Doing More With Less Tissue: Multiplex Immunofluorescence and the Future of Anatomic Pathology

Anatomic pathology is increasingly being asked to do more with less. A small lung biopsy may need to establish a diagnosis, classify tumor type, preserve material for next-generation sequencing, and support immunotherapy biomarker testing. A lymph node core biopsy may require evaluation of tissue architecture, lineage, proliferation, viral status, and multiple lineage- or subtype-defining markers. In many cases, the limiting factor is no longer the pathologist’s ability to ask the right diagnostic question. It is whether there is enough tissue available to answer all of them.

This tension has made tissue stewardship a central part of modern pathology practice. Every unstained slide cut from a small specimen is an allocation decision. Conventional immunohistochemistry has served pathology extraordinarily well, but it generally answers one question at a time on one tissue section. Multiplex immunofluorescence, or mIF, offers a different approach: multiple protein targets can be assessed on the same tissue section while preserving spatial relationships among tumor cells, inflammatory cells, stromal elements, and normal tissue structures.

The future clinical value of mIF is therefore unlikely to come from multiplexing for its own sake. It will come from practical use cases where pathologists need to conserve tissue, evaluate co-expression, preserve architecture, or understand the spatial relationship among cell populations. In that sense, mIF may become a bridge between conventional immunohistochemistry and the broader field of spatial biology.

What mIF adds

mIF uses antibodies to detect multiple antigens on a single tissue section, with fluorescent signals used for visualization. In lower-plex assays, several fluorophores may be imaged together, often with a nuclear counterstain. In more complex assays, spectral imaging and computational unmixing are used to separate overlapping fluorescent signals and tissue autofluorescence. Other platforms use sequential or cyclic approaches, in which the tissue is stained, imaged, and then subjected to additional rounds of staining and imaging.

The important distinction is that mIF is not simply more immunohistochemistry on one slide. Its additional value is co-localization and spatial context. In serial chromogenic immunohistochemistry (IHC), a pathologist may infer that two markers are present in the same cell population by comparing adjacent sections. In mIF, those markers can be visualized and quantified on the same section, potentially within the same cell. This matters when the clinical or biological question depends on co-expression, proximity, or cell phenotype rather than simple marker presence or absence.

For example, mIF may allow a laboratory to identify tumor cells, cytotoxic T cells, regulatory T cells, macrophages, checkpoint marker expression, proliferation, and spatial relationships among these populations in a single tissue section. These data are particularly attractive in immuno-oncology, where the biology of response may depend not only on whether immune cells are present, but where they are located and how they interact with tumor and stromal compartments. Reviews focused on clinical translation of spatial biology have emphasized that the path from compelling images to clinical diagnostics requires attention to assay design, analytical validation, clinical utility, economics, regulatory requirements, quality systems, and workflow integration.^1,2

Not all mIF is the same

One challenge in discussing mIF is that the term covers a wide range of technologies. A two- or three-color clinical IF assay, a six-marker spectral IF panel, a 20-channel single-round imaging platform, and a 40- to 100-marker spatial biology system all raise different questions for validation, workflow, interpretation, reporting, and reimbursement.

For practical clinical discussion, the following categories are useful:

This distinction matters. The first broadly adopted clinical mIF assays are unlikely to be exploratory 60-marker immune atlases. They are more likely to be low- or mid-plex assays that answer focused questions using markers pathologists already understand.

Several platforms illustrate the range of available approaches. Opal 6-plex detection kits are designed for multiplex fluorescent IHC workflows and include six reactive fluorophores plus spectral DAPI, with imaging compatibility described for systems such as Vectra and Mantra.³ InSituPlex uses DNA-barcoded primary antibodies, amplification, and sequential imaging across FFPE and frozen tissue.⁴ RareCyte’s Orion platform describes 20-channel whole-slide imaging in a single imaging round, a potentially attractive feature because it reduces reliance on repeated stain-image-strip cycles.⁵ Leica Cell DIVE supports visualization of more than 60 biomarkers, and Miltenyi’s MACSima Imaging Cyclic Staining technology is described as enabling analysis of hundreds of markers on a single sample.^6,7 Imaging mass cytometry platforms such as Standard BioTools Hyperion XTi use metal-tagged antibodies rather than fluorescence detection and are best considered adjacent spatial proteomics technologies rather than mIF platforms in the strict sense.⁸

