HRD Score Model Analyzes mRNA Expression Data
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Solution Overview
Problem
Current methods for predicting homologous recombination DNA repair deficiency (HRD) in cancer patients are inaccurate, particularly in identifying tumors with functional defects in HR pathways, which affects the efficacy of PARP inhibitor and platinum-based chemotherapy treatments.
Innovation Solution
A system that analyzes mRNA expression data from cancer patients using a trained HRD score model, integrating DNA mutation, copy number variation, methylation, and expression data to identify HR pathway gene activities and generate a homologous recombination DNA repair deficiency (HRD) score, enabling personalized treatment decisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If genomic signature-based approaches (mutational signatures and genomic scars) are used to estimate HRD in tumors, then HRD prediction can be performed, but the accuracy is insufficient because these signatures may not reflect current HR pathway functional status
Solution Approach 1:
The patent transitions from using static genomic signatures (mutational signatures and genomic scars) to dynamic transcriptomic parameters (mRNA expression profiles). This parameter change enables the system to detect current HR pathway functional status rather than historical genomic events, thereby improving both prediction accuracy and reflectiveness of current tumor state.
Solution Approach 2:
The patent replaces the mechanical/genomic-based detection system (sequencing-based mutational signature analysis) with a molecular expression-based system (mRNA profiling). This substitution allows real-time assessment of HR pathway function through transcriptional activity, overcoming the limitation of historical genomic markers that do not reflect current functional status.
2Ease of operation
If BRCA1/2 germline mutation testing is used to identify PARP inhibitor candidates, then treatment selection is simplified, but it excludes sporadic TNBC patients with somatic HR defects who may also benefit from PARP inhibitors
Solution Approach 1:
The patent creates a universal HRD prediction system that can identify HR-deficient tumors regardless of their etiology (germline BRCA1/2 mutations, somatic mutations, or other HR pathway defects). By using mRNA expression profiles to assess HR pathway function, the system universally applies to all TNBC patients including sporadic cases, thereby expanding adaptability while maintaining ease of operation through a single comprehensive assay.
Solution Approach 2:
The patent introduces mRNA expression analysis as an intermediary mechanism between genomic testing and treatment selection. This intermediary approach translates complex genomic information into functional HR pathway status assessment, enabling identification of PARP inhibitor candidates beyond BRCA1/2 mutation carriers while maintaining clinical simplicity through a standardized expression profiling workflow.
3Adaptability or versatility
If multiple HRD prediction models (HRDetect, SigMA, Myriad myChoice) are developed and used, then coverage of different tumor types is improved, but the complexity of selecting and validating the appropriate model increases
Solution Approach 1:
The patent merges the strengths of multiple existing HRD prediction approaches (HRDetect, SigMA, Myriad myChoice) into a unified mRNA expression-based system. By integrating multi-omics data analysis capabilities and using a common transcriptional profiling platform, the system achieves broad tumor type coverage while simplifying the workflow through a single standardized assay protocol, thereby reducing model selection and validation complexity.
Data Source
AI summary
A method (100) for providing a homologous recombination DNA repair deficiency (HRD) score for a cancer patient, comprising: receiving (120) information about the cancer patient, the information comprising at least mRNA expression data obtained from a tumor of the cancer patient; analyzing (130), using a trained HRD score model, the received information about the cancer patient to generate an HRD score for the cancer patient; and providing (140), via a user interface, the generated HRD score for the cancer patient.