FOXM1 Deubiquitination by USP21 Regulates Cell Cycle Progression and Paclitaxel Sensitivity in Basal-like Breast Cancer

Arceci, Anthony; Bonacci, Thomas; Wang, Xianxi; Stewart, Kyle G.; Damrauer, Jeffrey S.; Hoadley, Katherine A.; Emanuele, Michael J.

doi:10.1016/j.celrep.2019.02.054

Cited by 77 publications

(71 citation statements)

References 61 publications

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“…In addition, it has been shown that the FOXM1-PSMB4 axis can play a catalytic role in the proliferation and development of cervical cancer [28]. More surprisingly, FOXM1 plays a vital role in many other cancers [29][30][31][32]. In our study, FOXM1 was upregulated in tumor tissues compared to normal tissues, suggesting a signi cant correlation with melanoma.…”

Section: Discussionsupporting

confidence: 46%

Identification of Hub Genes Associated with Melanoma Development by Comprehensive Bioinformatics Analysis

Jiang

Liang

et al. 2020

Preprint

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Introduction: The aim of this study was to identify important genes associated with melanoma for further development of new target gene therapies and to analyze their significance in relation to prognosis.Materials and methods: Gene expression data for melanoma and normal tissue were downloaded from three databases. Differentially co-expressed genes were identified by WGCNA and DEGs analysis. These genes were subjected to GO and KEGG enrichment analysis as well as construction of the PPI, visualized with Cytoscape, and screened for the top 10 Hub genes using CytoHubba. We verified the protein levels of the Hub gene using the HPA database.Results: A total of 435 differentially co-expressed genes were obtained. Survival curves showed that high expression of FOXM1, EXO1, KIF20A, TPX2 and CDC20 in melanoma patients with 5 of the top 10 hub genes was associated with reduced overall survival (OS). The HPA database results showed that FOXM1, KIF20A, TPX2 and CDC20 showed upregulated expression in melanoma compared to normal tissues.Conclusion: FOXM1, KIF20A, TPX2, and CDC20 are prognosis-associated core genes of melanoma, and their high expression correlates with low prognosis of melanoma patients, and can be used as biomarkers for melanoma diagnosis, treatment, and prognosis prediction.

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Section: Discussionsupporting

confidence: 46%

Identification of Hub Genes Associated with Melanoma Development by Comprehensive Bioinformatics Analysis

Jiang

Liang

et al. 2020

Preprint

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“…In KICH, genes related to the aspartate-malate shuttle were also upregulated suggesting that aspartate can act as an anaplerotic source for the TCA cycle. Further, FOXM1 and its targets (ASNS and FASN) were upregulated in RCC 37 . ASNS promotes the synthesis of asparagine, which is shown to be a suppressor of apoptosis in response to the glutamine withdrawal 38 .…”

