FIGURE S1 Characterization of Mscs. A, Flow Cytometry Assay Was Used to Detect Classical MSC Marker Expression

Total Page:16

File Type:pdf, Size:1020Kb

FIGURE S1 Characterization of Mscs. A, Flow Cytometry Assay Was Used to Detect Classical MSC Marker Expression FIGURE S1 Characterization of MSCs. A, Flow cytometry assay was used to detect classical MSC marker expression. Passage: P4. B, MSCs were induced to osteocytes by incubation with osteogenic differentiation medium (RASMX-90021, Cyagen) and stained by alizarin red. C, MSCs were induced to adipocytes by incubation with adipogenic differentiation medium (RASMX-90031, Cyagen) and stained by Oil red O. D, MSCs were induced to chondrocytes by incubation with chondrogenic differentiation medium (RASMX-90041, Cyagen) and stained by HE. Bar: 100 μm FIGURE S2 Effect of miR-503 on A549 cells in vitro. A, XTT assay was used to detect cell proliferation in A549 cells transfected with miR-503 mimics or miR-503 AS, or their respective controls at 24 hours post-transfection. B, Flow cytometry assay was used to detect cell proliferation in A549 cells transfected with miR-503 mimics or miR-503 AS, or their respective controls at 24 hours post-transfection. Apoptosis inducer (Cisplatin, 1 μM, Beyotime) were added to the culture. All data are shown as the mean ± standard deviation based on three independent experiments, ** p<0.01, * p<0.05. C, Matrigel assay was used to detect the formation of capillary-like tubes in A549 cells transfected with miR-503 mimics or miR-503-AS, or their respective controls at 24 hours post-transfection. Bar: 100 μm. miR-nc AS: antisense strands for miR-nc; miR-503 AS: antisense strands for miR-503; FIGURE S3 miRNAs differentially expressed in rMSCs exposed to TCM, compared with control rMSCs. A, Heatmap showed the differentially expressed miRNAs in rMSCs exposed to TCM, compared with control rMSCs, Each small block indicates its own expression level. Red denotes a high expression level, green denotes a low expression level. B, List of miRNAs differentially expressed in rMSCs exposed to TCM, compared with control rMSCs. Supplementary Table 1. Oligonucleotide sequences for siRNA and target genes. Name Sequence miRNA miR-503 Sense 5’-uagcagcgggaacaguacugcag-3’ Antisense 5’-gcaguacuguucccgcugcuauu-3’ miR-NC Sense 5’-uucuccgaacgugucacgutt-3’ Antisense 5’-acgugacacguucggagaatt-3’ miR-503 AS 5’-cugcaguacuguucccgcugcua-3’ miR-nc AS 5’-uuguacuacacaaaaguacug-3’ Primers miR-503 Stem-loop 5’-gtcgtatccagtgcgtgtcgtggagtcggcaattgcactggatacgacctgcag-3’ Sense 5’- tagcagcgggaacagta -3’ Antisense 5’- tgcgtgtcgtggagtc -3’ u6 Sense 5’-gcttcggcagcacatatactaaaat-3’ Antisense 5’-cgcttcacgaatttgcgtgtcat-3’ α-SMA Sense 5’-aactggtattgtgctggactctg-3’ Antisense 5’-cccatcaggcagttcgtagc-3’ FAP Sense 5’-atgaagacatggctgaaaaccg-3’ Antisense 5’-ggctgtaaactcttgagggacg-3’ FSP Sense 5’-gaaggtgttgagcgggaagaa -3’ Antisense 5’-gagacgagaaggagcattggtt-3’ TNC Sense 5’-gctttgtttgccctcactcct-3’ Antisense 5’-caccactggctgattctcctct -3’ CCL20 Sense 5’-gcagccagtcagaagcagcaa-3’ Antisense 5’-ccaattccatcccagaaaagc-3’ IL1Β Sense 5’-acctgctagtgtgtgatgttccca -3’ Antisense 5’-aggtggagagctttcagctcacat-3’ CXCL2 Sense 5’-caatgcctgacgaccctacc-3’ Antisense 5’-ttttggacgatcctctgaacc-3’ CXCL3 Sense 5’-ccttcagggactgttgtggc-3’ Antisense 5’-ggctatgacttctgtctgggtg-3’ VEGF Sense 5’-cgaaaccatgaactttctgc -3’ Antisense 5’-cctcagtgggcacacactcc-3’ SDF-1 Sense 5’-tgcccatgccgattcttc-3’ Antisense 