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Results: 11 to 20 of 245

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Rhodol-based thallium sensors for cellular imaging of potassium channel activity.
Dutter BF, Ender A, Sulikowski GA, Weaver CD
(2018) Org Biomol Chem 16: 5575-5579
MeSH Terms: Fluorescent Dyes, HEK293 Cells, Humans, Methylation, Microscopy, Confocal, Optical Imaging, Potassium Channels, Spectrometry, Fluorescence, Thallium, Xanthones
Show Abstract · Added April 10, 2019
Thallium (Tl+) flux assays enable imaging of potassium (K+) channel activity in cells and tissues by exploiting the permeability of K+ channels to Tl+ coupled with a fluorescent Tl+ sensitive dye. Common Tl+ sensing dyes utilize fluorescein as the fluorophore though fluorescein exhibits certain undesirable properties in these assays including short excitation wavelengths and pH sensitivity. To overcome these drawbacks, the replacement of fluorescein with rhodols was investigated. A library of 13 rhodol-based Tl+ sensors was synthesized and their properties and performance in Tl+ flux assays evaluated. The dimethyl rhodol Tl+ sensor emerged as the best of the series and performed comparably to fluorescein-based sensors while demonstrating greater pH tolerance in the physiological range and excitation and emission spectra 30 nm red-shifted from fluorescein.
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Immunity drives regulation in cancer through NF-κB.
Collignon E, Canale A, Al Wardi C, Bizet M, Calonne E, Dedeurwaerder S, Garaud S, Naveaux C, Barham W, Wilson A, Bouchat S, Hubert P, Van Lint C, Yull F, Sotiriou C, Willard-Gallo K, Noel A, Fuks F
(2018) Sci Adv 4: eaap7309
MeSH Terms: Adaptive Immunity, Biomarkers, DNA Methylation, Epigenesis, Genetic, Gene Expression Profiling, Gene Expression Regulation, Neoplastic, Humans, Immunity, Immunity, Innate, Mixed Function Oxygenases, NF-kappa B, Neoplasms, Neoplasms, Basal Cell, Promoter Regions, Genetic, Protein Binding, Proto-Oncogene Proteins
Show Abstract · Added March 31, 2020
Ten-eleven translocation enzymes (TET1, TET2, and TET3), which induce DNA demethylation and gene regulation by converting 5-methylcytosine (5mC) to 5-hydroxymethylcytosine (5hmC), are often down-regulated in cancer. We uncover, in basal-like breast cancer (BLBC), genome-wide 5hmC changes related to regulation. We further demonstrate that repression is associated with high expression of immune markers and high infiltration by immune cells. We identify in BLBC tissues an anticorrelation between expression and the major immunoregulator family nuclear factor κB (NF-κB). In vitro and in mice, is down-regulated in breast cancer cells upon NF-κB activation through binding of p65 to its consensus sequence in the promoter. We lastly show that these findings extend to other cancer types, including melanoma, lung, and thyroid cancers. Together, our data suggest a novel mode of regulation for in cancer and highlight a new paradigm in which the immune system can influence cancer cell epigenetics.
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Integrated Molecular Characterization of Testicular Germ Cell Tumors.
