Immune Dysfunction Analysis
Immune Dysfunction Analysis - Related Videos
04:38
Analysis of Immune Cells in Mouse Nervous Tissues Using Flow Cytometry
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2025
Source: Hidmark, A. S., et al. Analysis of Immune Cells in Single Sciatic Nerves and Dorsal Root Ganglion from a Single Mouse Using Flow Cytometry. J. Vis. Exp. (2017). This video demonstrates the use of flow cytometry to analyze immune cells in mouse sciatic nerves and dorsal root ganglia (DRGs). The process involves labeling immune cells with fluorophore- and biotin-tagged antibodies, stabilizing and permeabilizing the cells, and using fluorescent markers to detect cell-surface and nuclear...
08:35
Qualitative and Quantitative Analysis of the Immune Synapse in the Human System Using Imaging Flow Cytometry
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Cited by 12 •
2019
Here, we describe a complete workflow for the qualitative and quantitative analysis of immune synapses between primary human T cells and antigen-presenting cells. The method is based on imaging flow cytometry, which allows the acquisition and evaluation of several thousand cell images within a relatively short period of time.
08:25
Mass Cytometry Analysis of Systemic and Local Immune Responses in Hepatocellular Carcinoma
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2025
This protocol outlines a comprehensive mass cytometry (cytometry by time-of-flight [CyTOF]) analysis method for evaluating both systemic and local immune responses in hepatocellular carcinoma (HCC). The approach aims to provide insights into the immune landscape of HCC, offering a deeper understanding of the tumor microenvironment and the associated immune mechanisms.
12:14
Isolation and Flow Cytometric Analysis of Immune Cells from the Ischemic Mouse Brain
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Cited by 80 •
2016
Inflammation plays a central role in the pathogenesis of ischemic stroke. Increasing evidence suggests that it acts as a double-edged sword which exacerbates early brain injury, but also contributes to later repair. This protocol describes the isolation of immune cells from the ischemic brain and their subsequent flow cytometric phenotyping.
02:38
Lipopolysaccharide-Induced Acute Lung Injury in Mice for Exosome and Immune Analysis
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2026
Source: Yuan, Z., et al. Bronchoalveolar Lavage Exosomes in Lipopolysaccharide-induced Septic Lung Injury. J. Vis. Exp. (2018)This video demonstrates an in vivo mouse model for inducing and analyzing acute lung injury (ALI) using intraperitoneal administration of bacterial lipopolysaccharide. The inflammatory cascade triggered by alveolar macrophages and neutrophils leads to epithelial and endothelial barrier disruption, allowing fluid and immune cells to accumulate in the alveoli. Alveolar...
FAQs
Tumors can interfere with several linked immune processes, including recognition of abnormal cells, signaling between immune and tumor cells, recruitment of immune populations, and effector activity. An analysis becomes more informative when these processes are considered together rather than treated as isolated measurements. This systems-level view helps identify whether immune changes may support disease progression or limit antitumor activity.
The distinction depends on interpreting immune-cell phenotypes, cytokine profiles, tissue staining results, and gene-expression patterns in relation to one another. Effective responses show patterns associated with active antitumor function, whereas suppressive or exhausted states reflect altered regulation and reduced effectiveness. Comparing these profiles with experimental or clinical outcomes strengthens interpretation and helps avoid relying on a single indicator.
Immune cells do not act independently within tumors. Their interactions can influence signaling, recruitment, regulation, and effector functions, producing either coordinated antitumor activity or a suppressive environment. Immune dysfunction analysis therefore examines cellular relationships alongside individual cell measurements. This approach can reveal mechanisms that are missed when immune populations are evaluated only by their abundance or isolated characteristics.
Treatment resistance may be associated with immune profiles showing disrupted recognition, altered signaling, unfavorable cell recruitment, or impaired effector functions. Immune dysfunction analysis links these features to treatment and disease outcomes to determine whether they correspond with resistance. Such comparisons can identify biological patterns that help explain why an antitumor response is ineffective or not sustained.
A workflow may combine immune-cell phenotyping, cytokine profiling, tissue staining, and gene-expression analysis. Phenotyping characterizes immune populations, while cytokine and gene-expression measurements describe signaling and regulatory patterns. Tissue staining adds information from the biological sample itself. Together, these readouts provide complementary evidence for characterizing the tumor immune microenvironment and its functional state.
It is useful when researchers need to characterize tumor-associated immune states, compare effective and suppressive responses, or relate immune features to disease progression and treatment outcomes. The resulting profiles can support biomarker development and patient stratification, allowing immune characteristics to be considered alongside experimental or clinical results when evaluating cancer biology and therapeutic response.
By measuring immune-cell states, signaling patterns, tissue features, and gene-expression changes, researchers can examine whether an immunotherapy is associated with altered antitumor immunity. Linking these measurements to treatment outcomes helps evaluate response and resistance rather than simply recording treatment exposure. The findings may also guide strategies intended to restore or enhance immune activity against tumors.