5’-ggctttgcccaggttgact-3’ IGF-1 Sense 5’-ggtggatgctcttcagttcgt-3’ Antisense 5’-cactccctctacttgcgttctt-3’ MMP-3 Sense 5’-ttcctggcatcccgaagt-3’ Antisense 5’-ggtccatcaaaagggtaaaagtc-3’ β-ACTIN Sense 5’-tggaatcctgtggcatccatgaaac -3’ (RAT) Antisense 5’-taaaacgcagctcagtaacagtccg -3’ GAPDH Sense 5’-gaccactttgtcaagctcatttcc-3’ (HUMAN) Antisense 5’-gtgagggtctctctcttcctcttgt-3’ Table S2. List of genes differentially expressed in MSCs exposed to TCM, compared with control MSCs Genes Up-regulat OLR1142, CCL20, HTR3B, IL1B, LOC683206, CXCL2, CXCL3, ion LOC100910497, CXCL1, ASS1, CCL7, CCL2, PLA2G2A, DRD1, (fold >1.5) MMP3, RSAD2, CCL4, CCL3, C3, HP, CXCL10, SLPI, RTP4, RBP1, CMPK2, TNIP3, OAS1K, MGC105649, GCH1, TYRP1, SLFN2, TLR2, RAC2, LOC100910885, IFIH1, NFKBIA, ISG15, OLR1695, MMP9, CCL12, TGM2, TMEM106A, ZC3H12A, HPN, CREG1, ANGPTL4, BDKRB1, CXCL14, LCN2, THBS4, CD83, NFKBIZ, TNF, IL18BP, C1S, ZC3HAV1, BCL3, ADORA2B, G0S2, RGD1305725, RGD1559629, FMOD, HSD11B1, VCAM1, LOC360228, CXCL13, PF4, EPN3, ACER1, PTGS1, CXCL16, CX3CL1, TRH, FCGR2B, FCGR1A, LOC24906, KRT12, CCL5, APOL9A, GDF15, IL1A, LOC498276, LRP1B, CYP7B1, ABCB1B, ANGPT4, SOD2, PTGS2, IRF7, CD40, TSPAN11, MT1A, NFKBIE, CP, BIRC3, RBM38, SLC25A37, PLK2, HDAC11, C1R, MAP3K8, DDX58, ENPP2, LOC654482, CYP4A8, STAP2, MT2A, GADD45A, SERPING1, ADM2, MMP12, CCR2, LOC678766, RAB32, RGD1311756, TUBA8, KCNT1, RAP1GAP2, NTN1, ICAM1, GJB2, TMEM86A, CAMP, CYP26B1, BMP6, DIP2C, USP18, GPRC5A, CD200, NCF1, IFI204, FLI1, ARHGDIB, KLF10, RGD1559864, RASL12, N4BP2L1, EGR2, RHBDF2, TCP11, SELP, ALDH3B1, SERINC2, HCK, KCNQ5, ABCG1, RGD1561149, CPXM1, ATOH7, RASD1, SLAMF9, CDC42EP3, CSF1, RGD1564086, RT1-CE2, DIO3, TAP2, OLR1, DNAJC12, GINS2, PADI3, LOC100362769, DAGLA, CEBPB, ITPKA, PLA1A, RT1-A2, RT1-CE16, TGS1, VEGFA, GRAMD1B, ZFP174, TNFRSF1B, GGT1, TFPI2, TMEM144, RGD1305587, POPDC2, LYZ2, IRF1, UPP1, RT1.AA, GBP5, LOC361914, F3, GREM1, LAMB3, SLC43A2, KLHL29, RPRD1B, CCRN4L, METRN, FSCN2, SPINT2, PSMB9, BOD1, OLR1616, PARVB, TNFSF15, PPP1R15A, RBPJ, CD14, EDN1, PHLDA1, ECHDC3, OPTN, EGR3, SLC35F2, CYP4F17, ZFP512B, LOC684871, TXNIP, EVA1C, BMP2, FAM110A, N4BP3, AGRP, STAC2, TSLP, FCER1G, SHROOM1, EML2, SLC9B2, ARSE, CCDC90A, EFNB1, WNT11, FOXS1, PHLDB3, SLC2A1, PTPDC1, DUSP16, TFRC, PPIP5K1, EMP2, LCN6, TMEM140, P2RX4, SMOC2, CLU, MAFK, ZFP133, LOC498752, WDSUB1, MOGAT2, LAMA5, MICALL2, BLOC1S6, ZMIZ1, ANXA3, MOSPD1, GLUL, IFI44, CST6, MGC125239, LOC687813, CPT1A, LOC100912739, MMACHC, NAGLU, CLCN3, HOGA1, MGMT, AKNA, SH2B2, CSRNP1, PVRL1, PMAIP1, ADAMTSL5, SLC20A1, SAMD4A, GDNF, TRAF2, DMRT2, HOOK2, CAMK1G, RT1-T18, KCNQ4, FAM206A, KLF5, BCL6, FAM5B, CDK17, LTBP2, GBP2, SLC38A7, LPCAT2, KDSR, LOXL4, VEGP2, LOC682105, SLC16A11, RGD1562079, KLK14, SCUBE3, NR1H3, PANX1, RDH12, ZNRF1, ARHGEF6, RGD1304982, RSPH9, SLC29A1, PKNOX1, B3GNT7, DFNB31, IER3, HTR6, DSN1, IRAK3, C8G, GAS7, RGD1566380, ENO2, MSH5, PLAT, UPK1B, PTX3, CORO1A, SMIM3, ABCA2, ANGEL1, LMNB1, ETV6, PYGL, TRIB3, WNT5A, TBC1D2, ISG20L2, SLC11A2, RNASE1, KLHL30, LOC100910973, SMG9, ITGA10, PLAGL2, EMR1, NMRAL1, ATF3, TNFAIP2, DPEP1, SLC3A2, TMEM132E, RGD1560281, ACOT2, CYP1A1, SPP1, HSPA2, RGD1566373, IFIT2, RAMP3, ATG16L2, TK2, CPEB1, RT1-A1, SH3BP2, PHLDA3, LOC690483, FBXO10, CHIC2, CYP2S1, LIF, SPRY2, NFKBIB, EEPD1, CD55, TRAF3, PDE10A, JUNB, CARS, SHISA8, RGD1304595, RTN4R, LOC100359980, RT1-S2, KLHL41, GPM6B, DUSP5, GIPC2, NCEH1, RENBP, MLLT4, AIF1, RAB36, CITED2, CRLF1, TRIO, BDH2, CYP4F5, TLE3, BLCAP, ALKBH7, GPD2, TNKS1BP1, PSEN2, PRKAB2, ENPP4, TRIT1, S1PR1, HNRNPUL2, PIM3, CCDC28B, CIDEA, BHLHE40, NUDT2, LOC691666, NR1D1, KLF15, ETS2, AGXT2L2, PLAC8, SIK1, LOC687696, UBE2L6, CYS1, CCDC8, DUSP14, SLC7A3, FUOM, FLCN, CDKN2AIPNL, WDR12, KLHDC8A, WDTC1, USP54, PLEKHG4, SLC7A5, PIGV, CCDC28A, UNK, HEMK1, KCNMA1, TNFRSF22, TNIP1, AMBRA1, MT3, DHRS3, MANBA, AGTR1A, NFKB2, HES1, SMURF1, LOC684681, RT1-S3, RAD9B, GMFB, RGD1564114, PARP14, RASL11B, LHFPL2, LEF1, LOC499770, STOML1, ACSF3, RGD735029, MAP2K5, SLC51B, GOT1, CTH, UAP1L1, ZC3H8, RT1-M6-1, CACNA1G, PLA2G6, RT1-CE7, PEX3, RT1-CE5, MAML1, TGFB2, MRI1, IL11RA1, GFER, STEAP3, BCL2, RASSF2, NCOA2, GRHL3, DPH2, UBALD2, BCAR1, PAOX, MDM2, PDE2A, SUN2, TIMP3, SERPINE1, RGD1304624, SPERT, YDJC, NFKB1, IFNGR2, ACOT8, HINT3, PROSC, PRND, CXCL12, CCDC32, SURF2, MAPKAPK3, LOC307263, PKMYT1, RWDD3, SAT2, RAB20, SDC4, CCDC19, ING3, CYP1B1, TAF8, ROPN1L, EXTL3, GINM1, SLC7A1, PRDX5, EVI2A, MGST1, GPNMB, PARP8, NMNAT3, IFI27L2B, AMDHD2, LOC501224, RT1-CE14, NRG1, FAM131B, PNRC1, DNASE2, RGD1309708, LOC100125367, CCBE1, MCOLN1, LGALS3, LYRM9, PEX6, RT1-CL, TYROBP, TMEM218, APOL3, GCAT, BCL2L1, ACADS, PROCR, DDX59, TFIP11, MIB2, YARS, LOC100911534, OTUB2, LOC684270, CYM, LOC685438, ZXDB, FAM49A, TMEM63A, PCED1A Down- MORC1, CSAD, IGSF11, OLR1266, HS3ST2, TMCO5A, PKM, regulation ZFP334, SHISA7, ITPR2, POU2AF1, VOM2R24, CCDC117, TREM3, SPTA1, IDI1, SPEM1, SCD1, CYP51, HMGCS1, RGD1561594, (fold >1.5) PCSK9, ASB15, RGD1560208, FDPS, ZC4H2, MEPE, ASPN, CDH6, FBXW8, INSIG1, EDNRA, DEPDC1, ELOVL6, SH3PXD2A, MEST, TRIL, PPARD, LOC689246, HSD17B7, MVD, H19, BLNK, DHCR7, PANX3, SQLE, COL6A3, OLR305, FADS1, POLH, ADAMTSL3, HMGCR, GZMB, ACAT3, NOX4, MALL, NEXN, FAM189A2, STARD4, FRMPD1, GAS2, SCD, PRELID2, OLR545, PROM1, RGD1305422, HTR4, MMP15, CADPS2, PCDH19, ERG, TCEAL8, VOM2R68, MSMO1, ADRA1D, GLS, ELN, OGN, MBOAT1, E2F7, NEFL, HYLS1, APOBEC2, CSTF1, NPAS2, FASN, ROCK1, PLN, PRPF39, VSNL1, SLC18A2, UHMK1, OLR857, SOX15, C1QL3, IGSF10, PARK2, ARSK, AMH, PLS3, SLC29A2, ITCH, ACSS2, C1QTNF3, SLC7A14, ANO1, ARHGAP11A, TMEM97, HLTF, THSD7A, AKAP17B, ASPM, MLC1, SOWAHA, VCSA1, ITM2A, UBE2QL1, OLR745, HTR2A, CDR2, PTH1R, SEMA3D, ABP10, SESN3, SERPINA11, LOC683788, TLR13, LRRC17, PCMTD2, BIRC6, OMD, CALCB, VAV3, FAM81A, ADA, MRVI1, CLOCK, RPL37, FAM13A, ETAA1, APOBEC1, PRM1, MIER1, PCOLCE2, SENP5, OLR416, USP9X, LOC691717, RGD1305110, HMGN5, LOC304131, UBD, LOC691984, DCLK1, SHANK3, SYNJ2BP, PNN, LOC494539, TPH1, RGD1563084, COL2A1, PBRM1, TYMP, SLC22A8, HOXC5, SRSF7, OLFML2A, GPER, FRAS1, KCTD2, PRRT1, FBN2, NMNAT1, INPP5F, OLR1057, ABCG2, OLR674, GUCY1B3, CD163L1, MYH1, PCDHA13, SEC23A, NOTCH1, FOXD4, RPF2, IPO7, AOC3, GAPDH-PS1, FUT8, DNM1L, NSDHL, RGD1563520, TNKS2, MAGEB7, GLT8D1, ZFP386, PSME4, TM7SF2, PCDH7, RGL1, ST6GALNAC3, PTGER3, SLC5A5, POLR3G, TDRD3, VCAN, VPS13B, TTC3, IBSP, MS4A15, NOXO1, CBFB, TUBA1A, TSC22D2, EIF5, DDX3X, GPR182, COBL, CCDC88A, SMARCA1,
Recommended publications
  • Further Delineation of Chromosomal Consensus Regions in Primary
