Dr. Wang from TerryDR Explains Spatial Biology in a Few Words

I. Technical Background: Observing Tumors with a "Spatial Telescope"

1. Protein localizers (e.g., MIBI-TOF): MIBI-TOF, for example, uses metal-labeled antibodies, which can simultaneously visualize the positions of more than 40 kinds of proteins, making it suitable for observing cell surface markers.

2. Gene localizers (e.g., 10x Visium): Through RNA capture, they can map the distribution of hundreds of genes and are good at detecting intracellular signals.

II. Tumor Microenvironment = Tumor's "Urban Planning"

1. Mixed city: Tumor cells, immune cells, and stromal cells are 杂乱交织.

2. Functional zone city: Tumor cells gather in zones, with a dense immune defense line (T cells, NK cells, activated macrophages) on the periphery.

III. Practical Suggestions: A Guide to Avoiding Pitfalls in Spatial Omics Research

1. Technology selection:

• Use gene localizers for initial exploration (can measure more targets)

• Use protein localizers for clinical verification (cheaper and more stable)

• Don't be greedy to measure both proteins and RNA at the same time; it is recommended to measure adjacent sections separately.

1. Sample strategy:

• For large-sample studies, make tissue microarrays first (multiple samples are assembled into one section)

• Find a data analysis team in advance (more critical than doing experiments)

1. Data analysis:

• A single section can extract thousands of features, so it is necessary to lock the analysis direction in advance.

• Focus on the "social distance" and "neighbor relationship" between cells.

• TerryDR's Qupath plugins, PhenoCluster (cell phenotype analysis) and Spa (spatial analysis), increase the analysis efficiency of the tumor microenvironment by dozens of times.

IV. Future Direction: The "Metaverse" of Tumor Research

1. Technical upgrading:

• Develop new tools that can detect carbohydrates/metabolites (blind spots of existing technologies)

• Create public sample libraries and analysis standards (to allow more hospitals to use them)

1. Expansion of research dimensions:

• Pay attention to systemic reactions such as lymph nodes (not just focusing on the tumor itself)

• Dynamically monitor the treatment process (similar to a "serial drama" of tumor structure)

1. Transformation of clinical application:

• Simplify complex data into clinical indicators (such as developing a "structural scorecard")

• Combine with AI pathological diagnosis systems (assist doctors in quick judgment)

V. Practical Significance of Spatial Biology: New Ideas for Cancer Treatment

• The tumor structure itself may become a prognostic indicator (like the structure of a house affecting its earthquake resistance)

• Repairing the damaged "cell barrier" may prevent cancer metastasis (similar to reinforcing a dyke)

• Immunotherapy may need to consider the "spatial layout" of the tumor (some structures are more easily penetrated by drugs)

VI. TerryDR Products

1. TerryDR automatic IHC staining machine
   Technical highlights:
   FMFX microfluidic technology (rapid staining, reducing time to within 15 minutes)
   Support for coverslip staining (eliminating the need for repeated covering/uncovering steps)
   Independent temperature control system
   Compatible with conventional IHC and mIF staining processes
   Application scenarios:
   Routine immunohistochemistry (integration of dewaxing, antigen retrieval, and antibody incubation)
   High-throughput processing (12-36 slices at a time)

2. QuickStart µIHC Mini
   Low-cost microfluidic, manual portable staining equipment
   Suitable for small samples or rapid experimental needs
   Complete IHC staining process in 15 minutes

3. MultiPlate ICC Immunocytochemistry Staining System
   High-throughput cytological staining for microplates

VII. Scanning Equipment

1. Automatic fluorescent digital pathology scanner
   5-channel fluorescence + H&E scanning, 100 slices

2. Staining-scanning integrated machine
   Microfluidic circulation staining-scanning integrated process (reducing manual intervention)
   Benchmarking against Lunaphore's Comet and Akoya Bio's PhenoCycler®-Fusion
   Support large-size whole-slide imaging (WSI)

VIII. Image Analysis Software

1. TR-PhenoCluster
   i. Cell phenotype analysis solution
   ii. Support single-cell clustering of high-dimensional protein data

2. TR-Spa
   i. Spatial biology analysis tool
   ii. Integrate spatial transcriptomics (ST) with pathological images

3. TR-Qupath-Cloud
   i. Cloud-based collaborative pathological analysis platform
   ii. Support multi-user real-time processing of large-scale data

IX. Solutions and Services

1. TerryDR Spatial Omics Solution
   i. Integrate the whole process of staining, scanning, and data analysis
   ii. Solve the fragmentation problem of traditional processes

2. TR-Path Remote Pathology Consultation
   i. Cloud-based and large-model-based remote pathological consultation service

3. TR-CellSeg Label
   i. Cell labeling tool (supporting AI-assisted segmentation and classification)