Shen H, Shih J, Hollern DP, Wang L, Bowlby R, Tickoo SK, Thorsson V, Mungall AJ, Newton Y, Hegde AM, Armenia J, Sánchez-Vega F, Pluta J, Pyle LC, Mehra R, Reuter VE, Godoy G, Jones J, Shelley CS, Feldman DR, Vidal DO, Lessel D, Kulis T, Cárcano FM, Leraas KM, Lichtenberg TM, Brooks D, Cherniack AD, Cho J, Heiman DI, Kasaian K, Liu M, Noble MS, Xi L, Zhang H, Zhou W, ZenKlusen JC, Hutter CM, Felau I, Zhang J, Schultz N, Getz G, Meyerson M, Stuart JM, Cancer Genome Atlas Research Network, Akbani R, Wheeler DA, Laird PW, Nathanson KL, Cortessis VK, Hoadley KA
(2018) Cell Rep 23: 3392-3406
MeSH Terms: DNA Copy Number Variations, DNA Methylation, Gene Expression Regulation, Neoplastic, Humans, Male, MicroRNAs, Neoplasms, Germ Cell and Embryonal, Proto-Oncogene Proteins c-kit, Seminoma, Testicular Neoplasms, ras Proteins
Show Abstract · Added October 30, 2019
We studied 137 primary testicular germ cell tumors (TGCTs) using high-dimensional assays of genomic, epigenomic, transcriptomic, and proteomic features. These tumors exhibited high aneuploidy and a paucity of somatic mutations. Somatic mutation of only three genes achieved significance-KIT, KRAS, and NRAS-exclusively in samples with seminoma components. Integrated analyses identified distinct molecular patterns that characterized the major recognized histologic subtypes of TGCT: seminoma, embryonal carcinoma, yolk sac tumor, and teratoma. Striking differences in global DNA methylation and microRNA expression between histology subtypes highlight a likely role of epigenomic processes in determining histologic fates in TGCTs. We also identified a subset of pure seminomas defined by KIT mutations, increased immune infiltration, globally demethylated DNA, and decreased KRAS copy number. We report potential biomarkers for risk stratification, such as miRNA specifically expressed in teratoma, and others with molecular diagnostic potential, such as CpH (CpA/CpC/CpT) methylation identifying embryonal carcinomas.
Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.
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Haploinsufficiency for Microtubule Methylation Is an Early Driver of Genomic Instability in Renal Cell Carcinoma.
Chiang YC, Park IY, Terzo EA, Tripathi DN, Mason FM, Fahey CC, Karki M, Shuster CB, Sohn BH, Chowdhury P, Powell RT, Ohi R, Tsai YS, de Cubas AA, Khan A, Davis IJ, Strahl BD, Parker JS, Dere R, Walker CL, Rathmell WK
(2018) Cancer Res 78: 3135-3146
MeSH Terms: Animals, Carcinogenesis, Carcinoma, Renal Cell, Cell Line, Tumor, Chromosomes, Human, Pair 3, Fibroblasts, Gene Knockdown Techniques, Genomic Instability, Haploinsufficiency, Histone-Lysine N-Methyltransferase, Histones, Humans, Kidney Neoplasms, Kidney Tubules, Proximal, Lysine, Methylation, Mice, Micronuclei, Chromosome-Defective, Microtubules
Show Abstract · Added October 30, 2019
Loss of the short arm of chromosome 3 (3p) occurs early in >95% of clear cell renal cell carcinoma (ccRCC). Nearly ubiquitous 3p loss in ccRCC suggests haploinsufficiency for 3p tumor suppressors as early drivers of tumorigenesis. We previously reported methyltransferase , which trimethylates H3 histones on lysine 36 (H3K36me3) and is located in the 3p deletion, to also trimethylate microtubules on lysine 40 (αTubK40me3) during mitosis, with αTubK40me3 required for genomic stability. We now show that monoallelic, -deficient cells retaining H3K36me3, but not αTubK40me3, exhibit a dramatic increase in mitotic defects and micronuclei count, with increased viability compared with biallelic loss. In -inactivated human kidney cells, rescue with a pathogenic mutant deficient for microtubule (αTubK40me3), but not histone (H3K36me3) methylation, replicated this phenotype. Genomic instability (micronuclei) was also a hallmark of patient-derived cells from ccRCC. These data show that the tumor suppressor displays a haploinsufficiency phenotype disproportionately impacting microtubule methylation and serves as an early driver of genomic instability. Loss of a single allele of a chromatin modifier plays a role in promoting oncogenesis, underscoring the growing relevance of tumor suppressor haploinsufficiency in tumorigenesis. .
©2018 American Association for Cancer Research.
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Machine Learning Identifies Stemness Features Associated with Oncogenic Dedifferentiation.
