Figure 6 - uploaded by Cyrus Khandanpour
Content may be subject to copyright.
Source publication
The DNA-binding zinc finger transcription factors Gfi1 and Gfi1b were discovered over 20 years ago and are recognized today as major regulators of both early hematopoiesis and hematopoietic stem cells. Both proteins function as transcriptional repressors by recruiting histone-modifying enzymes to promoters and enhancers of target genes. The establi...
Context in source publication
Context 1
... with transgenic or gene-deficient mice and with cell lines overexpressing Gfi1 or mutant versions of Gfi1 have enabled the discovery of important roles of both factors in hematopoiesis and blood cell differentiation. This knowledge has helped to clarify the biochemical function of both factors and to understand how mutations or perturbed expression of Gfi1 and Gfi1b are implicated in specific hematologic diseases in patients that range from congenital neutropenia to inherited bleeding disorders to leukemia and lymphoma ( Figure 6). Now, more than 20 years after the initial discovery of Gfi1 and Gfi1b, we have learned so much about their functions that a much clearer picture emerges that underlines their importance in gene regulatory networks that control blood cell formation. ...
Similar publications
It is common for primary care physicians to be faced with children with hematological disorders in everyday practice. The article seeks to provide realistic information for the first-contact physician in handling common hematological diseases in children. Practical step-wise approach to understanding and investigating anemia and bleeding disorders...
Citations
... The associated regions overlap zinc finger domains, which have previously been demonstrated to be involved with this trait ( Figure S5). 8,35,36 Compared with the original whole-gene model, the level of improvement from PW is often quite dramatic: for example, 55% of the significant PW coding models for quantitative traits show a more than 60% improvement in the normalized effect size. Overall, the median fold improvement for significant PW coding models is 2.2 for ORs (range 1.5-12.3; ...
Systematic determination of novel variant pathogenicity remains a major challenge, even when there is an established association between a gene and phenotype. Here we present Power Window (PW), a sliding window technique that identifies the impactful regions of a gene using population-scale clinico-genomic datasets. By sizing analysis windows on the number of variant carriers, rather than the number of variants or nucleotides, statistical power is held constant, enabling the localization of clinical phenotypes and removal of unassociated gene regions. The windows can be built by sliding across either the nucleotide sequence of the gene (through 1D space) or the positions of the amino acids in the folded protein (through 3D space). Using a training set of 350k exomes from the UK Biobank (UKB), we developed PW models for well-established gene-disease associations and tested their accuracy in two independent cohorts (117k UKB exomes and 65k exomes sequenced at Helix in the Healthy Nevada Project, myGenetics, or In Our DNA SC studies). The significant models retained a median of 49% of the qualifying variant carriers in each gene (range 2%–98%), with quantitative traits showing a median effect size improvement of 66% compared with aggregating variants across the entire gene, and binary traits’ odds ratios improving by a median of 2.2-fold. PW showcases that electronic health record-based statistical analyses can accurately distinguish between novel coding variants in established genes that will have high phenotypic penetrance and those that will not, unlocking new potential for human genomics research, drug development, variant interpretation, and precision medicine.
... 7 The expression of GFI1 and GFI1b is lineage and celldependent. 51,52 GFI1b is predominantly expressed in HSCs and megakaryocyte-erythrocyte progenitor cells, whereas GFI1 is highly expressed in the cells of the myeloid lineage. 52 Based on the current results and our previous data, we could say that the metabolic regulation of GFI1 and GFI1b is celldependent. ...
Growth factor independence 1 (GFI1) is a transcriptional repressor protein that plays an essential role in the differentiation of myeloid and lymphoid progenitors. We and other groups have shown that GFI1 has a dose‐dependent role in the initiation, progression, and prognosis of acute myeloid leukaemia (AML) patients by inducing epigenetic changes. We now demonstrate a novel role for dose‐dependent GFI1 expression in regulating metabolism in haematopoietic progenitor and leukaemic cells. Using in‐vitro and ex‐vivo murine models of MLL::AF9‐induced human AML and extra‐cellular flux assays, we now demonstrate that a lower GFI1 expression enhances oxidative phosphorylation rate via upregulation of the FOXO1‐ MYC axis. Our findings underscore the significance of therapeutic exploitation in GFI1‐low‐expressing leukaemia cells by targeting oxidative phosphorylation and glutamine metabolism.
