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Publication Record


Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas.
Schaub FX, Dhankani V, Berger AC, Trivedi M, Richardson AB, Shaw R, Zhao W, Zhang X, Ventura A, Liu Y, Ayer DE, Hurlin PJ, Cherniack AD, Eisenman RN, Bernard B, Grandori C, Cancer Genome Atlas Network
(2018) Cell Syst 6: 282-300.e2
MeSH Terms: Basic Helix-Loop-Helix Leucine Zipper Transcription Factors, Basic Helix-Loop-Helix Transcription Factors, Biomarkers, Tumor, Carcinogenesis, Chromatin, Computational Biology, Genes, myc, Genomics, Humans, Neoplasms, Oncogenes, Proteomics, Proto-Oncogene Proteins c-myc, Repressor Proteins, Signal Transduction, Transcription Factors
Show Abstract · Added October 30, 2019
Although the MYC oncogene has been implicated in cancer, a systematic assessment of alterations of MYC, related transcription factors, and co-regulatory proteins, forming the proximal MYC network (PMN), across human cancers is lacking. Using computational approaches, we define genomic and proteomic features associated with MYC and the PMN across the 33 cancers of The Cancer Genome Atlas. Pan-cancer, 28% of all samples had at least one of the MYC paralogs amplified. In contrast, the MYC antagonists MGA and MNT were the most frequently mutated or deleted members, proposing a role as tumor suppressors. MYC alterations were mutually exclusive with PIK3CA, PTEN, APC, or BRAF alterations, suggesting that MYC is a distinct oncogenic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such as immune response and growth factor signaling; chromatin, translation, and DNA replication/repair were conserved pan-cancer. This analysis reveals insights into MYC biology and is a reference for biomarkers and therapeutics for cancers with alterations of MYC or the PMN.
Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.
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MeSH Terms
Identification of Susceptibility Loci and Genes for Colorectal Cancer Risk.
Zeng C, Matsuda K, Jia WH, Chang J, Kweon SS, Xiang YB, Shin A, Jee SH, Kim DH, Zhang B, Cai Q, Guo X, Long J, Wang N, Courtney R, Pan ZZ, Wu C, Takahashi A, Shin MH, Matsuo K, Matsuda F, Gao YT, Oh JH, Kim S, Jung KJ, Ahn YO, Ren Z, Li HL, Wu J, Shi J, Wen W, Yang G, Li B, Ji BT, Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO), Brenner H, Schoen RE, Küry S, Colorectal Transdisciplinary (CORECT) Study, Gruber SB, Schumacher FR, Stenzel SL, Colon Cancer Family Registry (CCFR), Casey G, Hopper JL, Jenkins MA, Kim HR, Jeong JY, Park JW, Tajima K, Cho SH, Kubo M, Shu XO, Lin D, Zeng YX, Zheng W
(2016) Gastroenterology 150: 1633-1645
MeSH Terms: Adult, Aged, Asian Continental Ancestry Group, Basic Helix-Loop-Helix Leucine Zipper Transcription Factors, Case-Control Studies, Colorectal Neoplasms, Eukaryotic Initiation Factor-3, Female, Genetic Loci, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Male, Middle Aged, Polymorphism, Single Nucleotide, Qb-SNARE Proteins, Ribosomal Proteins, Risk Factors, Steroid 17-alpha-Hydroxylase, Suppressor of Cytokine Signaling Proteins, Young Adult
Show Abstract · Added May 4, 2017
BACKGROUND & AIMS - Known genetic factors explain only a small fraction of genetic variation in colorectal cancer (CRC). We conducted a genome-wide association study to identify risk loci for CRC.
METHODS - This discovery stage included 8027 cases and 22,577 controls of East-Asian ancestry. Promising variants were evaluated in studies including as many as 11,044 cases and 12,047 controls. Tumor-adjacent normal tissues from 188 patients were analyzed to evaluate correlations of risk variants with expression levels of nearby genes. Potential functionality of risk variants were evaluated using public genomic and epigenomic databases.
