Targeted Sequencing for Faster Tumor Mutational Burden Assessment
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Solution Overview
Problem
Current methods for evaluating tumor mutational burden, such as whole exome sequencing, are costly, time-intensive, and not widely available, making them unsuitable for routine clinical practice, and existing genomic profiling techniques fail to exclude functional alterations affecting cell division, growth, or survival.
Innovation Solution
A targeted next-generation sequencing approach is used to profile a small fraction of the genome or exome, focusing on a predetermined set of genes associated with cancer, to determine mutation load by excluding functional and germline alterations, and providing a surrogate for total mutation load through hybrid capture-based methods.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If whole exome sequencing is used to measure total mutation burden, then measurement precision is improved, but cost, time consumption, and technical complexity increase
Solution Approach 1:
The patent divides the genome into specific subgenomic intervals (hotspot regions) rather than sequencing the entire exome. This segmentation approach focuses sequencing efforts on predetermined cancer-associated genes and regions, reducing the overall complexity while maintaining measurement precision for mutation burden assessment.
Solution Approach 2:
The patent applies local quality by concentrating sequencing depth and coverage on specific subgenomic intervals that are most relevant for mutation burden measurement. Rather than uniform coverage across the entire exome, the method enhances local quality in critical regions while reducing coverage elsewhere, optimizing both precision and resource efficiency.
2Measurement precision
If whole exome sequencing is used to measure total mutation burden, then measurement precision is improved, but turnaround time increases
Solution Approach 1:
By segmenting the sequencing target into specific subgenomic intervals rather than the entire exome, the patent reduces the total sequencing workload and data processing requirements. This enables faster turnaround time while preserving measurement precision through focused coverage of mutation-relevant regions.
Solution Approach 2:
The patent applies partial action by sequencing only the necessary subgenomic intervals required for accurate mutation burden measurement, rather than performing complete exome sequencing. This partial sequencing approach achieves sufficient precision for clinical decision-making while significantly reducing turnaround time.
3Measurement precision
If whole exome sequencing is used to measure total mutation burden, then measurement precision is improved, but cost increases
Solution Approach 1:
The patent segments the sequencing target into essential subgenomic intervals, reducing the quantity of sequencing reactions, reagents, and computational resources required. This segmentation maintains measurement precision by focusing on mutation-rich regions while lowering overall testing costs.
Solution Approach 2:
The patent changes the parameter of sequencing coverage from comprehensive exome-wide coverage to focused subgenomic interval coverage. This parameter change reduces the total amount of sequencing performed, thereby reducing cost while preserving the precision needed for mutation burden measurement through targeted deep sequencing of critical regions.
4Productivity
If targeted sequencing of subgenomic intervals is performed, then productivity is improved, but measurement precision may be compromised
Solution Approach 1:
The patent segments the genome into comprehensive subgenomic intervals that collectively cover all known cancer-associated genes and mutation hotspots. This segmentation enables high productivity through streamlined sequencing while maintaining measurement precision by ensuring complete coverage of all clinically relevant mutation regions.
Solution Approach 2:
The patent creates a universal panel of subgenomic intervals that serves multiple functions: it enables high-throughput sequencing for productivity, maintains comprehensive cancer gene coverage for measurement precision, and provides actionable mutation data for clinical decision-making. This multi-functional design resolves the contradiction between speed and accuracy.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach offers a faster, more manageable, and cost-effective method for evaluating mutation load, enabling simultaneous detection of actionable alterations for targeted therapies and predicting immune therapy responses, with clinically actionable predictors of treatment outcomes.
Implementation Method 1
contacting the library with a bait set to provide selected tumor members by hybridization, thereby providing a library catch
Data Source
Figure 1A
Figure 1B
Figure 1C
AI summary
Methods of evaluating tumor mutational burden in a sample, e.g., a tumor sample or a sample derived from a tumor, from a subject, are disclosed.