Malta TM, Sokolov A, Gentles AJ, Burzykowski T, Poisson L, Weinstein JN, Kamińska B, Huelsken J, Omberg L, Gevaert O, Colaprico A, Czerwińska P, Mazurek S, Mishra L, Heyn H, Krasnitz A, Godwin AK, Lazar AJ, Cancer Genome Atlas Research Network, Stuart JM, Hoadley KA, Laird PW, Noushmehr H, Wiznerowicz M
(2018) Cell 173: 338-354.e15
MeSH Terms: Carcinogenesis, Cell Dedifferentiation, DNA Methylation, Databases, Genetic, Epigenesis, Genetic, Humans, Machine Learning, MicroRNAs, Neoplasm Metastasis, Neoplasms, Stem Cells, Transcriptome, Tumor Microenvironment
Show Abstract · Added October 30, 2019
Cancer progression involves the gradual loss of a differentiated phenotype and acquisition of progenitor and stem-cell-like features. Here, we provide novel stemness indices for assessing the degree of oncogenic dedifferentiation. We used an innovative one-class logistic regression (OCLR) machine-learning algorithm to extract transcriptomic and epigenetic feature sets derived from non-transformed pluripotent stem cells and their differentiated progeny. Using OCLR, we were able to identify previously undiscovered biological mechanisms associated with the dedifferentiated oncogenic state. Analyses of the tumor microenvironment revealed unanticipated correlation of cancer stemness with immune checkpoint expression and infiltrating immune cells. We found that the dedifferentiated oncogenic phenotype was generally most prominent in metastatic tumors. Application of our stemness indices to single-cell data revealed patterns of intra-tumor molecular heterogeneity. Finally, the indices allowed for the identification of novel targets and possible targeted therapies aimed at tumor differentiation.
Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.
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Cell-of-Origin Patterns Dominate the Molecular Classification of 10,000 Tumors from 33 Types of Cancer.
Hoadley KA, Yau C, Hinoue T, Wolf DM, Lazar AJ, Drill E, Shen R, Taylor AM, Cherniack AD, Thorsson V, Akbani R, Bowlby R, Wong CK, Wiznerowicz M, Sanchez-Vega F, Robertson AG, Schneider BG, Lawrence MS, Noushmehr H, Malta TM, Cancer Genome Atlas Network, Stuart JM, Benz CC, Laird PW
(2018) Cell 173: 291-304.e6
MeSH Terms: Aneuploidy, Chromosomes, Cluster Analysis, CpG Islands, DNA Methylation, Databases, Factual, Humans, MicroRNAs, Mutation, Neoplasm Proteins, Neoplasms, RNA, Messenger
Show Abstract · Added October 30, 2019
We conducted comprehensive integrative molecular analyses of the complete set of tumors in The Cancer Genome Atlas (TCGA), consisting of approximately 10,000 specimens and representing 33 types of cancer. We performed molecular clustering using data on chromosome-arm-level aneuploidy, DNA hypermethylation, mRNA, and miRNA expression levels and reverse-phase protein arrays, of which all, except for aneuploidy, revealed clustering primarily organized by histology, tissue type, or anatomic origin. The influence of cell type was evident in DNA-methylation-based clustering, even after excluding sites with known preexisting tissue-type-specific methylation. Integrative clustering further emphasized the dominant role of cell-of-origin patterns. Molecular similarities among histologically or anatomically related cancer types provide a basis for focused pan-cancer analyses, such as pan-gastrointestinal, pan-gynecological, pan-kidney, and pan-squamous cancers, and those related by stemness features, which in turn may inform strategies for future therapeutic development.
Copyright © 2018 Elsevier Inc. All rights reserved.
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Comparative Molecular Analysis of Gastrointestinal Adenocarcinomas.
