Cell Proliferation in the Absence of E2F1-3
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Specific Functions of the Wnt Signaling System in Gene Regulatory Networks
Specific functions of the Wnt signaling system in PNAS PLUS gene regulatory networks throughout the early sea urchin embryo Miao Cui, Natnaree Siriwon1, Enhu Li2, Eric H. Davidson3, and Isabelle S. Peter3 Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125 Contributed by Eric H. Davidson, October 9, 2014 (sent for review September 12, 2014; reviewed by Robert D. Burke and Randall T. Moon) Wnt signaling affects cell-fate specification processes throughout Fig. 1A. Cells located at the vegetal pole will become skeleto- embryonic development. Here we take advantage of the well-studied genic mesodermal cells. These cells are surrounded by the veg2 gene regulatory networks (GRNs) that control pregastrular sea urchin cell lineage. This lineage consists of veg2 mesodermal cells, lo- embryogenesis to reveal the gene regulatory functions of the entire cated adjacent to skeletogenic cells and giving rise to all other Wnt-signaling system. Five wnt genes, three frizzled genes, two se- mesodermal cell fates such as esophageal muscle cells, blasto- creted frizzled-related protein 1 genes, and two Dickkopf genes are coelar cells, and pigment cells, and of veg2 endoderm cells, expressed in dynamic spatial patterns in the pregastrular embryo of which will form the foregut and parts of the midgut. At a further Strongylocentrotus purpuratus. We present a comprehensive analysis distance from the vegetal pole, but still within the vegetal half of of these genes in each embryonic domain. Total functions of the the embryo, is the veg1 lineage, consisting of veg1 endoderm, Wnt-signaling system in regulatory gene expression throughout the located adjacent to veg2 endoderm and giving rise to the other embryo were studied by use of the Porcupine inhibitor C59, which parts of the midgut and the hindgut, and of veg1 ectoderm, the interferes with zygotic Wnt ligand secretion. -
Molecular Profile of Tumor-Specific CD8+ T Cell Hypofunction in a Transplantable Murine Cancer Model
Downloaded from http://www.jimmunol.org/ by guest on September 25, 2021 T + is online at: average * The Journal of Immunology , 34 of which you can access for free at: 2016; 197:1477-1488; Prepublished online 1 July from submission to initial decision 4 weeks from acceptance to publication 2016; doi: 10.4049/jimmunol.1600589 http://www.jimmunol.org/content/197/4/1477 Molecular Profile of Tumor-Specific CD8 Cell Hypofunction in a Transplantable Murine Cancer Model Katherine A. Waugh, Sonia M. Leach, Brandon L. Moore, Tullia C. Bruno, Jonathan D. Buhrman and Jill E. Slansky J Immunol cites 95 articles Submit online. Every submission reviewed by practicing scientists ? is published twice each month by Receive free email-alerts when new articles cite this article. Sign up at: http://jimmunol.org/alerts http://jimmunol.org/subscription Submit copyright permission requests at: http://www.aai.org/About/Publications/JI/copyright.html http://www.jimmunol.org/content/suppl/2016/07/01/jimmunol.160058 9.DCSupplemental This article http://www.jimmunol.org/content/197/4/1477.full#ref-list-1 Information about subscribing to The JI No Triage! Fast Publication! Rapid Reviews! 