Section: Discussionmentioning

confidence: 95%

Network-based metabolic characterization of renal cell carcinoma

Pandey

Lanke

Vinod

2020

Sci Rep

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An emerging hallmark of cancer is metabolic reprogramming, which presents opportunities for cancer diagnosis and treatment based on metabolism. We performed a comprehensive metabolic network analysis of major renal cell carcinoma (Rcc) subtypes including clear cell, papillary and chromophobe by integrating transcriptomic data with the human genome-scale metabolic model to understand the coordination of metabolic pathways in cancer cells. We identified metabolic alterations of each subtype with respect to tumor-adjacent normal samples and compared them to understand the differences between subtypes. We found that genes of amino acid metabolism and redox homeostasis are significantly altered in RCC subtypes. Chromophobe showed metabolic divergence compared to other subtypes with upregulation of genes involved in glutamine anaplerosis and aspartate biosynthesis. A difference in transcriptional regulation involving HIF1A is observed between subtypes. We identified E2F1 and FOXM1 as other major transcriptional activators of metabolic genes in RCC. Further, the co-expression pattern of metabolic genes in each patient showed the variations in metabolism within RCC subtypes. We also found that co-expression modules of each subtype have tumor stage-specific behavior, which may have clinical implications. Major biological processes namely reproduction, development, wound healing and tissue regeneration require cell proliferation. Cells proliferate in response to growth-promoting stimulus however, under adverse conditions they move into a reversible, non-proliferating state termed quiescence. Cells gauge the strength of proliferative and anti-proliferative signals through multiple molecular players to make cellular decisions. Cancer is a proliferative disease that arises when the regulatory control of quiescence-proliferation reversible transition is lost. An emerging hallmark of cancer is metabolic reprogramming, which helps to meet the energy demand for cell growth and division. Initial studies by Otto Warburg pointed to aerobic glycolysis, however recent advances have started to reveal other metabolic alterations and plasticity of cancer metabolism 1,2. Understanding the differences in metabolism between normal and cancer cells can shed light on the adaptations that promote disease progression and may also facilitate the identification of therapeutic metabolic targets. Mutations or epigenetic alterations in cancer can influence the expression of metabolic genes. Studies have explored transcriptome data of different cancers to understand the transcriptional dysregulation of metabolic genes. These studies are based on data generated by The Cancer Genome Atlas (TCGA) program. A pan-cancer analysis of different cancer types found a convergent metabolic landscape with upregulated nucleotide synthesis and downregulated mitochondrial metabolism as the main features 3. Rosario et al. 4 analyzed the gene expression of metabolic pathways in Kyoto Encyclopedia of Genes and Genomes (KEGG) and found that pentose and glucuronate inter...

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“…FOXM1, a transcription factor that contributes to cell cycle progression, is significantly upregulated in BLBC. 54 In hepatocellular carcinoma, USP21 was found to promote tumor growth through stabilization of MEK2. 55 In hematologic malignancy, USP9X was shown to stabilize BCR-ABL and to promote BCR-ABL kinase signaling in CML.…”

Section: Figure 5 Ba Restores the Sensitivity Of K562r Cells To Im Tmentioning

confidence: 99%

Betulinic acid restores imatinib sensitivity in BCR‐ABL1 kinase−independent, imatinib‐resistant chronic myeloid leukemia by increasing HDAC3 ubiquitination and degradation

Lü

Wei

et al. 2020

Annals of the New York Academy of Sciences

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Although imatinib (IM) has been demonstrated to be an efficient treatment in chronic myeloid leukemia (CML), some patients still experience IM resistance and disease relapse. Through in vitro studies, we observed that HDAC3 levels were elevated in BCR‐ABL1 kinase−independent, IM‐resistant primary cells from CML patients and in IM‐resistant K562 (K562R) cells and that downregulation of HDAC3 could enhance IM efficacy in K562R cells. Furthermore, betulinic acid (BA), a lupane‐type pentacyclic triterpenoid saponin isolated from birch trees, restored IM sensitivity in the BCR‐ABL1 kinase−independent, IM‐resistant primary cells and in K562R cells, as well as in primary CD34+ bone marrow cells from CML patients. We found that BA restored IM sensitivity through inhibition of HDAC3 accumulation in cells, and that this was mediated by BA‐dependent ubiquitination and degradation of HDAC3. BA at low dosage significantly increased IM antitumor effects on murine xenografts bearing K562R cells and inhibited HDAC3 expression in tumor tissue. Our findings demonstrated that HDAC3 is an essential factor in BCR‐ABL1 kinase−independent IM resistance, and that BA in combination with IM may be a novel treatment strategy for overcoming IM resistance in CML.

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FOXM1 Deubiquitination by USP21 Regulates Cell Cycle Progression and Paclitaxel Sensitivity in Basal-like Breast Cancer

Cited by 77 publications

References 61 publications

Identification of Hub Genes Associated with Melanoma Development by Comprehensive Bioinformatics Analysis

Identification of Hub Genes Associated with Melanoma Development by Comprehensive Bioinformatics Analysis

Network-based metabolic characterization of renal cell carcinoma

Betulinic acid restores imatinib sensitivity in BCR‐ABL1 kinase−independent, imatinib‐resistant chronic myeloid leukemia by increasing HDAC3 ubiquitination and degradation

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