Liu Y, Sethi NS, Hinoue T, Schneider BG, Cherniack AD, Sanchez-Vega F, Seoane JA, Farshidfar F, Bowlby R, Islam M, Kim J, Chatila W, Akbani R, Kanchi RS, Rabkin CS, Willis JE, Wang KK, McCall SJ, Mishra L, Ojesina AI, Bullman S, Pedamallu CS, Lazar AJ, Sakai R, Cancer Genome Atlas Research Network, Thorsson V, Bass AJ, Laird PW
(2018) Cancer Cell 33: 721-735.e8
MeSH Terms: Adenocarcinoma, Aneuploidy, Chromosomal Instability, DNA Methylation, DNA Polymerase II, DNA-Binding Proteins, Epigenesis, Genetic, Female, Gastrointestinal Neoplasms, Gene Regulatory Networks, Heterogeneous-Nuclear Ribonucleoproteins, Humans, Male, Microsatellite Instability, MutL Protein Homolog 1, Mutation, Poly-ADP-Ribose Binding Proteins, Polymorphism, Single Nucleotide, Proto-Oncogene Proteins p21(ras), RNA-Binding Proteins, SOX9 Transcription Factor
Show Abstract · Added October 30, 2019
We analyzed 921 adenocarcinomas of the esophagus, stomach, colon, and rectum to examine shared and distinguishing molecular characteristics of gastrointestinal tract adenocarcinomas (GIACs). Hypermutated tumors were distinct regardless of cancer type and comprised those enriched for insertions/deletions, representing microsatellite instability cases with epigenetic silencing of MLH1 in the context of CpG island methylator phenotype, plus tumors with elevated single-nucleotide variants associated with mutations in POLE. Tumors with chromosomal instability were diverse, with gastroesophageal adenocarcinomas harboring fragmented genomes associated with genomic doubling and distinct mutational signatures. We identified a group of tumors in the colon and rectum lacking hypermutation and aneuploidy termed genome stable and enriched in DNA hypermethylation and mutations in KRAS, SOX9, and PCBP1.
Copyright © 2018 Elsevier Inc. All rights reserved.
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lncRNA Epigenetic Landscape Analysis Identifies EPIC1 as an Oncogenic lncRNA that Interacts with MYC and Promotes Cell-Cycle Progression in Cancer.
Wang Z, Yang B, Zhang M, Guo W, Wu Z, Wang Y, Jia L, Li S, Cancer Genome Atlas Research Network, Xie W, Yang D
(2018) Cancer Cell 33: 706-720.e9
MeSH Terms: Animals, Binding Sites, Breast Neoplasms, Cell Cycle, Cell Line, Tumor, CpG Islands, DNA Methylation, Epigenesis, Genetic, Female, Gene Expression Regulation, Neoplastic, Humans, Mice, Neoplasm Transplantation, Prognosis, Promoter Regions, Genetic, Proto-Oncogene Proteins c-myc, RNA, Long Noncoding, Up-Regulation
Show Abstract · Added October 30, 2019
We characterized the epigenetic landscape of genes encoding long noncoding RNAs (lncRNAs) across 6,475 tumors and 455 cancer cell lines. In stark contrast to the CpG island hypermethylation phenotype in cancer, we observed a recurrent hypomethylation of 1,006 lncRNA genes in cancer, including EPIC1 (epigenetically-induced lncRNA1). Overexpression of EPIC1 is associated with poor prognosis in luminal B breast cancer patients and enhances tumor growth in vitro and in vivo. Mechanistically, EPIC1 promotes cell-cycle progression by interacting with MYC through EPIC1's 129-283 nt region. EPIC1 knockdown reduces the occupancy of MYC to its target genes (e.g., CDKN1A, CCNA2, CDC20, and CDC45). MYC depletion abolishes EPIC1's regulation of MYC target and luminal breast cancer tumorigenesis in vitro and in vivo.
Copyright © 2018 Elsevier Inc. All rights reserved.
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Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas.
