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Systematic Analysis of Splice-Site-Creating Mutations in Cancer.
Jayasinghe RG, Cao S, Gao Q, Wendl MC, Vo NS, Reynolds SM, Zhao Y, Climente-González H, Chai S, Wang F, Varghese R, Huang M, Liang WW, Wyczalkowski MA, Sengupta S, Li Z, Payne SH, Fenyö D, Miner JH, Walter MJ, Cancer Genome Atlas Research Network, Vincent B, Eyras E, Chen K, Shmulevich I, Chen F, Ding L
(2018) Cell Rep 23: 270-281.e3
MeSH Terms: BRCA1 Protein, GATA3 Transcription Factor, HEK293 Cells, Humans, Mutation, Neoplasms, Poly (ADP-Ribose) Polymerase-1, Programmed Cell Death 1 Receptor, RNA Splice Sites, Tumor Suppressor Protein p53, X-linked Nuclear Protein
Show Abstract · Added October 30, 2019
For the past decade, cancer genomic studies have focused on mutations leading to splice-site disruption, overlooking those having splice-creating potential. Here, we applied a bioinformatic tool, MiSplice, for the large-scale discovery of splice-site-creating mutations (SCMs) across 8,656 TCGA tumors. We report 1,964 originally mis-annotated mutations having clear evidence of creating alternative splice junctions. TP53 and GATA3 have 26 and 18 SCMs, respectively, and ATRX has 5 from lower-grade gliomas. Mutations in 11 genes, including PARP1, BRCA1, and BAP1, were experimentally validated for splice-site-creating function. Notably, we found that neoantigens induced by SCMs are likely several folds more immunogenic compared to missense mutations, exemplified by the recurrent GATA3 SCM. Further, high expression of PD-1 and PD-L1 was observed in tumors with SCMs, suggesting candidates for immune blockade therapy. Our work highlights the importance of integrating DNA and RNA data for understanding the functional and the clinical implications of mutations in human diseases.
Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.
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MeSH Terms
Fine-mapping identifies two additional breast cancer susceptibility loci at 9q31.2.
Orr N, Dudbridge F, Dryden N, Maguire S, Novo D, Perrakis E, Johnson N, Ghoussaini M, Hopper JL, Southey MC, Apicella C, Stone J, Schmidt MK, Broeks A, Van't Veer LJ, Hogervorst FB, Fasching PA, Haeberle L, Ekici AB, Beckmann MW, Gibson L, Aitken Z, Warren H, Sawyer E, Tomlinson I, Kerin MJ, Miller N, Burwinkel B, Marme F, Schneeweiss A, Sohn C, Guénel P, Truong T, Cordina-Duverger E, Sanchez M, Bojesen SE, Nordestgaard BG, Nielsen SF, Flyger H, Benitez J, Zamora MP, Arias Perez JI, Menéndez P, Anton-Culver H, Neuhausen SL, Brenner H, Dieffenbach AK, Arndt V, Stegmaier C, Hamann U, Brauch H, Justenhoven C, Brüning T, Ko YD, Nevanlinna H, Aittomäki K, Blomqvist C, Khan S, Bogdanova N, Dörk T, Lindblom A, Margolin S, Mannermaa A, Kataja V, Kosma VM, Hartikainen JM, Chenevix-Trench G, Beesley J, Lambrechts D, Moisse M, Floris G, Beuselinck B, Chang-Claude J, Rudolph A, Seibold P, Flesch-Janys D, Radice P, Peterlongo P, Peissel B, Pensotti V, Couch FJ, Olson JE, Slettedahl S, Vachon C, Giles GG, Milne RL, McLean C, Haiman CA, Henderson BE, Schumacher F, Le Marchand L, Simard J, Goldberg MS, Labrèche F, Dumont M, Kristensen V, Alnæs GG, Nord S, Borresen-Dale AL, Zheng W, Deming-Halverson S, Shrubsole M, Long J, Winqvist R, Pylkäs K, Jukkola-Vuorinen A, Grip M, Andrulis IL, Knight JA, Glendon G, Tchatchou S, Devilee P, Tollenaar RA, Seynaeve CM, Van Asperen CJ, Garcia-Closas M, Figueroa J, Chanock SJ, Lissowska J, Czene K, Darabi H, Eriksson M, Klevebring D, Hooning