Tissue Homogenization for Representative Clinical Diagnostics
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Solution Overview
Problem
Current tumor sampling methods in clinical oncology are inadequate for capturing the heterogeneous genetic and spatial diversity of tumors, leading to incomplete diagnostic information and potential misclassification of cancer prognosis and treatment regimens.
Innovation Solution
A methodology involving mechanical, chemical, and biochemical dissociation methods to generate a homogenate composition from intact tissue samples, ensuring a representative sample that reflects the original tissue's cellular structure ratios, suitable for diagnostic and therapeutic applications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional small biopsy samples (3-5 samples of 20×20×3 mm) are taken for TNM staging, then the sampling procedure is simple and quick, but the sample fails to represent the heterogeneous genetic and spatial diversity of the entire tumor
Solution Approach 1:
The tumor specimen is divided into multiple discrete tissue blocks (typically 10-20 blocks) that are systematically sampled from different anatomical regions. Each block represents a distinct spatial sector of the tumor, ensuring comprehensive coverage of tumor heterogeneity while maintaining manageable processing complexity
Solution Approach 2:
Different regions of the tumor are sampled with specific attention to capturing local variations in cellular architecture, genetic composition, and histological features. Each sampled block is treated as a unique representative of its specific tumor region, preserving the spatial and genetic diversity that would be missed by random or single-point sampling
2Reliability
If only 3-5 small tissue samples are taken for diagnostic testing, then the processing time and cost are reduced, but the detection of minor sub-clone populations and low prevalence events is compromised
Solution Approach 1:
Multiple tissue blocks are pre-sampled and systematically prepared before molecular analysis begins. The tissue is divided into discrete blocks that are processed in parallel through fixation, sectioning, and molecular extraction, allowing the laboratory to leverage existing infrastructure and workflows while capturing comprehensive tumor diversity
Solution Approach 2:
Genomic material is extracted and combined from multiple tissue blocks to create a composite molecular profile that represents the entire tumor population. This merging of samples from different spatial regions amplifies the detection sensitivity for rare sub-clones and low-prevalence genetic events that would be undetectable in single small biopsies
3Ease of manufacture
If traditional sampling methods are used, then the existing pathology infrastructure can be utilized without modification, but the spatial heterogeneity within the tumor leads to incomplete diagnostic information
Solution Approach 1:
The tumor specimen is divided into multiple discrete tissue blocks (typically 10-20 blocks) that are systematically sampled from different anatomical regions. Each block represents a distinct spatial sector of the tumor, ensuring comprehensive coverage of tumor heterogeneity while maintaining manageable processing complexity
Solution Approach 2:
Different regions of the tumor are sampled with specific attention to capturing local variations in cellular architecture, genetic composition, and histological features. Each sampled block is treated as a unique representative of its specific tumor region, preserving the spatial and genetic diversity that would be missed by random or single-point sampling
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 provides a more comprehensive and accurate representation of tumor heterogeneity, enhancing the detection of minor sub-clone populations and low prevalence events, thereby improving cancer staging and treatment selection.
Implementation Method 1
applying mechanical, chemical and/or biochemical, e.g., enzymatic, dissociation methods to intact fixed (or preserved) tissue samples
Implementation Method 2
applying mechanical, chemical and/or biochemical, e.g., enzymatic, dissociation methods to intact fixed (or preserved) tissue samples
Data Source
AI summary
The disclosure generally relates to the preparation of representative samples from clinical samples, e.g., tumors (whole or in part), lymph nodes, metastases, cysts, polyps, or a combination or portion thereof, using mechanical and/or biochemical dissociation methods to homogenize intact samples or large portions thereof. The resulting homogenate provides the ability to obtain a correct representative sample despite spatial heterogeneity within the sample, increasing detection likelihood of low prevalence subclones, and is suitable for use in various diagnostic assays as well as the production of therapeutics, especially “personalized” anti-tumor vaccines or immune cell based therapies.