Campbell JD, Yau C, Bowlby R, Liu Y, Brennan K, Fan H, Taylor AM, Wang C, Walter V, Akbani R, Byers LA, Creighton CJ, Coarfa C, Shih J, Cherniack AD, Gevaert O, Prunello M, Shen H, Anur P, Chen J, Cheng H, Hayes DN, Bullman S, Pedamallu CS, Ojesina AI, Sadeghi S, Mungall KL, Robertson AG, Benz C, Schultz A, Kanchi RS, Gay CM, Hegde A, Diao L, Wang J, Ma W, Sumazin P, Chiu HS, Chen TW, Gunaratne P, Donehower L, Rader JS, Zuna R, Al-Ahmadie H, Lazar AJ, Flores ER, Tsai KY, Zhou JH, Rustgi AK, Drill E, Shen R, Wong CK, Cancer Genome Atlas Research Network, Stuart JM, Laird PW, Hoadley KA, Weinstein JN, Peto M, Pickering CR, Chen Z, Van Waes C
(2018) Cell Rep 23: 194-212.e6
MeSH Terms: Carcinoma, Squamous Cell, Cell Line, Tumor, DNA Methylation, Epithelial-Mesenchymal Transition, Gene Expression Regulation, Neoplastic, Genomics, Humans, Metabolic Networks and Pathways, Polymorphism, Genetic
Show Abstract · Added October 30, 2019
This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smoking and/or human papillomavirus (HPV). SCCs harbor 3q, 5p, and other recurrent chromosomal copy-number alterations (CNAs), DNA mutations, and/or aberrant methylation of genes and microRNAs, which are correlated with the expression of multi-gene programs linked to squamous cell stemness, epithelial-to-mesenchymal differentiation, growth, genomic integrity, oxidative damage, death, and inflammation. Low-CNA SCCs tended to be HPV(+) and display hypermethylation with repression of TET1 demethylase and FANCF, previously linked to predisposition to SCC, or harbor mutations affecting CASP8, RAS-MAPK pathways, chromatin modifiers, and immunoregulatory molecules. We uncovered hypomethylation of the alternative promoter that drives expression of the ΔNp63 oncogene and embedded miR944. Co-expression of immune checkpoint, T-regulatory, and Myeloid suppressor cells signatures may explain reduced efficacy of immune therapy. These findings support possibilities for molecular classification and therapeutic approaches.
Published by Elsevier Inc.
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Set2 methyltransferase facilitates cell cycle progression by maintaining transcriptional fidelity.
Dronamraju R, Jha DK, Eser U, Adams AT, Dominguez D, Choudhury R, Chiang YC, Rathmell WK, Emanuele MJ, Churchman LS, Strahl BD
(2018) Nucleic Acids Res 46: 1331-1344
MeSH Terms: Anaphase-Promoting Complex-Cyclosome, Biological Evolution, Cdc20 Proteins, Cell Cycle, Gene Expression Regulation, Fungal, Histone-Lysine N-Methyltransferase, Histones, Humans, Lysine, Methylation, Methyltransferases, Nocodazole, Protein Processing, Post-Translational, Proteolysis, Saccharomyces cerevisiae, Saccharomyces cerevisiae Proteins, Transcription, Genetic, Tubulin Modulators
Show Abstract · Added October 30, 2019
Methylation of histone H3 lysine 36 (H3K36me) by yeast Set2 is critical for the maintenance of chromatin structure and transcriptional fidelity. However, we do not know the full range of Set2/H3K36me functions or the scope of mechanisms that regulate Set2-dependent H3K36 methylation. Here, we show that the APC/CCDC20 complex regulates Set2 protein abundance during the cell cycle. Significantly, absence of Set2-mediated H3K36me causes a loss of cell cycle control and pronounced defects in the transcriptional fidelity of cell cycle regulatory genes, a class of genes that are generally long, hence highly dependent on Set2/H3K36me for their transcriptional fidelity. Because APC/C also controls human SETD2, and SETD2 likewise regulates cell cycle progression, our data imply an evolutionarily conserved cell cycle function for Set2/SETD2 that may explain why recurrent mutations of SETD2 contribute to human disease.
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