... 7 The expression of GFI1 and GFI1b is lineage and celldependent. 51,52 GFI1b is predominantly expressed in HSCs and megakaryocyte-erythrocyte progenitor cells, whereas GFI1 is highly expressed in the cells of the myeloid lineage. 52 Based on the current results and our previous data, we could say that the metabolic regulation of GFI1 and GFI1b is celldependent. ...
... Furthermore, GFI1 is expressed in the granulocyte/ monocyte and lymphoid lineage, whereas GFI1B is absent in these cells. GFI1B is most highly expressed in megakaryocyte-erythrocyte progenitors and during maturation of these cell types [ Figure 1, reviewed by (36)]. ...
Acute Myeloid Leukemia (AML) is a type of cancer of the blood system that is characterized by an accumulation of immature hematopoietic cells in the bone marrow and blood. Its pathogenesis is characterized by an increase in self-renewal and block in differentiation in hematopoietic stem and progenitor cells. Underlying its pathogenesis is the acquisition of mutations in these cells. As there are many different mutations found in AML that can occur in different combinations the disease is very heterogeneous. There has been some progress in the treatment of AML through the introduction of targeted therapies and a broader application of the stem cell transplantation in its treatment. However, many mutations found in AML are still lacking defined interventions. These are in particular mutations and dysregulation in important myeloid transcription factors and epigenetic regulators that also play a crucial role in normal hematopoietic differentiation. While a direct targeting of the partial loss-of-function or change in function observed in these factors is very difficult to imagine, recent data suggests that the inhibition of LSD1, an important epigenetic regulator, can modulate interactions in the network of myeloid transcription factors and restore differentiation in AML. Interestingly, the impact of LSD1 inhibition in this regard is quite different between normal and malignant hematopoiesis. The effect of LSD1 inhibition involves transcription factors that directly interact with LSD1 such as GFI1 and GFI1B, but also transcription factors that bind to enhancers that are modulated by LSD1 such as PU.1 and C/EBPα as well as transcription factors that are regulated downstream of LSD1 such as IRF8. In this review, we are summarizing the current literature on the impact of LSD1 modulation in normal and malignant hematopoietic cells and the current knowledge how the involved transcription factor networks are altered. We are also exploring how these modulation of transcription factors play into the rational selection of combination partners with LSD1 inhibitors, which is an intense area of clinical investigation.
... Gfi1b is expressed during hematopoiesis and lymphopoiesis and is a key gene for early regulation of B lymphocytes and T lymphocytes (60). After starvation stress, Gfi1b was significantly downregulated in the trunk kidney of S. taeniatus, which may explain the decrease in the proportion of lymphocytes in DLC analysis (61). Malnutrition inhibited acquired immunity leading to depletion in lymphocytes and alteration of their functions (50). ...
Background
Food deprivation is a severe stress across multiple fields and it might be a challenge to immune system.
Methods
In the present study, adult male Sinibrama taeniatus were deprived of feed for 7 to 28 days. We explored the effects of starvation on immunity in S. taeniatus through hematological analysis, antioxidant capacity analysis, detection of the content or activity of immune factors in plasma, and transcriptomic analysis.
Results
The results indicated that biometric indexes significantly decreased in the fish after starvation, the proportion of thrombocyte, neutrophil and monocyte increased and, conversely, the proportion of lymphocyte decreased. The antioxidant indexes (SOD and CAT) and innate immune parameters (LZM, C3) were upregulated in fish suffering from a short period of starvation, while adaptive immune parameter (IgM) conversely declined. The transcriptome analysis revealed the changes of various metabolic regulatory pathways involved in fatty acids and amino acids, as well as the immune responses and antioxidant capacity.
Conclusions
Taken together, this research in the present study suggested an induced innate immunity while a partly suppressed adaptive immunity under a short period starvation.
... 29 GFI1 and GFI1B are important drivers of both hematopoietic stem cell (HSC) differentiation and leukemogenesis. 18,30,31 GFI1 promotes normal lymphoid and myeloid development whereas GFI1B promotes the generation of erythrocytes and megakaryocytes. 31,32 A common attribute of these SNAG-domain-containing transcription factors is their ability to negatively regulate their own gene expression and that of other members of their gene family. ...
