Spatial-ready Tissue Microarray (TMA) Construction Service
Our tissue microarray construction service builds spatial-ready tissue microarrays (TMAs) for cohort-scale spatial biology.
You can profile many FFPE tissues under identical staining and imaging conditions.
Service highlights
- 50–200 tissue samples per slide through high-density TMA design.
- Lower per-sample spatial assay cost by running many tissues together.
- Faster imaging workflows because regions are concentrated and standardised.
- Auditable traceability with a position matrix and annotation table.
- Platform-neutral compatibility for mainstream spatial and multiplex imaging workflows.
Cost impact varies by design and downstream workflow, but consolidation can reduce overall spend.
Service & Technical Overview: Spatial-ready Tissue Microarray (TMA) Construction
What is a tissue microarray (TMA)?
A tissue microarray (TMA) is a paraffin block built from many small tissue cores.
Each core comes from a different donor specimen, then gets placed in a defined grid.
When sectioned, one slide can carry many tissue microarray samples in fixed positions.
Why use a spatial-ready TMA in spatial biology and multiplex imaging?
Spatial assays become difficult to scale when each sample needs its own slide.
A TMA lets you process many tissues together, under the same staining conditions.
This reduces slide-to-slide variation and improves comparability across a cohort.
A consolidated layout also simplifies imaging work.
Regions are organised in one field of view, so scanning is more efficient.
Teams spend less time searching for comparable regions across separate slides.
What makes our tissue microarray construction "spatial-ready"?
Our tissue microarray construction workflow is designed for downstream spatial readouts.
We build arrays with consistent coring, stable orientation, and clear core indexing.
A position matrix links each coordinate to its sample ID for defensible provenance.
This combination supports spatial omics studies that depend on high-throughput consistency.
It is also well suited for multiplex imaging programmes that need standardised comparison.
Service Scope & Options
- Design & layout options: Define core diameter, spacing, grid layout, orientation markers, and control tissues.
- Slide and sectioning options: Sections and slides can be provided to your requested thickness and quantity. Optional QC staining is available.
- Documentation included: A core coordinate map and metadata table are provided for downstream handoff.
- Optional add-ons: Downstream-ready recommendations and workflow-dependent bioinformatics reporting are available upon request.
Technical Advantages for Spatial Omics and Multiplex Imaging
More reliable cohort comparisons
Because all cores are processed on the same slide, technical variation is easier to control.
This makes cross-sample differences more interpretable when you stratify a cohort.
Less rework in spatial and multiplex pipelines
A standardised array format reduces the number of slides you need to prepare and track.
Reduced handling steps can lower the risk of mix-ups and repeat work.
Cleaner linkage between sample identity and spatial readouts
The position matrix creates a stable reference between each core and its donor sample.
That is critical when results move between pathology review, imaging teams, and analysts.
Better use of limited or heterogeneous tissues
When tissues are variable, replicate cores and control placement can improve robustness.
You gain a practical way to compare patterns across tumour regions or tissue subtypes.
Scales to large studies without losing consistency
As cohorts grow, using the same design logic across multiple TMA blocks keeps outputs aligned.
This supports longitudinal or multi-batch studies where comparability is the priority.
Applications (Use Cases)
Spatial transcriptomics cohort studies (FFPE)
Use TMAs to screen many FFPE tissues in a single run and compare spatial patterns across groups.
This is useful for discovery-stage programmes where you need consistent, cohort-wide signals.
Multiplex imaging panels across large sample sets
TMAs support repeated staining and imaging cycles on standardised tissue regions.
That helps teams benchmark markers across samples without changing slide conditions.
Cancer tissue microarray programmes
Build cancer tissue microarrays to profile tumour microenvironments at scale.
Common goals include immune infiltration mapping, spatial biomarker localisation, and subgroup comparison.
Biomarker localisation and verification
When a biomarker looks promising in a small set, TMAs help you verify localisation patterns across a larger cohort.
