Gene Expression Tumor Grading for Breast Cancer Recurrence Risk
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Solution Overview
Problem
Existing genome-wide expression profiling studies for breast cancer prognosis yield overlapping prognostic information, and combining multiple signatures does not significantly improve predictive accuracy, suggesting a redundancy in proliferation-related genes, while simpler assays are needed for more accurate prognosis.
Innovation Solution
Identification of a 5-gene tumor grade signature (MGI) comprising Bub1B, CENPA, NEK2, RACGAP1, RRM2, and optionally HoxB13:IL17BR ratio, which can recapitulate tumor grade and predict clinical outcome, providing prognostic and predictive information for cancer recurrence and treatment response.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If multiple gene signatures are combined for cancer prognosis, then prognostic information coverage is improved, but predictive accuracy does not significantly improve and complexity increases
Solution Approach 1:
The patent extracts only the most critical proliferation-related genes from genome-wide expression profiling to create a simplified signature. Instead of using multiple overlapping signatures, the invention identifies and isolates the core genes (such as those in the 70-gene signature and 97-gene genomic grade index) that provide the essential prognostic information, eliminating redundant genes and signatures while maintaining predictive accuracy.
Solution Approach 2:
The patent creates a universal gene signature that can function across different cancer types and clinical contexts. The simplified signature is designed to be broadly applicable for predicting cancer recurrence and prognosis without requiring type-specific modifications, thereby providing both comprehensive prognostic information and accurate prediction with a single unified tool.
2Loss of information
If genome-wide expression profiling is used, then prognostic information is comprehensive, but assay complexity and cost increase
Solution Approach 1:
The patent extracts a minimal set of critical genes from the genome-wide expression profile that are sufficient for accurate prognosis prediction. By identifying and measuring only these essential proliferation-related genes rather than thousands of genes, the assay complexity and cost are dramatically reduced while maintaining comprehensive prognostic information coverage.
Solution Approach 2:
The patent changes the measurement parameters from genome-wide expression levels to focused expression levels of specific proliferation-related genes. This parameter change allows the use of simpler, more cost-effective assays (such as RT-PCR or immunohistochemistry) instead of complex microarray or sequencing technologies, while still providing complete prognostic information.
3Loss of information
If multiple gene signatures are used, then prognostic coverage is improved, but redundancy increases and simplicity is lost
Solution Approach 1:
The patent merges multiple overlapping gene signatures into a single unified signature. By combining the essential elements of the 70-gene signature, 97-gene genomic grade index, and other proliferation-related signatures into one integrated assay, the invention maintains comprehensive prognostic coverage while eliminating redundancy and preserving simplicity for clinical application.
Data Source
AI summary
The disclosure includes the identification and use of gene expression profiles, or patterns, with clinical relevance to cancer. In particular, the disclosure includes the identities of genes that are expressed in correlation with tumor grade. The levels of gene expression are disclosed as a molecular index for determining tumor grade in a patient and predicting clinical outcome, and so prognosis, for the patient. The molecular grading of cancer may optionally be used in combination with a second molecular index for diagnosing cancer and its prognosis. The disclosure further includes methods for predicting cancer recurrence, and/or predicting occurrence of metastatic cancer. For diagnosis or prognosis, the disclosure further includes methods for determining or selecting the treatment of cancer based upon the likelihood of life expectancy, cancer recurrence, and/or cancer metastasis.