Despite the rise of omics and multiplex platforms, IHC remains one of the most versatile and widely used techniques in research and clinical pathology. It combines the specificity of antibodies with the spatial resolution of histology, allowing researchers and clinicians to detect proteins in the context of intact tissue structure¹. Here’s how different applications of immunohistochemistry are being used across research and diagnostics—and why it still matters.

Understanding disease pathology in situ

One of the most important applications of immunohistochemistry is visualizing disease features directly in tissue. Whether it’s a cancer biopsy or postmortem brain tissue, IHC lets you see where proteins accumulate, how cells are organized, and what pathological changes are present. For example:

• In neurodegenerative diseases like Alzheimer’s disease, IHC is used to detect amyloid-β plaques and tau tangles².
• In cancer, it distinguishes tumor from stroma and can reveal immune cell infiltration^3,4.
• In inflammatory diseases, IHC can identify infiltrating immune subsets and cytokine production⁵.

With this approach, you’re not just looking at a molecular readout; you’re seeing biology unfold in its native context, with spatial fidelity that bulk omics can’t capture.

Classifying cell types in tissue

IHC is a go-to tool for identifying specific cell types based on lineage or state markers, including:

This type of cell classification is especially valuable when working with complex or heterogeneous samples. For example, in tumor microenvironments, combining markers like CD8, PD-1, and FOXP3 can distinguish between cytotoxic T cells, exhausted T cells, and regulatory T cells, helping researchers map immune evasion pathways⁶. Similarly, in neurodegenerative models, markers such as GFAP and CD68 reveal astrocyte activation and microglial response, shedding light on the tissue’s inflammatory status⁷.

By selecting marker panels tailored to the research question, IHC enables both spatial resolution and biological insight, supporting everything from fundamental discovery to translational studies.

Validating targets from screens

High-throughput techniques like RNA-seq or mass spectrometry are often used to identify candidate targets. However, they don’t tell you if those targets are expressed at the protein level, or where. That’s where IHC comes in.

IHC can:

• Confirm whether a transcriptomic “hit” is expressed at the protein level⁸.
• Determine where that protein is found (on the membrane, in the nucleus, or in a specific tissue compartment)⁹.
• Compare expression patterns across disease vs. healthy tissue.

Transcript and protein levels often do not correlate, especially in disease. IHC helps bridge the gap between discovery and relevance, bringing spatial, functional data into play for better target prioritization.

Guiding clinical decisions

IHC is indispensable for diagnosing, subtyping, and stratifying tumors in pathology labs. It helps define both what a tumor is and how it might behave. Some of the most impactful examples include:

●HER2: Used in breast and gastric cancer to determine eligibility for HER2-targeted therapy¹⁰.

●PD-L1: Assessed in lung and other cancers to guide immunotherapy¹¹.

●ER/PR:Hormone receptor testing helps determine endocrine therapy options for breast cancer patients.

Even basic classification relies on IHC. For instance, distinguishing lung adenocarcinoma from squamous cell carcinoma depends on markers like TTF-1  and Napsin A¹². These stains give pathologists diagnostic clarity that morphology alone can’t provide.

Mapping the tumor microenvironment

Recent advances in multiplex IHC allow researchers to detect multiple markers on a single tissue section. This greatly expands the information gathered from one slide and enables microenvironment mapping. Researchers can now:

• Label tumor cells (e.g., cytokeratin), T cells (CD3), macrophages (CD68), and checkpoint molecules (PD-L1) all at once¹³.
• Use digital pathology tools to quantify co-expression and map spatial relationships between cells¹⁴.
• Reveal how immune cells interact with tumors and whether therapies like checkpoint inhibitors are likely to succeed.

For example, the proximity of CD8+ T cells to PD-L1+ tumor cells can predict response to anti-PD-1 therapy¹⁵. In this way, IHC lets you go from observation to quantitative spatial biology.

Integrating IHC into multi-omic workflows

Modern studies rarely use IHC in isolation. It is increasingly paired with other spatial and molecular techniques, such as:

• Immunofluorescence (IF): Enables multiplexing and high-resolution subcellular localization.
• In situ hybridization (ISH): Detects RNA in tissue, which is useful when antibodies are not available or reliable
• Spatial transcriptomics: Maps mRNA expression across the tissue, while IHC provides the protein context.

In these workflows, IHC is a critical layer of multi-modal validation that helps connect gene expression to protein function in the right cells and compartments.

The ever-evolving applications of immunohistochemistry

Immunohistochemistry has earned its place as a foundational method in biomedical research and clinical diagnostics. From confirming protein targets to classifying tumors and guiding therapy, it connects molecular data with the realities of tissue structure and disease biology.

Even as newer techniques emerge, the applications of immunohistochemistry continue to evolve through multiplexing, automation, digital analysis, and integration with other omics. If you are working with complex tissues, validating protein expression, or translating molecular findings into disease models, IHC remains one of the most powerful and accessible tools in your experimental toolbox.

Want to learn more about IHC protocols, reagents, or troubleshooting? Visit our IHC staining guide.

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