Multiplex Immunohistochemistry (mIHC) Spatial Immune Profiling Services
Multiplex immunohistochemistry (mIHC) provides high-plex spatial immune profiling from a single FFPE tissue section. Our integrated service combines multiplex staining, high-resolution imaging, and quantitative analysis in one coordinated workflow, reducing hand-offs and rework for your team.
- High-content spatial maps of immune and tumor cells at the level of individual cells
- Consistent, centrally generated data suitable for TME, immuno-oncology, and biomarker studies
- Output formats ready for integration with spatial transcriptomics and other omics data
Services are provided for research use only.
What is mIHC-based spatial immune profiling?
mIHC-based spatial immune profiling is an imaging approach that measures several immune and tumor markers in the same tissue section while preserving the tissue architecture. Instead of comparing separate single-stain slides, you see multiple cell types and checkpoints together in their native context.
Compared with conventional single-plex IHC, multiplex immunohistochemistry captures more information from each specimen and reduces tissue consumption. You can characterize limited tissue specimens in greater depth, compare regions within a lesion, and minimize variability caused by cutting and staining separate sections.
Typical biological questions addressed by mIHC-based spatial immune profiling include:
- Which immune cell subsets are present within and around the lesion?
- How are T cells, B cells, macrophages, and tumor cells spatially organized?
- Where are checkpoint molecules such as PD-1 and PD-L1 expressed relative to effector cells?
- Do immune cell neighborhoods differ between study groups in a cohort (for example, exposure arms or molecular subtypes)?
By linking marker expression to precise cell locations, mIHC turns static images into quantitative spatial datasets that support robust, hypothesis-driven analysis.
How our mIHC-based multiparameter imaging workflow works
Our mIHC-based multiparameter imaging workflow keeps staining, imaging, and analysis on one coordinated pipeline. You interact with a single team and data structure, which simplifies management and downstream spatial omics integration.
- Study design and panel planning
We align on indications, tissue type, and target markers up front. This reduces later panel changes and ensures each marker supports a clear biological question.
- Sample receipt and quality control
FFPE blocks or slides are logged and screened against standard QC criteria. Early checks minimize failed runs and avoid unnecessary recuts or restaining.
- Optimized multiplex staining
Antigen retrieval and antibody conditions are tuned for your tissue and panel. This improves signal specificity and reduces background, giving cleaner images for quantification.
- High-resolution multichannel imaging
We capture whole slides or defined regions at cell-level resolution across all channels. Consistent imaging settings support reliable comparisons across samples and study batches.
- Image processing and cell-level phenotyping
Images are corrected, segmented, and summarized at the cell level. Automated phenotyping of major immune and tumor populations reduces manual scoring time and observer bias.
- Spatial analysis and reporting
We generate cell density maps, compartment summaries, and neighborhood metrics matched to your study design. Results are delivered as interpretable figures plus structured tables ready for statistical analysis or multi-omics integration.
Applications: tumor microenvironment and spatial immunology studies
mIHC-based spatial immune profiling is most powerful when you need to understand which cells are present, where they sit, and how they interact inside complex tissues. It is especially useful for tumor microenvironment projects and immunology studies where location matters as much as abundance.
Tumor microenvironment (TME) mapping
mIHC can quantify T cells, B cells, macrophages, tumor cells, and stromal elements in the same section. You can distinguish inflamed, immune-excluded, and immune-desert phenotypes, rather than relying only on bulk cell counts. This supports clearer interpretation of tumor biology and more rational biomarker selection.
Tertiary lymphoid structures and lymphoid niches
By staining coordinated B-cell, T-cell, and dendritic cell markers, mIHC helps confirm and characterize tertiary lymphoid structures. You gain insight into local antigen presentation and humoral responses, which are difficult to infer from sequencing alone.
Immuno-oncology mechanism and spatial phenotype studies
Panels including checkpoints, activation markers, and proliferation markers support side-by-side comparisons across defined research cohorts. Spatial metrics help reveal whether effector cells reach tumor nests or remain restricted to stroma, strengthening mechanism hypotheses and biomarker research readouts.