30 days* Why • • • Material References Permissions Email Alerts Subscription Supplementary The Journal of Immunology The American Association of Immunologists, Inc., 1451 Rockville Pike, Suite 650, Rockville, MD 20852 Copyright © 2016 by The American Association of Immunologists, Inc. All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. This information is current as of September 25, 2021. The Journal of Immunology Molecular Profile of Tumor-Specific CD8+ T Cell Hypofunction in a Transplantable Murine Cancer Model Katherine A. -
The E–Id Protein Axis Modulates the Activities of the PI3K–AKT–Mtorc1
Downloaded from genesdev.cshlp.org on October 6, 2021 - Published by Cold Spring Harbor Laboratory Press The E–Id protein axis modulates the activities of the PI3K–AKT–mTORC1– Hif1a and c-myc/p19Arf pathways to suppress innate variant TFH cell development, thymocyte expansion, and lymphomagenesis Masaki Miyazaki,1,8 Kazuko Miyazaki,1,8 Shuwen Chen,1 Vivek Chandra,1 Keisuke Wagatsuma,2 Yasutoshi Agata,2 Hans-Reimer Rodewald,3 Rintaro Saito,4 Aaron N. Chang,5 Nissi Varki,6 Hiroshi Kawamoto,7 and Cornelis Murre1 1Department of Molecular Biology, University of California at San Diego, La Jolla, California 92093, USA; 2Department of Biochemistry and Molecular Biology, Shiga University of Medical School, Shiga 520-2192, Japan; 3Division of Cellular Immunology, German Cancer Research Center, D-69120 Heidelberg, Germany; 4Department of Medicine, University of California at San Diego, La Jolla, California 92093, USA; 5Center for Computational Biology, Institute for Genomic Medicine, University of California at San Diego, La Jolla, California 92093, USA; 6Department of Pathology, University of California at San Diego, La Jolla, California 92093, USA; 7Department of Immunology, Institute for Frontier Medical Sciences, Kyoto University, Kyoto 606-8507, Japan It is now well established that the E and Id protein axis regulates multiple steps in lymphocyte development. However, it remains unknown how E and Id proteins mechanistically enforce and maintain the naı¨ve T-cell fate. Here we show that Id2 and Id3 suppressed the development and expansion of innate variant follicular helper T (TFH) cells. Innate variant TFH cells required major histocompatibility complex (MHC) class I-like signaling and were associated with germinal center B cells. -
Animal Cells Anterior Epidermis Anterior Epidermis A-Neural
Anterior Epidermis Anterior Epidermis KH2012 TF common name Log2FC -Log(pvalue) Log2FC -Log(pvalue) DE in Imai Matched PWM PWM Cluster KH2012 TF common name Log2FC -Log(pvalue) Log2FC -Log(pvalue) DE in Imai Matched PWM PWM Cluster gene model Sibling Cluster Sibling Cluster Parent Cluster Parent Cluster z-score z-score gene model Sibling Cluster Sibling Cluster Parent Cluster Parent Cluster z-score z-score KH2012:KH.C11.485 Irx-B 1.0982 127.5106 0.9210 342.5323 Yes No PWM Hits No PWM Hits KH2012:KH.C1.159 E(spl)/hairy-a 1.3445 65.6302 0.6908 14.3413 Not Analyzed -15.2125 No PWM Hits