Definition and research guide
This page combines a MeSH definition, publication statistics and selected research abstracts. It is a starting point for reading the literature, not a medical textbook or a systematic evidence review.
Content available: 4 complete abstracts (633 words), 10 references. Full article text is not stored or reproduced here; follow the PMID, DOI or PMC links to read the original sources and their access terms.
Definition
Process of classifying cells of the immune system based on structural and functional differences. The process is commonly used to analyze and sort T-lymphocytes into subsets based on CD antigens by the technique of flow cytometry.
Definition: NLM Medical Subject Headings (MeSH) scope note (Public domain (U.S. National Library of Medicine); attribution requested). View the MeSH record.
Also known as: Immunophenotypings; Immunologic Subtyping; Immunologic Subtypings; Subtyping, Immunologic; Subtypings, Immunologic; Lymphocyte Immunophenotyping; Immunophenotyping, Lymphocyte; Immunophenotypings, Lymphocyte.
Where it fits in the MeSH classification
- Broader topics
- Immunologic Tests
Research landscape
PubMed indexes 32,863 records tagged with the MeSH heading “Immunophenotyping” (counts retrieved 2026-11-04). 4,068 of them (12.4%) were published from 2020 onward, and the busiest period so far is 2010-2019 with 11,163 records.
Reviews account for 2,432 records (7.4%) and meta-analyses for 22. Randomized controlled trials number 222 (0.7%) as a share of all records on the topic. Randomized trials make up only a small share of this literature, so much of what is known comes from laboratory, observational or descriptive work.
Show the data
| Period | Records |
|---|---|
| through 1999 | 7,958 |
| 2000-2009 | 9,674 |
| 2010-2019 | 11,163 |
| 2020 onward | 4,068 |
Publication-type chart data
| Type | Records | Share |
|---|---|---|
| Reviews | 2,432 | 7.4% |
| Meta-analyses | 22 | 0.1% |
| Randomized controlled trials | 222 | 0.7% |
Method: PubMed query "Immunophenotyping"[MeSH Terms] with publication-type and date filters, retrieved 2026-11-04.
Reading the evidence in diagnostics and medical technology
A test or device is judged by how well it detects a condition, how often it gives false alarms or misses cases, and whether using it improves outcomes for people. Accuracy depends on who is tested and how common the condition is, so a test that performs well in a specialist hospital can perform differently in the community. Check the reference standard, the population studied, the sensitivity and specificity and whether results were confirmed in a separate group.
Evidence from open-access studies
These open-access studies come from PubMed’s best-match results for this heading (papers whose main topic it is), ranked here by citation count, with one recent addition. Each abstract is reproduced in full under its recorded open licence so that you can read the authors’ own words. They illustrate the literature; they are not a systematic summary of it. Citation counts measure attention, not reliability or clinical benefit.
| Study / authors | Year | Source label / design | Europe PMC citations | Licence / source |
|---|---|---|---|---|
| Immunophenotyping of COVID-19 and influenza highlights the role of type I interferons in development of severe COVID-19 | 2020 | Research article Design not recorded in structured metadata | 799 | cc by PMID 32651212 · DOI · PMC7402635 |
| Comprehensive Immune Monitoring of Clinical Trials to Advance Human Immunotherapy | 2019 | Research article Design not recorded in structured metadata | 111 | cc by PMID 31315057 · DOI · PMC6656694 |
| Characterising the phenotypic evolution of circulating tumour cells during treatment | 2018 | Research article Design not recorded in structured metadata | 77 | cc by PMID 29662054 · DOI · PMC5902511 |
| Deep immunophenotyping reveals circulating activated lymphocytes in individuals at risk for rheumatoid arthritis | 2025 | Research article Design not recorded in structured metadata | 38 | cc by PMID 40091833 · DOI · PMC11910230 |
Immunophenotyping of COVID-19 and influenza highlights the role of type I interferons in development of severe COVID-19 [1]
Abstract reading summary — source excerpts
- Opening excerpt
- Although most SARS-CoV-2-infected individuals experience mild coronavirus disease 2019 (COVID-19), some patients suffer from severe COVID-19, which is accompanied by acute respiratory distress syndrome and systemic inflammation.
- Closing excerpt
- Based on this, we propose that the type I IFN response plays a pivotal role in exacerbating inflammation in severe COVID-19.