MJ, Hollestelle A, van Deurzen CH, Kriege M, Hall P, Li J, Liu J, Humphreys K, Cox A, Cross SS, Reed MW, Pharoah PD, Dunning AM, Shah M, Perkins BJ, Jakubowska A, Lubinski J, Jaworska-Bieniek K, Durda K, Ashworth A, Swerdlow A, Jones M, Schoemaker MJ, Meindl A, Schmutzler RK, Olswold C, Slager S, Toland AE, Yannoukakos D, Muir K, Lophatananon A, Stewart-Brown S, Siriwanarangsan P, Matsuo K, Ito H, Iwata H, Ishiguro J, Wu AH, Tseng CC, Van Den Berg D, Stram DO, Teo SH, Yip CH, Kang P, Ikram MK, Shu XO, Lu W, Gao YT, Cai H, Kang D, Choi JY, Park SK, Noh DY, Hartman M, Miao H, Lim WY, Lee SC, Sangrajrang S, Gaborieau V, Brennan P, Mckay J, Wu PE, Hou MF, Yu JC, Shen CY, Blot W, Cai Q, Signorello LB, Luccarini C, Bayes C, Ahmed S, Maranian M, Healey CS, González-Neira A, Pita G, Alonso MR, Álvarez N, Herrero D, Tessier DC, Vincent D, Bacot F, Hunter DJ, Lindstrom S, Dennis J, Michailidou K, Bolla MK, Easton DF, dos Santos Silva I, Fletcher O, Peto J, GENICA Network, kConFab Investigators, Australian Ovarian Cancer Study Group
(2015) Hum Mol Genet 24: 2966-84
MeSH Terms: Adult, Aged, Asian Continental Ancestry Group, Breast Neoplasms, Chromosome Mapping, Chromosomes, Human, Pair 9, Enhancer Elements, Genetic, Estrogen Receptor alpha, European Continental Ancestry Group, Female, GATA3 Transcription Factor, Genetic Association Studies, Genetic Loci, Genetic Predisposition to Disease, Hepatocyte Nuclear Factor 3-alpha, Humans, Kruppel-Like Transcription Factors, Middle Aged, Polymorphism, Single Nucleotide, Risk
Show Abstract · Added September 28, 2015
We recently identified a novel susceptibility variant, rs865686, for estrogen-receptor positive breast cancer at 9q31.2. Here, we report a fine-mapping analysis of the 9q31.2 susceptibility locus using 43 160 cases and 42 600 controls of European ancestry ascertained from 52 studies and a further 5795 cases and 6624 controls of Asian ancestry from nine studies. Single nucleotide polymorphism (SNP) rs676256 was most strongly associated with risk in Europeans (odds ratios [OR] = 0.90 [0.88-0.92]; P-value = 1.58 × 10(-25)). This SNP is one of a cluster of highly correlated variants, including rs865686, that spans ∼14.5 kb. We identified two additional independent association signals demarcated by SNPs rs10816625 (OR = 1.12 [1.08-1.17]; P-value = 7.89 × 10(-09)) and rs13294895 (OR = 1.09 [1.06-1.12]; P-value = 2.97 × 10(-11)). SNP rs10816625, but not rs13294895, was also associated with risk of breast cancer in Asian individuals (OR = 1.12 [1.06-1.18]; P-value = 2.77 × 10(-05)). Functional genomic annotation using data derived from breast cancer cell-line models indicates that these SNPs localise to putative enhancer elements that bind known drivers of hormone-dependent breast cancer, including ER-α, FOXA1 and GATA-3. In vitro analyses indicate that rs10816625 and rs13294895 have allele-specific effects on enhancer activity and suggest chromatin interactions with the KLF4 gene locus. These results demonstrate the power of dense genotyping in large studies to identify independent susceptibility variants. Analysis of associations using subjects with different ancestry, combined with bioinformatic and genomic characterisation, can provide strong evidence for the likely causative alleles and their functional basis.
© The Author 2015. Published by Oxford University Press.
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20 MeSH Terms
TLR4 genotype and environmental LPS mediate RSV bronchiolitis through Th2 polarization.