KH2012:KH.L39.1 FoxH-b 0.6677 45.8148 1.1074 185.2909 No -3.3335 5.2695 KH2012:KH.C1.99 SoxB1 1.2482 73.2413 0.3331 9.3534 Not Analyzed No PWM match No PWM match KH2012:KH.C1.159 E(spl)/hairy-a 0.6233 47.2239 0.4339 77.0192 Yes -10.496 No PWM Hits KH2012:KH.C11.485 Irx-B 1.2355 72.8859 0.1608 0.0137 Not Analyzed No PWM Hits No PWM Hits KH2012:KH.C7.43 AP-2-like2 0.4991 31.7939 0.4775 68.8091 Yes 10.551 21.586 KH2012:KH.C1.1016 GCNF 0.8556 36.2030 1.3828 100.1236 Not Analyzed No PWM match No PWM match KH2012:KH.C1.99 SoxB1 0.4913 33.7808 0.3406 39.0890 No No PWM match No PWM match KH2012:KH.L108.4 CREB/ATF-a 0.6859 37.8207 0.3453 15.8154 Not Analyzed 6.405 8.6245 KH2012:KH.C7.157 Emc 0.4139 19.2080 1.1001 173.3024 Yes No PWM match No PWM match KH2012:KH.S164.12 SoxB2 0.6194 22.8414 0.6433 35.7335 Not Analyzed 8.722 17.405 KH2012:KH.C4.366 ERF2 -0.4878 -32.3767 -0.1770 -0.2316 No -10.324 9.7885 KH2012:KH.L4.17 Zinc Finger (C2H2)-18 0.6166 24.8925 0.2386 5.3130 -
1 AGING Supplementary Table 2
SUPPLEMENTARY TABLES Supplementary Table 1. Details of the eight domain chains of KIAA0101. Serial IDENTITY MAX IN COMP- INTERFACE ID POSITION RESOLUTION EXPERIMENT TYPE number START STOP SCORE IDENTITY LEX WITH CAVITY A 4D2G_D 52 - 69 52 69 100 100 2.65 Å PCNA X-RAY DIFFRACTION √ B 4D2G_E 52 - 69 52 69 100 100 2.65 Å PCNA X-RAY DIFFRACTION √ C 6EHT_D 52 - 71 52 71 100 100 3.2Å PCNA X-RAY DIFFRACTION √ D 6EHT_E 52 - 71 52 71 100 100 3.2Å PCNA X-RAY DIFFRACTION √ E 6GWS_D 41-72 41 72 100 100 3.2Å PCNA X-RAY DIFFRACTION √ F 6GWS_E 41-72 41 72 100 100 2.9Å PCNA X-RAY DIFFRACTION √ G 6GWS_F 41-72 41 72 100 100 2.9Å PCNA X-RAY DIFFRACTION √ H 6IIW_B 2-11 2 11 100 100 1.699Å UHRF1 X-RAY DIFFRACTION √ www.aging-us.com 1 AGING Supplementary Table 2. Significantly enriched gene ontology (GO) annotations (cellular components) of KIAA0101 in lung adenocarcinoma (LinkedOmics). Leading Description FDR Leading Edge Gene EdgeNum RAD51, SPC25, CCNB1, BIRC5, NCAPG, ZWINT, MAD2L1, SKA3, NUF2, BUB1B, CENPA, SKA1, AURKB, NEK2, CENPW, HJURP, NDC80, CDCA5, NCAPH, BUB1, ZWILCH, CENPK, KIF2C, AURKA, CENPN, TOP2A, CENPM, PLK1, ERCC6L, CDT1, CHEK1, SPAG5, CENPH, condensed 66 0 SPC24, NUP37, BLM, CENPE, BUB3, CDK2, FANCD2, CENPO, CENPF, BRCA1, DSN1, chromosome MKI67, NCAPG2, H2AFX, HMGB2, SUV39H1, CBX3, TUBG1, KNTC1, PPP1CC, SMC2, BANF1, NCAPD2, SKA2, NUP107, BRCA2, NUP85, ITGB3BP, SYCE2, TOPBP1, DMC1, SMC4, INCENP. RAD51, OIP5, CDK1, SPC25, CCNB1, BIRC5, NCAPG, ZWINT, MAD2L1, SKA3, NUF2, BUB1B, CENPA, SKA1, AURKB, NEK2, ESCO2, CENPW, HJURP, TTK, NDC80, CDCA5, BUB1, ZWILCH, CENPK, KIF2C, AURKA, DSCC1, CENPN, CDCA8, CENPM, PLK1, MCM6, ERCC6L, CDT1, HELLS, CHEK1, SPAG5, CENPH, PCNA, SPC24, CENPI, NUP37, FEN1, chromosomal 94 0 CENPL, BLM, KIF18A, CENPE, MCM4, BUB3, SUV39H2, MCM2, CDK2, PIF1, DNA2, region CENPO, CENPF, CHEK2, DSN1, H2AFX, MCM7, SUV39H1, MTBP, CBX3, RECQL4, KNTC1, PPP1CC, CENPP, CENPQ, PTGES3, NCAPD2, DYNLL1, SKA2, HAT1, NUP107, MCM5, MCM3, MSH2, BRCA2, NUP85, SSB, ITGB3BP, DMC1, INCENP, THOC3, XPO1, APEX1, XRCC5, KIF22, DCLRE1A, SEH1L, XRCC3, NSMCE2, RAD21. -
Rb-Mediated Neuronal Differentiation Through Cell-Cycle–Independent Regulation of E2f3a
