Transcriptome Immune Repertoire Profiling for Non-Invasive Cancer Detection
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Solution Overview
Problem
Existing cancer diagnosis methods using liquid biopsies have limitations in sensitivity and accuracy, particularly in predicting cancer types and patients, and there is a need for more effective non-invasive monitoring of tumor genotypes.
Innovation Solution
A method involving whole transcriptome sequencing (WTS) to extract immune cell receptor features and transcriptome features, aligned to a reference genome database, and inputting these features into an artificial intelligence model trained to distinguish between cancer patients and normal subjects, using immune cell receptor features such as TCR and BCR CDR3 sequences, and transcriptome features like gene enrichment scores.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If liquid biopsy methods are used for cancer diagnosis, then non-invasive monitoring is enabled, but sensitivity and accuracy are limited
Solution Approach 1:
The patent combines multiple types of sequencing data (DNA mutation information, RNA transcriptome information, epigenomic information) from liquid biopsy samples into a unified analysis framework. This integration of multiple data sources enhances the sensitivity and accuracy of cancer detection while maintaining the non-invasive nature of liquid biopsy, resolving the contradiction between ease of operation and measurement precision.
Solution Approach 2:
The invention creates a composite diagnostic approach by integrating heterogeneous data types (genomic, transcriptomic, epigenomic) into a comprehensive cancer detection system. This composite methodology leverages the strengths of each data type to achieve high accuracy in non-invasive cancer monitoring, addressing the limitation of individual liquid biopsy methods.
2Measurement precision
If comprehensive multiparameter analysis is performed on tumor materials, then accurate tumor classification is achieved, but invasive methods are required
Solution Approach 1:
The patent uses liquid biopsy to obtain circulating tumor DNA (ctDNA) and other tumor-derived materials from blood samples, creating a non-invasive copy of tumor genetic information. This allows comprehensive multiparameter analysis to be performed on the copied material rather than requiring direct access to primary tumor tissue through invasive biopsies, thus achieving accurate tumor classification without invasiveness.
Solution Approach 2:
The invention uses circulating tumor cells (CTCs) and cell-free DNA in blood as intermediary materials that carry tumor genetic information from the primary tumor to the diagnostic laboratory. These intermediaries enable comprehensive molecular profiling without requiring direct sampling of the tumor itself, resolving the contradiction between diagnostic accuracy and invasiveness.
3Productivity
If continuous monitoring of tumor genotypes is performed, then disease progression tracking is enabled, but invasive repeated biopsies are required
Solution Approach 1:
The patent leverages the body's natural circulation of tumor-derived materials in the bloodstream, allowing continuous monitoring through routine blood draws. The tumor continuously releases ctDNA and CTCs into circulation, enabling repeated sampling without invasive procedures. This self-service approach allows frequent genotype monitoring while maintaining patient comfort and safety.
Data Source
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AI summary
The present invention relates to a method for diagnosing cancer using transcriptome-based immune repertoire profiling and, more particularly, to a method for diagnosing cancer by using a method of obtaining transcriptome sequence information from biological samples, then extracting, from the transcriptome sequence information, the features of immune cell receptors and the features of transcriptomes, and then analyzing same by input into an artificial intelligence model trained to determine the presence or absence of cancer. The method for diagnosing cancer using transcriptome-based immune repertoire profiling, according to the present invention, diagnoses all cancers on the basis of artificial intelligence by using both the features of immune cell receptors and the features of gene expression levels, the features being extracted from transcriptome samples generated by next generation sequencing (NGS), and is useful with high commercial applicability due to its high accuracy and sensitivity compared to diagnostic methods that use only the sequence information of immune cell receptors.