Cancer Diagnosis via Codon Context Analysis of Somatic Mutations
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Solution Overview
Problem
Current methods lack accuracy in determining the likelihood of targeted somatic mutagenesis and identifying causative mutagenic agents, which is crucial for diagnosing cancer and developing appropriate treatment protocols.
Innovation Solution
Developing methods to analyze the sequence of nucleic acid molecules to determine the codon context of mutations, identifying motifs targeted by mutagenic agents, and assessing the likelihood of targeted somatic mutagenesis by analyzing the frequency and position of specific mutations, such as G>A or C>T mutations in specific motifs like GYW or CG, to determine the involvement of agents like AID, APOBEC3G, or aflatoxin.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current methods are used to determine the likelihood of targeted somatic mutagenesis, then the diagnostic process can be completed, but the accuracy in identifying causative mutagenic agents is insufficient
Solution Approach 1:
The method segments the analysis by dividing mutations into different codon contexts (first, second, and third positions) and analyzing each position separately. This segmentation allows for more precise determination of targeted somatic mutagenesis by examining the specific positional distribution of mutations rather than treating all mutations uniformly, thereby improving measurement precision while preserving information about causative agents.
Solution Approach 2:
The invention applies local quality by assigning different analytical approaches to different codon positions. Mutations at the first codon position are analyzed differently from those at the second or third positions, with specific statistical thresholds applied to each position. This localized analysis improves accuracy in determining targeted mutagenesis while maintaining detailed information about the specific mutagenic patterns.
2Reliability
If comprehensive analysis of all mutations is performed, then complete diagnostic information is obtained, but the complexity of the diagnostic method increases
Solution Approach 1:
The method extracts only the relevant information needed for diagnosis by focusing specifically on codon position distribution of mutations. Rather than analyzing all mutation properties equally, the invention extracts and analyzes the positional context of mutations within codons, which provides sufficient diagnostic reliability while simplifying the overall analytical complexity by ignoring less relevant features.
Solution Approach 2:
The invention changes the parameter of analysis from treating all mutations uniformly to analyzing mutations based on their codon position. By transforming the data into positional categories (first, second, third position mutations) and applying position-specific statistical thresholds, the method achieves comprehensive diagnostic information with a manageable analytical framework that doesn't require overly complex methodologies.
Data Source
AI summary
A method determines the likelihood that a subject has or will develop cancer. The method is based on identifying whether targeted somatic mutagenesis of a nucleic acid molecule by a mutagenic agent has occurred. The mutations are at one or more motifs recognized or targeted by the mutagenic agent such as AID, an APOBEC cytidine deaminase or aflatoxin, The nucleic acid molecule includes the whole exome. The cancer can be any of breast, prostate, liver, colon, pancreatic, skin, cervical, lymphoid, hematopoietic and ovarian cancer; and the biological sample comprises, respectively, breast, prostate, liver, colon, pancreatic, skin, cervical, lymphoid, hematopoietic or ovarian tissue or cells.