Methylome-Based Neoantigen Detection from Fusions and Deletions

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Solution Overview

Problem

Existing cancer vaccines targeting tumor-associated antigens face challenges due to immune tolerance and inefficiencies in predicting effective neoantigens, leading to high costs and time in vaccine manufacturing.

Innovation Solution

Detecting genetic fusions or deletions in circulating tumor DNA using methylome-based assays and long-read sequencing to identify neoantigens, which are then used to develop personalized or population-specific vaccines.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If traditional cancer vaccines targeting tumor-associated antigens are used, then immune response is triggered, but immune tolerance prevents effective immune activation

Engineering Contradiction:
Improveeffectiveness of cancer vaccineVSAvoidimmune tolerance
Core Design Contradiction:
ReliabilityVSObject-affected harmful factors

Solution Approach 1:

The patent extracts and isolates only the neoantigen-specific sequences from the complex tumor genome, separating them from the vast number of non-immunogenic mutations. This extraction process identifies only those mutations that are actually expressed on the tumor cell surface and have potential immunogenicity, thereby avoiding the problem of immune tolerance by focusing exclusively on tumor-specific neoantigens rather than shared tumor-associated antigens

Inventive Principle:
Principle #2Taking out (Extraction)

Solution Approach 2:

The patent applies local quality by customizing the vaccine composition for each patient based on their unique neoantigen profile. Instead of using a universal approach with tumor-associated antigens, the vaccine is tailored to contain only the specific neoantigens relevant to that patient's tumor mutations, thereby overcoming immune tolerance through personalized antigen selection

Inventive Principle:
Principle #3Local quality

2Loss of information

If comprehensive sequencing is performed to identify all mutations, then complete mutational landscape is obtained, but most mutations do not result in effective neoantigens

Engineering Contradiction:
Improvecompleteness of mutational dataVSAvoidpredictive accuracy of neoantigen effectiveness
Core Design Contradiction:
Loss of informationVSReliability

Solution Approach 1:

The patent performs preliminary filtering and prioritization of mutations before vaccine design. It uses bioinformatic algorithms to predict which mutations are likely to be immunogenic based on features such as predicted T-cell epitope binding affinity, mutation type (e.g., frameshifts, insertions/deletions), and expression levels. This preliminary action reduces the vast number of sequenced mutations to a focused set of high-probability neoantigen candidates

Inventive Principle:
Principle #10Preliminary action

Solution Approach 2:

The patent employs feedback mechanisms through iterative bioinformatic analysis where predicted neoantigen candidates are evaluated against multiple criteria including MHC binding predictions, peptide stability calculations, and comparison with known immunogenic mutation patterns. This feedback loop refines the selection process to identify only those mutations with highest likelihood of producing effective neoantigens

Inventive Principle:
Principle #23Feedback

3Adaptability or versatility

If neoantigen vaccines are manufactured for each patient, then personalized treatment is achieved, but cost and time for manufacture are significant

Engineering Contradiction:
Improvepersonalization of cancer vaccineVSAvoidvaccine manufacturing time
Core Design Contradiction:
Adaptability or versatilityVSLoss of time

Solution Approach 1:

The patent segments the vaccine development process into modular components: (1) rapid sequencing and mutation identification, (2) bioinformatic prediction and prioritization of neoantigens, (3) selection of top candidates based on immunogenicity scores, and (4) accelerated manufacturing of the finalized vaccine composition. This segmentation allows parallel processing and reduces overall development time while maintaining personalization

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

The patent applies partial action by selecting and focusing on only the top predicted neoantigen candidates (e.g., top 3-5 highest-scoring neoantigens) rather than including all possible mutations. This selective approach reduces the complexity and manufacturing burden while still providing comprehensive coverage of the patient's tumor-specific antigens, thereby reducing manufacturing time and cost

Inventive Principle:
Principle #16Partial or excessive action

Data Source

PatentUS20250302935A1Detection of a genetic fusion or deletion that results in expression of a neoantigen
Publication Date: 2025.10.02 FLAGSHIP PIONEERING INNOVATIONS VI LLC
  • US20250302935A1 patent drawing
  • US20250302935A1 patent drawing
  • US20250302935A1 patent drawing

AI summary

The invention provides methods of detecting a sequence modification (e.g., a genetic fusion or deletion) associated with cancer development that results in expression of a neoantigen. The neoepitope serves as the basis for manufacture of a vaccine, which is administered to a subject to induce an immune response against those cells producing the neoantigen.