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1.
Br J Cancer ; 128(10): 1862-1878, 2023 05.
Artículo en Inglés | MEDLINE | ID: mdl-36932191

RESUMEN

BACKGROUND: One-third of cancers activate endogenous synthesis of serine/glycine, and can become addicted to this pathway to sustain proliferation and survival. Mechanisms driving this metabolic rewiring remain largely unknown. METHODS: NKX2-1 overexpressing and NKX2-1 knockdown/knockout T-cell leukaemia and lung cancer cell line models were established to study metabolic rewiring using ChIP-qPCR, immunoblotting, mass spectrometry, and proliferation and invasion assays. Findings and therapeutic relevance were validated in mouse models and confirmed in patient datasets. RESULTS: Exploring T-cell leukaemia, lung cancer and neuroendocrine prostate cancer patient datasets highlighted the transcription factor NKX2-1 as putative driver of serine/glycine metabolism. We demonstrate that transcription factor NKX2-1 binds and transcriptionally upregulates serine/glycine synthesis enzyme genes, enabling NKX2-1 expressing cells to proliferate and invade in serine/glycine-depleted conditions. NKX2-1 driven serine/glycine synthesis generates nucleotides and redox molecules, and is associated with an altered cellular lipidome and methylome. Accordingly, NKX2-1 tumour-bearing mice display enhanced tumour aggressiveness associated with systemic metabolic rewiring. Therapeutically, NKX2-1-expressing cancer cells are more sensitive to serine/glycine conversion inhibition by repurposed anti-depressant sertraline, and to etoposide chemotherapy. CONCLUSION: Collectively, we identify NKX2-1 as a novel transcriptional regulator of serine/glycine synthesis addiction across cancers, revealing a therapeutic vulnerability of NKX2-1-driven cancers. Transcription factor NKX2-1 fuels cancer cell proliferation and survival by hyperactivating serine/glycine synthesis, highlighting this pathway as a novel therapeutic target in NKX2-1-positive cancers.


Asunto(s)
Neoplasias Pulmonares , Serina , Animales , Humanos , Ratones , Línea Celular , Línea Celular Tumoral , Glicina , Neoplasias Pulmonares/patología , Serina/metabolismo , Factor Nuclear Tiroideo 1/metabolismo , Factores de Transcripción/genética , Factores de Transcripción/metabolismo
2.
Genome Res ; 30(12): 1815-1834, 2020 12.
Artículo en Inglés | MEDLINE | ID: mdl-32732264

RESUMEN

Deciphering the genomic regulatory code of enhancers is a key challenge in biology because this code underlies cellular identity. A better understanding of how enhancers work will improve the interpretation of noncoding genome variation and empower the generation of cell type-specific drivers for gene therapy. Here, we explore the combination of deep learning and cross-species chromatin accessibility profiling to build explainable enhancer models. We apply this strategy to decipher the enhancer code in melanoma, a relevant case study owing to the presence of distinct melanoma cell states. We trained and validated a deep learning model, called DeepMEL, using chromatin accessibility data of 26 melanoma samples across six different species. We show the accuracy of DeepMEL predictions on the CAGI5 challenge, where it significantly outperforms existing models on the melanoma enhancer of IRF4 Next, we exploit DeepMEL to analyze enhancer architectures and identify accurate transcription factor binding sites for the core regulatory complexes in the two different melanoma states, with distinct roles for each transcription factor, in terms of nucleosome displacement or enhancer activation. Finally, DeepMEL identifies orthologous enhancers across distantly related species, where sequence alignment fails, and the model highlights specific nucleotide substitutions that underlie enhancer turnover. DeepMEL can be used from the Kipoi database to predict and optimize candidate enhancers and to prioritize enhancer mutations. In addition, our computational strategy can be applied to other cancer or normal cell types.


Asunto(s)
Biología Computacional/métodos , Melanoma/genética , Pez Cebra/genética , Animales , Aprendizaje Profundo , Perros , Elementos de Facilitación Genéticos , Regulación Neoplásica de la Expresión Génica , Caballos , Humanos , Ratones , Porcinos
3.
FEBS Lett ; 598(12): 1506-1512, 2024 Jun.
Artículo en Inglés | MEDLINE | ID: mdl-38594214

RESUMEN

Natural resistance-associated macrophage protein 2 (NRAMP 2; also known as DMT1 and encoded by SLC11A2) is mainly known for its iron transport activity. Recently, the DMT1 isoform lacking the iron-response element (nonIRE) was associated with aberrant NOTCH pathway activity. In this report, we investigated the function of DMT1 nonIRE in normal and malignant hematopoiesis. Knockdown of Dmt1 nonIRE in mice showed that it has non-canonical functions in hematopoietic stem cell differentiation: its knockdown suppressed development along the myeloid and lymphoid lineages, while promoting the production of platelets. These phenotypic effects on the hematopoietic system induced by Dmt1 nonIRE knockdown were linked to suppression of Notch/Myc pathway activity. Conversely, our data indicate a non-canonical function for DMT1 nonIRE overexpression in boosting NOTCH pathway activity in T-cell leukemia homeobox protein 1 (TLX1)-defective leukemia. This work sets the stage for future investigation using a multiple-hit T-cell acute lymphoblastic leukemia (T-ALL) model to further investigate the function of DMT1 nonIRE in T-ALL disease development and progression.


Asunto(s)
Proteínas de Transporte de Catión , Hematopoyesis , Isoformas de Proteínas , Receptores Notch , Transducción de Señal , Animales , Hematopoyesis/genética , Ratones , Receptores Notch/metabolismo , Receptores Notch/genética , Proteínas de Transporte de Catión/metabolismo , Proteínas de Transporte de Catión/genética , Isoformas de Proteínas/genética , Isoformas de Proteínas/metabolismo , Leucemia-Linfoma Linfoblástico de Células T Precursoras/metabolismo , Leucemia-Linfoma Linfoblástico de Células T Precursoras/genética , Leucemia-Linfoma Linfoblástico de Células T Precursoras/patología , Humanos , Hierro/metabolismo , Células Madre Hematopoyéticas/metabolismo , Diferenciación Celular , Proteínas de Homeodominio/genética , Proteínas de Homeodominio/metabolismo
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