CRISPR In Vivo Tumor Screening via Segmented Guide Pools
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Solution Overview
Problem
Current genetic screens for cancer, particularly in vivo studies, face challenges in modeling cancer mutations and metastasis due to the complexity of library representation and cellular dynamics in animals, limiting the ability to identify genes involved in tumorigenesis and metastasis effectively.
Innovation Solution
The use of the CRISPR/Cas system for genome perturbation and selective perturbation of genetic elements in non-human eukaryotes, allowing for the introduction of specific mutations and epigenetic modifications in cells, which are then transplanted to model tumor formation and evolution, enabling the identification of genes involved in tumorigenesis and metastasis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If pooled CRISPR libraries are used in vivo, then comprehensive genetic screening is enabled, but library complexity and representation requirements become unmanageable
Solution Approach 1:
The patent divides the comprehensive genetic screen into multiple smaller, manageable pools of CRISPR guides. Instead of using a single large pooled library with complex representation requirements, the invention creates multiple smaller pools that can be independently managed and tracked. Each pool targets a specific subset of genes, making the overall system more manageable while maintaining comprehensive coverage through systematic division of the genetic landscape.
Solution Approach 2:
The patent performs preliminary organization and categorization of CRISPR guides into structured pools before introducing them into the in vivo model. By pre-organizing the guides into manageable groups with defined representation requirements, the system avoids the complexity of tracking individual guides in a large pooled library. This preliminary structuring enables comprehensive screening while maintaining practical manageability.
2Measurement precision
If complex cellular dynamics are modeled in vivo, then accurate tumor progression understanding is achieved, but experimental control and library representation become challenging
Solution Approach 1:
The patent applies different levels of guide RNA representation to different functional categories of genes based on their specific roles in tumor progression. Instead of uniform representation throughout the library, the invention assigns localized quality control measures to specific gene sets, allowing accurate modeling of complex cellular dynamics for critical pathways while maintaining simpler representation for less critical genes. This differentiated approach maintains modeling accuracy while improving experimental manageability.
Solution Approach 2:
The patent incorporates feedback mechanisms to monitor and adjust library representation in response to observed tumor progression patterns. By tracking which gene sets show the most significant effects in the in vivo models, the system can refine subsequent experimental designs to better represent the complex cellular dynamics. This feedback loop enables accurate modeling while simplifying the experimental control through data-driven optimization.
3Adaptability or versatility
If multiple mutations are introduced to model cancer evolution, then tumor progression and metastasis can be studied, but the complexity of tracking and managing mutations increases
Solution Approach 1:
The patent segments the multiple mutations into distinct pools organized by their functional impact on tumor progression and metastasis. By dividing the mutation set into manageable groups (e.g., primary tumor initiation mutations, metastasis mutations, drug resistance mutations), the system can track and manage each mutation type independently. This segmentation reduces the overall complexity of tracking multiple simultaneous mutations while maintaining the ability to study comprehensive cancer evolution.
Solution Approach 2:
The patent creates a dynamic system where the mutation pools can be selectively activated and deactivated based on the specific tumor progression stage being studied. The system allows flexible combination and separation of mutation pools to model different aspects of cancer evolution, from early tumorigenesis to late-stage metastasis. This dynamic reconfiguration capability enables comprehensive modeling of tumor progression without the permanent complexity of tracking all possible mutations simultaneously.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach allows for the rapid and direct modeling of cancer mutations and metastasis, enabling the identification of tumor suppressor genes and metastasis suppressor genes, and provides a robust system for studying genetic interactions and potential therapeutic interventions.
Implementation Method 1
The use of the CRISPR/Cas system for genome perturbation and selective perturbation of genetic elements in non-human eukaryotes, allowing for the introduction of specific mutations and epigenetic modifications in cells
Data Source
AI summary
The present invention relates to in vivo methods for modeling tumor formation and/or tumor evolution comprising the use of eukaryotic cells in which one or more genetic target locus has been altered by the CRISPR/Cas system, and which cells are transplanted in non-human eukaryote as a model system for tumor formation and tumor evolution. In particular in vivo genetic screening methods for identifying genes involved in tumorigenesis and metastasis are disclosed. The invention further relates to kits and components for practicing the methods, as well as materials obtainable by the methods, in particular tumor and metastasis samples and cells or cell lines derived therefrom. The invention also relates to diagnostic and therapeutic methods derived from the information obtained in the modeling methods.