PLoS BIOLOGY Rb-Mediated Neuronal Differentiation through Cell-Cycle–Independent Regulation of E2f3a Danian Chen1,2,3, Rene Opavsky4,5,6, Marek Pacal1,2,3, Naoyuki Tanimoto7, Pamela Wenzel4,5,6, Mathias W. Seeliger7, Gustavo Leone4,5,6, Rod Bremner1,2,3* 1 Genetics and Development Division, Toronto Western Research Institute, University Health Network, University of Toronto, Ontario, Canada, 2 Department of Ophthalmology and Visual Science, University of Toronto, Ontario, Canada, 3 Department of Laboratory Medicine and Pathobiology, University of Toronto, Ontario, Canada, 4 Human Cancer Genetics Program, Department of Molecular Virology, Immunology and Medical Genetics, Ohio State University, Columbus, Ohio, United States of America, 5 Department of Molecular Genetics, Ohio State University, Columbus, Ohio, United States of America, 6 Comprehensive Cancer Center, Ohio State University, Columbus, Ohio, United States of America, 7 Ocular Neurodegeneration Research Group, Centre for Ophthalmology, Institute for Ophthalmic Research, University of Tuebingen, Germany It has long been known that loss of the retinoblastoma protein (Rb) perturbs neural differentiation, but the underlying mechanism has never been solved. Rb absence impairs cell cycle exit and triggers death of some neurons, so differentiation defects may well be indirect. Indeed, we show that abnormalities in both differentiation and light- evoked electrophysiological responses in Rb-deficient retinal cells are rescued when ectopic division and apoptosis are blocked specifically by deleting E2f transcription factor (E2f) 1. However, comprehensive cell-type analysis of the rescued double-null retina exposed cell-cycle–independent differentiation defects specifically in starburst amacrine cells (SACs), cholinergic interneurons critical in direction selectivity and developmentally important rhythmic bursts. Typically, Rb is thought to block division by repressing E2fs, but to promote differentiation by potentiating tissue- specific factors. -
1714 Gene Comprehensive Cancer Panel Enriched for Clinically Actionable Genes with Additional Biologically Relevant Genes 400-500X Average Coverage on Tumor
xO GENE PANEL 1714 gene comprehensive cancer panel enriched for clinically actionable genes with additional biologically relevant genes 400-500x average coverage on tumor Genes A-C Genes D-F Genes G-I Genes J-L AATK ATAD2B BTG1 CDH7 CREM DACH1 EPHA1 FES G6PC3 HGF IL18RAP JADE1 LMO1 ABCA1 ATF1 BTG2 CDK1 CRHR1 DACH2 EPHA2 FEV G6PD HIF1A IL1R1 JAK1 LMO2 ABCB1 ATM BTG3 CDK10 CRK DAXX EPHA3 FGF1 GAB1 HIF1AN IL1R2 JAK2 LMO7 ABCB11 ATR BTK CDK11A CRKL DBH EPHA4 FGF10 GAB2 HIST1H1E IL1RAP JAK3 LMTK2 ABCB4 ATRX BTRC CDK11B CRLF2 DCC EPHA5 FGF11 GABPA HIST1H3B IL20RA JARID2 LMTK3 ABCC1 AURKA BUB1 CDK12 CRTC1 DCUN1D1 EPHA6 FGF12 GALNT12 HIST1H4E IL20RB JAZF1 LPHN2 ABCC2 AURKB BUB1B CDK13 CRTC2 DCUN1D2 EPHA7 FGF13 GATA1 HLA-A IL21R JMJD1C LPHN3 ABCG1 AURKC BUB3 CDK14 CRTC3 DDB2 EPHA8 FGF14 GATA2 HLA-B IL22RA1 JMJD4 LPP ABCG2 AXIN1 C11orf30 CDK15 CSF1 DDIT3 EPHB1 FGF16 GATA3 HLF IL22RA2 JMJD6 LRP1B ABI1 AXIN2 CACNA1C CDK16 CSF1R DDR1 EPHB2 FGF17 GATA5 HLTF IL23R JMJD7 LRP5 ABL1 AXL CACNA1S