Automated sequential and cyclic IF platforms are particularly relevant to the translational-to-clinical bridge because they preserve tissue architecture while enabling high-plex protein measurement on pathology-compatible specimens. Several platforms now support high-plex iterative imaging workflows on FFPE tissue sections, including Cell DIVE, PhenoCycler-Fusion/CODEX, CellScape, and COMET, although they differ substantially in reagent chemistry, automation, fluorophore/barcode strategy, and antibody requirements. COMET is a useful example from the peer-reviewed literature because Rivest and colleagues described a fully automated sequential IF workflow capable of detecting 40 markers in a single automated run while using unconjugated primary antibodies.⁹ That combination does not by itself make the platform a routine clinical diagnostic instrument, and current use should be framed appropriately in the translational setting while recognizing the near-future potential for clinical deployment.

Tissue stewardship as the near-term clinical value proposition

The most compelling near-term argument for mIF is tissue stewardship. This is particularly important in lung cancer, where small biopsies and cytology cell blocks are often expected to support histologic classification, immunohistochemistry, PD-L1 testing, and molecular profiling. Expert recommendations for advanced non-small cell lung cancer small specimens emphasize that available tissue quantity is often a key constraint, particularly because minimally invasive biopsies may return limited material.¹⁰

In this setting, mIF could allow laboratories to consolidate selected markers onto fewer slides. A low- or mid-plex assay might not replace the full diagnostic workup, but it could reduce the number of sections consumed by common immunophenotypic questions. The value is not only efficiency. It is preserving tissue for downstream molecular testing that may directly determine therapy.

Lymphoma is another attractive use case, although the role of mIF would be different. Hematopathology often requires correlation of morphology, architecture, immunophenotype, flow cytometry, cytogenetics, fluorescence in situ hybridization, and molecular findings. mIF will not replace that integrated approach. However, it may be useful when tissue is limited, when architecture is critical, or when co-expression and spatial distribution of cell populations are diagnostically or biologically relevant. For example, mIF could help characterize relationships among B cells, T cells, macrophages, proliferation markers, EBV-positive cells, and immune microenvironment features while preserving tissue architecture.

Other plausible use cases include metastatic tumors of uncertain origin, small biopsies requiring broad lineage workups, tissue-limited pediatric or rare tumors, and immuno-oncology studies where tumor, immune, and stromal compartments need to be evaluated together. The strongest near-term applications will likely be those in which the markers are already clinically meaningful, the tissue is limited, and the multiplex format either preserves tissue or adds co-localization information that serial sections cannot provide as reliably.

Emerging clinical applications

The literature around mIF is still weighted toward translational research, but several emerging applications show why this technology may become clinically relevant.

One of the most tangible examples is immunotherapy response prediction. In a systematic review and meta-analysis published in JAMA Oncology, Lu and colleagues compared tissue-based biomarker modalities for predicting response to PD-1 and PD-L1 checkpoint blockade. Across tumor specimens from 8,135 patients, multiplex IHC/IF had higher diagnostic accuracy for response prediction than PD-L1 IHC, tumor mutational burden, or gene expression profiling alone.¹¹ This finding should not be overinterpreted as proof that any specific mIF assay is ready for routine clinical use. It does, however, support a biologically intuitive point: single-marker assays may miss important information about which cells express a marker and how those cells are spatially organized.

Melanoma provides a more concrete spatial example. Johnson and colleagues used quantitative spatial profiling of PD-1/PD-L1 interactions and HLA-DR/IDO-1 in metastatic melanoma. Their study found that spatially defined immune interaction signatures were associated with response to anti-PD-1 therapy and improved outcomes.¹² The implication is not merely that PD-L1 is present or absent, but that the location and interaction of PD-1- and PD-L1-expressing cells may carry clinically meaningful information. For pathologists, this is a familiar conceptual extension of morphology: location matters.

