Single-Nucleus RNA-seq for PDAC Stroma Analysis
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Solution Overview
Problem
Pancreatic ductal adenocarcinoma (PDAC) is projected to become a leading cause of cancer death due to limited effective treatments, with existing diagnostic and therapeutic approaches failing to provide meaningful clinical management, particularly due to challenges in characterizing PDAC through mRNA profiling and the impact of dense desmoplastic stroma on RNA quality and cell type representation in tumors.
Innovation Solution
The use of robust single-nucleus RNA-seq and spatial transcriptomics techniques optimized for frozen archival samples to detect malignant cell signatures, cancer-associated fibroblast signatures, tumor spatial communities, and co-expressed receptor-ligand pairs in PDAC tumors, enabling improved diagnosis, classification, and prognosis, and guiding treatment decisions with agents such as PDAC malignant cell modulators, immune modulators, and apoptosis inhibitors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional mRNA profiling methods are used to characterize PDAC, then the analysis can be performed, but the dense desmoplastic stroma degrades RNA quality and compromises cell type representation
Solution Approach 1:
The patent applies single-nucleus RNA sequencing to segment and individually analyze nuclei from different cell types within the tumor microenvironment, allowing independent characterization of malignant cells, cancer-associated fibroblasts, and immune cells despite the presence of dense stroma that degrades overall RNA quality
Solution Approach 2:
The patent uses nuclear RNA (nRNA) as an intermediary molecule that is more resilient to degradation by the dense desmoplastic stroma compared to cytoplasmic mRNA, enabling successful profiling of gene expression in the challenging PDAC tumor microenvironment
2Loss of information
If bulk tissue analysis is performed, then the overall tumor profile can be obtained, but cell type-specific signatures and spatial relationships are lost
Solution Approach 1:
The patent segments bulk tissue analysis into single-nucleus level analysis, enabling simultaneous capture of cell type-specific molecular signatures and spatial location information through integrated multi-omics approaches without requiring overly complex instrumentation
Solution Approach 2:
The patent adds spatial and single-cell resolution dimensions to traditional bulk transcriptomics, transforming the analysis from a single averaged profile to multi-dimensional data that includes cell type, spatial position, and molecular expression characteristics
3Reliability
If existing diagnostic and therapeutic approaches are used, then treatment can be administered, but meaningful clinical management and prognostic information are not provided
Solution Approach 1:
The patent generates comprehensive molecular profiles that provide feedback information about tumor characteristics, microenvironment composition, and potential treatment responses, enabling personalized clinical management decisions and prognostic stratification based on the detailed single-nucleus RNA-seq data
Solution Approach 2:
The patent changes the diagnostic parameters from conventional bulk mRNA expression to single-nucleus RNA expression profiles, enabling detection of cell type-specific and spatially-resolved molecular signatures that provide meaningful prognostic and predictive information for clinical management
Data Source
AI summary
Described herein are pancreatic ductal adenocarcinoma (PDAC) signatures and methods of detecting the same in a sample from a subject. Also described herein, are methods of methods of diagnosing, prognosing, and/or treating PDAC in a subject that can include detecting one or more of the PDAC signatures.