CDK17 CSF2RA DDR2 EPHB3 FGF18 GATA6 HMGA1 IL2RA JMJD8 LRP6 ABL2 B2M CACNB2 CDK18 CSF2RB DDX3X EPHB4 FGF19 GDNF HMGA2 IL2RB JUN LRRK2 ACE BABAM1 CADM2 CDK19 CSF3R DDX5 EPHB6 FGF2 GFI1 HMGCR IL2RG JUNB LSM1 ACSL6 BACH1 CALR CDK2 CSK DDX6 EPOR FGF20 GFI1B HNF1A IL3 JUND LTK ACTA2 BACH2 CAMTA1 CDK20 CSNK1D DEK ERBB2 FGF21 GFRA4 HNF1B IL3RA JUP LYL1 ACTC1 BAG4 CAPRIN2 CDK3 CSNK1E DHFR ERBB3 FGF22 GGCX HNRNPA3 IL4R KAT2A LYN ACVR1 BAI3 CARD10 CDK4 CTCF DHH ERBB4 FGF23 GHR HOXA10 IL5RA KAT2B LZTR1 ACVR1B BAP1 CARD11 CDK5 CTCFL DIAPH1 ERCC1 FGF3 GID4 HOXA11 IL6R KAT5 ACVR2A -
Estradiol-Regulated Micrornas Control Estradiol Response in Breast Cancer Cells Poornima Bhat-Nakshatri1, Guohua Wang2, Nikail R
4850–4861 Nucleic Acids Research, 2009, Vol. 37, No. 14 Published online 14 June 2009 doi:10.1093/nar/gkp500 Estradiol-regulated microRNAs control estradiol response in breast cancer cells Poornima Bhat-Nakshatri1, Guohua Wang2, Nikail R. Collins1, Michael J. Thomson3, Tim R. Geistlinger4, Jason S. Carroll4, Myles Brown4, Scott Hammond3, Edward F. Srour2, Yunlong Liu2 and Harikrishna Nakshatri1,5,* 1Department of Surgery, 2Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, 3Department of Cell and Developmental Biology, Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC, 4Department of Medical Oncology, Dana-Farber Medical School, Harvard Medical School, Boston, MA and 5Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, IN, USA Received May 4, 2009; Revised May 22, 2009; Accepted May 24, 2009 ABSTRACT INTRODUCTION Estradiol (E2) regulates gene expression at the Estradiol (E2) controls several biological processes by transcriptional level by functioning as a ligand for functioning as a ligand for nuclear receptors estrogen estrogen receptor alpha (ERa) and estrogen receptor receptor alpha (ERa) and beta (ERb) (1). ERs may par- beta (ERb). E2-inducible proteins c-Myc and E2Fs are ticipate in the genomic (transcriptional) and non-genomic required for optimal ERa activity and secondary actions of E2 (1,2). The genomic action involves binding of ERa to the regulatory regions of target genes either estrogen responses, respectively. We show that directly or through protein–protein interaction. DNA- E2 induces 21 microRNAs and represses seven bound ERa then recruits various co-regulatory molecules microRNAs in MCF-7 breast cancer cells; these to induce chromatin modifications that either increase or microRNAs have the potential to control 420 decrease the level of target gene transcription. -
Supplementary Materials
Supplementary Materials + - NUMB E2F2 PCBP2 CDKN1B MTOR AKT3 HOXA9 HNRNPA1 HNRNPA2B1 HNRNPA2B1 HNRNPK HNRNPA3 PCBP2 AICDA FLT3 SLAMF1 BIC CD34 TAL1 SPI1 GATA1 CD48 PIK3CG RUNX1 PIK3CD SLAMF1 CDKN2B CDKN2A CD34 RUNX1 E2F3 KMT2A RUNX1 T MIXL1 +++ +++ ++++ ++++ +++ 0 0 0 0 hematopoietic potential H1 H1 PB7 PB6 PB6 PB6.1 PB6.1 PB12.1 PB12.1 Figure S1. Unsupervised hierarchical clustering of hPSC-derived EBs according to the mRNA expression of hematopoietic lineage genes (microarray analysis). Hematopoietic-competent cells (H1, PB6.1, PB7) were separated from hematopoietic-deficient ones (PB6, PB12.1). In this experiment, all hPSCs were tested in duplicate, except PB7. Genes under-expressed or over-expressed in blood-deficient hPSCs are indicated in blue and red respectively (related to Table S1). 