HMGA1 negatively regulates NUMB expression at transcriptional and post transcriptional level in glioblastoma stem cells

Puca, Francomichele; Tosti, Nadia; Federico, Antonella; Kuzay, Yalçın; Pepe, Anna; Morlando, Sonia; Savarese, Teresa; D'Alessio, Federica; Colamaio, Marianna; Sarnataro, Daniela; Ziberi, Sihana; Martino, Marco De; Battista, Sabrina

doi:10.1080/15384101.2019.1618541

Cited by 25 publications

(19 citation statements)

References 47 publications

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“…NUMB is fundamental in the balance between symmetric and asymmetric divisions in stem cells, and it is lost/reduced in many tumors including GBM; NUMB mRNA translation is regulated by the mRNA-binding protein MUSASHI-1 (MSI1) and by the micro-RNA miR-146a. HMGA1 binds to the NUMB promoter and negatively regulates its transcription in GBM [247]; HMGA1 also counteracts NUMB expression at the post-transcriptional level, by upregulating MSI1 and miR-146a, both of which inhibit NUMB mRNA translation [247,248]. Noteworthy, NUMB exerts its major effect for maintaining normal neural and glioma stem cell state by inhibiting NOTCH1 signaling, which allows brain tumor growth and glioma stem cell proliferation [249][250][251].…”

Section: Hmga In Stemness Maintenancementioning

confidence: 99%

“…Noteworthy, NUMB exerts its major effect for maintaining normal neural and glioma stem cell state by inhibiting NOTCH1 signaling, which allows brain tumor growth and glioma stem cell proliferation [249][250][251]. Therefore, NUMB upregulation induced by HMGA1 depletion in turn leads to the downregulation of the NOTCH1 pathway, and to the asymmetric mode of cell division typical of non-pathological cells [226,236,247].…”

Section: Hmga In Stemness Maintenancementioning

confidence: 99%

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HMGA Genes and Proteins in Development and Evolution

Vignali

Marracci

2020

IJMS

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HMGA (high mobility group A) (HMGA1 and HMGA2) are small non-histone proteins that can bind DNA and modify chromatin state, thus modulating the accessibility of regulatory factors to the DNA and contributing to the overall panorama of gene expression tuning. In general, they are abundantly expressed during embryogenesis, but are downregulated in the adult differentiated tissues. In the present review, we summarize some aspects of their role during development, also dealing with relevant studies that have shed light on their functioning in cell biology and with emerging possible involvement of HMGA1 and HMGA2 in evolutionary biology.

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Section: Hmga In Stemness Maintenancementioning

confidence: 99%

Section: Hmga In Stemness Maintenancementioning

confidence: 99%

HMGA Genes and Proteins in Development and Evolution

Vignali

Marracci

2020

IJMS

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“…In this study, it was proposed that the transcription of NUMB, a Notch inhibitory factor, is activated by let-7c, subsequently inhibiting the expression of Notch and stemness factors in pancreatic cancer cells. Since it was confirmed that NUMB is transcriptionally and post-transcriptionally inhibited by high mobility group AT-hook 1 (HMGA1) [ 260 ] and that Wnt/β-catenin signaling, which can increase HMGA1 levels, is repressed by let-7c [ 261 , 262 ], quercetin may affect Notch and stemness factor expression via the let-7c/Wnt/β-catenin/HMGA1/NUMB axis. Likewise, miR-200 induced by quercetin can contribute to repress the stemness property of pancreatic cancer cells via directly targeting Notch1 [ 148 ].…”

