Immune Suppression Analysis
Immune Suppression Analysis - Related Videos
09:38
Determining Immune System Suppression versus CNS Protection for Pharmacological Interventions in Autoimmune Demyelination
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Cited by 7 •
2016
This protocol describes how to determine whether pharmacological treatments for experimental autoimmune encephalomyelitis show CNS protection as a consequence of suppressing immune cell infiltration or are neuroprotective during the onslaught of immune cell infiltration.
14:01
Human In Vitro Suppression as Screening Tool for the Recognition of an Early State of Immune Imbalance
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2011
Tregs are potent suppressors of the immune system. There is a lack of unique surface markers to define them, hence, definitions of Tregs are primarily functional. Here we describe an optimized in vitro assay capable of identifying immune imbalance in subjects at risk to develop T1D.
03:35
Analysis of Virus-Induced Host Transcriptional Suppression Using Flow Cytometry
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2026
Source: Kalveram, B., et al. Using Click Chemistry to Measure the Effect of Viral Infection on Host-Cell RNA Synthesis. J. Vis. Exp. (2013)This video demonstrates the use of click chemistry and flow cytometry to measure virus-induced suppression of host-cell transcription. Mammalian cells are infected with a virus that expresses a nuclear virulence protein disrupting the host transcription factor complex, while control cells remain transcriptionally active. Incorporation of 5-ethynyl uridine...
08:34
The Measurement and Treatment of Suppression in Amblyopia
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Cited by 54 •
2012
Amblyopia is a developmental disorder of the visual cortex that is often accompanied by strong suppression of one eye. We present a new technique for measuring and treating interocular suppression in patients with amblyopia that can be deployed using virtual reality goggles or a portable iPod Touch device.
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...
FAQs
Inhibitory immune-checkpoint signaling can restrain immune activity within the tumor microenvironment, reducing the effectiveness of cancer-directed immune responses. Analysis focuses on measuring these signals alongside immune-cell behavior rather than treating checkpoint activity as an isolated marker. This helps researchers evaluate whether suppressed immunity may contribute to limited tumor control or resistance to immunotherapy.
Regulatory T cells and myeloid-derived suppressor cells serve as important cellular indicators of suppressive tumor conditions. Their activity can be assessed with cellular assays and related molecular measurements to determine how immune-cell behavior is altered. Comparing their presence or function across samples helps connect the cellular environment with tumor progression and treatment outcomes.
Suppressive cytokines provide a complementary view of the signals that weaken immune responses. Measuring them together with checkpoint signaling can reveal whether multiple suppressive mechanisms operate within the same tumor microenvironment. This combined assessment gives a more informative picture of tumor–immune interactions and may help explain why an immune response remains ineffective despite treatment.
Resistance can be investigated by linking molecular signals, suppressive-cell activity, and functional immune responses with therapeutic outcomes. If these measurements differ between treatment-responsive and treatment-resistant samples, the pattern can suggest which suppressive mechanisms are associated with poor control. Such comparisons help distinguish general immune restraint from changes specifically related to treatment failure.
A workflow may combine molecular, cellular, and functional assays, with each level answering a different question. Molecular assays examine suppressive signals, cellular assays characterize relevant immune-cell populations or activity, and functional assays evaluate the resulting immune behavior. Integrating these measurements supports interpretation of tumor–immune interactions rather than relying on a single readout.
Researchers can apply the analysis when comparing treatment responses across tumors, samples, or experimental conditions. Measurements of checkpoint signaling, suppressive cytokines, regulatory T cells, myeloid-derived suppressor cells, and immune function provide multiple points of comparison. The resulting profiles can show whether a treatment is associated with altered immune suppression and improved or limited antitumor activity.
Biomarker development benefits from measurements that connect immune features with clinically or experimentally relevant outcomes. Suppressive signals and immune-cell behaviors can be evaluated alongside tumor progression and therapeutic response to identify patterns associated with those outcomes. These patterns may help characterize which immune states are informative for treatment comparison or prediction of response.
Results can identify which suppressive mechanisms are most closely linked to weakened immune control, including checkpoint signaling, cytokine activity, or suppressive immune-cell behavior. That information provides a rationale for designing strategies aimed at restoring antitumor immunity. Functional outcomes remain important because reducing a suppressive signal is relevant only if immune behavior and cancer control also improve.