Lymphoma is also emerging as a clinically relevant area, particularly for architecture-preserving phenotyping. Recent abstract-level work has begun to explore COMET sequential immunofluorescence for lymphoma tissue diagnostics.¹³ This is not yet equivalent to broad clinical validation, but it points to a plausible direction. Lymphoma diagnosis often depends on both the phenotype of cells and their tissue distribution. A method that preserves architecture while evaluating multiple markers on the same section could be valuable in selected tissue-limited or diagnostically complex cases.

Taken together, these examples suggest that the first clinical wins for mIF may not come from broad, exploratory spatial profiling. They may come from narrower applications where the added information is easy to understand: improved tissue conservation, better co-localization, spatially informed immunotherapy biomarkers, and architecture-preserving phenotyping.

Spatial context and the future of biomarkers

The long-term promise of mIF is not simply that more markers can be measured. It is that pathologists and computational systems may be able to measure spatially organized biology.

In immuno-oncology, for example, a single-marker assay may classify a tumor as positive or negative for a checkpoint protein. A spatial assay might instead ask whether cytotoxic T cells are excluded from tumor nests, whether PD-L1 expression is present on tumor cells or macrophages, whether PD-1-positive T cells are near PD-L1-positive cells, whether antigen-presenting cells are interacting with effector cells, or whether a tumor contains tertiary lymphoid structures. These questions are biologically appealing because they more closely reflect how immune responses occur in tissue.

The challenge is that biologically appealing is not the same as clinically useful. A beautiful multiplex image is not a diagnostic test. To become part of routine practice, an mIF-derived signature must be analytically valid, reproducible across specimens and laboratories, interpretable by pathologists, compatible with clinical workflow, and tied to a clinical decision. Spatial biology companion diagnostic discussions have emphasized these requirements, including assay design, verification, validation, quality systems, and regulatory expectations.¹

Thus, the most likely pathway is staged adoption. First, mIF will continue to mature in translational research and clinical trials. Second, selected laboratories will implement low- to high-plex tissue-sparing assays where the clinical problem is obvious. Third, high to hyper-plex assays may support clinical trial enrollment, pharmacodynamic studies, or exploratory endpoints. Finally, if spatial signatures prove predictive or prognostic in specific settings, they may enter routine care as validated laboratory-developed tests or regulated companion diagnostics.

Reimbursement: better positioned than many emerging technologies, but not automatic

Unlike some new technologies that enter pathology before any clear coding pathway exists, immunofluorescence is already part of clinical practice. Routine immunofluorescence has established CPT coding, including 88346 for an initial single-antibody immunofluorescence procedure and 88350 for each additional single-antibody immunofluorescence procedure. CAP’s digital pathology code listing also identifies add-on digitization codes +0845T and +0846T for glass slides digitized for immunofluorescence in conjunction with 88346 and 88350, respectively.¹⁴

This matters. mIF does not begin from a complete coding vacuum. For clinically justified IF-based workflows, there is already a reimbursement framework that may support adoption more readily than for some entirely novel diagnostic technologies.

However, coding should not be confused with coverage, payment adequacy, or clinical utility. High-plex mIF may involve costs that conventional IF codes were not designed to capture, including instrument acquisition, complex antibody panel validation, spectral or cyclic imaging, image analysis, data storage, algorithm review, and professional interpretation of spatial outputs. In addition, payer acceptance will depend on the clinical indication and whether the result changes diagnosis, prognosis, treatment selection, or downstream testing.

There is also a coding nuance that should not be ignored. CMS NCCI guidance states that the unit of service for immunofluorescent antibody studies, including CPT codes 88346 and 88350, is each antibody staining procedure per specimen.¹⁵ It also notes that if a single antibody staining procedure for one or more antibodies is performed on multiple blocks or slides from the same specimen, only one unit of service is reported for each separate specimen.¹⁵ Final coding decisions will depend on the specific assay, the reportable results, payer policy, and current CPT guidance.