Caballero MT, Serra ME, Acosta PL, Marzec J, Gibbons L, Salim M, Rodriguez A, Reynaldi A, Garcia A, Bado D, Buchholz UJ, Hijano DR, Coviello S, Newcomb D, Bellabarba M, Ferolla FM, Libster R, Berenstein A, Siniawaski S, Blumetti V, Echavarria M, Pinto L, Lawrence A, Ossorio MF, Grosman A, Mateu CG, Bayle C, Dericco A, Pellegrini M, Igarza I, Repetto HA, Grimaldi LA, Gudapati P, Polack NR, Althabe F, Shi M, Ferrero F, Bergel E, Stein RT, Peebles RS, Boothby M, Kleeberger SR, Polack FP
(2015) J Clin Invest 125: 571-82
MeSH Terms: Animals, Bronchiolitis, Viral, Disease Models, Animal, Environmental Exposure, Female, GATA3 Transcription Factor, Genotype, Humans, Infant, Infant, Newborn, Interferon-gamma, Interleukin-4, Lipopolysaccharides, Male, Mice, Respiratory Syncytial Virus Infections, Respiratory Syncytial Viruses, T-Box Domain Proteins, Th2 Cells, Toll-Like Receptor 4
Show Abstract · Added January 20, 2015
While 30%-70% of RSV-infected infants develop bronchiolitis, 2% require hospitalization. It is not clear why disease severity differs among healthy, full-term infants; however, virus titers, inflammation, and Th2 bias are proposed explanations. While TLR4 is associated with these disease phenotypes, the role of this receptor in respiratory syncytial virus (RSV) pathogenesis is controversial. Here, we evaluated the interaction between TLR4 and environmental factors in RSV disease and defined the immune mediators associated with severe illness. Two independent populations of infants with RSV bronchiolitis revealed that the severity of RSV infection is determined by the TLR4 genotype of the individual and by environmental exposure to LPS. RSV-infected infants with severe disease exhibited a high GATA3/T-bet ratio, which manifested as a high IL-4/IFN-γ ratio in respiratory secretions. The IL-4/IFN-γ ratio present in infants with severe RSV is indicative of Th2 polarization. Murine models of RSV infection confirmed that LPS exposure, Tlr4 genotype, and Th2 polarization influence disease phenotypes. Together, the results of this study identify environmental and genetic factors that influence RSV pathogenesis and reveal that a high IL-4/IFN-γ ratio is associated with severe disease. Moreover, these molecules should be explored as potential targets for therapeutic intervention.
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20 MeSH Terms
Identification of prognosis-relevant subgroups in patients with chemoresistant triple-negative breast cancer.
Yu KD, Zhu R, Zhan M, Rodriguez AA, Yang W, Wong S, Makris A, Lehmann BD, Chen X, Mayer I, Pietenpol JA, Shao ZM, Symmans WF, Chang JC
(2013) Clin Cancer Res 19: 2723-33
MeSH Terms: Adult, Cohort Studies, Drug Resistance, Neoplasm, Estrogen Receptor beta, Female, GATA3 Transcription Factor, Gene Expression Profiling, Gene Expression Regulation, Neoplastic, Homeodomain Proteins, Humans, Kaplan-Meier Estimate, Keratin-16, Matrix Metalloproteinases, Secreted, Middle Aged, Neoadjuvant Therapy, Neoplasm, Residual, Oligonucleotide Array Sequence Analysis, Prognosis, Receptors, Androgen, Triple Negative Breast Neoplasms, Wnt Proteins
Show Abstract · Added September 3, 2013
PURPOSE - Patients with triple-negative breast cancer (TNBC) and residual disease after neoadjuvant chemotherapy generally have worse outcome; however, some patients with residual tumor after neoadjuvant chemotherapy do not relapse. We hypothesize that there are subgroups of patients with chemoresistant TNBC with different prognosis.
EXPERIMENTAL DESIGN - Forty-nine chemoresistant cases from 111 patients with TNBC treated with neoadjuvant chemotherapy (M.D. Anderson Cancer Center, Houston, TX) constituted the discovery cohort, and 25 chemoresistant samples from 47 neoadjuvant chemotherapy-treated TNBC (The Methodist Hospital, Houston, TX) were chosen for validation. Extended validation was carried out in 269 operable TNBC predicted to be chemoresistant by expression pattern from published datasets.
