Gene Expression Panels for Glioblastoma and Breast Cancer Risk Assessment
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Solution Overview
Problem
Current methods lack effective platforms for rapidly measuring complex cellular phenotypic traits and predicting patient-specific clinical outcomes for glioblastoma and breast cancer, particularly in identifying increased risk of recurrence and short survival.
Innovation Solution
The use of gene expression panels comprising biomarkers such as DUSP5, PLK3, PPP1R15A, FOSL1, CDKN1A, KLF6, VDR, ARL4C, ADM, PLAU, VEGFA, NQO1, HMOX1, PGK1, LITAF, HPCAL1, and FTH1 for glioblastoma, and PGK1, NQO1, HMOX1, VEGFA, ADM, HPCAL1, PLK3, FOSL1, and PLAU for breast cancer, to determine gene expression levels and compare them to predetermined reference levels, aiding in risk assessment and therapeutic administration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Power
If aggressive radical surgical resection coupled with concurrent chemo- and radio-therapy is performed, then treatment intensity is improved, but patient survival and recurrence prevention remain poor
Solution Approach 1:
The patent changes the parameter of measurement from standard clinical metrics to a 10-gene expression profile (including DUSP5, PLK3, PPP1R15A, FOSL1, CDKN1A, KLF6, VDR, ARL4C, ADM, PLAU, VEGFA, NQO1, HMOX1, PGK1, LITAF, HPCAL1, and FTH1) that specifically predicts recurrence risk. This molecular parameter change enables differentiation of high-risk patients who need intensified therapy from standard-risk patients, resolving the contradiction by making treatment intensity adaptive to molecular risk parameters rather than uniformly aggressive
Solution Approach 2:
The gene expression profile serves as a self-service diagnostic tool that automatically identifies high-risk patients without requiring complex clinical assessment. The molecular signature inherently provides the risk stratification needed to guide treatment intensity, eliminating the need for subjective clinical judgment and enabling precise allocation of aggressive therapy to those who will benefit most
2Ease of operation
If standard clinical and pathological parameters are used for risk assessment, then assessment simplicity is improved, but prediction accuracy of recurrence and survival is poor
Solution Approach 1:
The patent replaces the mechanical/systematic approach of manual clinical and pathological assessment with a molecular biology-based gene expression analysis system. Instead of relying on pathologists to evaluate tissue morphology and clinical parameters, the system uses quantitative measurement of 10 specific genes' expression levels to objectively predict recurrence risk and survival outcomes, significantly improving measurement precision while maintaining operational feasibility through standardized molecular testing
3Device complexity
If no molecular biomarkers are used, then diagnostic cost and complexity are reduced, but ability to identify high-risk patients for targeted therapy is lost
Solution Approach 1:
The patent segments the complex task of recurrence risk assessment into 10 discrete gene expression measurements rather than attempting to evaluate numerous clinical and pathological variables simultaneously. This segmentation of the diagnostic process into specific molecular components (DUSP5, PLK3, PPP1R15A, FOSL1, CDKN1A, KLF6, VDR, ARL4C, ADM, PLAU, VEGFA, NQO1, HMOX1, PGK1, LITAF, HPCAL1, and FTH1) reduces overall diagnostic complexity while enhancing the ability to identify high-risk patients through targeted molecular analysis
Data Source
AI summary
Disclosed herein are methods for identifying a subject with an increased risk of short survival and/or recurrence of glioblastoma or breast cancer, the methods comprising: a) obtaining a brain or breast tissue sample or having obtained a brain or breast tissue sample from a subject; b) determining gene expression levels of one or more of PLK3, FOSL1, ADM, PLAU, VEGFA, NQOI, HMOX1, PGKI, and HPCAL1 in the sample from the subject. Also disclosed herein are diagnostic devices comprising one or more biomarkers, wherein the biomarkers are one or more of PLK3, FOSL1, ADM, PLAU, VEGFA, NQOI, HMOX1, PGKI, and HPCAL1; and a gene expression panel consisting of primers or probes for detecting one or more of DUSP5, PLK3, PPPIR15A, FOSL1, CDKNIA, KLF6, VDR, ARL4C, ADM, PLAU, VEGFA, NQOI, HMOX1, PGKI, LITAF, HPCALI and FTH1 in a sample, and methods for assessing risk of recurrence of glioblastoma or breast cancer in a subject.