FLT3-ITD drives Ara-C resistance in leukemic cells via the induction of RUNX3

Damdinsuren, Anar; Matsushita, Hiromichi; Ito, Masatoshi; Tanaka, Masayuki; Gui-lan, Jin; Tsukamoto, Hideo; Asai, Satoshi; Ando, Kiyoshi; Miyachi, Hayato

doi:10.1016/j.leukres.2015.09.009

Cited by 15 publications

(12 citation statements)

References 44 publications

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“…Regarding the simulation of over-expression mutants, 11 simulations reproduce the observed phenotypes, 2 simulations disagree with the reported experimental results, and there are no reports regarding the over-expression of 10 genes in the context of NK cell determination, which allows us to propose the phenotypes of these last as predictions of the model. It is noteworthy that the simulated over-expression of FLT3 resulted in an attractor FLT3 + RUNX3 + , which resembles the phenotype of some leukemic cells as shown by Damdinsuren et al ( 2015 ). However, to delve in the study of this disease, more information about regulators related to it must be incorporated.…”

Section: Resultssupporting

confidence: 53%

Dynamical Analysis of the Regulatory Network Controlling Natural Killer Cells Differentiation

Liquitaya-Montiel

Mendoza

2018

Front. Physiol.

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Many disease fighting strategies have focused on the generation of NK cells, since they constitute the main immune barrier against cancer and intracellular pathogens such as viruses. Therefore, a predictive model for the development of NK cells would constitute a useful tool to test several hypotheses regarding the production of these cells during both physiological and pathological conditions. Here, we present a boolean network model that reproduces experimental results reported on the literature regarding the progressive stages of the development of NK cells in wild-type and mutant backgrounds. The model allows for the simulation of different conditions, including extracellular micro-environment as well as the simulation of genetic alterations. It also describes how NK cell differentiation depends on a molecular regulatory network that controls the specification of lymphoid lineages, such as T and B cells, which share a common progenitor with NKs. Furthermore, the study shows that the structure of the regulatory network strongly determines the stability of the expression patterns against perturbations.

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Section: Resultssupporting

confidence: 53%

Dynamical Analysis of the Regulatory Network Controlling Natural Killer Cells Differentiation

Liquitaya-Montiel

Mendoza

2018

Front. Physiol.

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“…Recently it has been demonstrated that RUNX3 when associates with MYC functions as a tumor promoter whereas; acts as a tumor suppressor when interacts with p53 [47]. Various other studies have demonstrated the oncogenic role of RUNX3 [46,[48][49][50][51][52][53][54].…”

Section: Discussionmentioning

confidence: 99%

Elevated expression of RUNX3 co-expressing with EZH2 in esophageal cancer patients from India

Rehman¹,

Iqbal

Sattar³

et al. 2020

Cancer Cell Int

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Background Runt related transcription factor3 (RUNX3) is considered as a tumor suppressor gene (TSG) that functions through the TGF-β dependent apoptosis. Promoter methylation of the CpG islands of RUNX3 and overexpression of enhancer of zeste homolog 2 (EZH2) has been suggested to downregulate RUNX3 in cancer. Methods Here, we studied the expression of RUNX3 and EZH2 in 58 esophageal tumors along with paired adjacent normal tissue. mRNA levels, protein expressions and cellular localizations of EZH2 and RUNX3 were analyzed using real-time PCR and immunohistochemistry, respectively. DNA methylation was further assessed by the methylation specific-PCR. Results Compared to normal tissue, a significant increase in expression of RUNX3 mRNA in 31/57 patient’s tumor tissue (p < 0.04) was observed. The expression of EZH2 was found to be upregulated compared to normal, and a significant positive correlation between EZH2 and RUNX3 expression was observed (p = 0.002). 22 of the 27 unmethylated cases at the promoter region of the RUNX3 had elevated RUNX3 protein expression (p < 0.001). Conclusion The data presented in this study provide new insights into the biology of RUNX3 and highlights the need to revisit our current understanding of the role of RUNX3 in cancer.

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“…Studies conducted in human leukemic K562 transduced with FLT3 -ITD and profiled by gene expression showed the transcriptional induction of RUNX3 in this model. Moreover, the downregulation of RUNX3 expression in these cells increased the sensitivity to Ara-C [ 13 ]. In the recent years, many FLT3 inhibitors have been approved to overcome the genetic disadvantage of this AML category.…”

Section: Mechanisms Of Therapeutic Resistancementioning

confidence: 99%

Deciphering the Therapeutic Resistance in Acute Myeloid Leukemia

Gurnari

Pagliuca

Visconte

2020

IJMS

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Acute myeloid leukemia (AML) is a clonal hematopoietic disorder characterized by abnormal proliferation, lack of cellular differentiation, and infiltration of bone marrow, peripheral blood, or other organs. Induction failure and in general resistance to chemotherapeutic agents represent a hindrance for improving survival outcomes in AML. Here, we review the latest insights in AML biology concerning refractoriness to therapies with a specific focus on cytarabine and daunorubicin which still represent milestones agents for inducing therapeutic response and disease eradication. However, failure to achieve complete remission in AML is still high especially in elderly patients (40–60% in patients >65 years old). Several lines of basic and clinical research have been employed to improve the achievement of complete remission. These lines of research include molecular targeted therapy and more recently immunotherapy. In terms of molecular targeted therapies, specific attention is given to DNMT3A and TP53 mutant AML by reviewing the mechanisms underlying epigenetic therapies’ (e.g., hypomethylating agents) resistance and providing critical points and hints for possible future therapies overcoming AML refractoriness.

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FLT3-ITD drives Ara-C resistance in leukemic cells via the induction of RUNX3

Cited by 15 publications

References 44 publications

Dynamical Analysis of the Regulatory Network Controlling Natural Killer Cells Differentiation

Dynamical Analysis of the Regulatory Network Controlling Natural Killer Cells Differentiation

Elevated expression of RUNX3 co-expressing with EZH2 in esophageal cancer patients from India

Deciphering the Therapeutic Resistance in Acute Myeloid Leukemia

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