This can reduce uncertainty before you commit to broader validation workflows.
Drug response and tissue microenvironment comparisons
TMAs are well suited for comparing spatial features between treatment arms or time points.
They provide a practical format for side-by-side interpretation in translational research.
Best fit: cohort-scale comparisons and screening. Not intended for diagnostic interpretation.
TMA Design Options for Cohort Studies (Core Size, Layout, Controls)
A strong tissue microarray starts with design choices that match your cohort and endpoints.
We translate your study structure into an array plan that stays practical for sectioning and review.
Array density and sample allocation
We can build TMAs that place many samples on one slide, while keeping cores readable for imaging.
For larger cohorts, we can distribute samples across multiple blocks using the same layout logic.
Core size, spacing, and orientation
Core diameter and spacing can be tuned to balance tissue representation and array capacity.
Orientation markers help keep sections aligned across runs and reviewers.
Replicate strategy for heterogeneous tissues
For variable tissues, replicate cores can improve robustness and reduce the chance of sampling bias.
This is often relevant for tumour tissues and mixed microenvironments.
Controls and reference tissues
Optional control tissues and blank positions can be included to support consistent interpretation.
We can also place references to simplify cross-slide comparison when multiple blocks are used.
Documentation for downstream handoff
The final design is captured in a coordinate map and metadata table.
This keeps imaging plans, analysis, and reporting aligned with the physical array.
Platform Compatibility (Platform-neutral)
Our spatial-ready TMAs are prepared to support mainstream spatial omics and multiplex imaging workflows without locking you into a specific vendor ecosystem.
We describe compatibility in platform-neutral terms so you can apply the same array to the workflow you already use.
Supported downstream workflow types
- Capture-area spatial transcriptomics workflows for FFPE or tissue sections
- In situ probe–based spatial assays (RNA/DNA target panels)
- Multiplex fluorescence imaging pipelines, including iterative stain-and-scan approaches
- Spatial proteomic labelling and imaging workflows
- Whole-slide scanning and ROI-based quantification for cohort comparisons
Practical compatibility considerations
Array density and core spacing can be tailored to your imaging field of view and region-of-interest strategy.
Section thickness and slide handling can also be aligned to your planned staining and imaging cycles.
Workflow: Tissue Microarray Construction Process
Step 1. Array design and sample coding
We review your cohort structure, tissue types, and study groups to draft an array plan.
A consistent sample coding scheme is set up to support downstream tracking.
Step 2. Tissue coring and array construction
Cores are taken from donor blocks with controlled depth and placement.
This helps maintain uniform core geometry across the array.
Step 3. Recipient block preparation and build QC
Cores are embedded into a recipient block and stabilised for sectioning.
Basic build checks confirm array integrity before slide production.
Step 4. Sectioning and optional QC staining
Sections can be cut to your preferred thickness and delivered on slides.
Optional staining can be used to verify tissue presence and section quality.
Step 5. Workflow readiness support
We provide handling and preparation recommendations aligned to your intended downstream workflow.
This guidance stays platform-neutral and does not depend on proprietary steps.
Step 6. Optional downstream analysis
If requested, we support post-run data organisation and analysis reporting.
This is scoped to your workflow and study questions.
Bioinformatics & Reporting (Optional)
Bioinformatics support is available when you want a consistent reporting layer across a TMA cohort.
We scope analysis to your workflow type and the biological questions you need answered.
What we can deliver (workflow-dependent)
- Data QC summaries that highlight sample-level usability and outliers
- ROI-level quantification or feature extraction outputs aligned to your imaging plan
- Cross-sample comparison tables for predefined groups (e.g., case vs control)
- Interpretation-ready figures such as spatial maps, summary plots, and group comparisons
- A concise technical report describing methods, parameters, and key readouts
How this helps your programme
A standardised output format makes it easier to compare tissues across a cohort.
