FTI Cancer Treatment Patient Stratification via KIR Genotyping
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for predicting the responsiveness of cancer patients to farnesyltransferase inhibitor (FTI) treatment are inadequate, as patients respond differently to FTI therapy, necessitating a more effective approach for patient stratification and treatment selection.
Innovation Solution
The use of specific immunologically related genes, such as KIR2DS2, KIR2DS5, KIR2DL2, KIR2DL5, and GZMM, for genotyping and expression level analysis to predict the clinical sensitivity and therapeutic response to FTI treatment in cancer patients, including HLA typing and biomarker ratio assessments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If FTI treatment is administered to cancer patients, then therapeutic effect is achieved in some patients, but patient response varies significantly making treatment selection difficult
Solution Approach 1:
The patent performs KIR and HLA genotyping before FTI treatment to identify patients likely to respond. This preliminary genetic analysis allows clinicians to select appropriate candidates for FTI therapy in advance, improving predictive accuracy while maintaining a relatively simple two-step process (genotyping followed by treatment selection).
Solution Approach 2:
The patent uses specific genetic parameters (KIR2DS2, KIR2DS5, HLA-C2 presence) as biomarkers to predict treatment response. By focusing on these specific genetic variants rather than comprehensive genomic analysis, the method achieves reliable prediction with manageable complexity in patient stratification.
2Measurement precision
If comprehensive patient analysis is performed to improve treatment selection accuracy, then predictive precision improves, but time and resource requirements increase
Solution Approach 1:
The patent extracts and focuses on specific genetic markers (KIR2DS2, KIR2DS5, HLA-C2) that are most predictive of FTI response. Rather than analyzing the entire genome or all possible biomarkers, this targeted approach achieves high prediction accuracy while minimizing testing time and resources required.
3Reliability
If patient populations are stratified using multiple biomarkers, then treatment efficacy improves, but the complexity of the selection process increases
Solution Approach 1:
The patent segments the patient population based on specific genetic characteristics (KIR2DS2 carriers, KIR2DS5 carriers, HLA-C2 carriers). This segmentation creates distinct subgroups with different predicted responses to FTI treatment, allowing for targeted therapy selection that improves efficacy while maintaining a clear, stepwise selection process.
Data Source
Figure 1A
Figure 1B
Figure 2A~2B
AI summary
Provided herein is a farnesyltransferase inhibitor (FTI) for use in a method of treating head and neck squamous cell carcinoma (HNSCC) in a human, wherein said human has a H-Ras mutation, and wherein said HNSCC is at an advanced stage, metastatic, relapsed, recurrent or refractory. Further provided herein are suitable dosage regimens for said use and said use in combination therapies.