- Interpretation limits
- Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (148 words)
Although most SARS-CoV-2-infected individuals experience mild coronavirus disease 2019 (COVID-19), some patients suffer from severe COVID-19, which is accompanied by acute respiratory distress syndrome and systemic inflammation. To identify factors driving severe progression of COVID-19, we performed single-cell RNA-seq using peripheral blood mononuclear cells (PBMCs) obtained from healthy donors, patients with mild or severe COVID-19, and patients with severe influenza. Patients with COVID-19 exhibited hyper-inflammatory signatures across all types of cells among PBMCs, particularly up-regulation of the TNF/IL-1β-driven inflammatory response as compared to severe influenza. In classical monocytes from patients with severe COVID-19, type I IFN response co-existed with the TNF/IL-1β-driven inflammation, and this was not seen in patients with milder COVID-19. Interestingly, we documented type I IFN-driven inflammatory features in patients with severe influenza as well. Based on this, we propose that the type I IFN response plays a pivotal role in exacerbating inflammation in severe COVID-19.
Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 32651212 · DOI · PMC7402635
Comprehensive Immune Monitoring of Clinical Trials to Advance Human Immunotherapy [2]
Abstract reading summary — source excerpts
- Opening excerpt
- The success of immunotherapy has led to a myriad of clinical trials accompanied by efforts to gain mechanistic insight and identify predictive signatures for personalization.
- Closing excerpt
- Together, this validated workflow ensures comprehensive immunophenotypic analysis and data comparability and will accelerate biomarker discovery.
- Interpretation limits
- Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (152 words)
The success of immunotherapy has led to a myriad of clinical trials accompanied by efforts to gain mechanistic insight and identify predictive signatures for personalization. However, many immune monitoring technologies face investigator bias, missing unanticipated cellular responses in limited clinical material. We present here a mass cytometry (CyTOF) workflow for standardized, systems-level biomarker discovery in immunotherapy trials. To broadly enumerate immune cell identity and activity, we established and extensively assessed a reference panel of 33 antibodies to cover major cell subsets, simultaneously quantifying activation and immune checkpoint molecules in a single assay. This assay enumerates ≥98% of peripheral immune cells with ≥4 positively identifying antigens. Robustness and reproducibility are demonstrated on multiple samples types, across two research centers and by orthogonal measurements. Using automated analysis, we identify stratifying immune signatures in bone marrow transplantation-associated graft-versus-host disease. Together, this validated workflow ensures comprehensive immunophenotypic analysis and data comparability and will accelerate biomarker discovery.
Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 31315057 · DOI · PMC6656694
Characterising the phenotypic evolution of circulating tumour cells during treatment [3]
Abstract reading summary — source excerpts
- Opening excerpt
- Real-time monitoring of cancer cells' phenotypic evolution during therapy can provide vital tumour biology information for treatment management.
- Closing excerpt
- We believe our proposed method is of general interest in the CTC relevant research and translation fields.
- Interpretation limits
- Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (150 words)
Real-time monitoring of cancer cells' phenotypic evolution during therapy can provide vital tumour biology information for treatment management. Circulating tumour cell (CTC) analysis has emerged as a useful monitoring tool, but its routine usage is restricted by either limited multiplexing capability or sensitivity. Here, we demonstrate the use of antibody-conjugated and Raman reporter-coated gold nanoparticles for simultaneous labelling and monitoring of multiple CTC surface markers (named as "cell signature"), without the need for isolating individual CTCs. We observe cell heterogeneity and phenotypic changes of melanoma cell lines during molecular targeted treatment. Furthermore, we follow the CTC signature changes of 10 stage-IV melanoma patients receiving immunological or molecular targeted therapies. Our technique maps the phenotypic evolution of patient CTCs sensitively and rapidly, and shows drug-resistant clones having different CTC signatures of potential clinical value. We believe our proposed method is of general interest in the CTC relevant research and translation fields.
Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 29662054 · DOI · PMC5902511
Deep immunophenotyping reveals circulating activated lymphocytes in individuals at risk for rheumatoid arthritis [4]
Abstract reading summary — source excerpts
- Opening excerpt
- Rheumatoid arthritis (RA) is a systemic autoimmune disease currently with no universally highly effective prevention strategies.
- Closing excerpt
- Our integrated study provides a promising approach to identify targets to improve prevention strategy development for RA.
