How Flow Cytometry Powers Cancer Immunotherapy Research

Despite substantial advances in cancer research in recent years, cancer remains the second most prevalent cause of death in the US, with around two million new cases and 626,410 deaths projected for 2026 alone (Siegel et al. 2026).

As a result, researchers are always seeking innovative cancer treatments, while also improving established approaches.

Immunotherapy, which involves modifying the immune system to achieve a beneficial effect against disease or infection, has been revolutionary in the treatment of cancer.

In this blog, we discuss how flow cytometry is used to support cancer immunotherapy research, from characterizing immune cell populations to understanding treatment responses.

The Different Immunotherapies Used for Cancer

First things first, let’s get up to speed on a few of the different types of immunotherapies used in the treatment of cancer.

Monoclonal Antibody Drugs

A common option is the use of monoclonal antibodies to specifically target proteins and trigger or block specific pathways. In particular, immune checkpoint inhibitors (ICI) are a well-established and commonly used class of monoclonal antibody drugs.

Immune checkpoint pathways are the body’s defense mechanism against an overreactive immune system and act to dampen the immune response to avoid damage. However, wily tumor cells have evolved to exploit these pathways to quell immune cells and avoid elimination. Therefore, ICIs act to reinvigorate the immune response against tumor cells (Rezazadeh-Gavgani et al. 2025).

Examples of ICIs include pembrolizumab, a PD-1 inhibitor, atezolizumab, a PD-L1 inhibitor, and ipilimumab, a CTLA-4 inhibitor (Justiz-Vaillant et al. 2025).

Adoptive Cell Transfer

Adoptive cell transfer (ACT) involves harvesting cells from the patient, enhancing them to boost their antitumor capabilities, and then reinfusing them back into the body to unleash their bolstered effects on cancer cells.

The most clinically established form of ACT is chimeric antigen receptor (CAR) T-cell therapy. In this approach, the host T cells are isolated and genetically engineered to express CARs, which recognize specific molecules on cancer cells, before being reinfused into the patient.

CARs can be designed to recognize different targets. For example, a common target is CD19, which is expressed on B cells. CD19-targeting CAR T cells are often used to treat hematological cancers, such as B-cell lymphomas and acute lymphoblastic leukemia. However, using CAR T cells for the treatment of solid tumors has proved more challenging (Rui et al. 2023).

Cancer Vaccines

Cancer vaccines can be either preventive or therapeutic. Preventive vaccines work by training the immune system to respond to viruses that can lead to cancer development, such as HPV, which is the main cause of cervical cancer.

Developing therapeutic cancer vaccines to treat ongoing disease has proven trickier, due to the high heterogeneity of tumors. The overall goal is to train the immune system to recognize and react to tumor-associated antigens.

Some of the most common mechanisms to induce this effect are peptide-based vaccines, in which synthetic tumor-associated peptides are administered often alongside adjuvants to trigger an immune reaction, and autologous dendritic cell (DC)-based vaccines, where DCs from the patient are isolated and loaded with tumor antigens, which they will then present to T cells once reintroduced into the body to activate their functions (Rui et al. 2023, Shah et al. 2025).

Why Is Flow Cytometry Ideal for Immunotherapy?

So, how does flow cytometry fit into this?

Well, the challenge with many immunotherapies is the heterogeneous and dynamic nature of the immune response. Put simply, two patients receiving the same treatment may have completely different immune responses and, therefore, clinical outcomes.

Since cancer immunotherapies typically work by modulating immune cells rather than directly targeting tumor cells, it’s critical for researchers to know which immune cells are present in the tumor microenvironment, what state they are in, and how/if they respond to the treatment.

Flow cytometry is a powerful, high-throughput technique that enables the rapid, multiparametric evaluation of immune populations at the single-cell level. It allows multiple cell populations and subtypes to be characterized within a single sample.

This comprehensive immune-profiling capability positions flow cytometry as a pivotal tool in the discovery, development, and clinical use of cancer immunotherapies (Rusdi and Pawitan 2019).