Inflammation and autoimmune disease models
In non-oncology tissues, mIHC can track immune cell positioning around lesions, vessels, or parenchyma. This supports studies of chronic inflammation, tissue damage patterns, and the effects of candidate compounds or experimental interventions at the tissue level."
Host–pathogen and infection research
When combined with pathogen localization methods or lesion mapping, mIHC shows how immune subsets organize around infected foci. This helps connect systemic readouts, such as cytokine profiles, with local immune architecture.
Preclinical drug evaluation and biomarker discovery
In preclinical studies, mIHC provides a sensitive readout of how compounds reshape immune landscapes. You can link dosing regimens to changes in cell proximity, checkpoint expression, and proliferation, supporting earlier go or no-go decisions.
Example mIHC panels for spatial immune profiling
Our multiplex immunohistochemistry (mIHC) panels are designed to capture key immune and tumor markers in a single tissue section. Each panel provides coordinated readouts across several cell types and checkpoints, so you can interpret immune context and tumor biology in one integrated view rather than stitching together results from multiple slides.
Below are representative panel designs for spatial immune profiling. Final marker sets are adjusted to your species, tissue type, and study questions.
| Panel type | Representative markers* | Research focus |
|---|---|---|
| TME immune infiltration panel | CD3, CD4, CD8, FOXP3, PD-1, PD-L1, Ki-67, pan-CK, DAPI | T cell balance, checkpoint expression, proliferative status in and around tumor nests |
| TLS / B-cell structure panel | CD20, CD79a, CD21, CD23, CD3, CD138, DAPI | Organization of tertiary lymphoid structures and B-cell–driven responses |
| Macrophage and myeloid compartment | CD68, CD163, CD11c, HLA-DR, CD16, pan-CK, DAPI | Myeloid subsets, macrophage polarization, antigen-presenting niches |
| NK / cytotoxic effector panel | CD56, Granzyme B, Perforin, CD3, CD8, DAPI | Cytotoxic activity, NK and cytotoxic T cell localization relative to tumor areas |
*Exact antibody clones and combinations are finalized during project planning.
Using these multiplex immunohistochemistry panels, you obtain coordinated marker intensities for each cell, together with precise tissue coordinates. This approach concentrates information from limited biopsy material, reduces the number of staining runs, and supports more confident interpretation of tumor microenvironment and immuno-oncology studies. For broader immune profiling strategies across assays, we recommend cross-referencing our immunology and immuno-oncology solution pages.
Bioinformatics and spatial data analysis
Our team provides basic bioinformatics and spatial data analysis to turn mIHC outputs into clear, interpretable results. The goal is to give you ready-to-use summaries and figures without requiring extensive in-house scripting.
Typical analysis options include:
Quality and composition summaries
Overview of marker expression, cell-type composition, and region-level statistics for each sample or group.
Cell-level phenotyping and signatures
Definition of major immune and tumor cell categories based on marker patterns, plus optional composite scores such as "inflamed" or "immune-excluded" profiles.
Spatial metrics and comparisons
Quantification of cell densities, distances, and neighborhood patterns across tumor, stroma, and other defined compartments, with group comparisons where appropriate.
Data export and integration support
Delivery of analysis-ready tables and simple guidance on how to link these results with your existing transcriptomic or genomic datasets.
Analysis scope is agreed during study design, so you receive exactly the level of interpretation you need while keeping full flexibility for your own downstream modeling.
What you will receive
Our multiplex immunohistochemistry service provides images and structured data that can be used directly for analysis and reporting.
- Imaging files
- Multichannel whole-slide or region-of-interest images in standard formats, plus optional overlays highlighting regions of interest.
- Quantitative data tables
- Cell-level marker intensity tables with coordinates, and region-based summaries for tumor, stroma, margins, or other defined areas.
- Compact study report
- A short methods summary, key plots, and main spatial findings aligned with your study objectives.
These outputs give both visual confirmation and ready-to-use numeric data, reducing time spent on re-annotation and file conversion.
Sample requirements for mIHC projects
To ensure stable staining quality, please prepare samples according to the following guidelines:
Sample types
FFPE blocks, paraffin sections, or fresh tissue (for subsequent fixation and embedding).