RESULTS - We identified 4 loci associated with CRC risk; P values for the most significant variant in each locus ranged from 3.92 × 10(-8) to 1.24 × 10(-12): 6p21.1 (rs4711689), 8q23.3 (rs2450115, rs6469656), 10q24.3 (rs4919687), and 12p13.3 (rs11064437). We also identified 2 risk variants at loci previously associated with CRC: 10q25.2 (rs10506868) and 20q13.3 (rs6061231). These risk variants, conferring an approximate 10%-18% increase in risk per allele, are located either inside or near protein-coding genes that include transcription factor EB (lysosome biogenesis and autophagy), eukaryotic translation initiation factor 3, subunit H (initiation of translation), cytochrome P450, family 17, subfamily A, polypeptide 1 (steroidogenesis), splA/ryanodine receptor domain and SOCS box containing 2 (proteasome degradation), and ribosomal protein S2 (ribosome biogenesis). Gene expression analyses showed a significant association (P < .05) for rs4711689 with transcription factor EB, rs6469656 with eukaryotic translation initiation factor 3, subunit H, rs11064437 with splA/ryanodine receptor domain and SOCS box containing 2, and rs6061231 with ribosomal protein S2.
CONCLUSIONS - We identified susceptibility loci and genes associated with CRC risk, linking CRC predisposition to steroid hormone, protein synthesis and degradation, and autophagy pathways and providing added insight into the mechanism of CRC pathogenesis.
Copyright © 2016 AGA Institute. Published by Elsevier Inc. All rights reserved.
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21 MeSH Terms
The MYC-WDR5 Nexus and Cancer.
Thomas LR, Foshage AM, Weissmiller AM, Tansey WP
(2015) Cancer Res 75: 4012-5
MeSH Terms: Antineoplastic Agents, Basic Helix-Loop-Helix Leucine Zipper Transcription Factors, Chromatin Assembly and Disassembly, DNA, DNA Methylation, Drug Discovery, Epigenesis, Genetic, Gene Expression Regulation, Neoplastic, Genes, myc, Histone-Lysine N-Methyltransferase, Histones, Humans, Intracellular Signaling Peptides and Proteins, Models, Genetic, Molecular Targeted Therapy, Neoplasm Proteins, Neoplasms, Protein Binding, Proto-Oncogene Proteins c-myc, Repressor Proteins, Signal Transduction
Show Abstract · Added March 26, 2019
The MYC oncogenes encode a family of transcription factors that feature prominently in cancer. MYC proteins are overexpressed or deregulated in a majority of malignancies and drive tumorigenesis by inducing widespread transcriptional reprogramming that promotes cell proliferation, metabolism, and genomic instability. The ability of MYC to regulate transcription depends on its dimerization with MAX, which creates a DNA-binding domain that recognizes specific sequences in the regulatory elements of MYC target genes. Recently, we discovered that recognition of target genes by MYC also depends on its interaction with WDR5, a WD40-repeat protein that exists as part of several chromatin-regulatory complexes. Here, we discuss how interaction of MYC with WDR5 could create an avidity-based chromatin recognition mechanism that allows MYC to select its target genes in response to both genetic and epigenetic determinants. We rationalize how the MYC-WDR5 interaction provides plasticity in target gene selection by MYC and speculate on the biochemical and genomic contexts in which this interaction occurs. Finally, we discuss how properties of the MYC-WDR5 interface make it an attractive point for discovery of small-molecule inhibitors of MYC function in cancer cells.
©2015 American Association for Cancer Research.
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21 MeSH Terms
Alveolar soft part sarcoma and granular cell tumor: an immunohistochemical comparison study.
Chamberlain BK, McClain CM, Gonzalez RS, Coffin CM, Cates JM
(2014) Hum Pathol 45: 1039-44
MeSH Terms: Basic Helix-Loop-Helix Leucine Zipper Transcription Factors, Calbindin 2, Granular Cell Tumor, Humans, Immunohistochemistry, Inhibins, Nestin, S100 Proteins, SOXE Transcription Factors, Sarcoma, Alveolar Soft Part, Sensitivity and Specificity, Staining and Labeling
Show Abstract · Added February 15, 2016
Although the histologic features of alveolar soft part sarcoma and granular cell tumor are typically distinctive, occasional cases show a significant morphologic overlap. Differentiating these entities is crucial because granular cell tumor is almost always benign and alveolar soft part sarcoma is invariably malignant. We evaluated a panel of immunohistochemical stains (S-100 protein, inhibin, SOX10, nestin, calretinin, and TFE3) in 13 alveolar soft part sarcomas and 11 granular cell tumors. Tissue sections were also stained by the periodic acid-Schiff method after diastase digestion (PAS-D) and evaluated for coarse cytoplasmic granularity or crystalline cytoplasmic inclusions. S-100 protein, inhibin, SOX10, and nestin each distinguished granular cell tumor and alveolar soft part sarcoma with 100% sensitivity and specificity. PAS-D staining also distinguished cases with 100% accuracy, as granular cell tumor consistently demonstrated coarsely granular, PAS-D-positive cytoplasm and alveolar soft part sarcoma showed only focal intracytoplasmic crystalline inclusions. Although all granular cell tumors were calretinin positive, so were 46% of alveolar soft part sarcomas. TFE3 was positive in 91% of granular cell tumors and all alveolar soft part sarcomas. Together with PAS-D, immunohistochemical stains for S-100 protein, inhibin, SOX10, and nestin accurately identify alveolar soft part sarcoma and granular cell tumor. Although TFE3 has been reported as a relatively specific marker for alveolar soft part sarcoma, it should be recalled that it is also expressed in most granular cell tumors.
