Global Chromosomal Aberration Score for Cancer Treatment Prediction
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Solution Overview
Problem
Medical oncologists face challenges in predicting which patients will respond to anti-cancer therapies, as current methods cannot accurately determine patient responsiveness to chemotherapeutic treatments, leading to variable treatment outcomes.
Innovation Solution
A method involving the determination of a global chromosomal aberration score (GCAS) is developed, which assesses chromosomal aberrations such as allelic imbalance, loss of heterozygosity, and copy number changes in biological samples to predict the outcome of anti-cancer treatment, specifically using techniques like molecular inversion probes, SNP arrays, and next-generation sequencing to analyze chromosomal regions and their impact on treatment response.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If genomic sequencing and bioinformatics technologies are used to analyze genetic alterations in human cancers, then the ability to understand genetic elements underlying cancer is improved, but the ability to predict patient responsiveness to anti-cancer treatment remains insufficient
Solution Approach 1:
The patent extracts specific chromosomal aberration features (copy number changes, loss of heterozygosity, allelic imbalance) from the complex genomic data and focuses analysis on these key parameters. By isolating and measuring specific chromosomal regions with aberrations, the method transforms overwhelming genomic information into actionable predictive metrics that correlate with treatment response.
Solution Approach 2:
The patent changes the parameter of analysis from individual gene mutations to global chromosomal aberration patterns. By measuring copy number changes across multiple chromosomal loci and calculating a GCAS based on the number and distribution of aberrations, the method transforms qualitative genomic data into a quantitative predictive score that reliably indicates treatment responsiveness.
2Loss of information
If comprehensive genomic analysis is performed to identify all genetic alterations, then understanding of tumorigenesis mechanisms is improved, but clinical utility for predicting treatment response is hampered
Solution Approach 1:
The patent segments the genome into multiple chromosomal loci and analyzes copy number changes at each locus independently. By dividing the comprehensive genomic analysis into discrete, measurable segments (chromosomal regions with gains or losses), the method makes the data manageable and suitable for clinical prediction while retaining comprehensive information.
Solution Approach 2:
The patent creates a universal GCAS methodology that can be applied across different cancer types and treatment regimens. The same approach of measuring copy number changes at multiple chromosomal loci and calculating a standardized score can predict response to various anti-cancer therapies, making the method broadly applicable in clinical settings.
3Measurement precision
If multiple chromosomal loci are analyzed for copy number changes, then prediction accuracy is improved, but complexity of the method increases
Solution Approach 1:
The patent divides the genome into multiple chromosomal loci and analyzes copy number changes at each segment independently. This segmentation allows comprehensive coverage of the genome while maintaining manageable analysis units, improving prediction accuracy without overwhelming complexity.
Solution Approach 2:
The patent merges the results from multiple chromosomal locus analyses into a single GCAS value. By combining the number of loci with copy number changes into one integrated score, the method maintains high prediction accuracy while simplifying the final output for clinical interpretation.
Data Source
AI summary
The present invention is based, in part, on the identification of novel methods for defining predictive biomarkers of response to anti-cancer drugs.