It also reduces the time your team spends harmonising files from multiple runs or reviewers.
Reporting formats
Outputs are delivered as structured tables, figures, and a concise written summary.
If your team has an internal template, we can align headings and file structure to it.
Deliverables
Your project package is designed to be usable immediately by imaging and analysis teams.
Core deliverables
- TMA recipient block(s) constructed to your approved layout
- Slides/sections (quantity and thickness as specified)
- Core position matrix showing coordinates for every sample
- Sample annotation sheet linking coordinates to your metadata and group labels
- QC summary documenting construction and section checks
Optional deliverables (as scoped)
- Imaging-ready organisation of files and sample indices, if required by your workflow
- Bioinformatics outputs and reporting
Why Choose Us
- Built for cohort scale: Designed to support studies ranging from dozens to hundreds of samples with consistent layout logic across blocks.
- One-stop execution: TMA construction with optional sectioning, QC staining, and workflow-dependent reporting that simplifies coordination across pathology review, imaging, and analysis.
- Traceable by design: Core coordinates and sample annotations are delivered in a clear mapping package for defensible provenance.
- Platform-neutral support: Workflow recommendations stay vendor-agnostic, helping you keep compatibility with mainstream spatial and multiplex approaches.
Sample Requirements
To build a reliable array, we need tissue inputs that are suitable for coring and consistent sectioning.
Preferred input material
- FFPE donor blocks for cohort construction and long-term stability
- One donor block per tissue microarray sample, with clear identifiers
Information to submit with your samples
- Sample list with IDs, tissue type, and study group labels
- Any constraints on replicate cores or control placement
- Notes on target regions, if specific areas should be represented
Practical considerations
- Use consistent naming across blocks, slides, and metadata files.
- If sections will be used for multiplex workflows, let us know the planned cycle number and staining intensity expectations so we can align sectioning and handling.
If you have atypical formats or limited material, we can review feasibility and suggest a design approach that preserves interpretability.
FAQ: What Is Tissue Microarray and How Many Samples per Slide?
Ready to Start
To scope your spatial-ready tissue microarray (TMA) construction project, send:
- Number of samples and tissue types (FFPE donor blocks)
- Study groups and key comparisons (e.g., cohorts, arms, time points)
- Any preferences for core size, replicates, controls, and layout
- Downstream workflow type (spatial omics or multiplex imaging) and slide needs
References
- Kononen, J., et al. "Tissue Microarrays for High-Throughput Molecular Profiling of Tumor Specimens." Nature Medicine, vol. 4, no. 7, 1998, pp. 844–847. doi:10.1038/nm0798-844.
- Camp, Robert L., Lori A. Charette, and David L. Rimm. "Validation of Tissue Microarray Technology in Breast Carcinoma." Laboratory Investigation, vol. 80, 2000, pp. 1943–1949.
- Hutchins, Gordon, and Heike I. Grabsch. "How to Make Tissue Microarrays." Diagnostic Histopathology, vol. 24, no. 4, 2018, pp. 127–135. doi:10.1016/j.mpdhp.2018.02.008.
- Behling, Felix, and Jens Schittenhelm. "Tissue Microarrays—Translational Biomarker Research in the Fast Lane." Expert Review of Molecular Diagnostics, vol. 18, no. 10, 2018, pp. 833–835. doi:10.1080/14737159.2018.1522252.
- Taube, Janis M., et al. "Multi-institutional TSA-Amplified Multiplexed Immunofluorescence Reproducibility Evaluation (MITRE) Study." Journal for ImmunoTherapy of Cancer, vol. 9, no. 7, 2021, e002197. doi:10.1136/jitc-2020-002197.
- Wisner, Lee, Brandon Larsen, and Alanna Maguire. "Manual Construction of a Tissue Microarray Using the Tape Method and a Handheld Microarrayer." Journal of Visualized Experiments, 10 June 2022. doi:10.3791/63086-v.