Copyright © 2014 Elsevier Inc. All rights reserved.
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12 MeSH Terms
A role for presenilins in autophagy revisited: normal acidification of lysosomes in cells lacking PSEN1 and PSEN2.
Zhang X, Garbett K, Veeraraghavalu K, Wilburn B, Gilmore R, Mirnics K, Sisodia SS
(2012) J Neurosci 32: 8633-48
MeSH Terms: Animals, Autophagy, Basic Helix-Loop-Helix Leucine Zipper Transcription Factors, Blastocyst, Blotting, Western, Cathepsin D, Cell Line, Tumor, Cells, Cultured, DNA Primers, Gene Expression, Humans, Hydrogen-Ion Concentration, Lysosomes, Mice, Mice, Knockout, Neurons, Polymerase Chain Reaction, Presenilin-1, Presenilin-2, Presenilins, RNA, RNA, Small Interfering, Vacuolar Proton-Translocating ATPases
Show Abstract · Added May 19, 2014
Presenilins 1 and 2 (PS1 and PS2) are the catalytic subunits of the γ-secretase complex, and genes encoding mutant PS1 and PS2 variants cause familial forms of Alzheimer's disease. Lee et al. (2010) recently reported that loss of PS1 activity lead to impairments in autophagosomal function as a consequence of lysosomal alkalinization, caused by failed maturation of the proton translocating V0a1 subunit of the vacuolar (H+)-ATPase and targeting to the lysosome. We have reexamined these issues in mammalian cells and in brains of mice lacking PS (PScdko) and have been unable to find evidence that the turnover of autophagic substrates, vesicle pH, V0a1 maturation, or lysosome function is altered compared with wild-type counterparts. Collectively, our studies fail to document a role for presenilins in regulating cellular autophagosomal function. On the other hand, our transcriptome studies of PScdko mouse brains reveal, for the first time, a role for PS in regulating lysosomal biogenesis.
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23 MeSH Terms
Attenuation of the beta-catenin/TCF4 complex in colorectal cancer cells induces several growth-suppressive microRNAs that target cancer promoting genes.
Schepeler T, Holm A, Halvey P, Nordentoft I, Lamy P, Riising EM, Christensen LL, Thorsen K, Liebler DC, Helin K, Ørntoft TF, Andersen CL
(2012) Oncogene 31: 2750-60
MeSH Terms: Aged, Aged, 80 and over, Basic Helix-Loop-Helix Leucine Zipper Transcription Factors, Cell Line, Tumor, Cell Proliferation, Chromatography, Liquid, Colon, Colorectal Neoplasms, Female, Gene Expression Profiling, Genes, Dominant, Humans, Luciferases, Male, MicroRNAs, Middle Aged, Oligonucleotide Array Sequence Analysis, Oncogenes, RNA, Messenger, RNA, Small Interfering, Rectum, Reverse Transcriptase Polymerase Chain Reaction, Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization, Transcription Factor 4, Transcription Factors, Transcriptome, Tumor Cells, Cultured, Wnt Signaling Pathway, beta Catenin
Show Abstract · Added March 20, 2014
Aberrant activation of the Wnt signaling pathway is causally involved in the formation of most colorectal cancers (CRCs). Although detailed knowledge exists regarding Wnt-regulated protein-coding genes, much less is known about the possible involvement of non-coding RNAs. Here we used TaqMan Array MicroRNA Cards, capable of detecting 664 unique human microRNAs (miRNAs), to describe changes of the miRNA transcriptome following disruption of beta-catenin/TCF4 activity in DLD1 CRC cells. Most miRNAs appeared to respond independent of host gene regulation and proximal TCF4 chromatin occupancy as inferred from expression microarray and ChIP-chip data. A module of miRNAs induced by abrogated Wnt signaling in vitro was downregulated in two independent series of human primary CRCs (n=76) relative to normal adjacent mucosa (n=34). Several of these miRNAs (miR-145, miR-126, miR-30e-3p and miR-139-5p) markedly inhibited CRC cell growth in vitro when ectopically expressed. By using an integrative approach of proteomics and expression microarrays, we found numerous mRNAs and proteins to be affected by ectopic miR-30e-3p levels. This included HELZ and PIK3C2A that were directly repressed by several miRNA binding sites as confirmed by luciferase reporter assays in combination with mutational analyses. Finally, small interfering RNA-mediated downregulation of PIK3C2A, but not HELZ, was sufficient on its own to restrict CRC cell growth. Collectively, our study demonstrates that multiple miRNAs are upregulated as a consequence of forced attenuation of Wnt signaling in CRC cells, and some of these miRNAs inhibit cell growth with concomitant suppression of several growth-stimulatory cancer-related genes.