Flow Cytometry in Cancer Immunotherapy Research

Flow cytometry is a key technique in cancer immunotherapy research due to its ability to perform high-throughput analysis of individual cells. This allows a deeper understanding of tumor biology and immune interactions, supporting the identification of novel targets for treatment.

For example, a recent study by Liu et al. (2025) aimed to investigate how depletion of Lypd6b impacted the progression of tumors in a mouse model of colorectal cancer. Flow cytometry was used extensively throughout the study to confirm that the depletion of specific cells was effective and to identify the presence of tumor-infiltrating cells, their cytokine production, and their activation statuses in knockout compared to wild-type mice.

Another key benefit of flow cytometry in cancer research is its competence in the detection of rare cells—subpopulations that represent less than 0.001% of a population. This supports the analysis of circulating tumor cells (CTCs), offering a non-invasive way to obtain tumor material for monitoring disease progression and treatment response (Danova et al. 2018).

Flow Cytometry in Biomarker Discovery

Due to the heterogeneity of cancers and the immune system, not all immunotherapies will be equally effective for every patient. Therefore, identifying biomarkers that indicate how well a patient will respond to a specific treatment is crucial.

An example of an established biomarker is PD-L1. Patients with PD-L1 expression on at least 50% of tumor cells are much more likely to respond to treatments that block the PD-1/PD-L1 immune checkpoint pathway. The use of predictive biomarkers can reduce treatment costs and the risk of adverse reactions (Wang et al. 2022).

Flow cytometry is a valuable tool in clinical trials for novel biomarkers. It facilitates not only the analysis of the relative abundance of immune cells in a sample, which can itself be a biomarker, but also the in-depth analysis of individual cells, including their activation, proliferation, and differentiation states (Dyikanov et al. 2024).

This extensive immunophenotyping permits the identification of populations or subsets that may be more responsive to specific treatments.

Flow Cytometry and CAR T-Cell Therapy

CAR T-cell therapy uses flow cytometry throughout the entire workflow. It is used in the manufacturing and development process—from ensuring efficient CAR expression and binding to the target to assessing the phenotype and viability of CAR T cells—and in product quality control (for a more comprehensive overview, see our CAR T-Cell Development with Flow Cytometry page).

After infusion into the patient, flow cytometry continues to be of use in the monitoring of CAR T-cell expansion and persistence in the blood. Using flow cytometry, Venglar et al. (2025) found that among patients receiving axi-cel, a CD19-targeting CAR T-cell product, greater expansion was associated with improved progression-free survival but also with higher toxicity. 

Flow Cytometry in Cancer Diagnosis

While not directly related to immunotherapy, flow cytometry can also play an important role in the diagnosis of cancer. In hematological cancers, in particular, flow cytometry is widely used in the identification and characterization of disease.

For example, acute leukemia is a type of blood cancer characterized by the abnormal proliferation of non-functional lymphoid or hematopoietic precursor cells (blasts). Not only can flow cytometry detect leukemia by the percentage of blasts in a sample, but it can also further classify the disease based on blast phenotype.

In B-cell acute lymphoblastic leukemia (B-ALL), blasts exhibit a precursor B-cell phenotype (CD19+ Ig– with cytoplasmic CD22 and CD79a), whereas for T-cell ALL (T-ALL), blasts exhibit a precursor T-cell phenotype (CD3+ CD7+ TdT+) (Li 2022).

The ability of flow cytometry to perform high-parameter analysis enables rapid immunophenotyping of cancer cells, facilitating diagnosis and classification.

Summary

Flow cytometry provides an invaluable method for identifying and characterizing immune cells in cancer immunotherapy. This rapid, high-parameter analysis empowers the detailed understanding of immune-cancer dynamics at the single-cell level, supporting preclinical discovery of novel therapeutic targets, development of innovative therapies and biomarkers, and diagnosis and monitoring of treatment responses in individual patients.