    Leukemia (2007) 21, 2463–2469 & 2007 Nature Publishing Group All rights reserved 0887-6924/07 $30.00 www.nature.com/leu ORIGINAL ARTICLE Further delineation of chromosomal consensus regions in primary mediastinal B-cell lymphomas: an analysis of 37 tumor samples using high-resolution genomic profiling (array-CGH) S Wessendorf1,6, TFE Barth2,6, A Viardot1, A Mueller3, HA Kestler3, H Kohlhammer1, P Lichter4, M Bentz5,HDo¨hner1,PMo¨ller2 and C Schwaenen1 1Klinik fu¨r Innere Medizin III, Zentrum fu¨r Innere Medizin der Universita¨t Ulm, Ulm, Germany; 2Institut fu¨r Pathologie, Universita¨t Ulm, Ulm, Germany; 3Forschungsdozentur Bioinformatik, Universita¨t Ulm, Ulm, Germany; 4Abt. Molekulare Genetik, Deutsches Krebsforschungszentrum, Heidelberg, Germany and 5Sta¨dtisches Klinikum Karlsruhe, Karlsruhe, Germany Primary mediastinal B-cell lymphoma (PMBL) is an aggressive the expression of BSAP, BOB1, OCT2, PAX5 and PU1 was extranodal B-cell non-Hodgkin’s lymphoma with specific clin- added to the spectrum typical of PMBL features.9 ical, histopathological and genomic features. To characterize Genetically, a pattern of highly recurrent karyotype alterations further the genotype of PMBL, we analyzed 37 tumor samples and PMBL cell lines Med-B1 and Karpas1106P using array- with the hallmark of chromosomal gains of the subtelomeric based comparative genomic hybridization (matrix- or array- region of chromosome 9 supported the concept of a unique CGH) to a 2.8k genomic microarray. Due to a higher genomic disease entity that distinguishes PMBL from other B-cell non- resolution, we identified altered chromosomal regions in much Hodgkin’s lymphomas.10,11 Together with less specific gains on higher frequencies compared with standard CGH: for example, 2p15 and frequent mutations of the SOCS1 gene, a notable þ 9p24 (68%), þ 2p15 (51%), þ 7q22 (32%), þ 9q34 (32%), genomic similarity to classical Hodgkin’s lymphoma was þ 11q23 (18%), þ 12q (30%) and þ 18q21 (24%).
    [Show full text]
  • A Computational Approach for Defining a Signature of Β-Cell Golgi Stress in Diabetes Mellitus
    Page 1 of 781 Diabetes A Computational Approach for Defining a Signature of β-Cell Golgi Stress in Diabetes Mellitus Robert N. Bone1,6,7, Olufunmilola Oyebamiji2, Sayali Talware2, Sharmila Selvaraj2, Preethi Krishnan3,6, Farooq Syed1,6,7, Huanmei Wu2, Carmella Evans-Molina 1,3,4,5,6,7,8* Departments of 1Pediatrics, 3Medicine, 4Anatomy, Cell Biology & Physiology, 5Biochemistry & Molecular Biology, the 6Center for Diabetes & Metabolic Diseases, and the 7Herman B. Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, IN 46202; 2Department of BioHealth Informatics, Indiana University-Purdue University Indianapolis, Indianapolis, IN, 46202; 8Roudebush VA Medical Center, Indianapolis, IN 46202. *Corresponding Author(s): Carmella Evans-Molina, MD, PhD ([email protected]) Indiana University School of Medicine, 635 Barnhill Drive, MS 2031A, Indianapolis, IN 46202, Telephone: (317) 274-4145, Fax (317) 274-4107 Running Title: Golgi Stress Response in Diabetes Word Count: 4358 Number of Figures: 6 Keywords: Golgi apparatus stress, Islets, β cell, Type 1 diabetes, Type 2 diabetes 1 Diabetes Publish Ahead of Print, published online August 20, 2020 Diabetes Page 2 of 781 ABSTRACT The Golgi apparatus (GA) is an important site of insulin processing and granule maturation, but whether GA organelle dysfunction and GA stress are present in the diabetic β-cell has not been tested. We utilized an informatics-based approach to develop a transcriptional signature of β-cell GA stress using existing RNA sequencing and microarray datasets generated using human islets from donors with diabetes and islets where type 1(T1D) and type 2 diabetes (T2D) had been modeled ex vivo. To narrow our results to GA-specific genes, we applied a filter set of 1,030 genes accepted as GA associated.