1 C) Mesoderm B) Endoderm + - KDR HAND1 GATA6 MEF2C DKK1 MSX1 GATA4 WNT3A GATA4 COL2A1 HNF1B ZFPM2 A) Ectoderm GATA4 GATA4 GSC GATA4 T ISL1 NCAM1 FOXH1 NCAM1 MESP1 CER1 WNT3A MIXL1 GATA4 PAX6 CDX2 T PAX6 SOX17 HBB NES GATA6 WT1 SOX1 FN1 ACTC1 ZIC1 FOXA2 MYF5 ZIC1 CXCR4 TBX5 PAX6 NCAM1 TBX20 PAX6 KRT18 DDX4 TUBB3 EPCAM TBX5 SOX2 KRT18 NKX2-5 NES AFP COL1A1 +++ +++ 0 0 0 0 ++++ +++ ++++ +++ +++ ++++ +++ ++++ 0 0 0 0 +++ +++ ++++ +++ ++++ 0 0 0 0 hematopoietic potential H1 H1 H1 H1 H1 H1 PB6 PB6 PB7 PB7 PB6 PB6 PB7 PB6 PB6 PB6.1 PB6.1 PB6.1 PB6.1 PB6.1 PB6.1 PB12.1 PB12.1 PB12.1 PB12.1 PB12.1 PB12.1 Figure S2. Unsupervised hierarchical clustering of hPSC-derived EBs according to the mRNA expression of germ layer differentiation genes (microarray analysis) Selected ectoderm (A), endoderm (B) and mesoderm (C) related genes differentially expressed between hematopoietic-competent (H1, PB6.1, PB7) and -deficient cells (PB6, PB12.1) are shown (related to Table S1). -
Supplemental Table 1. Primers and Probes for RT-Pcrs
Supplemental Table 1. Primers and probes for RT-PCRs Gene Direction Sequence Quantitative RT-PCR E2F1 Forward Primer 5’-GGA TTT CAC ACC TTT TCC TGG AT-3’ Reverse Primer 5’-CCT GGA AAC TGA CCA TCA GTA CCT-3’ Probe 5’-FAM-CGA GCT GGC CCA CTG CTC TCG-TAMRA-3' E2F2 Forward Primer 5'-TCC CAA TCC CCT CCA GAT C-3' Reverse Primer 5'-CAA GTT GTG CGA TGC CTG C-3' Probe 5' -FAM-TCC TTT TGG CCG GCA GCC G-TAMRA-3' E2F3a Forward Primer 5’-TTT AAA CCA TCT GAG AGG TAC TGA TGA-3’ Reverse Primer 5’-CGG CCC TCC GGC AA-3’ Probe 5’-FAM-CGC TTT CTC CTA GCT CCA GCC TTC G-TAMRA-3’ E2F3b Forward Primer 5’-TTT AAA CCA TCT GAG AGG TAC TGA TGA-3’ Reverse Primer 5’-CCC TTA CAG CAG CAG GCA A-3’ Probe 5’-FAM-CGC TTT CTC CTA GCT CCA GCC TTC G-TAMRA-3’ IRF-1 Forward Primer 5’-TTT GTA TCG GCC TGT GTG AAT G-3’ Reverse Primer 5’-AAG CAT GGC TGG GAC ATC A-3’ Probe 5’-FAM-CAG CTC CGG AAC AAA CAG GCA TCC TT-TAMRA-3' IRF-2 Forward Primer 5'-CGC CCC TCG GCA CTC T-3' Reverse Primer 5'-TCT TCC TAT GCA GAA AGC GAA AC-3' Probe 5'-FAM-TTC ATC GCT GGG CAC ACT ATC AGT-TAMRA-3' TBP Forward Primer 5’-CAC GAA CCA CGG CAC TGA TT-3’ Reverse Primer 5’-TTT TCT TGC TGC CAG TCT GGA C-3’ Probe 5’-FAM-TGT GCA CAG GAG CCA AGA GTG AAG A-BHQ1-3’ Primers and Probes for quantitative RT-PCRs were designed using the computer program “Primer Express” (Applied Biosystems, Foster City, CA, USA). -
Integrative Bulk and Single-Cell Profiling of Premanufacture T-Cell Populations Reveals Factors Mediating Long-Term Persistence of CAR T-Cell Therapy