... 18,30,31 GFI1 promotes normal lymphoid and myeloid development whereas GFI1B promotes the generation of erythrocytes and megakaryocytes. 31,32 A common attribute of these SNAG-domain-containing transcription factors is their ability to negatively regulate their own gene expression and that of other members of their gene family. 29,[33][34][35][36][37][38][39] The SNAG-dependent transcriptional feedback loops as well as the GFI-and SNAIL-mediated developmental programs are dependent on interactions between these transcription factors and LSD1 in vitro 26,40 ; however, whether such interactions also mediate feedbacks loops during embryogenesis remains unknown. ...
... The gfi1aa and gfi1ab genes are homologous to human GFI1, whereas gfi1b is homologous to human GFI1B. 43 We performed WISH in 24-hpf lsd1 mutants and siblings and found that gfi1aa expression is normally observed exclusively in the ICM and is upregulated in lsd1 mutants ( Genetic mutants in gfi1/1b phenocopy lsd1 mutant hematopoietic defects Gfi1/1b family members control the differentiation of stem/progenitor cells into different lineages during hematopoiesis, 18,30,31 in part through repressing their own expression during lineage commitment. [33][34][35][36][37] Our WISH analysis of gfi1/1b genes in lsd1 mutants suggested that Lsd1 is required for Gfi1 and Gfi1b to repress their own expression in vivo, particularly gfi1ab. ...
Lsd1 functions both as a histone demethylase enzyme and as a scaffold for assembling chromatin modifier and transcription factor complexes to regulate gene expression. The relative contributions of Lsd1’s demethylase and scaffolding functions during embryogenesis are not known. Here, we analyze two independent zebrafish lsd1/kdm1a mutant lines and show Lsd1 is required to repress primitive hematopoietic stem cell gene expression. Lsd1 rescue constructs containing point mutations that selectively abrogate its demethylase or scaffolding capacity demonstrate the scaffolding function of Lsd1, not its demethylase activity, is required for repression of gene expression in vivo. Lsd1’s SNAG-binding domain mediates its scaffolding function and reinforces a negative feedback loop to repress the expression of SNAG-domain-containing genes during embryogenesis, including gfi1 and snai1/2. Our findings reveal a model in which the SNAG-binding and scaffolding function of Lsd1, and its associated negative feedback loop, provide transient and reversible regulation of gene expression during hematopoietic development.
... Gfi1 protein contains a SNAG domain which recruits corepressors (Grimes et al., 1996;Zweidler-Mckay et al., 1996;Velinder et al., 2016), and it acts as a major transcriptional repressor during haematopoiesis (van der Meer et al., 2010;Möröy and Khandanpour 2011;Möröy et al., 2015). However, the Drosophila orthologue of Gfi1 (Senseless, SENS) (Nolo et al., 2000) has been reported to have dual functionality: SENS can act as a DNA-binding transcriptional repressor but also as a transcriptional co-activator of proneural TFs (including Atonal), enhancing their ability to stimulate sensory gene expression (Jafar-Nejad et al., 2003;Acar et al., 2006;Powell et al., 2008;Powell et al., 2012). ...
Although the lineage-determining ability of transcription factors is often modulated according to cellular context, the mechanisms by which such switching occurs are not well known. Using a transcriptional programming model, we found that Atoh1 is repurposed from a neuronal to an inner ear hair cell (HC) determinant by the combined activities of Gfi1 and Pou4f3. In this process, Atoh1 maintains its regulation of neuronal genes but gains ability to regulate HC genes. Pou4f3 enables Atoh1 access to genomic locations controlling the expression of sensory (including HC) genes, but Atoh1 + Pou4f3 are not sufficient for HC differentiation. Gfi1 is key to the Atoh1-induced lineage switch, but surprisingly does not alter Atoh1’s binding profile. Gfi1 acts in two divergent ways. It represses the induction by Atoh1 of genes that antagonise HC differentiation, a function in keeping with its well-known repressor role in haematopoiesis. Remarkably, we find that Gfi1 also acts as a co-activator: it binds directly to Atoh1 at existing target genes to enhance its activity. These findings highlight the diversity of mechanisms by which one TF can redirect the activity of another to enable combinatorial control of cell identity.
... It has also been shown to be associated with neutrophils (the TIMER database also shows a correlation). When GFI1 is mutated, it can lead to neutropenia (Moroy et al., 2015). The relationship between GFI1 and immunoinhibitors and immunostimulators, as well as the way of regulating TILs, provides a direction for the development of new targeted drugs in the future. ...