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29 MeSH Terms
Impaired-inactivation of FoxO1 contributes to glucose-mediated increases in serum very low-density lipoprotein.
Wu K, Cappel D, Martinez M, Stafford JM
(2010) Endocrinology 151: 3566-76
MeSH Terms: Adenoviridae, Animals, Basic Helix-Loop-Helix Leucine Zipper Transcription Factors, Cell Nucleus, Forkhead Transcription Factors, Glucose, Glucose Clamp Technique, Hyperinsulinism, Insulin, Lipid Metabolism, Lipoproteins, VLDL, Liver, Male, Nerve Tissue Proteins, Rats, Rats, Long-Evans, Rats, Transgenic, Transduction, Genetic, Up-Regulation
Show Abstract · Added October 8, 2015
For patients with diabetes, insulin resistance and hyperglycemia both contribute to increased serum triglyceride in the form of very low-density lipoprotein (VLDL). Our objective was to define the insulin conditions in which hyperglycemia promotes increased serum VLDL in vivo. We performed hyperglycemic-hyperinsulinemic clamp studies and hyperglycemic-hypoinsulinemic clamp studies in rats, with metabolic tracers for glucose flux and de novo fatty acid synthesis. When blood glucose was clamped at hyperglycemia (17 mm) for 2 h under hyperinsulinemic conditions (4 mU/kg . min), serum VLDL levels were not increased compared with baseline. We speculated that hyperinsulinemia minimized glucose-mediated VLDL changes and performed hyperglycemic-hypoinsulinemic clamp studies in which insulin was clamped near fasting levels with somatostatin (17 mm blood glucose, 0.25 mU/kg . min insulin). Under low-insulin conditions, serum VLDL levels were increased 4.7-fold after hyperglycemia, and forkhead box O1 (FoxO1) was not excluded from the nucleus of liver cells. We tested the extent that impaired inactivation of FoxO1 by insulin was sufficient for glucose to promote increased serum VLDL. We found that, when the ability of insulin to inactivate FoxO1 is blocked after adenoviral delivery of constitutively active FoxO1, glucose increased serum VLDL triglyceride when given both by ip glucose tolerance testing (3.5-fold increase) and by a hyperglycemic clamp (4.6-fold). Under both experimental conditions in which insulin signaling to FoxO1 was impaired, we found increased activation of carbohydrate response element binding protein. These data suggest that glucose more potently promotes increased serum VLDL when insulin action is impaired, with either low insulin levels or disrupted downstream signaling to the transcription factor FoxO1.
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19 MeSH Terms
Hepatic glucose sensing: does flux matter?
Shiota M, Magnuson MA
(2008) J Clin Invest 118: 841-4
MeSH Terms: Animals, Basic Helix-Loop-Helix Leucine Zipper Transcription Factors, DNA-Binding Proteins, Gene Expression Regulation, Glucose, Lipogenesis, Liver, Liver X Receptors, Mice, Nuclear Proteins, Orphan Nuclear Receptors, Receptors, Cytoplasmic and Nuclear, Sterol Regulatory Element Binding Protein 1, Transcription Factors
Show Abstract · Added February 23, 2011
In this issue of the JCI, Denechaud et al. report studies investigating the role of the liver X receptors (LXRs) LXRalpha and LXRbeta in carbohydrate sensing by the liver (see the related article beginning on page 956). The results of this study, which utilized LXRalpha/beta double-KO mice, strongly contradict a recent Nature report that proposed that LXRalpha/beta sense glucose independent of metabolic flux. The reported findings further support a key role for the carbohydrate-responsive element-binding protein (ChREBP) in the regulation of lipogenic genes by glucose and dietary carbohydrates.