Published OnlineFirst April 5, 2021; DOI: 10.1158/2159-8290.CD-20-1677 RESEARCH ARTICLE Integrative Bulk and Single-Cell Profiling of Premanufacture T-cell Populations Reveals Factors Mediating Long-Term Persistence of CAR T-cell Therapy Gregory M. Chen1, Changya Chen2,3, Rajat K. Das2, Peng Gao2, Chia-Hui Chen2, Shovik Bandyopadhyay4, Yang-Yang Ding2,5, Yasin Uzun2,3, Wenbao Yu2, Qin Zhu1, Regina M. Myers2, Stephan A. Grupp2,5, David M. Barrett2,5, and Kai Tan2,3,5 Downloaded from cancerdiscovery.aacrjournals.org on October 1, 2021. © 2021 American Association for Cancer Research. Published OnlineFirst April 5, 2021; DOI: 10.1158/2159-8290.CD-20-1677 ABSTRACT The adoptive transfer of chimeric antigen receptor (CAR) T cells represents a breakthrough in clinical oncology, yet both between- and within-patient differences in autologously derived T cells are a major contributor to therapy failure. To interrogate the molecular determinants of clinical CAR T-cell persistence, we extensively characterized the premanufacture T cells of 71 patients with B-cell malignancies on trial to receive anti-CD19 CAR T-cell therapy. We performed RNA-sequencing analysis on sorted T-cell subsets from all 71 patients, followed by paired Cellular Indexing of Transcriptomes and Epitopes (CITE) sequencing and single-cell assay for transposase-accessible chromatin sequencing (scATAC-seq) on T cells from six of these patients. We found that chronic IFN signaling regulated by IRF7 was associated with poor CAR T-cell persistence across T-cell subsets, and that the TCF7 regulon not only associates with the favorable naïve T-cell state, but is maintained in effector T cells among patients with long-term CAR T-cell persistence. -
Dialogue Between Estrogen Receptor and E2F Signaling Pathways: the Transcriptional Coregulator RIP140 at the Crossroads*
Advances in Bioscience and Biotechnology, 2013, 4, 45-54 ABB http://dx.doi.org/10.4236/abb.2013.410A3006 Published Online October 2013 (http://www.scirp.org/journal/abb/) Dialogue between estrogen receptor and E2F signaling pathways: The transcriptional coregulator RIP140 at the * crossroads Marion Lapierre1,2,3,4, Aurélie Docquier1,2,3,4, Audrey Castet-Nicolas1,2,3,4, Stéphan Jalaguier1,2,3,4, Catherine Teyssier1,2,3,4, Patrick Augereau1,2,3,4, Vincent Cavaillès1,2,3,4 1IRCM—Institut de Recherche en Cancérologie de Montpellier, Montpellier, France 2INSERM, U896, Montpellier, France 3Université Montpellier1, Montpellier, France 4Institut Régional du Cancer Montpellier, Montpellier, France Email: [email protected] Received 25 July 2013; revised 25 August 2013; accepted 19 September 2013 Copyright © 2013 Marion Lapierre et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. ABSTRACT Estrogen Receptors; Gene Expression; Cell Proliferation; Breast Cancer; Endocrine Therapies Estrogen receptors and E2F transcription factors are the key players of two nuclear signaling pathways which exert a major role in oncogenesis, particularly 1. ESTROGEN RECEPTOR AND E2F in the mammary gland. Different levels of dialogue SIGNALING PATHWAYS between these two pathways have been deciphered 1.1. Estrogen Signaling in Breast Cancer Cells and deregulation of the E2F pathway has been shown to impact the response of breast cancer cells to endo- Estrogens are steroid hormones that regulate growth and crine therapies. The present review focuses on the differentiation of a large number of target tissues such as transcriptional coregulator RIP140/NRIP1 which is the mammary gland, the reproductive tract and skeletal involved in several regulatory feed-back loops and and cardiovascular systems [1].