapy

Publication Date: 2022.12.08 MEMORIAL SLOAN KETTERING CANCER CENT

AI summary

Molecular determinants of cancer response to immunotherapy are described.