    [Show full text]
  • Supplemental Materials ZNF281 Enhances Cardiac Reprogramming
    Supplemental Materials ZNF281 enhances cardiac reprogramming by modulating cardiac and inflammatory gene expression Huanyu Zhou, Maria Gabriela Morales, Hisayuki Hashimoto, Matthew E. Dickson, Kunhua Song, Wenduo Ye, Min S. Kim, Hanspeter Niederstrasser, Zhaoning Wang, Beibei Chen, Bruce A. Posner, Rhonda Bassel-Duby and Eric N. Olson Supplemental Table 1; related to Figure 1. Supplemental Table 2; related to Figure 1. Supplemental Table 3; related to the “quantitative mRNA measurement” in Materials and Methods section. Supplemental Table 4; related to the “ChIP-seq, gene ontology and pathway analysis” and “RNA-seq” and gene ontology analysis” in Materials and Methods section. Supplemental Figure S1; related to Figure 1. Supplemental Figure S2; related to Figure 2. Supplemental Figure S3; related to Figure 3. Supplemental Figure S4; related to Figure 4. Supplemental Figure S5; related to Figure 6. Supplemental Table S1. Genes included in human retroviral ORF cDNA library. Gene Gene Gene Gene Gene Gene Gene Gene Symbol Symbol Symbol Symbol Symbol Symbol Symbol Symbol AATF BMP8A CEBPE CTNNB1 ESR2 GDF3 HOXA5 IL17D ADIPOQ BRPF1 CEBPG CUX1 ESRRA GDF6 HOXA6 IL17F ADNP BRPF3 CERS1 CX3CL1 ETS1 GIN1 HOXA7 IL18 AEBP1 BUD31 CERS2 CXCL10 ETS2 GLIS3 HOXB1 IL19 AFF4 C17ORF77 CERS4 CXCL11 ETV3 GMEB1 HOXB13 IL1A AHR C1QTNF4 CFL2 CXCL12 ETV7 GPBP1 HOXB5 IL1B AIMP1 C21ORF66 CHIA CXCL13 FAM3B GPER HOXB6 IL1F3 ALS2CR8 CBFA2T2 CIR1 CXCL14 FAM3D GPI HOXB7 IL1F5 ALX1 CBFA2T3 CITED1 CXCL16 FASLG GREM1 HOXB9 IL1F6 ARGFX CBFB CITED2 CXCL3 FBLN1 GREM2 HOXC4 IL1F7
    [Show full text]
  • Original Article Diagnostic and Prognostic Values of Forkhead Box D4 Gene in Colonic Adenocarcinoma
    Int J Clin Exp Pathol 2020;13(10):2615-2627 www.ijcep.com /ISSN:1936-2625/IJCEP0117403 Original Article Diagnostic and prognostic values of forkhead box D4 gene in colonic adenocarcinoma Qiu-Xia Li1, Ning-Qin Li2, Jin-Yuan Liao2 1Department of Health Management and Division of Physical Examination, The First Affiliated Hospital of Guangxi Medical University, Nanning 530021, Guangxi Zhuang Autonomous Region, People’s Republic of China; 2Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, Nanning 530021, Guangxi Zhuang Autonomous Region, People’s Republic of China Received July 2, 2020; Accepted August 31, 2020; Epub October 1, 2020; Published October 15, 2020 Abstract: Previous studies found that Forkhead box D4 (FOXD4) overexpressed in human colorectal cancer had the worst prognosis. However, the diagnostic value and further mechanism have not been fully researched. Statistical examinations for FOXD4 expression colon adenocarcinoma (COAD) patients were obtained from The Cancer Genome Atlas (TCGA). Survival analysis was used to assess its prognostic value. Nomogram model was used for visual pre- diction of patient survival rate. The online functional enrichment analysis tool was used to evaluate the biological functions and pathways of FOXD4 and its co-expressed genes. Receiver operating characteristic curve analysis suggested that FOXD4 might be a diagnostic biomarker for COAD (P<0.001, area under the curve [AUC]=0.728, 95% confidence interval [CI]=0.669-0.787). Low expression ofFOXD4 was associated with a good clinical outcome (P=0.001, HR=0.517, 95% CI=0.341-0.782). A total of 797 genes were correlated with FOXD4 and associated with cell proliferation, cell differentiation, nuclear matrix, Rap1 signaling pathway, RNA transport, and VEGF signaling pathway.
