FLI1 Regulates Histamine Decarboxylase Expression to Control Inflammation Signaling and Leukemia Progression
Bibliographic record
Abstract
Jifen Hu,1,2,* Jian Gao,1,2,* Chunlin Wang,1,2,* Wuling Liu,1,2 Anling Hu,1,2 Xiao Xiao,1,2 Yi Kuang,1,2 Kunlin Yu,1,2 Babu Gajendran,1– 3 Eldad Zacksenhaus,4 Weidong Pan,1,2 Yaacov Ben-David1,2 1State Key Laboratory for Functions and Applications of Medicinal Plants, Guizhou Medical University, Guiyang, Guizhou, 550014, People’s Republic of China; 2The Key Laboratory of Chemistry for Natural Products of Guizhou Province and Chinese Academic of Sciences, Guiyang, Guizhou, People’s Republic of China; 3School of Pharmaceutical Sciences, Guizhou Medical University, Guiyang, Guizhou Province, 550025, People’s Republic of China; 4Department of Medicine, University of Toronto, Toronto, Ontario, Canada, and Division of Advanced Diagnostics, Toronto General Research Institute, University Health Network, Toronto, Ontario, Canada*These authors contributed equally to this workCorrespondence: Yaacov Ben-David, State Key Laboratory for Functions and Applications of Medicinal Plants, Guizhou Medical University, Province Science City, High Tech Zone, Baiyun District, Guiyang, 550014, People’s Republic of China, Email yaacovbendavid@hotmail.comAim: Histamine decarboxylase (HDC) catalyzes decarboxylation of histidine to generate histamine. This enzyme affects several biological processes including inflammation, allergy, asthma, and cancer, although the underlying mechanism is not fully understood. The present study provides a novel insight into the relationship between the transcription factor FLI1 and its downstream target HDC, and their effects on inflammation and leukemia progression.Methods: Promoter analysis combined with chromatin immunoprecipitation (ChIp) was used to demonstrate binding of FLI1 to the promoter of HDC in leukemic cells. Western blotting and RT-qPCR were used to determine expression of HDC and allergy response genes, and lentivirus shRNA was used to knock-down target genes. Proliferation, cell cycle, apoptosis assays and molecular docking were used to determine the effect of HDC inhibitors in culture. An animal model of leukemia was employed to test the effect of HDC inhibitory compounds in vivo.Results: Results presented herein demonstrate that FLI1 transcriptionally regulates HDC by direct binding to its promoter. Using genetic and pharmacological inhibition of HDC, or the addition of histamine, the enzymatic product of HDC, we show neither have a discernable effect on leukemic cell proliferation in culture. However, HDC controls several inflammatory genes including IL1B and CXCR2 that may influence leukemia progression in vivo through the tumor microenvironment. Indeed, diacerein, an IL1B inhibitor, strongly blocked Fli-1-induced leukemia in mice. In addition to allergy, FLI1 is shown to regulate genes associated with asthma such as IL1B, CPA3 and CXCR2. Toward treatment of these inflammatory conditions, epigallocatechin (EGC), a tea polyphenolic compound, is found strongly inhibit HDC independently of FLI1 and its downstream effector GATA2. Moreover, the HDC inhibitor, tetrandrine, suppressed HDC transcription by directly binding to and inhibiting the FLI1 DNA binding domain, and like other FLI1 inhibitors, tetrandrine strongly suppressed cell proliferation in culture and leukemia progression in vivo.Conclusion: These results suggest a role for the transcription factor FLI1 in inflammation signaling and leukemia progression through HDC and point to the HDC pathway as potential therapeutics for FLI1-driven leukemia.Graphical Abstract: Keywords: HDC, histamine, FLI1, inflammation, allergy, asthma, leukemia progression
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".