Proteogenomic Subtype Determination for Pancreatic Ductal Adenocarcinoma
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Solution Overview
Problem
Current diagnostic methods for pancreatic ductal adenocarcinoma (PDAC) are inadequate in predicting treatment responsiveness, recurrence, and prognosis, and existing treatments have low efficacy, necessitating a novel approach for subclassification based on biological mechanisms to enable precision medicine.
Innovation Solution
A method and kit for determining the subtype of pancreatic ductal adenocarcinoma using proteogenomic analysis by measuring the expression levels of specific genes from pancreatic ductal adenocarcinoma subtypes, including CLDN18, EPS8L3, CAPN5, and others, to stratify patients and predict prognosis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If traditional clinical diagnostic methods (imaging and pathological examinations) are used, then diagnosis can be obtained, but treatment responsiveness prediction and prognosis prediction are not possible
Solution Approach 1:
The patent segments pancreatic ductal adenocarcinoma into six molecular subtypes (Sub1-Sub6) based on proteogenomic profiles. Each subtype is characterized by specific protein expression patterns and genomic alterations, enabling granular classification that reveals treatment responsiveness and prognosis information hidden in the heterogeneous disease population.
Solution Approach 2:
The patent transforms diagnostic parameters from traditional anatomical and histological features to molecular-level parameters including proteogenomic profiles, gene expression levels, and protein quantification data. This parameter transformation enables prediction of treatment responsiveness and prognosis by capturing biological mechanisms underlying disease behavior.
2Measurement precision
If proteogenomic analysis with multiple gene measurements is performed, then subtype determination accuracy is improved, but measurement complexity and cost increase
Solution Approach 1:
The patent develops a multi-functional diagnostic system that simultaneously performs subtype classification, treatment responsiveness prediction, and prognosis assessment using integrated proteogenomic analysis. The same measurement platform quantifies multiple protein markers and genomic features to achieve multiple diagnostic objectives in a unified framework.
Solution Approach 2:
The patent integrates multiple types of biological data (proteomic profiles, transcriptomic data, genomic alterations) into a composite proteogenomic signature for each subtype. This composite approach combines information from different molecular layers to achieve high-precision subtype determination that surpasses single-modality analysis.
3Adaptability or versatility
If pancreatic cancer is classified into multiple subtypes, then precision medicine and optimal treatment selection are enabled, but diagnostic and treatment complexity increase
Solution Approach 1:
The patent assigns specific therapeutic recommendations to each molecular subtype based on their distinct biological characteristics. For example, Sub1 (proliferative) may respond to anti-proliferative agents, while Sub4 (inflammatory) may benefit from immunotherapy or anti-inflammatory treatments. This local customization of treatment strategies to subtype-specific biology enables precision medicine while maintaining operational clarity through standardized subtype-defined protocols.
Data Source
AI summary
The present invention relates to a method of determining the subtype of a pancreatic ductal adenocarcinoma patient through proteogenomic analysis of PDAC. The method of determining the subtype of pancreatic cancer according to one embodiment of the present invention comprises steps of: (1) pulverizing a pancreatic ductal adenocarcinoma lesion tissue isolated from a pancreatic ductal adenocarcinoma patient; (2) obtaining a peptide sample for the patient by extracting and digesting proteins from the lesion tissue; (3) measuring the expression levels of representative genes of pancreatic ductal adenocarcinoma subtypes 1 to 6 from the peptide sample for the patient; and (4) determining the subtype of the pancreatic ductal adenocarcinoma patient by comparing the expression levels of the representative genes of pancreatic ductal adenocarcinoma subtypes 1 to 6.