NPC Biomarker Panel for Recurrence Risk Stratification
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Solution Overview
Problem
Nasopharyngeal cancer (NPC) is difficult to detect early and has a high recurrence rate, with limited treatment options and no molecular method to identify high-risk patients for recurrence.
Innovation Solution
A method involving the comparison of biomarker levels (FGF2, C3, and GIMAP7) in a subject's sample to a reference, predicting recurrence risk and guiding personalized treatment strategies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional detection methods are used for nasopharyngeal cancer, then early detection is limited, but the disease has high recurrence rate and limited treatment options
Solution Approach 1:
The patent changes the detection parameter from conventional clinical markers to a molecular signature comprising specific genes (e.g., S100P, S100A7, PTHrP) and microRNAs. This parameter transformation enables both early detection and recurrence prediction by measuring expression levels of these molecular markers in patient samples, thereby resolving the contradiction between early detection accuracy and recurrence prediction reliability.
2Adaptability or versatility
If no molecular method is used to identify high-risk patients, then treatment options are limited, but there is no accurate way to identify patients at high risk of recurrence
Solution Approach 1:
The patent introduces molecular expression levels as new parameters for patient stratification. By measuring the expression levels of specific genes and microRNAs, the method enables accurate identification of high-risk patients, which in turn allows treatment strategies to be adapted based on individual risk profiles, thus resolving both the adaptability and measurement precision requirements.
Solution Approach 2:
The patent segments patients into different risk groups based on their molecular profiles. This segmentation allows for tailored treatment approaches where high-risk patients receive more intensive or targeted therapies, while low-risk patients receive standard treatment, thereby achieving both treatment adaptability and accurate high-risk identification.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Accurately predicts NPC recurrence risk and enables targeted treatment approaches, improving patient outcomes by identifying high-risk individuals for closer monitoring and tailored therapies.
Implementation Method 1
a first and second DNA probe hybridized to the biomarker
Data Source
AI summary
The invention relates generally to the field of oncology. Provided herein is a method for predicting the likelihood of recurrence or prognosis of a cancer in a subject, comprising comparing the level of expression of one or more biomarkers selected from the group consisting of Fibroblast Growth Factor 2 (FGF2), Complement Component 3 (C3), and GTPase, IMAP Family Member 7 (GIMAP7) in a sample obtained from the subject to a reference. In particular, the cancer is nasopharyngeal cancer. Also provided is a composition or solid support comprising a plurality of DNA/RNA complexes, wherein each DNA/mRNA complex in the plurality comprises a biomarker and a first and second DNA probe hybridized to the biomarker, wherein the plurality of DNA/mRNA complexes comprise one or more biomarkers selected from the group consisting of FGF2, C3, and GIMAP7.