    [Show full text]
  • Supplementary Table S4. FGA Co-Expressed Gene List in LUAD
    Supplementary Table S4. FGA co-expressed gene list in LUAD tumors Symbol R Locus Description FGG 0.919 4q28 fibrinogen gamma chain FGL1 0.635 8p22 fibrinogen-like 1 SLC7A2 0.536 8p22 solute carrier family 7 (cationic amino acid transporter, y+ system), member 2 DUSP4 0.521 8p12-p11 dual specificity phosphatase 4 HAL 0.51 12q22-q24.1histidine ammonia-lyase PDE4D 0.499 5q12 phosphodiesterase 4D, cAMP-specific FURIN 0.497 15q26.1 furin (paired basic amino acid cleaving enzyme) CPS1 0.49 2q35 carbamoyl-phosphate synthase 1, mitochondrial TESC 0.478 12q24.22 tescalcin INHA 0.465 2q35 inhibin, alpha S100P 0.461 4p16 S100 calcium binding protein P VPS37A 0.447 8p22 vacuolar protein sorting 37 homolog A (S. cerevisiae) SLC16A14 0.447 2q36.3 solute carrier family 16, member 14 PPARGC1A 0.443 4p15.1 peroxisome proliferator-activated receptor gamma, coactivator 1 alpha SIK1 0.435 21q22.3 salt-inducible kinase 1 IRS2 0.434 13q34 insulin receptor substrate 2 RND1 0.433 12q12 Rho family GTPase 1 HGD 0.433 3q13.33 homogentisate 1,2-dioxygenase PTP4A1 0.432 6q12 protein tyrosine phosphatase type IVA, member 1 C8orf4 0.428 8p11.2 chromosome 8 open reading frame 4 DDC 0.427 7p12.2 dopa decarboxylase (aromatic L-amino acid decarboxylase) TACC2 0.427 10q26 transforming, acidic coiled-coil containing protein 2 MUC13 0.422 3q21.2 mucin 13, cell surface associated C5 0.412 9q33-q34 complement component 5 NR4A2 0.412 2q22-q23 nuclear receptor subfamily 4, group A, member 2 EYS 0.411 6q12 eyes shut homolog (Drosophila) GPX2 0.406 14q24.1 glutathione peroxidase
    [Show full text]
  • Identification of Spatially Associated Subpopulations by Combining
    Supplementary Tables Supplementary Table 1: List of genes that are profiled by the seqFISH experiment. 4931431F19Rik Ctla4 Hnf1a Obsl1 Cpne5 4932429P05Rik Cyp2c70 Hoxb3 Olr1 Nes Abca15 Cyp2j5 Hoxb8 Osr2 Acta2 Abca9 Dbx1 Hyal5 Pld1 Gja1 Adcy4 Dcstamp Kif16b Pld5 Omg Aldh3b2 Ddb2 Laptm5 Poln Nov Ankle1 Egln3 Lefty2 Ppp1r3b Col5a1 Ano7 Fam69c Lhx3 Psmd5 Dcx Anxa9 Fbll1 Lhx4 Rbm31y Itpr2 Arhgef26 Foxa1 Lmod1 Rrm2 Rhob B3gat2 Foxa2 Mertk Scml2 Sox2 Barhl1 Foxd1 Mgam Senp1 Cldn5 Bcl2l14 Foxd4 Mmgt1 Serpinb11 Mrc1 Blzf1 Galnt3 Mmp8 Sis Tbr1 Bmpr1b Gata6 Mrgprb1 Slc4a8 Pax6 Capn13 Gdf2 Murc Slc6a16 Calb1 Cdc5l Gdf5 Nell1 Spag6 Gda Cdc6 Gm15688 Neurod4 Sumf2 Slc5a7 Cdh1 Gm6377 Neurog1 Tnfrsf1b Sema3e Cecr2 Gm805 Nfkb2 Vmn1r65 Mfge8 Cilp Gpc4 Nfkbiz Vps13c Lyve1 Clec5a Gpr114 Nhlh1 Wrn Loxl1 Creb1 Gykl1 Nkd2 Zfp182 Slco1c1 Creb3l1 Hdx Nlrp12 Zfp715 Amigo2 Nature Biotechnology: doi:10.1038/nbt.4260 Csf2rb2 Hn1l Npy2r Zfp90 Kcnip2 Supplementary Table 2: List of 43 genes used for cell type mapping. Fbll1 Itpr2 Vps13c Tnfrsf1b Sox2 Hdx Wrn Sumf2 Vmn1r65 Rhob Mrgprb1 Calb1 Pld1 Laptm5 Tbr1 Slc5a7 Abca9 Ankle1 Olr1 Cecr2 Cpne5 Blzf1 Mertk Nell1 Npy2r Cdc5l Slco1c1 Pax6 Cldn5 Cyp2j5 Mfge8 Col5a1 Bmpr1b Rrm2 Gja1 Dcx Spag6 Csf2rb2 Gda Arhgef26 Slc4a8 Gm805 Omg Supplementary Table 3: Astrocyte prediction accuracy, evaluated using fluorescent staining images. We examined and contrasted DAPI, Nissl staining on astrocyte cells. Percentage of cells with no Nissl, and with DAPI staining are recorded (these are accurate instances) % predicted % predicted Total predicted astrocytes with weak astrocytes with astrocytes or no Nissl stain present Nissl stain Cortex Column 1 100% 0% 11 Cortex Column 2 88% 12% 25 Cortex Column 3 87% 13% 24 Cortex Column 4 87% 13% 24 Supplementary Table 4: List of 69 genes used for HMRF.