1 Communities
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14 MeSH Terms
TFE3 transcriptionally activates hepatic IRS-2, participates in insulin signaling and ameliorates diabetes.
Nakagawa Y, Shimano H, Yoshikawa T, Ide T, Tamura M, Furusawa M, Yamamoto T, Inoue N, Matsuzaka T, Takahashi A, Hasty AH, Suzuki H, Sone H, Toyoshima H, Yahagi N, Yamada N
(2006) Nat Med 12: 107-13
MeSH Terms: Adenoviridae, Animals, Basic Helix-Loop-Helix Leucine Zipper Transcription Factors, Blood Glucose, Blotting, Northern, Cells, Cultured, Chromatin Immunoprecipitation, Cloning, Molecular, Diabetes Mellitus, Diabetes Mellitus, Experimental, Dose-Response Relationship, Drug, Glycogen, Glycogen Synthase Kinase 3, Glycogen Synthase Kinase 3 beta, Green Fluorescent Proteins, Hepatocytes, Hexokinase, Humans, Immunoblotting, Immunoprecipitation, Insulin, Insulin Receptor Substrate Proteins, Intracellular Signaling Peptides and Proteins, Male, Membrane Proteins, Mice, Mice, Inbred C57BL, Mice, Knockout, Models, Biological, Phosphoproteins, Phosphorylation, Plasmids, Promoter Regions, Genetic, Protein Structure, Tertiary, Proto-Oncogene Proteins c-akt, Rats, Ribosomal Protein S6 Kinases, 70-kDa, Signal Transduction, Streptozocin, Time Factors, Transcriptional Activation
Show Abstract · Added March 27, 2013
Using an expression cloning strategy, we have identified TFE3, a basic helix-loop-helix protein, as a transactivator of metabolic genes that are regulated through an E-box in their promoters. Adenovirus-mediated expression of TFE3 in hepatocytes in culture and in vivo strongly activated expression of IRS-2 and Akt and enhanced phosphorylation of insulin-signaling kinases such as Akt, glycogen synthase kinase 3beta and p70S6 kinase. TFE3 also induced hexokinase II (HK2) and insulin-induced gene 1 (INSIG1). These changes led to metabolic consequences, such as activation of glycogen and protein synthesis, but not lipogenesis, in liver. Collectively, plasma glucose levels were markedly reduced both in normal mice and in different mouse models of diabetes, including streptozotocin-treated, db/db and KK mice. Promoter analyses showed that IRS2, HK2 and INSIG1 are direct targets of TFE3. Activation of insulin signals in both insulin depletion and resistance suggests that TFE3 could be a therapeutic target for diabetes.
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41 MeSH Terms
Control of pancreas and liver gene expression by HNF transcription factors.
Odom DT, Zizlsperger N, Gordon DB, Bell GW, Rinaldi NJ, Murray HL, Volkert TL, Schreiber J, Rolfe PA, Gifford DK, Fraenkel E, Bell GI, Young RA
(2004) Science 303: 1378-81
MeSH Terms: Basic Helix-Loop-Helix Leucine Zipper Transcription Factors, Carbohydrate Metabolism, DNA-Binding Proteins, Diabetes Mellitus, Type 2, Gene Expression Profiling, Gene Expression Regulation, Genome, Human, Gluconeogenesis, Hepatocyte Nuclear Factor 1, Hepatocyte Nuclear Factor 1-alpha, Hepatocyte Nuclear Factor 1-beta, Hepatocyte Nuclear Factor 4, Hepatocyte Nuclear Factor 6, Hepatocytes, Homeodomain Proteins, Humans, Islets of Langerhans, Lipid Metabolism, Nuclear Proteins, Oligonucleotide Array Sequence Analysis, Phosphoproteins, Precipitin Tests, Promoter Regions, Genetic, RNA Polymerase II, Trans-Activators, Transcription Factors, Transcription, Genetic
Show Abstract · Added April 19, 2011
The transcriptional regulatory networks that specify and maintain human tissue diversity are largely uncharted. To gain insight into this circuitry, we used chromatin immunoprecipitation combined with promoter microarrays to identify systematically the genes occupied by the transcriptional regulators HNF1alpha, HNF4alpha, and HNF6, together with RNA polymerase II, in human liver and pancreatic islets. We identified tissue-specific regulatory circuits formed by HNF1alpha, HNF4alpha, and HNF6 with other transcription factors, revealing how these factors function as master regulators of hepatocyte and islet transcription. Our results suggest how misregulation of HNF4alpha can contribute to type 2 diabetes.
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27 MeSH Terms