RESULTS - We established a seven-gene prognostic signature using dChip and gene set enrichment analyses. In the independent validation cohort, the classifier predicted correctly with positive predictive value of 75.0% and negative predictive value (i.e., relapse-free survival; RFS) of 76.9% at 3 years. Those predicted to relapse had a HR of 4.67 [95% confidence interval (CI): 1.27-17.15] for relapse in 3 years. In extended validation, patients predicted not to relapse exhibited 3-year RFS of 78.9%, whereas the 3-year RFS was 48.5% for patients predicted to relapse, with HR of 2.61 (95% CI: 1.52-4.49). The TNBC subgroup that predicted to have relatively favorable prognosis was characterized by high expression of "luminal-like" genes [androgen-receptor (AR) and GATA3], whereas the subgroup with worse prognosis was characterized by expression of cancer stem-cell markers.
CONCLUSION - We developed a clinically relevant signature for patients with chemoresistant TNBC. For these women, new therapeutic strategies like targeting AR activation or cancer stem cells may need to be developed.
©2013 AACR
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21 MeSH Terms
Functional variants at the 11q13 risk locus for breast cancer regulate cyclin D1 expression through long-range enhancers.
French JD, Ghoussaini M, Edwards SL, Meyer KB, Michailidou K, Ahmed S, Khan S, Maranian MJ, O'Reilly M, Hillman KM, Betts JA, Carroll T, Bailey PJ, Dicks E, Beesley J, Tyrer J, Maia AT, Beck A, Knoblauch NW, Chen C, Kraft P, Barnes D, González-Neira A, Alonso MR, Herrero D, Tessier DC, Vincent D, Bacot F, Luccarini C, Baynes C, Conroy D, Dennis J, Bolla MK, Wang Q, Hopper JL, Southey MC, Schmidt MK, Broeks A, Verhoef S, Cornelissen S, Muir K, Lophatananon A, Stewart-Brown S, Siriwanarangsan P, Fasching PA, Loehberg CR, Ekici AB, Beckmann MW, Peto J, dos Santos Silva I, Johnson N, Aitken Z, Sawyer EJ, Tomlinson I, Kerin MJ, Miller N, Marme F, Schneeweiss A, Sohn C, Burwinkel B, Guénel P, Truong T, Laurent-Puig P, Menegaux F, Bojesen SE, Nordestgaard BG, Nielsen SF, Flyger H, Milne RL, Zamora MP, Arias Perez JI, Benitez J, Anton-Culver H, Brenner H, Müller H, Arndt V, Stegmaier C, Meindl A, Lichtner P, Schmutzler RK, Engel C, Brauch H, Hamann U, Justenhoven C, GENICA Network, Aaltonen K, Heikkilä P, Aittomäki K, Blomqvist C, Matsuo K, Ito H, Iwata H, Sueta A, Bogdanova NV, Antonenkova NN, Dörk T, Lindblom A, Margolin S, Mannermaa A, Kataja V, Kosma VM, Hartikainen JM, kConFab Investigators, Wu AH, Tseng CC, Van Den Berg D, Stram DO, Lambrechts D, Peeters S, Smeets A, Floris G, Chang-Claude J, Rudolph A, Nickels S, Flesch-Janys D, Radice P, Peterlongo P, Bonanni B, Sardella D, Couch FJ, Wang X, Pankratz VS, Lee A, Giles GG, Severi G, Baglietto L, Haiman CA, Henderson BE, Schumacher F, Le Marchand L, Simard J, Goldberg MS, Labrèche F, Dumont M, Teo SH, Yip CH, Ng CH, Vithana EN, Kristensen V, Zheng W, Deming-Halverson S, Shrubsole M, Long J, Winqvist R, Pylkäs K, Jukkola-Vuorinen A, Grip M, Andrulis IL, Knight JA, Glendon G, Mulligan AM, Devilee P, Seynaeve C, García-Closas M, Figueroa J, Chanock SJ, Lissowska J, Czene K, Klevebring D, Schoof N, Hooning MJ, Martens JW, Collée JM, Tilanus-Linthorst M, Hall P, Li J, Liu J, Humphreys K, Shu XO, Lu W, Gao YT, Cai H, Cox A, Balasubramanian SP, Blot W, Signorello LB, Cai Q, Pharoah PD, Healey CS, Shah M, Pooley KA, Kang D, Yoo KY, Noh DY, Hartman M, Miao H, Sng JH, Sim X, Jakubowska A, Lubinski J, Jaworska-Bieniek K, Durda K, Sangrajrang S, Gaborieau V, McKay J, Toland AE, Ambrosone CB, Yannoukakos D, Godwin AK, Shen CY, Hsiung CN, Wu PE, Chen ST, Swerdlow A, Ashworth A, Orr N, Schoemaker MJ, Ponder BA, Nevanlinna H, Brown MA, Chenevix-Trench G, Easton DF, Dunning AM
(2013) Am J Hum Genet 92: 489-503