    [Show full text]
  • A W148R Mutation in the Human FOXD4 Gene Segregating with Dilated Cardiomyopathy, Obsessive-Compulsive Disorder, and Suicidality
    369-372 29/1/07 17:44 Page 369 INTERNATIONAL JOURNAL OF MOLECULAR MEDICINE 19: 369-372, 2007 369 A W148R mutation in the human FOXD4 gene segregating with dilated cardiomyopathy, obsessive-compulsive disorder, and suicidality PIERCARLO MINORETTI1, MARIAROSA ARRA1, ENZO EMANUELE1, VALENTINA OLIVIERI1, ALESSIA ALDEGHI1, PIERLUIGI POLITI2, VALENTINA MARTINELLI2, SARA PESENTI2 and COLOMBA FALCONE1 1Interdepartmental Center for Research in Molecular Medicine (CIRMC); 2Department of Applied Health and Behavioural Sciences, Section of Psychiatry, University of Pavia, Pavia, Italy Received May 3, 2006; Accepted July 25, 2006 Abstract. The forkhead/winged helix box (FOX) gene including some neuropsychiatric phenotypes such as speech family comprises at least 43 different genes encoding and language disorders (10) and schizophrenia (11). transcriptional factors with a highly conserved DNA-binding The human FOXD4 is an intronless gene located at 9p24 domain. To date, mutations in members of the FOX gene (1,12). It has been shown to be highly expressed in the heart family have been causally linked to a variety of different and skeletal muscle, as well as in the adult and fetal brain human diseases. We describe a three-generation Albanian (13,14). In the present study, we describe a three-generation pedigree in which a complex phenotype consisting of dilated Albanian pedigree in which a complex phenotype consisting cardiomyopathy, obsessive-compulsive disorder, and of dilated cardiomyopathy (DCM), obsessive-compulsive suicidality is segregated with a missense mutation (W148R) in disorder (OCD), and suicidality is segregated with a missense the human FOXD4 gene. This mutation disrupts an extremely mutation (W148R) in FOXD4. highly conserved tryptophan residue in the forkhead domain of We reasoned that FOXD4 could be a plausible biological FOXD4, possibly resulting in reduced DNA binding capacity candidate gene for the complex phenotype displayed by this and altered transcriptional activity.
    [Show full text]
  • Foxc1 Regulates Pecam-1 Expression in Embryonic Endothelial Progenitor Cells
    Dissertation der Fakultät für Biologie der Ludwig-Maximilians-Universität München Foxc1 regulates Pecam-1 Expression in embryonic Endothelial Progenitor Cells Eingereicht von Mathias Lamparter München, 15. Januar 2008 Angefertigt am Institut für Klinische Molekularbiologie und Tumorgenetik, Helmholtz Zentrum München – Deutsches Forschungszentrum für Gesundheit und Umwelt, und Division of Cardiovascular Medicine, Vanderbilt University Medical Center, Nashville, TN, USA Erster Gutachter: Prof. Dr. Dirk Eick Zweiter Gutachter: Prof. Dr. Manfred Schliwa Tag der mündlichen Prüfung: 02. Juli 2008 SUMMARY ................................................................................................................. 1 1. INTRODUCTION .................................................................................................... 3 1.1 The Vascular System........................................................................................ 3 1.2 De novo formation of the vasculature – Vasculogenesis................................... 3 1.3 Expansion and maturation of the vasculature – Angiogenesis.......................... 4 1.4 The vasculature in disease states..................................................................... 5 1.5 Characteristics of adult EPCs ........................................................................... 5 1.6 EPC promote neovascularization...................................................................... 6 1.7 Molecular control of blood vessel formation .....................................................
    [Show full text]
  • Forkhead Box Family Transcription Factors As Versatile Regulators for Cellular Reprogramming to Pluripotency
    Fu et al. Cell Regeneration (2021) 10:17 https://doi.org/10.1186/s13619-021-00078-4 RESEARCH ARTICLE Open Access Forkhead box family transcription factors as versatile regulators for cellular reprogramming to pluripotency Meijun Fu1,2,3,4†, Huan Chen1,2,4†, Zepo Cai1,2,4, Yihang Yang2,3,4, Ziyu Feng5, Mengying Zeng5, Lijun Chen1,2,4, Yue Qin2,3,4, Baomei Cai5, Pinghui Zhu5, Chunhua Zhou2,4, Shengyong Yu2,3,4, Jing Guo2,4, Jing Liu2,4,5*, Shangtao Cao5* and Duanqing Pei1,2,3,4,5* Abstract Forkhead box (Fox) transcription factors play important roles in mammalian development and disease. However, their function in mouse somatic cell reprogramming remains unclear. Here, we report that FoxD subfamily and FoxG1 accelerate induced pluripotent stem cells (iPSCs) generation from mouse fibroblasts as early as day4 while FoxA and FoxO subfamily impede this process obviously. More importantly, FoxD3, FoxD4 and FoxG1 can replace Oct4 respectively and generate iPSCs with germline transmission together with Sox2 and Klf4. On the contrary, FoxO6 almost totally blocks reprogramming through inhibiting cell proliferation, suppressing the expression of pluripotent genes and hindering the process of mesenchymal to epithelial transition (MET). Thus, our study uncovers unexpected roles of Fox transcription factors in reprogramming and offers new insights into cell fate transition. Background factor cocktails Oct4, Sox2, Klf4 and Myc or OSKM Reprogramming somatic cells to induced pluripotent also named Yamanaka factors cooperatively function stem cells (iPSCs) by defined transcription factors is a to regulate the expression of genes essential for the revolutionary concept for biology and medicine, pluripotency induction (Buganim et al., 2012; providing not only cellular sources for disease therapy Buganim et al., 2014; Chronis et al., 2017).
