Gene Expression Profiles Predict Ovarian Cancer Chemotherapy Response
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Solution Overview
Problem
Current methods lack effective predictive biomarkers to differentiate between ovarian cancer patients who will respond well to platinum-paclitaxel or platinum-only chemotherapy, leading to suboptimal treatment outcomes.
Innovation Solution
Identification of specific gene expression profiles, including biomarkers such as ICAM1, TUBB2A, GLDC, PLAU, AURKA, NEAT1, MXRA5, GSN, and MUC16 for platinum-paclitaxel chemotherapy, and FCGBP, TFPI, NUAK1, LRRC17, FLRT2, IL12A, HSPA2, CDC20, FOXM1, and MAP4K2 for platinum-only chemotherapy, to predict treatment response.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If standard chemotherapy treatment is administered to ovarian cancer patients, then treatment coverage is provided, but treatment efficacy cannot be predicted and outcomes remain suboptimal
Solution Approach 1:
The patent applies preliminary action by identifying and measuring biomarker expression levels in tumor tissue before initiating chemotherapy treatment. This allows the treatment approach to be selected or adjusted in advance based on predicted response, rather than observing outcomes after treatment begins. The biomarkers (such as those listed in Tables 6-7) are assessed pre-treatment to predict whether a patient will respond well to platinum-paclitaxel or platinum-only chemotherapy.
Solution Approach 2:
The patent uses biomarkers as intermediary elements that mediate between the patient's tumor biology and the chemotherapy treatment decision. These biomarkers serve as measurable indicators that translate complex tumor characteristics into actionable predictive information, enabling clinicians to select the most appropriate chemotherapy regimen before treatment begins.
2Adaptability or versatility
If platinum-paclitaxel or platinum-only chemotherapy is selected without predictive biomarkers, then treatment can be administered, but treatment selection is based on convention rather than patient-specific response likelihood
Solution Approach 1:
The patent applies parameter changes by measuring specific biomarker expression levels (such as ICAM1, TUBB2A, GLDC, PLAU, AURKA, NEAT1, MXRA5, GSN, and MUC16 for platinum-paclitaxel; or FCGBP, TFPI, NUAK1, LRRC17, FLRT2, IL12A, HSPA2, CDC20, FOXM1, and MAP4K2 for platinum-only) to determine the most appropriate chemotherapy regimen. This transforms treatment selection from a conventional approach to a personalized one based on measurable biological parameters.
3Productivity
If no predictive biomarkers are used, then treatment decisions can be made quickly, but one-third of patients experience disease progression or recurrence after initial treatment
Solution Approach 1:
The patent enables preliminary assessment of treatment likelihood through biomarker measurement before chemotherapy initiation. This allows treatment decisions to be made with predictive information, improving outcome reliability while maintaining efficient decision-making through objective biomarker criteria rather than prolonged observation or trial-and-error approaches.
Data Source
AI summary
The present disclosure generally relates to gene expression profiling of tissue samples obtained from ovarian cancer patients who are candidates for chemotherapy treatment. More specifically, the disclosure provides methods based on characterization of gene expression which allow a physician to predict whether a patient is likely to respond well to treatment with a chemotherapeutic reagent.