Immune Gene Expression Profiling for Prostate Radiotherapy Response
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Solution Overview
Problem
Current methods for predicting the response of prostate cancer patients to radiotherapy are inadequate, leading to ineffective treatments and significant side effects, with a need for improved predictive tools to optimize therapy selection and reduce costs.
Innovation Solution
A method utilizing a gene expression profile of five or more immune defense response genes (AIM2, APOBEC3A, CIAO1, DDX58, DHX9, IFI16, IFIH1, IFIT1, IFIT3, LRRFIP1, MYD88, OAS1, TLR8, and ZBP1) to predict radiotherapy response in prostate cancer patients, based on RNASeq expression data and molecular pathway analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current prediction methods are used for radiotherapy response, then treatment decisions can be made, but the prediction accuracy is inadequate leading to ineffective treatments
Solution Approach 1:
The patent changes the parameters used for prediction from conventional clinical factors (PSA levels, Gleason score, tumor stage) to molecular-level parameters (gene expression profiles of immune defense response genes). This parameter transformation enables more accurate prediction of radiotherapy response by capturing the biological state of the tumor microenvironment, directly resolving the contradiction between measurement precision and treatment reliability
Solution Approach 2:
The patent introduces gene expression profiles as an intermediary between the tumor characteristics and treatment outcome prediction. These molecular markers serve as mediators that provide deeper insight into the tumor's response potential to radiotherapy, bridging the gap between observable clinical features and actual treatment effectiveness
2Productivity
If radiotherapy is administered to all patients, then treatment coverage is maximized, but unnecessary toxicity and costs increase for non-responders
Solution Approach 1:
The patent performs prediction of radiotherapy response before treatment administration using gene expression profiling. This preliminary assessment identifies patients who are likely to respond to radiotherapy, allowing clinicians to proceed with treatment only for those patients. By acting in advance, the method prevents unnecessary exposure to radiation and its associated toxicity for patients who would not benefit from the treatment
Solution Approach 2:
The patent extracts the subgroup of patients who are predicted to respond to radiotherapy based on their gene expression profiles. By separating responders from non-responders before treatment, the method applies radiotherapy only to the extracted subgroup that will benefit, thereby eliminating unnecessary toxicity for the remaining patients who would not respond
3Measurement precision
If more comprehensive prediction methods are developed, then treatment optimization improves, but complexity of the diagnostic process increases
Solution Approach 1:
The patent segments the complex diagnostic process into distinct modules: (1) RNA extraction from clinical samples, (2) gene expression profiling for specific immune defense response genes, (3) data analysis using established algorithms, and (4) prediction output. This segmentation allows each step to be performed by standardized, automated techniques, reducing overall complexity while maintaining high prediction accuracy through focused measurement of key molecular markers
Data Source
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AI summary
The invention relates to a method of predicting a response of a prostate cancer subject to radiotherapy, comprising determining or receiving the result of a determination of a gene expression profile for each of five or more immune defense response genes selected from the group consisting of: AIM2, APOBEC3A, CIAO1, DDX58, DHX9, IFI16, IFIH1, IFIT1, IFIT3, LRRFIP1, MYD88, OAS1, TLR8, and ZBP1, said gene expression profiles being determined in a biological sample obtained from the subject, and determining, by a processor, the prediction of the radiotherapy response based on the gene expression profiles for the five or more immune defense response genes.