- Interpretation limits
- Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (183 words)
Rheumatoid arthritis (RA) is a systemic autoimmune disease currently with no universally highly effective prevention strategies. Identifying pathogenic immune phenotypes in at-risk populations prior to clinical onset is crucial to establishing effective prevention strategies. Here, we applied multimodal single-cell technologies (mass cytometry and CITE-Seq) to characterize the immunophenotypes in blood from at-risk individuals (ARIs) identified through the presence of serum antibodies against citrullinated protein antigens (ACPAs) and/or first-degree relative (FDR) status, as compared with patients with established RA and people in a healthy control group. We identified significant cell expansions in ARIs compared with controls, including CCR2+CD4+ T cells, T peripheral helper (Tph) cells, type 1 T helper cells, and CXCR5+CD8+ T cells. We also found that CD15+ classical monocytes were specifically expanded in ACPA-negative FDRs, and an activated PAX5lo naive B cell population was expanded in ACPA-positive FDRs. Further, we uncovered the molecular phenotype of the CCR2+CD4+ T cells, expressing high levels of Th17- and Th22-related signature transcripts including CCR6, IL23R, KLRB1, CD96, and IL22. Our integrated study provides a promising approach to identify targets to improve prevention strategy development for RA.
Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 40091833 · DOI · PMC11910230
Key reviews and meta-analyses
The most cited review-type papers among PubMed’s best-match results for this heading, listed with bibliographic details only. Follow the links for the full text and access terms.
- Research article Towards the introduction of the 'Immunoscore' in the classification of malignant tumours [5]
- Research article Standardizing immunophenotyping for the Human Immunology Project [6]
- Research article EuroFlow standardization of flow cytometer instrument settings and immunophenotyping protocols [7]
- Research article Implications for immunosurveillance of altered HLA class I phenotypes in human tumours [8]
- Research article Flow cytometric immunophenotyping for hematologic neoplasms [9]
- Research article Neutrophils and granulocytic myeloid-derived suppressor cells: immunophenotyping, cell biology and clinical relevance in human oncology [10]
References
- Lee JS, Park S, Jeong HW, Ahn JY, Choi SJ, Lee H, et al.. Immunophenotyping of COVID-19 and influenza highlights the role of type I interferons in development of severe COVID-19. . 2020. PMID 32651212 · DOI · PMC7402635
- Hartmann FJ, Babdor J, Gherardini PF, Amir ED, Jones K, Sahaf B, et al.. Comprehensive Immune Monitoring of Clinical Trials to Advance Human Immunotherapy. . 2019. PMID 31315057 · DOI · PMC6656694
- Tsao SC, Wang J, Wang Y, Behren A, Cebon J, Trau M. Characterising the phenotypic evolution of circulating tumour cells during treatment. . 2018. PMID 29662054 · DOI · PMC5902511
- Inamo J, Keegan J, Griffith A, Ghosh T, Horisberger A, Howard K, et al.. Deep immunophenotyping reveals circulating activated lymphocytes in individuals at risk for rheumatoid arthritis. . 2025. PMID 40091833 · DOI · PMC11910230
- Galon J, Mlecnik B, Bindea G, Angell HK, Berger A, Lagorce C, et al.. Towards the introduction of the 'Immunoscore' in the classification of malignant tumours. J Pathol. 2014. PMID 24122236 · DOI · PMC4255306
- Maecker HT, McCoy JP, Nussenblatt R. Standardizing immunophenotyping for the Human Immunology Project. Nat Rev Immunol. 2012. PMID 22343568 · DOI · PMC3409649
- Kalina T, Flores-Montero J, van der Velden VH, Martin-Ayuso M, Böttcher S, Ritgen M, et al.. EuroFlow standardization of flow cytometer instrument settings and immunophenotyping protocols. Leukemia. 2012. PMID 22948490 · DOI · PMC3437409
- Garrido F, Ruiz-Cabello F, Cabrera T, Pérez-Villar JJ, López-Botet M, Duggan-Keen M, et al.. Implications for immunosurveillance of altered HLA class I phenotypes in human tumours. Immunol Today. 1997. PMID 9057360 · DOI
- Craig FE, Foon KA. Flow cytometric immunophenotyping for hematologic neoplasms. Blood. 2008. PMID 18198345 · DOI
- Dumitru CA, Moses K, Trellakis S, Lang S, Brandau S. Neutrophils and granulocytic myeloid-derived suppressor cells: immunophenotyping, cell biology and clinical relevance in human oncology. Cancer Immunol Immunother. 2012. PMID 22692756 · DOI · PMC11028504
About this article
- Sources
- NLM Medical Subject Headings (definition, synonyms); NCBI PubMed (counts, identifiers); Europe PMC (open-access abstracts and citation counts).
- Verification
- Every reference was resolved against PubMed on 2026-11-04; title, year and DOI matched.
- Review state
- automated source verified; no human expert review has been recorded yet.
- Version
- 1, last updated 2026-11-04.
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Evidence strength
EvidenceHelix's computed view of the study designs behind this topic: how common meta-analyses, randomized trials and reviews are, how recent the literature is, and a plain-language reading. It describes the design mix of the literature. It is not a quality appraisal of any study, and it is not medical advice.