Tumor Mutational Burden Adjustment for Low-Coverage Sequencing
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Solution Overview
Problem
Existing methods for determining tumor mutational burden (TMB) are inaccurate when tumor fraction and coverage are low, leading to erroneous reporting of TMB levels, which can have significant consequences for cancer treatment decisions.
Innovation Solution
Adjust observed mutational counts based on tumor fraction and coverage to generate sequencing parameters, determine an expected mutational fraction and distribution, and adjust the observed counts to generate an accurate TMB score, considering factors like neoantigens and haplotype-specific mutation clusters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional TMB counting methods are used, then the assay is simple to perform, but the measurement precision deteriorates when tumor fraction and coverage are low
Solution Approach 1:
The patent applies parameter changes by adjusting the TMB calculation based on tumor fraction and coverage parameters. When tumor fraction or coverage is low, the system modifies the mutation counting approach to compensate for reduced sensitivity, thereby maintaining measurement precision across varying assay conditions without complicating the overall workflow.
Solution Approach 2:
The system incorporates feedback mechanisms where observed TMB values are compared against expected values based on tumor fraction and coverage. This feedback loop allows the system to identify and correct measurement errors, ensuring accurate TMB reporting even when assay sensitivity is reduced due to low tumor fraction or coverage.
2Productivity
If observed TMB is reported without adjustment, then the reporting process is simple, but reliability deteriorates due to erroneous TMB classification
Solution Approach 1:
The system uses feedback by comparing observed TMB values against expected values derived from tumor fraction and coverage data. This allows the system to automatically adjust and reclassify TMB results, ensuring reliable TMB-High or TMB-Low classification while maintaining efficient reporting throughput.
Solution Approach 2:
The patent applies preliminary action by pre-calculating expected TMB values based on tumor fraction and coverage before final reporting. This preliminary adjustment ensures that TMB results are accurately classified from the outset, preventing erroneous TMB-Low reports for samples that should be TMB-High, thereby improving reliability without significantly impacting reporting speed.
3Measurement precision
If TMB adjustment methods are implemented, then measurement precision improves for low tumor fraction samples, but device complexity increases
Solution Approach 1:
The system manages complexity by implementing parameter-based adjustments rather than fundamentally changing the assay methodology. The TMB calculation framework is extended with adjustment parameters for tumor fraction and coverage, allowing precise measurements without requiring complex new instrumentation or methodologies.
Solution Approach 2:
The patent uses an intermediary computational framework that mediates between the raw sequencing data and the final TMB report. This intermediary layer processes the adjustment calculations based on tumor fraction and coverage, absorbing the complexity of accurate measurement while presenting simple, reliable TMB results to users.
Data Source
AI summary
Provided herein are methods for detecting tumor mutational burden (TMB) in subjects. In one aspect, the methods include determining observed mutational counts from sequence information obtained from nucleic acids in samples from the subjects and determining a tumor fraction and/or a coverage of the nucleic acids to generate sequencing parameters. The methods also include determining an expected mutational fraction and/or an expected distribution of the expected mutational fraction given the sequencing parameters to generate an expected result, and adjusting the observed mutational count given the expected result to generate an adjusted result, thereby detecting the TMB in the subject. Other aspects are directed to methods of selecting customized therapies for treating cancer in subjects, and methods of treating cancer in subjects. Yet other aspects include related systems and computer readable media used to detect TMB in subjects.