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Human leukocyte antigen analysis focuses on the study of HLA molecules, a group of proteins encoded by the major histocompatibility complex (MHC) located on chromosome 6.
HLA molecules play a central role in the immune system by presenting peptide fragments to T cells, enabling the recognition of pathogens and abnormal cells. This mechanism is essential for adaptive immunity, immune surveillance, and self/non-self discrimination.
HLA variability is a key determinant of immune responses, influencing susceptibility to diseases, transplant compatibility, and responses to immunotherapies.
Human leukocyte antigen analysis relies on gene expression-based approaches to study antigen presentation and immune activation pathways.
Human leukocyte antigen biomarker list
Explore the key genes involved in HLA-mediated antigen presentation and immune regulation.
View the full biomarker list.
Human leukocyte antigen analysis is essential in multiple research and clinical contexts.
It is commonly used to:
Class I HLA molecules
(HLA-A, HLA-B, HLA-C)
Present endogenous antigens to CD8+ T cells and enable elimination of infected or tumor cells.
Class II HLA molecules
(HLA-DP, HLA-DQ, HLA-DR)
Expressed on antigen-presenting cells, they present exogenous antigens to CD4+ T cells and regulate immune responses.
The HLA region is functionally connected to broader immune regulation pathways, including cytokine signaling and immune checkpoint mechanisms.
Immune checkpoints
CD274 (PD-L1), PDCD1, PDCD1LG2, CTLA4, LAG3, HAVCR2, CD276, VTCN1
Co-stimulatory molecules
CD80, CD86, CD28, ICOS, ICOSLG, CD40, CD40LG, TNFRSF4, TNFRSF9, TNFRSF14, CD27, CD70, TNFSF4, TNFSF9, TNFSF14
Cytokines and chemokines
IL1A, IL2, IL4, IL5, IL6, IL10, IL12B, IL13, IL17A, IL18, IFNG, IFNB1, TNF, TGFB1, CCL5, CXCL9
Immune signaling pathways
AKT1, STAT3, PIK3CA, NFKBIL1
Immune receptors and regulators
BTLA, LILRB1, KIR3DL1, CD160, KLRG1, CD244, NCR3
Immunometabolism and suppression
IDO1, ENTPD1, NT5E, ADORA2A
Additional HLA locus-associated genes
HSPA1A, HSPA1B, HSPA1L, TAP1, TAP2, SKIV2L, NOTCH4, TRIM39, RNF39, AIF1, BTNL2, DAXX, HSD17B8, GNL1, ALK, C6orf10, OR2H2, TUBB
Analyzing HLA pathways can be challenging due to the high polymorphism and complexity of the MHC region.
Human leukocyte antigen analysis is commonly performed using gene expression profiling approaches to evaluate antigen presentation and immune activation.
Transcriptomic methods provide a global overview of gene expression patterns across HLA-related pathways.
qPCR-based approaches provide targeted and highly reproducible measurement of HLA-related genes, enabling precise analysis of antigen presentation pathways.
This approach is particularly relevant for focused studies and limited sample availability.
Workflow:
Key considerations:
Transplantation
HLA matching is critical to reduce rejection risk and improve graft survival.
Autoimmune diseases
Specific HLA alleles are associated with diseases such as rheumatoid arthritis and type 1 diabetes.
Infectious diseases
HLA variability influences susceptibility to infections such as HIV and tuberculosis.
Cancer immunotherapy
HLA molecules regulate antigen presentation and influence responses to immunotherapies.
Studying HLA pathways requires reliable gene expression tools.
AnyGenes® supports researchers with customized qPCR panels designed for HLA pathway analysis and immune profiling.
Key advantages:
These solutions are widely used in immunology and translational research.
Scientific data is only as powerful as the analysis behind it.
AnyGenes® provides a dedicated data analysis tool specifically developed for SignArrays® pathway panels.
What does it allow you to do?
Developed on Excel (compatible with 2007+), the software is user-friendly and requires no advanced bioinformatics skills.
Customize your own signaling pathways (SignArrays®) with the factors of your choice!
Simply download and complete our Personalized SignArrays® information file
and send it at
[email protected]
to initiate your project.
HLA refers to a group of proteins responsible for antigen presentation and immune recognition.
HLA analysis is typically performed using gene expression profiling and qPCR-based approaches to evaluate antigen presentation and immune activation.
qPCR arrays, transcriptomic methods, and targeted gene panels are commonly used.
They help understand immune responses, disease susceptibility, and transplant compatibility.
Key genes include HLA class I and II molecules and antigen processing genes such as TAP1 and TAP2.
HLA pathways can be studied using gene expression profiling techniques such as qPCR.
| Signaling Pathways | Product ref | Informations |
|---|---|---|
Human Leukocyte Antigen | HLA1H1 |
| Signaling Pathways | Product ref | Informations |
|---|---|---|
Major Histocompatibility Complex (H-2) | H21M1 |
| Signaling Pathways | Product ref | Informations |
|---|---|---|
******* | ******* |
Biomarker list in progress. |
| Signaling Pathways | Product ref | Informations |
|---|---|---|
******* | ******* |
Biomarker list in progress. |
Looking for more answers? Visit our Help & FAQ section to find detailed information about our products, services, and technical support.
1. Medhasi S, Chantratita N. Human Leukocyte Antigen (HLA) System: Genetics and Association with Bacterial and Viral Infections. J Immunol Res. (2022)26;2022:9710376..
2. Wang C, et al. Human leukocyte antigen (HLA) and cancer immunotherapy: HLA-dependent and -independent adoptive immunotherapies. (2020).
3. Crux NB, Elahi S. Human Leukocyte Antigen (HLA) and Immune Regulation: How Do Classical and Non-Classical HLA Alleles Modulate Immune Response to Human Immunodeficiency Virus and Hepatitis C Virus Infections? Front Immunol. (2017)18:8:832.
4. Zhang GL, et al. Human Leukocyte Antigen Typing Using a Knowledge Base Coupled with a High-Throughput Oligonucleotide Probe Array Analysis. Front Immunol. (2014)27;5:597.
5. Cruz-Tapias P, et al. Chapter 10: Major histocompatibility complex: Antigen processing and presentation.
6. Castiblanco J, Anaya JM. Genetics and Vaccines in the Era of Personalized Medicine.Curr Genomics. (2015)16(1):47–59.