The practical reimbursement message is therefore balanced: mIF benefits from the fact that immunofluorescence is already codable, but successful adoption will still require clinically meaningful use cases and sustainable laboratory economics.

Barriers to clinical adoption

The barriers to mIF adoption are substantial and should not be minimized.

First, analytical validation is more complicated than for a single stain. Each antibody must perform acceptably, but the full multiplex panel must also be validated as a system. Fluorophore selection, signal intensity, tissue autofluorescence, epitope stability, and marker order in cyclic workflows may affect results. Sequential platforms add additional considerations, including tissue integrity across cycles, registration of images across rounds, and potential changes in antigen detectability after repeated processing.

Second, preanalytic variables remain important. Fixation time, cold ischemia, decalcification, section thickness, tissue age, and storage conditions may all affect staining. These variables are familiar to anatomic pathologists, but multiplexing can amplify their importance because multiple targets and computational outputs may depend on consistent tissue and staining quality.

Third, mIF creates interpretive complexity. Outside of tissue preservation use-cases, signature outputs are not simple positive or negative calls. They may include cell segmentation, phenotype classification, marker intensity, cell density, tumor-immune distance, or neighborhood analysis. These measurements can be powerful, but they must be transparent enough for clinical review. Pathologists will need to understand not only the stain, but also the image analysis pipeline.

Fourth, clinical reporting must be simplified. A 20-marker mIF signature assay can produce an enormous amount of data, but most clinical reports must answer a focused question. The pathologist’s role will be to translate and reduce complex spatial information into a clinically meaningful, validated result. Without a clear reporting model, high-plex data risk becoming impressive but challenging to use.

Finally, implementation requires infrastructure. Laboratories may need fluorescent whole-slide imaging, spectral or cyclic imaging platforms, image analysis software, data storage, quality control processes, and LIS integration. These requirements favor staged adoption and focused use cases rather than broad replacement of conventional IHC.

A likely future: complement, not replacement

mIF is unlikely to replace conventional IHC across routine anatomic pathology. Chromogenic IHC is familiar, inexpensive, robust, widely available, and clinically entrenched. For many diagnostic questions, one well-chosen IHC stain on one slide is entirely sufficient.

The more realistic future is complementary. mIF will likely enter clinical practice where it offers something conventional IHC cannot easily provide: preservation of limited tissue, assessment of co-expression, evaluation of spatial relationships, or consolidation of multiple clinically meaningful markers into a single tissue section. The most successful early applications will probably be narrow and practical rather than broad and exploratory.

In the longer term, mIF may help pathology move from single-marker testing toward spatially informed tissue diagnostics. That transition will require evidence, validation, reimbursement, and workflow integration. But the direction is clear: as oncology and other fields ask more complex questions of smaller specimens, technologies that preserve tissue while retaining spatial context will become increasingly important.

For pathologists, the opportunity is to shape this adoption thoughtfully. mIF should not be adopted simply because it can generate more data. It should be adopted when the added information is reproducible, interpretable, clinically actionable, and worth the tissue, time, and cost required to produce it. When used in that way, multiplex immunofluorescence may become one of the most practical bridges between today’s diagnostic immunopathology and tomorrow’s spatially informed precision medicine.

References

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12. Johnson DB, Bordeaux J, Kim JY, et al. Quantitative spatial profiling of PD-1/PD-L1 interaction and HLA-DR/IDO-1 predicts improved outcomes of anti-PD-1 therapies in metastatic melanoma. Clin Cancer Res. 2018;24(21):5250-5260.
13. Shah N, et al. The clinical utility of COMET sequential immunofluorescence in lymphoma tissue diagnostics: next generation diagnosis. Blood. 2025;146(suppl 1):4339. Abstract.
14. College of American Pathologists. Digital Pathology Codes. Accessed May 19, 2026. (College of American Pathologists)
15. Centers for Medicare & Medicaid Services. Medicare NCCI 2026 Coding Policy Manual, Chapter 10. Revision date January 1, 2026. (CMS)