Systemic lupus erythematosus Cell Models for Research
Disease Burden and Research Significance
Systemic lupus erythematosus (SLE) is a chronic autoimmune disease with a global prevalence estimated at 3.41 million cases (WHO, 2023). Incidence ranges from 0.3 to 23.2 per 100,000 person-years, with a female-to-male ratio of 9:1. The 5-year survival rate exceeds 95% in developed countries, but morbidity remains high due to organ damage and infections (NCI). Risk factors include genetic predisposition, hormonal influences, and environmental triggers such as UV light and infections.
SLE is ideal for mechanistic studies due to its complex autoimmune pathogenesis involving dysregulated innate and adaptive immunity. Public datasets such as GEO and ImmPort provide extensive transcriptomic and epigenetic data from patient samples. Open questions include the role of specific genetic variants in disease susceptibility and the molecular mechanisms driving flares. Gene-edited cell models enable functional validation of these variants and identification of novel therapeutic targets.
Core Molecular Pathogenesis
- • SLE pathogenesis involves several key pathways:
- • Type I Interferon (IFN) Pathway: Overproduction of IFN-α by plasmacytoid dendritic cells drives immune dysregulation.
- • B Cell Signaling: Enhanced B cell receptor signaling and defective tolerance lead to autoantibody production.
- • T Cell Dysregulation: Abnormal T cell subsets, including Th17 and Tfh, promote inflammation.
- • Neutrophil Extracellular Traps (NETs): Excessive NET formation exposes self-antigens and activates innate immunity.
| Gene | Frequency (%) | Mutation Type | Functional Effect |
|---|---|---|---|
| IRF5 | 15-20 | SNPs | Increased IFN production |
| STAT4 | 10-15 | SNPs | Enhanced Th1 responses |
| TLR7 | 5-10 | Copy number gain | Increased IFN and autoantibody production |
| PTPN22 | 5-8 | Missense | Altered T cell signaling |
| BANK1 | 5-10 | SNPs | B cell signaling modulation |
Data from TCGA and COSMIC.
- • Key signaling networks in SLE include:
- • Type I IFN Signaling: Activation of JAK-STAT pathway leads to expression of interferon-stimulated genes (ISGs).
- • NF-κB Pathway: Involved in inflammatory cytokine production.
- • PI3K/AKT/mTOR: Regulates lymphocyte survival and proliferation.
- • MAPK Pathway: Modulates cytokine responses in immune cells.
Key nodes: IRF5, STAT4, TLR7, MyD88, TRAF6, and IKKα/β.
Experimental Model Systems
| Cell Line | Origin | Key Mutations |
|---|---|---|
| HEK293 | Human embryonic kidney | None (used for overexpression) |
| THP-1 | Human monocytic leukemia | None (used for innate immune studies) |
| Jurkat | Human T cell leukemia | None (used for T cell signaling) |
| Raji | Human B cell lymphoma | None (used for B cell studies) |
Organoids derived from patient tissues are emerging as more physiologically relevant models, but they are limited by complexity and cost.
- • MRL/lpr mice: Spontaneous lupus-like disease with lymphoproliferation.
- • NZB/W F1 mice: Spontaneous autoimmune disease resembling SLE.
- • Induced models: Pristane-induced lupus in BALB/c mice.
- • PDX models: Patient-derived xenografts are less common for SLE due to the immune component.
CRISPR-based gene editing enables the creation of isogenic cell lines with specific genetic modifications, such as knockouts of susceptibility genes (e.g., IRF5) or knock-ins of disease-associated variants (e.g., TLR7 gain-of-function). These models are commercially available and sequence-verified, providing reproducible tools for mechanistic studies and drug screening. For example, an IRF5 knockout THP-1 line can be used to study IFN pathway regulation, while a TLR7 knock-in HEK293 line can be used for high-throughput screening of TLR7 inhibitors.
Related Disease
| Disease name | Disease type |
|---|
Related Services
Related Products
| Product name | Cat.No. | Species | Gene ID | |
|---|---|---|---|---|
| Clec1a Knockout DC2.4 Cell Line | EDJ-KQ78170 | Mouse | 243653 | Details Get a Quote |
| IKBKE Knockout HEK293 Cell Line | EDJ-KQ246 | Human | 9641 | Details Get a Quote |
| IFNA14 Knockout HEK293 Cell Line | EDJ-KQ469 | Human | 3448 | Details Get a Quote |
| ZFP36 Knockout HEK293 Cell Line | EDJ-KQ1014 | Human | 7538 | Details Get a Quote |
| CRP Knockout HEK293 Cell Line | EDJ-KQ1281 | Human | 1401 | Details Get a Quote |
| CAMK4 Knockout HEK293 Cell Line | EDJ-KQ1455 | Human | 814 | Details Get a Quote |
| FCER1G Knockout HEK293 Cell Line | EDJ-KQ1704 | Human | 2207 | Details Get a Quote |
| MFGE8 Knockout HEK293 Cell Line | EDJ-KQ1889 | Human | 4240 | Details Get a Quote |
| DDX60L Knockout HEK293 Cell Line | EDJ-KQ2065 | Human | 91351 | Details Get a Quote |
| HNRNPAB Knockout HEK293 Cell Line | EDJ-KQ2201 | Human | 3182 | Details Get a Quote |
| LGALS1 Knockout HEK293 Cell Line | EDJ-KQ2283 | Human | 3956 | Details Get a Quote |
| CD6 Knockout HEK293 Cell Line | EDJ-KQ2286 | Human | 923 | Details Get a Quote |
| MS4A4A Knockout HEK293 Cell Line | EDJ-KQ2296 | Human | 51338 | Details Get a Quote |
| MBL2 Knockout HEK293 Cell Line | EDJ-KQ2402 | Human | 4153 | Details Get a Quote |
| IL18BP Knockout HEK293 Cell Line | EDJ-KQ2452 | Human | 10068 | Details Get a Quote |
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Applications of Gene-Edited Cells
Knockout and knock-in lines are used to validate the role of specific genes in SLE pathogenesis. For instance, knocking out IRF5 in THP-1 cells reduces IFN-α production, confirming its role in the pathway. Similarly, introducing a TLR7 gain-of-function mutation into HEK293 cells recapitulates enhanced signaling, enabling study of downstream effects.
Isogenic pairs (wild-type vs. knockout) are used in drug screening to identify compounds that specifically target the mutated pathway. For example, screening a library of kinase inhibitors against a STAT4 knockout line can reveal selective inhibitors. Resistance mechanisms can be studied by exposing cells to increasing drug concentrations and identifying genetic changes.
CRISPR synthetic lethality screens can identify genes that are essential only in the context of a specific mutation. For example, in a TLR7-activated cell line, knocking out genes involved in the IFN pathway may reveal novel therapeutic targets. Such screens can also identify biomarkers for patient stratification.
Public Data Resources
| Database | URL | Description |
|---|---|---|
| TCGA | https://www.cancer.gov/tcga | Cancer genome data (not SLE-specific but useful for immune genes) |
| cBioPortal | https://www.cbioportal.org | Genomic data visualization and analysis |
| DepMap | https://depmap.org | CRISPR screens and cell line data |
| GEO | https://www.ncbi.nlm.nih.gov/geo/ | Gene expression omnibus for transcriptomic data |
| ClinVar | https://www.ncbi.nlm.nih.gov/clinvar/ | Clinical variant database |
| UniProt | https://www.uniprot.org | Protein sequence and function data |