MeSH Terms: Binding Sites, Breast Neoplasms, Case-Control Studies, Cell Line, Tumor, Chromatin, Chromatin Immunoprecipitation, Chromosomes, Human, Pair 11, Cyclin D1, Electrophoretic Mobility Shift Assay, Enhancer Elements, Genetic, Female, GATA3 Transcription Factor, Gene Expression Regulation, Neoplastic, Humans, Luciferases, Polymorphism, Single Nucleotide, Promoter Regions, Genetic, RNA, Messenger, RNA, Small Interfering, Real-Time Polymerase Chain Reaction, Reverse Transcriptase Polymerase Chain Reaction, Silencer Elements, Transcriptional, ets-Domain Protein Elk-4
Show Abstract · Added March 10, 2014
Analysis of 4,405 variants in 89,050 European subjects from 41 case-control studies identified three independent association signals for estrogen-receptor-positive tumors at 11q13. The strongest signal maps to a transcriptional enhancer element in which the G allele of the best candidate causative variant rs554219 increases risk of breast cancer, reduces both binding of ELK4 transcription factor and luciferase activity in reporter assays, and may be associated with low cyclin D1 protein levels in tumors. Another candidate variant, rs78540526, lies in the same enhancer element. Risk association signal 2, rs75915166, creates a GATA3 binding site within a silencer element. Chromatin conformation studies demonstrate that these enhancer and silencer elements interact with each other and with their likely target gene, CCND1.
Copyright © 2013 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.
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23 MeSH Terms
Comprehensive molecular portraits of human breast tumours.
Cancer Genome Atlas Network
(2012) Nature 490: 61-70
MeSH Terms: Breast Neoplasms, Class I Phosphatidylinositol 3-Kinases, DNA Copy Number Variations, DNA Methylation, DNA Mutational Analysis, Exome, Female, GATA3 Transcription Factor, Gene Expression Profiling, Gene Expression Regulation, Neoplastic, Genes, BRCA1, Genes, Neoplasm, Genes, erbB-2, Genes, p53, Genetic Heterogeneity, Genome, Human, Genomics, Humans, MAP Kinase Kinase Kinase 1, MicroRNAs, Mutation, Oligonucleotide Array Sequence Analysis, Ovarian Neoplasms, Phosphatidylinositol 3-Kinases, Protein Array Analysis, Proteomics, RNA, Messenger, RNA, Neoplasm, Receptors, Estrogen, Retinoblastoma Protein
Show Abstract · Added March 28, 2014
We analysed primary breast cancers by genomic DNA copy number arrays, DNA methylation, exome sequencing, messenger RNA arrays, microRNA sequencing and reverse-phase protein arrays. Our ability to integrate information across platforms provided key insights into previously defined gene expression subtypes and demonstrated the existence of four main breast cancer classes when combining data from five platforms, each of which shows significant molecular heterogeneity. Somatic mutations in only three genes (TP53, PIK3CA and GATA3) occurred at >10% incidence across all breast cancers; however, there were numerous subtype-associated and novel gene mutations including the enrichment of specific mutations in GATA3, PIK3CA and MAP3K1 with the luminal A subtype. We identified two novel protein-expression-defined subgroups, possibly produced by stromal/microenvironmental elements, and integrated analyses identified specific signalling pathways dominant in each molecular subtype including a HER2/phosphorylated HER2/EGFR/phosphorylated EGFR signature within the HER2-enriched expression subtype. Comparison of basal-like breast tumours with high-grade serous ovarian tumours showed many molecular commonalities, indicating a related aetiology and similar therapeutic opportunities. The biological finding of the four main breast cancer subtypes caused by different subsets of genetic and epigenetic abnormalities raises the hypothesis that much of the clinically observable plasticity and heterogeneity occurs within, and not across, these major biological subtypes of breast cancer.
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30 MeSH Terms
Transforming growth factor beta is dispensable for the molecular orchestration of Th17 cell differentiation.
