Immune Factor Expression
Immune Factor Expression - Related Videos
08:51
Applying an Inducible Expression System to Study Interference of Bacterial Virulence Factors with Intracellular Signaling
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Cited by 11 •
2015
The method described here is used to induce the apoptotic signaling cascade at defined steps in order to dissect the activity of an anti-apoptotic bacterial effector protein. This method can also be used for inducible expression of pro-apoptotic or toxic proteins, or for dissecting interference with other signaling pathways.
10:08
Flow Cytometry Analysis of Tissue Factor Expression in Human Platelets
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Cited by 2 •
2024
This article outlines the protocol for quantifying the percentage of Tissue Factor (TF)-positive platelets using whole blood flow cytometry, assessing the protein: (1) intracellularly in resting conditions, and (2) on the cell surface, in both resting and activated conditions. Guidance is also provided for evaluating TF-positive platelets in platelet-rich plasma.
14:43
Differentiating Functional Roles of Gene Expression from Immune and Non-immune Cells in Mouse Colitis by Bone Marrow Transplantation
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Cited by 2 •
2012
Bone marrow transplantation provides a way to change the genotype of the bone marrow derived cells. If the gene of interest is expressed in both bone marrow derived cells and non-bone marrow derived cells, bone marrow transplantation can change the bone marrow derived cells to a different genotype without changing the non-bone marrow derived cell genotype.
02:16
Transcription Factors
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2019
Tissue-specific transcription factors contribute to diverse cellular functions in mammals. For example, the gene for beta globin, a major component of hemoglobin, is present in all cells of the body. However, it is only expressed in red blood cells because the transcription factors that can bind to the promoter sequences of the beta globin gene are only expressed in these cells. Tissue-specific transcription factors also ensure that mutations in these factors may impair only the function of...
08:00
Analyzing Tumor Gene Expression Factors with the CorExplorer Web Portal
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2019
We introduce the CorExplorer web portal, an resource for exploration of tumor RNA sequencing factors found by the machine learning algorithm CorEx (Correlation Explanation), and show how factors can be analyzed relative to survival, database annotations, protein-protein interactions, and one another to gain insight into tumor biology and therapeutic interventions.
FAQs
Signals can activate or repress specific genes, producing corresponding changes in RNA and protein levels. This regulation may occur in immune cells, tumor cells, or surrounding stromal cells, allowing the same tumor environment to display distinct immune-related patterns. Examining these signal-linked changes helps researchers connect cellular communication with inflammatory, immunosuppressive, or antitumor states.
RNA and protein measurements represent different stages of gene regulation. Changes in RNA indicate altered gene activity, whereas protein levels show the abundance of the resulting immune-related molecule. Considering both provides a broader view of how signaling affects cytokines, chemokines, receptors, or antigen-presenting proteins and supports more complete interpretation of immune behavior in tumors.
Immune cells, tumor cells, and stromal cells can each contribute distinct expression patterns to the tumor microenvironment. Their combined activity may reveal whether local conditions are inflammatory or immunosuppressive and how tumors influence immune recognition and antitumor activity. Separating or comparing these cellular sources therefore adds context that a single overall expression measurement may not provide.
An expression profile can characterize the immune state surrounding a tumor by showing patterns among cytokines, chemokines, receptors, and antigen-presenting proteins. These patterns may indicate inflammatory or immunosuppressive conditions and can help clarify how the tumor affects immune recognition. The resulting profile gives researchers a molecular way to compare tumor environments and investigate their biological behavior.
Researchers assess expression patterns by examining immune-related RNA and protein levels in relevant cells or tumor-associated samples. The analysis can include immune cells, tumor cells, and surrounding stromal cells so that cell-specific contributions are considered. Comparing these measurements helps identify coordinated patterns linked to the tumor microenvironment, disease progression, or response to treatment.
Expression patterns can serve as biomarkers associated with disease progression or treatment response. They also help researchers investigate immune checkpoint therapy by showing inflammatory or immunosuppressive features of the tumor environment and clarifying changes in immune recognition or antitumor activity. These data support studies that connect molecular profiles with therapeutic outcomes without treating every tumor as immunologically identical.