Biopsy Imprinted Gene Assay for Early Cancer Classification
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Solution Overview
Problem
Current cancer diagnosis methods, such as fine needle aspiration, core needle aspiration, endoscope-guided tissue biopsy, and brush biopsy, face challenges in accurately determining the benignity or malignancy of early-stage cancers due to small sample sizes and low histological heteromorphism, leading to low diagnostic accuracy and missed diagnoses.
Innovation Solution
A method for cancer diagnosis through assaying imprinted genes in biopsy samples, using expression profiles of imprinted genes Z1 and Z16 to classify tumors into 5 grades based on loss of imprinting (LOI) and copy number variation (CNV), determining benignity or malignancy, and staging cancers as benign, cancer potential, early-stage, medium-stage, or late-stage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional biopsy methods (fine needle aspiration, core needle aspiration, endoscope-guided tissue biopsy, brush biopsy) are used for cancer diagnosis, then biopsy sampling can be performed, but the sample size is small and histological morphology is hard to indicate, leading to low diagnostic accuracy
Solution Approach 1:
The patent extracts and detects specific molecular features (imprinted gene expression patterns) from the biopsy sample rather than relying on the entire sample's histological morphology. By focusing on the molecular level characteristics of imprinted genes, the method achieves high diagnostic accuracy even with small sample sizes obtained through traditional biopsy methods.
Solution Approach 2:
The patent replaces the mechanical/histological evaluation system with a molecular biology-based detection system. Instead of relying on pathologists to visually assess tissue morphology and heteromorphism, the method uses molecular detection techniques to measure imprinted gene expression, providing objective and precise diagnostic information that overcomes the limitations of traditional mechanical sampling.
2Reliability
If traditional pathology methods are used for early-stage cancer diagnosis, then biopsy sampling can be performed, but cell heteromorphism is low and histological morphology is hard to indicate, resulting in missed diagnoses
Solution Approach 1:
The patent transitions from two-dimensional histological morphology assessment to three-dimensional molecular expression analysis. By detecting imprinted gene expression patterns at the molecular level, the method reveals diagnostic information that is not visible through traditional light microscopy, enabling reliable detection of early-stage cancers with low cell heteromorphism.
Solution Approach 2:
The patent changes the detection parameter from morphological characteristics to molecular expression characteristics. By measuring the expression levels of imprinted genes (such as Z1 and Z16) and calculating imprinted gene loss ratios, the method creates sensitive detection parameters that can identify early-stage cancers before significant morphological changes occur.
3Measurement precision
If biomarkers such as BRAF, BRAC, CEA, and PSA are used for cancer diagnosis, then molecular level detection can be performed, but sensitivity and specificity are insufficient, leading to false positive rates
Solution Approach 1:
The patent develops a universal detection system based on imprinted gene expression patterns that can be applied across multiple cancer types. Unlike tumor-specific biomarkers (such as BRAF for papillary thyroid carcinoma only), the imprinted gene detection method can diagnose various cancers (thyroid, breast, pancreatic, lung, gastrointestinal, urinary system, etc.) using the same molecular mechanism, thereby improving both sensitivity and specificity while reducing false positive rates.
Data Source
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AI summary
The present application refers to a method for cancer diagnosis via biopsy samples. The method grades the expression status of imprinted genes by calculating the change of the expression of imprinted genes with loss of imprinting, the expression of imprinted genes with copy number variation, and the total expression of imprinted genes in tumor; wherein the imprinted genes are Z1 and/or Z16. Z1 is Gnas, and Z16 is Snrpn/Snurf. The method in the present application presents the expression of loss of imprinting in biopsy samples in a direct way for the first time, which can provide a quantitative model, to make a great contribution especially to the early diagnosis of transformation from tumor to cancer and screening of tumor.