Das J, Ren G, Zhang L, Roberts AI, Zhao X, Bothwell AL, Van Kaer L, Shi Y, Das G
(2009) J Exp Med 206: 2407-16
MeSH Terms: Animals, Cell Differentiation, Cytokines, Encephalomyelitis, Autoimmune, Experimental, GATA3 Transcription Factor, Interleukin-6, Lymphocyte Activation, Mice, Mice, Knockout, STAT4 Transcription Factor, STAT6 Transcription Factor, T-Box Domain Proteins, T-Lymphocytes, Helper-Inducer, Th1 Cells, Th2 Cells, Transforming Growth Factor beta
Show Abstract · Added December 10, 2013
Interleukin (IL)-17-producing T helper (Th17) cells play a critical role in the pathophysiology of several autoimmune disorders. The differentiation of Th17 cells requires the simultaneous presence of an unusual combination of cytokines: IL-6, a proinflammatory cytokine, and transforming growth factor (TGF) beta, an antiinflammatory cytokine. However, the molecular mechanisms by which TGF-beta exerts its effects on Th17 cell differentiation remain elusive. We report that TGF-beta does not directly promote Th17 cell differentiation but instead acts indirectly by blocking expression of the transcription factors signal transducer and activator of transcription (STAT) 4 and GATA-3, thus preventing Th1 and Th2 cell differentiation. In contrast, TGF-beta had no effect on the expression of retinoic acid receptor-related orphan nuclear receptor gammat, a Th17-specific transcription factor. Interestingly, in Stat-6(-/-)T-bet(-/-) mice, which are unable to generate Th1 and Th2 cells, IL-6 alone was sufficient to induce robust differentiation of Th17 cells, whereas TGF-beta had no effect, suggesting that TGF-beta is dispensable for Th17 cell development. Consequently, BALB/c Stat-6(-/-)T-bet(-/-) mice, but not wild-type BALB/c mice, were highly susceptible to the development of experimental autoimmune encephalomyelitis, which could be blocked by anti-IL-17 antibodies but not by anti-TGF-beta antibodies. Collectively, these data provide evidence that TGF-beta is not directly required for the molecular orchestration of Th17 cell differentiation.
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16 MeSH Terms
Human natural killer T cells are heterogeneous in their capacity to reprogram their effector functions.
Eger KA, Sundrud MS, Motsinger AA, Tseng M, Van Kaer L, Unutmaz D
(2006) PLoS One 1: e50
MeSH Terms: Adult, Age Factors, CD4-Positive T-Lymphocytes, Cell Differentiation, Cytokines, Cytotoxicity, Immunologic, GATA3 Transcription Factor, Humans, Immunophenotyping, In Vitro Techniques, Infant, Newborn, L-Selectin, NK Cell Lectin-Like Receptor Subfamily B, NK Cell Lectin-Like Receptor Subfamily D, Natural Killer T-Cells, Receptors, CCR7, Recombinant Proteins, Signal Transduction, T-Box Domain Proteins, T-Lymphocyte Subsets, Th1 Cells, Th2 Cells, Transduction, Genetic
Show Abstract · Added December 10, 2013
BACKGROUND - Natural killer T (NKT) cells are a subset of T cells that help potentiate and regulate immune responses. Although human NKT cell subsets with distinct effector functions have been identified, it is unclear whether the effector functions of these subsets are imprinted during development or can be selectively reprogrammed in the periphery.
RESULTS - We found that neonatal NKT cells are predominantly CD4+ and express higher levels of CCR7 and CD62L and lower levels of CD94 and CD161 than adult CD4+ or CD4- NKT cell subsets. Accordingly, neonatal NKT cells were more flexible than adult CD4+ NKT cells in their capacity to acquire Th1- or Th2-like functions upon either cytokine-mediated polarization or ectopic expression of the Th1 or Th2 transcription factors T-bet and GATA-3, respectively. Consistent with their more differentiated phenotype, CD4- NKT cells were predominantly resistant to functional reprogramming and displayed higher cytotoxic function. In contrast to conventional T cells, neither the expression of CXCR3 nor the cytotoxic capacity of neonatal NKT cells could be reprogrammed.