Handling and fixation
Fix tissue as soon as possible after collection, ideally within about 30 minutes.
Section preparation
Use adhesive (charged) slides.
Recommended section thickness: around 4 μm.
Tissue quality and lesion content
Sections should be intact, without obvious cracking, tearing, scratches, or ink contamination.
Red blood cell contamination and necrotic areas should each be kept below roughly 20%.
Place the lesion near the center of the slide and include the region of interest specified for analysis.
Integration with our spatial multi-omics platform
mIHC sits alongside our spatial transcriptomics, genomics, and other imaging assays as part of a coherent spatial multi-omics platform. Using shared sample IDs, harmonized metadata, and compatible file formats, results from multiplex immunohistochemistry can be combined directly with sequencing-based readouts.
Typical integration strategies include:
mIHC + spatial transcriptomics
- Use mIHC to define immune and tumor phenotypes by protein markers and spatial transcriptomics to characterize gene expression domains in the same lesion or adjacent sections.
mIHC + bulk or targeted sequencing
- Link cell-level spatial patterns of checkpoints, proliferation, and immune composition to bulk RNA-seq, targeted panels, or whole-exome data from matched samples.
mIHC + other imaging assays
- Combine multiplex immunohistochemistry with additional immunofluorescence or in situ hybridization to refine mechanisms suggested by sequencing data.
By aligning these layers within one platform, you obtain coordinated molecular and spatial context, reducing time spent on cross-vendor data wrangling and enabling more robust biomarker and mechanism-of-action insights. For related options, we recommend cross-referencing our spatial transcriptomics and spatial genomics service pages.
Project workflow and typical turnaround
Our mIHC projects follow a simple, transparent workflow. You have one point of contact from inquiry to data delivery.
Project steps
1. inquiry and feasibility
- Share your study goals, tissue types, and target markers.
- We assess feasibility and outline a suitable mIHC strategy.
2. Panel design and quotation
- Panel options, sample numbers, and analyses are defined.
- You receive a detailed quote with scope, deliverables, and indicative timing.
3. Sample shipment and QC
- Samples are received and checked against agreed requirements.
- Any issues are raised before staining to avoid failed runs.
4. Pilot (if needed)
- A small subset is used to optimize staining and imaging settings.
- Pilot outputs are shared for your confirmation.
5. Full study and analysis
- Remaining samples are processed under validated conditions.
- Imaging and spatial analysis follow the agreed plan.
6. Delivery and follow-up
- Images, data tables, and report are delivered in defined formats.
- Optional review calls can be arranged to discuss key findings.
Turnaround time depends on cohort size and panel complexity. A project-specific estimate is provided with the quotation.
Frequently asked questions (FAQ)
References
- Harms, Paul W., et al. "Multiplex Immunohistochemistry and Immunofluorescence: A Practical Update for Pathologists." Modern Pathology, vol. 36, no. 7, 2023.
- Taube, Janis M., et al. "The Society for Immunotherapy of Cancer Statement on Best Practices for Multiplex Immunohistochemistry (IHC) and Immunofluorescence (IF) Staining and Validation." Journal for ImmunoTherapy of Cancer, vol. 8, no. 1, 2020.
- Taube, Janis M., et al. "Society for Immunotherapy of Cancer: Updates and Best Practices for Multiplex Immunohistochemistry (IHC) and Immunofluorescence (IF) Image Analysis and Data Sharing." Journal for Immunotherapy of Cancer, vol. 13, no. 1, 2025, e008875.
- Rojas, Frank, et al. "Multiplex Immunofluorescence and the Digital Image Analysis Workflow for Evaluation of the Tumor Immune Environment in Translational Research." Frontiers in Oncology, vol. 12, 2022.
- Kumar, Gayatri, et al. "Spatial Modelling of the Tumor Microenvironment from Multiplex Immunofluorescence Images: Methods and Applications." Frontiers in Immunology, vol. 14, 2023.
- Lee, Chung-Wein, et al. "Multiplex Immunofluorescence Staining and Image Analysis Assay for Diffuse Large B Cell Lymphoma." Journal of Immunological Methods, vol. 478, 2020.
