Faecal Microbiota Signature for Early Pancreatic Cancer Detection
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Solution Overview
Problem
There is a need for sensitive, specific, non-invasive, and affordable tests for early detection of pancreatic cancer, particularly pancreatic ductal adenocarcinoma (PDAC), as existing methods are ineffective in early stages due to non-specific symptoms and limited therapeutic options.
Innovation Solution
A method for diagnosing PDAC based on a faecal microbiota signature using specific microbial species (Alloscardovia omnicolens, Veillonella atypica, Veillonella dispar, Veillonella parvula, Veillonella sp. [meta-mOTU-v2.5 13135], Butyrivibrio crossotus, Faecalibacillus faecis, Streptococcus anginosus/intermedius, Methanobrevibacter smithii, and Bacteroides finegoldii) and optionally additional species, combined with serum CA19-9 levels, to identify pancreatic cancer through faecal sample analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing diagnostic methods are used for pancreatic cancer detection, then they can detect advanced stages, but they fail to detect early stages due to non-specific symptoms
Solution Approach 1:
The patent introduces faecal microbiota as an intermediary biomarker that mediates between the pancreatic tumor and detectable symptoms. The tumor-induced microbiota changes in the gut serve as a detectable intermediate signal that appears earlier and is more specific than traditional symptoms, enabling early detection through fecal sample analysis
Solution Approach 2:
The patent replaces traditional mechanical/symptom-based diagnosis (physical examinations, symptom reporting) with a biochemical detection system. By substituting the detection mechanism from observing physical symptoms to analyzing microbiota composition through sequencing and qPCR, the system achieves higher early detection accuracy
2Measurement precision
If invasive diagnostic procedures are used to improve detection accuracy, then early cancer can be detected, but patient comfort and accessibility are reduced
Solution Approach 1:
The patent employs disposable, non-invasive fecal sample collection as a temporary, single-use diagnostic approach. The fecal sample serves as a disposable biomaterial source that provides sufficient genetic material for microbiota analysis without requiring repeated invasive procedures, making the test convenient and accessible
Solution Approach 2:
The patent extracts the diagnostic information from an easily accessible source (fecal material) rather than requiring direct tissue sampling. By taking out the microbiota signature from the tumor microenvironment and detecting it in feces, the system achieves high detection accuracy while maintaining sample collection convenience
3Measurement precision
If comprehensive microbiome analysis is performed to achieve high diagnostic accuracy, then early pancreatic cancer can be detected, but test complexity and cost increase
Solution Approach 1:
The patent segments the complex microbiome analysis into discrete, targeted steps: DNA extraction from fecal samples, PCR amplification of 16S rRNA genes, sequencing of specific bacterial taxa, and classification based on predefined microbial signatures. This segmentation transforms a potentially overwhelming comprehensive analysis into a manageable, stepwise process with high diagnostic specificity
Solution Approach 2:
The patent changes the analysis parameters from examining all microbiome components to focusing on specific bacterial taxa and their relative abundances. By adjusting the scope of analysis to target only the most relevant microbial species associated with pancreatic cancer, the system achieves high diagnostic specificity while reducing overall test complexity
4Reliability
If traditional biomarkers like CA19-9 are used alone, then they provide limited sensitivity, but combining with microbiome analysis improves detection robustness
Solution Approach 1:
The patent merges two independent detection systems: traditional serum biomarker analysis (CA19-9) and novel microbiome-based detection. By combining these approaches, the system leverages the strengths of each method, achieving enhanced detection robustness and sensitivity that neither approach could achieve alone, as demonstrated by the improved AUC values in combined models
Data Source
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AI summary
The present invention relates to a method for diagnosing pancreatic cancer in a subject comprising determining the abundance of several Microbiome species in a faecal sample from said subject, and identifying the subject as having pancreatic cancer when the profile of abundance for the analysed species corresponds to a profile of abundance of the analysed species of a pancreatic cancer reference group, or not having pancreatic cancer when the profile of abundance for the analysed species corresponds to a profile of abundance of the analysed species of a reference group not having pancreatic cancer, as well as to a kit and its use for the diagnosis of pancreatic cancer.