Multiplatform single-sample estimates of transcriptional activation

Piccolo, Stephen R.; Withers, Michelle Rachel; Francis, Owen; Bild, Andrea; Johnson, W. Evan

doi:10.1073/pnas.1305823110

Cited by 87 publications

(95 citation statements)

References 36 publications

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“…We obtained exon array gene-expression data on breast cancer cell lines from the Gray cell line panel deposited at ArrayExpress E-MTAB-181 (44). Both datasets were normalized using the SCAN algorithm, and a distant weighted discriminant method was applied (45).…”

Section: Methodsmentioning

confidence: 99%

Metabolic reprogramming in triple-negative breast cancer through Myc suppression of TXNIP

Shen

O’Shea

Kaadige

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

189

197

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Triple-negative breast cancers (TNBCs) are aggressive and lack targeted therapies. Understanding how nutrients are used in TNBCs may provide new targets for therapeutic intervention. We demonstrate that the transcription factor c-Myc drives glucose metabolism in TNBC cells but does so by a previously unappreciated mechanism that involves direct repression of thioredoxin-interacting protein (TXNIP). TXNIP is a potent negative regulator of glucose uptake, aerobic glycolysis, and glycolytic gene expression; thus its repression by c-Myc provides an alternate route to c-Myc-driven glucose metabolism. c-Myc reduces TXNIP gene expression by binding to an E-box-containing region in the TXNIP promoter, possibly competing with the related transcription factor MondoA. TXNIP suppression increases glucose uptake and drives a dependence on glycolysis. Ectopic TXNIP expression decreases glucose uptake, reduces cell proliferation, and increases apoptosis. Supporting the biological significance of the reciprocal relationship between c-Myc and TXNIP, a Myc high /TXNIP low gene signature correlates with decreased overall survival and decreased metastasis-free survival in breast cancer. The correlation between the Myc high /TXNIP low gene signature and poor clinical outcome is evident only in TNBC, not in other breast cancer subclasses. Mutation of TP53, which is a defining molecular feature of TNBC, enhances the correlation between the Myc high /TXNIP low gene signature and death from breast cancer. Because Myc drives nutrient utilization and TXNIP restricts glucose availability, we propose that the Myc high /TXNIP low gene signature coordinates nutrient utilization with nutrient availability. Further, our data suggest that loss of the p53 tumor suppressor cooperates with Myc high /TXNIP low -driven metabolic dysregulation to drive the aggressive clinical behavior of TNBC.Myc | MondoA | thioredoxin-interacting protein | glycolysis | triple-negative breast cancer

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Section: Methodsmentioning

confidence: 99%

Metabolic reprogramming in triple-negative breast cancer through Myc suppression of TXNIP

Shen

O’Shea

Kaadige

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

189

197

View full text Add to dashboard Cite

show abstract

“…The Universal exPression Code approach was used to calculate normalized expression as previously described (30). For coexpression analysis, the Spearman's rank correlation coefficient test was performed.…”

Section: Database Analysismentioning

confidence: 99%

H3K27 Demethylase JMJD3 Employs the NF-κB and BMP Signaling Pathways to Modulate the Tumor Microenvironment and Promote Melanoma Progression and Metastasis

et al. 2016

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Histone methylation is a key epigenetic mark that regulates gene expression. Recently, aberrant histone methylation patterns caused by deregulated histone demethylases have been associated with carcinogenesis. However, the role of histone demethylases, particularly the histone H3 lysine 27 (H3K27) demethylase JMJD3, remains largely uncharacterized in melanoma. Here, we used human melanoma cell lines and a mouse xenograft model to demonstrate a requirement for JMJD3 in melanoma growth and metastasis. Notably, in contrast with previous reports examining T-cell acute lymphoblastic leukemia and hepatoma cells, JMJD3 did not alter the general proliferation rate of melanoma cells in vitro. However, JMJD3 conferred melanoma cells with several malignant features such as enhanced clonogenicity, self-renewal, and transendothelial migration. In addition, JMJD3 enabled melanoma cells not only to create a favorable tumor microenvironment by promoting angiogenesis and macrophage recruitment, but also to activate protumorigenic PI3K signaling upon interaction with stromal components. Mechanistic investigations demonstrated that JMJD3 transcriptionally upregulated several targets of NF-kB and BMP signaling, including stanniocalcin 1 (STC1) and chemokine (C-C motif) ligand 2 (CCL2), which functioned as downstream effectors of JMJD3 in self-renewal and macrophage recruitment, respectively. Furthermore, JMJD3 expression was elevated and positively correlated with that of STC1 and CCL2 in human malignant melanoma. Moreover, we found that BMP4, another JMJD3 target gene, regulated JMJD3 expression via a positive feedback mechanism. Our findings reveal a novel epigenetic mechanism by which JMJD3 promotes melanoma progression and metastasis, and suggest JMJD3 as a potential target for melanoma treatment.

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“…Binary classifications of the 37 chemicals summarized in Table 1 into sensitizers or non-sensitizers were performed with the previously established model based on SVM, using SCAN-normalized (Piccolo et al, 2012(Piccolo et al, , 2013) expression data from the GPS as variable input into the learning algorithm (Johansson et al, 2011). Prior to model construction, potential batch effects between training set and test chemicals were eliminated by scaling array expression values for test chemicals against the training set.…”

Section: Binary Classificationsmentioning

confidence: 99%

“…Array data was imported into the R statistical environment and normalized using the SCANfast algorithm (Piccolo et al, 2012(Piccolo et al, , 2013. As several experimental campaigns needed to be combined, this dataset was normalized using the ComBat method (Leek et al, 2014;Johnson et al, 2007) in order to remove batch effects between samples.…”

Section: Data Handling and Statistical Analysismentioning

confidence: 99%

The GARD platform for potency assessment of skin sensitizing chemicals_suppl

2017

ALTEX

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Multiplatform single-sample estimates of transcriptional activation

Cited by 87 publications

References 36 publications

Metabolic reprogramming in triple-negative breast cancer through Myc suppression of TXNIP

Metabolic reprogramming in triple-negative breast cancer through Myc suppression of TXNIP

H3K27 Demethylase JMJD3 Employs the NF-κB and BMP Signaling Pathways to Modulate the Tumor Microenvironment and Promote Melanoma Progression and Metastasis

The GARD platform for potency assessment of skin sensitizing chemicals_suppl

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