Deciphering the Immune Microenvironment on A Single Archival Formalin-Fixed Paraffin-Embedded Tissue Section by An Immediately Implementable Multiplex Fluorescence Immunostaining Protocol.
Adrien GuillotMarlene S KohlheppAlix BruneauFelix HeymannFrank TackePublished in: Cancers (2020)
Technological breakthroughs have fundamentally changed our understanding on the complexity of the tumor microenvironment at the single-cell level. Characterizing the immune cell composition in relation to spatial distribution and histological changes may provide important diagnostic and therapeutic information. Immunostaining on formalin-fixed paraffin-embedded (FFPE) tissue samples represents a widespread and simple procedure, allowing the visualization of cellular distribution and processes, on preserved tissue structure. Recent advances in microscopy and molecular biology have made multiplexing accessible, yet technically challenging. We herein describe a novel, simple and cost-effective method for a reproducible and highly flexible multiplex immunostaining on archived FFPE tissue samples, which we optimized for solid organs (e.g., liver, intestine, lung, kidney) from mice and humans. Our protocol requires limited specific equipment and reagents, making multiplexing (>12 antibodies) immediately implementable to any histology laboratory routinely performing immunostaining. Using this method on single sections and combining it with automated whole-slide image analysis, we characterize the hepatic immune microenvironment in preclinical mouse models of liver fibrosis, steatohepatitis and hepatocellular carcinoma (HCC) and on human-patient samples with chronic liver diseases. The data provide useful insights into tissue organization and immune-parenchymal cell-to-cell interactions. It also highlights the profound macrophage heterogeneity in liver across premalignant conditions and HCC.
Keyphrases
- single cell
- high throughput
- liver fibrosis
- rna seq
- cell therapy
- randomized controlled trial
- stem cells
- single molecule
- healthcare
- endothelial cells
- machine learning
- adipose tissue
- type diabetes
- mass spectrometry
- mouse model
- skeletal muscle
- insulin resistance
- minimally invasive
- high resolution
- metabolic syndrome
- mesenchymal stem cells
- bone marrow
- social media
- label free