Background: Colon cancer (CRC) is one of the malignant tumors with a high incidence in the world. Many previous studies on CRC have focused on clinical research. With the in-depth study of CRC, the role of molecular mechanisms in CRC has become increasingly important. Currently, machine learning is widely used in medicine. By combining machine learning with molecular mechanisms, we can better understand CRC’s pathogenesis and develop new treatments for it.
Methods and materials: We used the R language to construct molecular subtypes of colon cancer and subsequently explored prognostic genes with GEPIA2. Enrichment analysis is used by WebGestalt to obtain differential genes. Protein–protein interaction networks of differential genes were constructed using the STRING database and the Cytoscape tool. TIMER2.0 and TISIDB databases were used to investigate the correlation of these genes with immune-infiltrating cells and immune targets. The cBioportal database was used to explore genomic alterations.
Results: In our study, the molecular prognostic model of CRC was constructed to study the prognostic factors of CRC, and finally, it was found that Charcot–Leyden crystal galectin (CLC), zymogen granule protein 16 (ZG16), leucine-rich repeat-containing protein 26 (LRRC26), intelectin 1 (ITLN1), UDP-GlcNAc: betaGal beta-1,3-N-acetylglucosaminyltransferase 6 (B3GNT6), chloride channel accessory 1 (CLCA1), growth factor independent 1 transcriptional repressor (GFI1), aquaporin 8 (AQP8), HEPACAM family member 2 (HEPACAM2), and UDP glucuronosyltransferase family 2 member B15 (UGT2B15) were correlated with the subtype model of CRC prognosis. Enrichment analysis shows that differential genes were mainly associated with immune-inflammatory pathways. GFI1 and CLC were associated with immune cells, immunoinhibitors, and immunostimulator. Genomic analysis shows that there were no significant changes in differential genes.
Conclusion: By constructing molecular subtypes of colon cancer, we discovered new colon cancer prognostic markers, which can provide direction for new treatments in the future.
... Recent reports have shown that GFI1 acts as an oncoprotein in multiple malignancies, such as leukemia and several solid tumors, by promoting cell proliferation or suppressing the immune system (36)(37)(38)(39). Consistently, we showed that GFI1 also functions as an oncoprotein in lung cancer. ...
The switch from anchorage-dependent to anchorage-independent growth is essential for epithelial metastasis. The underlying mechanism, however, is not fully understood. Here in this study, we identified growth factor independent-1 (GFI1), a transcription factor that drives transition from adherent endothelial cells to suspended hematopoietic cells during hematopoiesis, as a critical regulator of anchorage-independence in lung cancer cells. GFI1 elevated the numbers of circulating and lung infiltrating tumor cells in xenograft models and predicted poor prognosis of lung cancer patients. Mechanistically, GFI1 inhibited the expression of multiple adhesion molecules and facilitated substrate detachment. Concomitantly, GFI1 reconfigured chromatin structure of the RASGRP2 gene and increased its expression, causing Rap1 activation and subsequent sustained ERK activation upon detachment, and this leaded to ERK signaling dependency in tumor cells. Our studies unveiled a mechanism by which carcinoma cells hijacked a hematopoietic factor to gain anchorage independence and suggested that the intervention of ERK signaling may suppress metastasis and improve the therapeutic outcome of GFI1-positive lung cancer patients.
... EGR1/2 interact with NAB2, and these complexes (EGR/NAB) regulate MDP differentiation and functioning 46 . A key factor for ensuring a neutrophil over MDP cell fate is CCAAT/enhancer binding protein alpha (C/EBPα) and its downstream repressor Gfi-1 45,46 . Gfi-1 ensures the activation of neutrophil specific genes, and represses MDP cell fate through the inhibition of EGR/NAB complexes 47 . ...
Neutrophils are the most abundant white blood cell, and differentiate in homeostasis in the bone marrow from hematopoietic stem cells (HSCs) via multiple intermediate progenitor cells into mature cells that enter the circulation. Recent findings support a continuous model of differentiation in the bone marrow of heterogeneous HSCs and progenitor populations. Cell fate decisions both at the level of proliferation and differentiation are enforced through expression of lineage-determining transcription factors (LDTFs) and their interactions, that are influenced by both intrinsic (intracellular) as well as extrinsic (extracellular) mechanisms. Neutrophil homeostasis is subjected to positive feedback loops, stemming from the gut microbiome, as well as negative feedback loops resulting from the clearance of apoptotic neutrophils by mature macrophages. Finally, the cellular kinetics regarding the replenishing of the mature neutrophil pool is discussed in light of recent, contradictory data.