CONCLUSIONS AND SIGNIFICANCE - Together, these results suggest that neonatal CD4+, adult CD4+, and adult CD4- NKT may represent unique states of maturation and that some functions of human NKT cells may be developmentally imprinted, while others are acquired similar to conventional T cell subsets during peripheral maturation and differentiation. Given the potent immuno-regulatory functions of NKT cells, these findings have important implications for the development of novel NKT cell-based therapeutics and vaccines.
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23 MeSH Terms
Lipid defect underlies selective skin barrier impairment of an epidermal-specific deletion of Gata-3.
de Guzman Strong C, Wertz PW, Wang C, Yang F, Meltzer PS, Andl T, Millar SE, Ho IC, Pai SY, Segre JA
(2006) J Cell Biol 175: 661-70
MeSH Terms: Animals, Animals, Newborn, Base Sequence, Binding Sites, Cell Differentiation, Cell Proliferation, Embryo, Mammalian, Embryonic Development, Epidermis, Exons, GATA3 Transcription Factor, Gene Deletion, Immunity, Innate, Introns, Keratin-13, Kruppel-Like Transcription Factors, Lipid Metabolism, Mice, Molecular Sequence Data, Protein Binding, Skin Transplantation, Transcription, Genetic
Show Abstract · Added January 30, 2013
Skin lies at the interface between the complex physiology of the body and the external environment. This essential epidermal barrier, composed of cornified proteins encased in lipids, prevents both water loss and entry of infectious or toxic substances. We uncover that the transcription factor GATA-3 is required to establish the epidermal barrier and survive in the ex utero environment. Analysis of Gata-3 mutant transcriptional profiles at three critical developmental stages identifies a specific defect in lipid biosynthesis and a delay in differentiation. Genomic analysis identifies highly conserved GATA-3 binding sites bound in vivo by GATA-3 in the first intron of the lipid acyltransferase gene AGPAT5. Skin from both Gata-3-/- and previously characterized barrier-deficient Kruppel-like factor 4-/- newborns up-regulate antimicrobial peptides, effectors of innate immunity. Comparison of these animal models illustrates how impairment of the skin barrier by two genetically distinct mechanisms leads to innate immune responses, as observed in the common human skin disorders psoriasis and atopic dermatitis.
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22 MeSH Terms
Opposing roles for RelB and Bcl-3 in regulation of T-box expressed in T cells, GATA-3, and Th effector differentiation.
Corn RA, Hunter C, Liou HC, Siebenlist U, Boothby MR
(2005) J Immunol 175: 2102-10
MeSH Terms: Animals, B-Cell Lymphoma 3 Protein, Cell Differentiation, Cells, Cultured, DNA-Binding Proteins, GATA3 Transcription Factor, Humans, Interferon-gamma, Jurkat Cells, Mice, Mice, Inbred C57BL, Mice, Knockout, Mice, Transgenic, Polycomb Repressive Complex 1, Proto-Oncogene Proteins, Proto-Oncogene Proteins c-rel, T-Box Domain Proteins, T-Lymphocytes, Helper-Inducer, Th1 Cells, Th2 Cells, Transcription Factors
Show Abstract · Added December 10, 2013
CD4+ T cells with a block in the NF-kappaB signaling pathway exhibit decreases in Th1 responses and diminished nuclear levels of multiple transactivating NF-kappaB/Rel/IkappaB proteins. To determine the lineage-intrinsic contributions of these transactivators to Th differentiation, T cells from mice deficient in specific subunits were cultured in exogenous cytokines promoting either Th1 or Th2 differentiation. RelB-deficient cells exhibited dramatic defects in Th1 differentiation and IFN-gamma production, whereas no consistent defect in either Th1 or Th2 responses was observed with c-Rel-deficient cells. In sharp contrast, Bcl-3-null T cells displayed no defect in IFN-gamma production, but their Th2 differentiation and IL-4, IL-5, and IL-13 production were significantly impaired. The absence of RelB led to a dramatic decrease in the expression of T-box expressed in T cells and Stat4. In contrast, Bcl-3-deficient cells exhibited decreased GATA-3, consistent with evidence that Bcl-3 can transactivate a gata3 promoter. These data indicate that Bcl-3 and RelB exert distinct and opposing effects on the expression of subset-determining transcription factors, suggesting that the characteristics of Th cell responses may be regulated by titrating the stoichiometry of transactivating NF-kappaB/Rel/IkappaB complexes in the nuclei of developing helper effector cells.
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21 MeSH Terms