Section: Tumor-suppressive Mirnas Induced By Phytochemicals Currenmentioning

confidence: 99%

Participation of MicroRNAs in the Treatment of Cancer with Phytochemicals

et al. 2020

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Cancer is a global health concern and one of the main causes of disease-related death. Even with considerable progress in investigations on cancer therapy, effective anti-cancer agents and regimens have thus far been insufficient. There has been compelling evidence that natural phytochemicals and their derivatives have potent anti-cancer activities. Plant-based anti-cancer agents, such as etoposide, irinotecan, paclitaxel, and vincristine, are currently being applied in medical treatments for patients with cancer. Further, the efficacy of plenty of phytochemicals has been evaluated to discover a promising candidate for cancer therapy. For developing more effective cancer therapy, it is required to apprehend the molecular mechanism deployed by natural compounds. MicroRNAs (miRNAs) have been realized to play a pivotal role in regulating cellular signaling pathways, affecting the efficacy of therapeutic agents in cancer. This review presents a feature of phytochemicals with anti-cancer activity, focusing mainly on the relationship between phytochemicals and miRNAs, with insights into the role of miRNAs as the mediators and the regulators of anti-cancer effects of phytochemicals.

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“…Src: SRC proto-oncogene, non-receptor tyrosine kinase Reduce human glioma stem cell migration, invasion, and survival 28712848 [56] Egfr: Epidermal growth factor receptor Promote glioma growth and angiogenesis 22139077 [47] Gab1: GRB2 associated binding protein 1 Promote glioma cell proliferation 30016785 [57] App: amyloid beta precursor protein Promote the proliferation of glioma cells to inhibit the differentiation of glioma cells 28789439 [58] Numb: NUMB endocytic adaptor protein Effective anti-cancer therapy 31116627 [59] Plcg1: phospholipase C gamma 1 Induce Glioblastoma Radioresistance 26896280 [60] Efnb3: ephrin B3 Support glioblastoma growth 28423606 [61] Notch2: notch receptor 2…”

Section: Symbol: Gene Name Function Roles In Gbm Pmid Referencesmentioning

confidence: 99%

Kernel Differential Subgraph Analysis to Reveal the Key Period Affecting Glioblastoma

et al. 2020

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Glioblastoma (GBM) is a fast-growing type of malignant primary brain tumor. To explore the mechanisms in GBM, complex biological networks are used to reveal crucial changes among different biological states, which reflect on the development of living organisms. It is critical to discover the kernel differential subgraph (KDS) that leads to drastic changes. However, identifying the KDS is similar to the Steiner Tree problem that is an NP-hard problem. In this paper, we developed a criterion to explore the KDS (CKDS), which considered the connectivity and scale of KDS, the topological difference of nodes and function relevance between genes in the KDS. The CKDS algorithm was applied to simulated datasets and three single-cell RNA sequencing (scRNA-seq) datasets including GBM, fetal human cortical neurons (FHCN) and neural differentiation. Then we performed the network topology and functional enrichment analyses on the extracted KDSs. Compared with the state-of-art methods, the CKDS algorithm outperformed on simulated datasets to discover the KDSs. In the GBM and FHCN, seventeen genes (one biomarker, nine regulatory genes, one driver genes, six therapeutic targets) and KEGG pathways in KDSs were strongly supported by literature mining that they were highly interrelated with GBM. Moreover, focused on GBM, there were fifteen genes (including ten regulatory genes, three driver genes, one biomarkers, one therapeutic target) and KEGG pathways found in the KDS of neural differentiation process from activated neural stem cells (aNSC) to neural progenitor cells (NPC), while few genes and no pathway were found in the period from NPC to astrocytes (Ast). These experiments indicated that the process from aNSC to NPC is a key differentiation period affecting the development of GBM. Therefore, the CKDS algorithm provides a unique perspective in identifying cell-type-specific genes and KDSs.

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HMGA1 negatively regulates NUMB expression at transcriptional and post transcriptional level in glioblastoma stem cells

Cited by 25 publications

References 47 publications

HMGA Genes and Proteins in Development and Evolution

HMGA Genes and Proteins in Development and Evolution

Participation of MicroRNAs in the Treatment of Cancer with Phytochemicals

Kernel Differential Subgraph Analysis to Reveal the Key Period Affecting Glioblastoma

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