Tumor Copy Number Analysis for Doxorubicin Resistance Prediction
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Solution Overview
Problem
Current methods for predicting treatment response in cancers with high chromosomal instability, such as ovarian cancer, are inadequate due to low recurrent oncogenic mutations and complex genomic profiles, leading to ineffective targeted therapies like doxorubicin.
Innovation Solution
Analyze the tumor copy number profile to identify the presence of focal amplifications, characterized by specific copy number features, to predict resistance to chemotherapies that induce micronuclei formation, such as doxorubicin.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If gene panel-based tests are used to identify actionable mutations in cancers with high chromosomal instability, then targeted agents can be selected, but the tests frequently produce false positives due to complex genomic profiles
Solution Approach 1:
The patent extracts and focuses on specific copy number features (segment size, copy number change-point, segment copy number) from the complex genomic profile, separating the predictive signal from the noise of other genomic variations. This extraction approach allows identification of focal amplifications as a reliable predictor of doxorubicin resistance without being confounded by the complexity of high chromosomal instability cancers
Solution Approach 2:
The patent applies local quality by examining specific local genomic features (focal amplifications characterized by particular segment sizes, copy number change-points, and segment copy numbers) rather than relying on global genomic characteristics. This localized analysis of copy number features provides accurate prediction of treatment response despite the overall genomic complexity
2Productivity
If doxorubicin is administered to patients with high chromosomal instability cancers, then treatment coverage is comprehensive, but response rates are low due to undetected resistance mechanisms
Solution Approach 1:
The patent performs preliminary action by analyzing copy number features to predict doxorubicin resistance before treatment begins. By identifying focal amplifications through examination of segment size, copy number change-point, and segment copy number in the tumor genome, the method predicts treatment outcome in advance, allowing clinicians to avoid administering doxorubicin to patients with predicted resistance and instead select alternative therapies
Solution Approach 2:
The patent implements feedback by using tumor genomic characteristics (copy number features) to inform treatment selection. The analysis of focal amplification patterns provides feedback about the tumor's likely response to doxorubicin, creating a closed loop where genomic data directly guides therapeutic decisions to maximize response rates and minimize time on ineffective treatment
Data Source
AI summary
The present invention provides methods for predicting the treatment response of a cancer patient, using a tumour copy number profile for the patient. The method comprise analysing the copy number profile to assess whether the characteristics of at least one copy number feature are indicative of the presence of focal amplifications in the tumour genome, wherein the at least one copy number feature is selected from: copy number change-point, segment size and segment copy number. The patient is predicted as being likely to be resistant to treatment with an agent that induces the formation of micronuclei (e.g. doxorubicin) if the characteristics of the at least one copy number features are indicative of the presence of focal amplifications in the tumour genome. Also provided a related methods and systems.