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Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection
Published on: July 6, 2022
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Mapping Spatial Genetic Landscapes in Tissue Sections through Microscale Integration of Sampling Methodology into
Lena Voith von Voithenberg1, Aditya Kashyap1, Lennart Opitz2
1IBM Research Europe, Säumerstrasse 4, Rüschlikon, CH-8803, Switzerland.
Small (Weinheim an Der Bergstrasse, Germany)
|April 14, 2021
Summary
This study introduces GeneScape, a microfluidic technology for analyzing spatial genomics in tumors. It reveals intratumoral heterogeneity, suggesting metastatic cancers may arise from multiple origins and evolve with location-specific drivers.
Area of Science:
- Oncology
- Genomics
- Biotechnology
Background:
- Genomic profiling of cancer tissues often uses homogenized samples, losing spatial context and underutilizing biopsy material.
- Spatial genomic information is crucial for understanding cancer heterogeneity and progression.
- Existing microscale sampling methods can be destructive and lack multiplexability.
Purpose of the Study:
- To implement a modular microfluidic technology for microscale cell recovery from tumor tissues.
- To develop an integrated workflow (GeneScape) for evaluating intratumoral genomic heterogeneity.
- To assess the genomic landscape of a metastatic mammary carcinoma.
Main Methods:
- A modular microfluidic device was developed to recover cells at the microscale from tumor sections with minimal disruption.
- The GeneScape workflow was integrated for genome profiling of microdissected samples.
- Intratumoral genomic heterogeneity was analyzed in a metastatic mammary carcinoma model.
Main Results:
- GeneScape successfully evaluated genomic heterogeneity within different regions of the tumor.
- Distinct single nucleotide variants and copy number variations were identified across tumor tissue regions.
- Analysis revealed evidence supporting a polyclonal origin of the metastasis.
Conclusions:
- The microfluidic approach preserves tissue architecture while enabling detailed spatial genomic analysis.
- The findings suggest metastatic mammary carcinoma development is driven by multiple, location-specific genetic alterations.
- This technology facilitates deeper insights into cancer evolution and heterogeneity.
