| Literature DB >> 34421907 |
Svetlana Korinfskaya1, Sreeja Parameswaran2, Matthew T Weirauch2,3,4, Artem Barski1,4,5.
Abstract
Runx proteins (also known as Runt-domain transcription factors) have been studied for a long time as key regulators of cellular differentiation. RUNX2 has been described as essential for osteogenesis, whereas RUNX1 and RUNX3 are known to control blood cell development during different stages of cell lineage specification. However, recent studies show evidence of complex relationships between RUNX proteins, chromatin-modifying machinery, the cytoskeleton and different transcription factors in various non-embryonic contexts, including mature T cell homeostasis, inflammation and cancer. In this review, we discuss the diversity of Runx functions in mature T helper cells, such as production of cytokines and chemokines by different CD4 T cell populations; apoptosis; and immunologic memory acquisition. We then briefly cover recent findings about the contribution of RUNX1, RUNX2 and RUNX3 to various immunologic diseases. Finally, we discuss areas that require further study to better understand the role that Runx proteins play in inflammation and immunity.Entities:
Keywords: RUNX1; RUNX2; RUNX3; Runt domain; cytokines; mature CD4 T cells; transcription factors
Mesh:
Substances:
Year: 2021 PMID: 34421907 PMCID: PMC8377396 DOI: 10.3389/fimmu.2021.701924
Source DB: PubMed Journal: Front Immunol ISSN: 1664-3224 Impact factor: 7.561
Human and murine Runx family protein domain interactions.
| RUNX1 | RUNX2 | RUNX3 | |
|---|---|---|---|
| Runt (N-terminus) | Transcription factors | ||
| AP-1 ( | AP-1 ( | GATA3 ( | |
| ETS1 ( | ATF4 ( | SMADs ( | |
| FOXP3 ( | ETS ( | STAT5 ( | |
| GATA-1 ( | LET1 ( | TCF4 ( | |
| KLF4 ( | STAT1 ( | ||
| PU.1 ( | STAT5 ( | ||
| SMADs ( | TWIST ( | ||
| STAT5 ( | |||
| Co-regulators | |||
| BRD1 and INI1 (SWI/SNF) ( | CBFβ ( | BRD2 (SWI/SNF) ( | |
| CBFβ ( | CBFβ ( | ||
| CDK6 ( | JAB1/CSN5 ( | ||
| SUV39H1 ( | MDM2 ( | ||
| MLL1 (KMT2A) ( | PIM-1 ( | ||
| TAD | ERK ( | CDK4 ( | CDK4 ( |
| FOXP3 ( | HDAC3 ( | HDACs ( | |
| HDAC1/3 ( | HDAC4 ( | p300 ( | |
| HIPK2 ( | HDAC6 ( | SUV39H1 ( | |
| MOZ ( | MOZ ( | ||
| p300 ( | p300 ( | ||
| SIN3A ( | pRb ( | ||
| SUV39H1 ( | |||
| VWRPY (C-terminus) | TLE/GRG ( | TLE/GRG ( | TLE/GRG ( |
Figure 1RUNX gene expression and function in T helper populations. (A) Expression of Runx proteins in different Th subsets of human CD4+ T cells (129) (GSE149090) processed in SciDAP (https://scidap.com, Datirium); (B) Runx-mediated Th differentiation. In the Th1 subtype (top left), RUNX1 and RUNX3 compete with GATA3 and suppress expression of Th2-signature cytokines, such as IL-4. RUNX3 and T-bet induce IFNG expression. In the Th2 subtype (top right), RUNX1 interacts with the SWI/SNF complex to induce IL3. In the Th17 subtype (bottom left), RUNX1 and RORγt cooperate to induce expression of IL17. In T regulatory cell (Treg) populations (bottom right), RUNX1 is essential for transcription of FOXP3, whose protein product forms a complex with RUNX1 and RUNX3 to inhibit IL2.
Regulatory element locus intersection (RELI) analysis (191) of the overlap between RUNX1 Jurkat T cell chromatin immunoprecipitation sequencing (ChIP-seq) peaks and disease-risk single-nucleotide polymorphisms (SNPs) in the blood and immune system.
| Phenotype | % overlap (observed n/total n) | Adjusted p-value |
|---|---|---|
| Mixed phenotype: chronic inflammatory diseases, ankylosing spondylitis, Crohn disease, psoriasis, primary sclerosing cholangitis, ulcerative colitis, pleiotropy | 21% (45/215) | 1.59E-12 |
| Crohn disease | 24% (39/167) | 4.59E-08 |
| Systemic lupus erythematosus | 25% (24/96) | 6.28E-08 |
| Celiac disease | 33% (14/43) | 2.67E-07 |
| Inflammatory bowel disease | 20% (40/197) | 7.63E-07 |
| Multiple sclerosis | 22% (27/121) | 2.06E-06 |
| Asthma | 18% (22/121) | 5.78E-06 |
| Allergic disease, asthma hay fever or eczema | 17% (23/136) | 1.8E-04 |
| Rheumatoid arthritis | 14% (17/122) | 1.32E-03 |
| Chronic lymphocytic leukemia | 17% (8/48) | 2.72E-03 |
The top 10 most significant genome-wide association study (GWAS) terms are shown. ChIP-seq data from Jurkat cells were obtained from the GEO database, accession number: GSM1697879 (189) and processed using the BioWardrobe software package (192, 193).