Gene Expression Pattern Analysis for Primary Tumor Site Identification
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Solution Overview
Problem
Current methods for determining the primary site of cancer, especially in cases of Carcinoma of Unknown Primary (CUP), are inadequate, leading to lower 5-year survival rates due to the inability to accurately specify the primary site using existing techniques like immunohistochemical staining and molecular genetic testing.
Innovation Solution
A method utilizing gene expression pattern analysis to classify the primary tumor site by comparing gene expression data from tumor cells with specific patterns for various tumor types, excluding patterns attributed to metastatic sites, thereby improving diagnostic accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If immunohistochemical staining and molecular genetic testing are performed, then diagnostic procedures are completed, but primary site specification accuracy remains insufficient for Carcinoma of Unknown Primary
Solution Approach 1:
The patent changes the diagnostic parameter from traditional immunohistochemical staining and molecular genetic testing to gene expression pattern analysis. By measuring and comparing gene expression profiles (transcriptional activity) against reference patterns from known primary sites, the system achieves more accurate primary site specification for CUP cases, improving both measurement precision and diagnostic reliability.
2Reliability
If combination treatment with multiple alkaloid-based anti-malignant-tumor agents is used, then standard treatment is provided for CUP, but 5-year survival rate remains significantly lower
Solution Approach 1:
The patent applies preliminary action by accurately determining the primary site before initiating treatment. By using gene expression pattern analysis to identify the primary tumor site in advance, clinicians can select the most effective targeted therapy for that specific cancer type, rather than using generic combination chemotherapy. This preliminary classification enables personalized treatment strategies that improve 5-year survival rates.
3Measurement precision
If gene expression pattern analysis is used to classify primary tumor site, then diagnostic accuracy is improved, but complexity of analysis increases
Solution Approach 1:
The patent uses an intermediary approach by creating a classification system that compares gene expression patterns against reference data from known primary sites. The system employs pattern recognition algorithms that automatically match unknown tumor samples against stored reference profiles, translating complex molecular data into actionable diagnostic classifications without requiring excessive computational complexity.
Data Source
AI summary
Disclosed is a method for diagnosing carcinoma of unknown primary, using artificial intelligence. A diagnostic method for carcinoma of unknown primary, using artificial intelligence according to an embodiment of the present invention includes the steps of: producing gene expression pattern information of a sample collected from a tissue where metastatic cancer is generated; removing already learned gene expression pattern information attributed to the tissue from the gene expression pattern information of the sample collected from the tissue where metastatic cancer is generated; comparing the gene expression pattern information deprived of the tissue-attributed gene expression pattern information with gene expression pattern information by carcinoma; and specifying a primary site of the sample collected from the tissue where the metastatic cancer is generated.