DNA Sample Characterisation Through Multi-Signature Tumour Profiling

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Solution Overview

Problem

Current methods for characterizing cancer genomes focus primarily on protein-coding exons, neglecting mutations in untranslated, intronic, and intergenic regions, limiting the understanding of breast cancer's molecular pathogenesis and the role of driver rearrangements and indels in non-coding regions.

Innovation Solution

A computer-implemented method for characterizing DNA samples by determining base substitution, rearrangement, and insertion/deletion signatures, along with copy number profiles and putative driver mutations, to construct an interpreted profile of the tumor, aiding in prognosis, treatment suitability, and patient selection for clinical trials.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Loss of information

If current methods focus primarily on protein-coding exons, then the analysis is simpler and more focused, but the understanding of molecular pathogenesis and driver rearrangements in non-coding regions is limited

Engineering Contradiction:
Improveinformation on non-coding mutationsVSAvoidcomplexity of genomic analysis
Core Design Contradiction:
Loss of informationVSDevice complexity

Solution Approach 1:

The patent applies universality by using a single genomic analysis method that simultaneously analyzes both coding and non-coding regions, as well as multiple mutation types (base substitutions, insertions, deletions, rearrangements) within a unified framework. This multi-functional approach eliminates the need for separate analyses for different genomic regions and mutation types, thereby reducing information loss while managing complexity through integration.

Inventive Principle:
Principle #6Universality (Multi-functionality)

Solution Approach 2:

The patent applies segmentation by dividing the genomic analysis into distinct mutation type categories (base substitutions, insertions, deletions, rearrangements) and regional categories (coding, non-coding, regulatory elements). This structured segmentation allows comprehensive coverage of non-coding regions while organizing the complexity into manageable analytical components that can be systematically evaluated.

Inventive Principle:
Principle #1Segmentation

2Measurement precision

If comprehensive genomic analysis including non-coding regions is performed, then the understanding of molecular pathogenesis improves, but the complexity and computational requirements increase

Engineering Contradiction:
Improveprecision of molecular pathogenesis characterizationVSAvoidcomplexity of analysis system
Core Design Contradiction:
Measurement precisionVSDevice complexity

Solution Approach 1:

The patent applies parameter changes by systematically varying the scope and depth of genomic analysis parameters - analyzing different mutation types (substitutions, insertions, deletions, rearrangements), different genomic regions (coding, non-coding, regulatory), and different scales of genomic organization. This structured parameter variation enables precise characterization of molecular pathogenesis while managing complexity through controlled analytical parameters that can be adjusted based on specific research questions.

Inventive Principle:
Principle #35Parameter changes

Solution Approach 2:

The patent introduces computational frameworks and analytical intermediaries that process and integrate data from comprehensive genomic analyses. These intermediary systems organize the complex data from non-coding region analysis, rearrangement detection, and multiple mutation type characterization into coherent interpretations, thereby enabling high measurement precision while managing the inherent complexity through structured data processing layers.

Inventive Principle:
Principle #24Intermediary (Mediator)

3Reliability

If multiple mutation types and signatures are analyzed, then the characterization of tumour properties improves, but the time and computational resources required increase

Engineering Contradiction:
Improvereliability of tumour prognosisVSAvoidtime for genomic characterisation
Core Design Contradiction:
ReliabilityVSLoss of time

Solution Approach 1:

The patent applies preliminary action by performing comprehensive genomic characterization including all mutation types and signatures upfront, before clinical decision-making. This advance comprehensive analysis captures all relevant tumour properties in a single integrated assessment, ensuring high reliability of prognosis without requiring repeated or sequential analyses, thereby reducing total time investment despite the comprehensive nature of the initial analysis.

Inventive Principle:
Principle #10Preliminary action

Solution Approach 2:

The patent merges multiple mutation type analyses (base substitutions, insertions, deletions, rearrangements) and multiple signature characterizations into a unified tumour profile. This consolidation integrates what would otherwise require separate analytical processes into a single comprehensive assessment, improving reliability through holistic characterization while reducing total analysis time by eliminating redundant processing steps and enabling parallel evaluation of multiple parameters.

Inventive Principle:
Principle #5Merging (Combining)

Data Source

PatentEP3452937B1Method of characterising a DNA sample
Publication Date: 2025.10.22 GENOME RES LTD
  • EP3452937B1 patent drawingFigure 1
  • EP3452937B1 patent drawingFigure 2
  • EP3452937B1 patent drawingFigure 3A~3B

AI summary

The present invention provides methods of characterising a DNA sample obtained from a tumour to produce an interpreted profile of the tumour based on a combination of a range of tests on the tumour, the tests including a selection from: determining a catalogue of base substitution signatures which are present in the sample; determining a catalogue of rearrangement signatures which are present in the sample; determining a catalogue of insertion/deletion signatures which are present in the sample; determining the overall copy number profile in the sample and identifying putative driver mutations present in the sample.