    [Show full text]
  • The Transcription Factor E2A Drives Neural Differentiation in Pluripotent Cells Chandrika Rao1, Mattias Malaguti1, John O
    © 2020. Published by The Company of Biologists Ltd | Development (2020) 147, dev184093. doi:10.1242/dev.184093 STEM CELLS AND REGENERATION RESEARCH ARTICLE The transcription factor E2A drives neural differentiation in pluripotent cells Chandrika Rao1, Mattias Malaguti1, John O. Mason2,3 and Sally Lowell1,* ABSTRACT the activity of a factor that would otherwise trigger the onset of The intrinsic mechanisms that link extracellular signalling to the onset neural commitment. of neural differentiation are not well understood. In pluripotent mouse Id proteins lack a DNA-binding domain and function primarily as cells, BMP blocks entry into the neural lineage via transcriptional dominant-negative inhibitors of basic helix-loop-helix (bHLH) upregulation of inhibitor of differentiation (Id) factors. We have transcription factors (TFs), binding to and preventing them from previously identified the major binding partner of Id proteins in forming functional dimers (Norton, 2000). It has previously been pluripotent cells as the basic helix-loop-helix (bHLH) transcription reported that Id1 indirectly inhibits the activity of the bHLH TF factor (TF) E2A. Id1 can prevent E2A from forming heterodimers with Tcf15. However, Tcf15 appears to play a role in general priming for bHLH TFs or from forming homodimers. Here, we show that differentiation by enabling morphological changes, and does not overexpression of a forced E2A homodimer is sufficient to drive have a specific instructive role in neural commitment (Davies et al., robust neural commitment in pluripotent cells, even under non- 2013; Lin et al., 2019 preprint). We have also found that E-cadherin permissive conditions. Conversely, we find that E2A null cells display (Cdh1) acts downstream of BMP to help suppress neural a defect in their neural differentiation capacity.
    [Show full text]
  • (12) Patent Application Publication (10) Pub. No.: US 2009/0269772 A1 Califano Et Al
    US 20090269772A1 (19) United States (12) Patent Application Publication (10) Pub. No.: US 2009/0269772 A1 Califano et al. (43) Pub. Date: Oct. 29, 2009 (54) SYSTEMS AND METHODS FOR Publication Classification IDENTIFYING COMBINATIONS OF (51) Int. Cl. COMPOUNDS OF THERAPEUTIC INTEREST CI2O I/68 (2006.01) CI2O 1/02 (2006.01) (76) Inventors: Andrea Califano, New York, NY G06N 5/02 (2006.01) (US); Riccardo Dalla-Favera, New (52) U.S. Cl. ........... 435/6: 435/29: 706/54; 707/E17.014 York, NY (US); Owen A. (57) ABSTRACT O'Connor, New York, NY (US) Systems, methods, and apparatus for searching for a combi nation of compounds of therapeutic interest are provided. Correspondence Address: Cell-based assays are performed, each cell-based assay JONES DAY exposing a different sample of cells to a different compound 222 EAST 41ST ST in a plurality of compounds. From the cell-based assays, a NEW YORK, NY 10017 (US) Subset of the tested compounds is selected. For each respec tive compound in the Subset, a molecular abundance profile from cells exposed to the respective compound is measured. (21) Appl. No.: 12/432,579 Targets of transcription factors and post-translational modu lators of transcription factor activity are inferred from the (22) Filed: Apr. 29, 2009 molecular abundance profile data using information theoretic measures. This data is used to construct an interaction net Related U.S. Application Data work. Variances in edges in the interaction network are used to determine the drug activity profile of compounds in the (60) Provisional application No. 61/048.875, filed on Apr.
    [Show full text]
  • Effector Gene Expression Potential to Th17 Cells by Promoting Microrna
    The Journal of Immunology MicroRNA-155 Confers Encephalogenic Potential to Th17 Cells by Promoting Effector Gene Expression Ruozhen Hu,* Thomas B. Huffaker,* Dominique A. Kagele,* Marah C. Runtsch,* Erin Bake,* Aadel A. Chaudhuri,† June L. Round,* and Ryan M. O’Connell* Th17 cells are central to the pathogenesis of autoimmune disease, and recently specific noncoding microRNAs have been shown to regulate their development. However, it remains unclear whether microRNAs are also involved in modulating Th17 cell effector functions. Consequently, we examined the role of miR-155 in differentiated Th17 cells during their induction of experimental au- toimmune encephalomyelitis. Using adoptive transfer experiments, we found that highly purified, myelin oligodendrocyte glyco- protein Ag-specific Th17 cells lacking miR-155 were defective in their capacity to cause experimental autoimmune encephalomyelitis. Gene expression profiling of purified miR-1552/2IL-17F+ Th17 cells identified a subset of effector genes that are dependent on miR-155 for their proper expression through a mechanism involving repression of the transcription factor Ets1. Among the genes reduced in the absence of miR-155 was IL-23R, resulting in miR-1552/2 Th17 cells being hyporesponsive to IL-23. Taken together, our study demonstrates a critical role for miR-155 in Th17 cells as they unleash autoimmune inflammation and finds that this occurs through a signaling network involving miR-155, Ets1, and the clinically relevant IL-23–IL-23R pathway. The Journal of Immunology, 2013, 190: 5972–5980. utoimmunity occurs when dysregulated, autoreactive im- how miRNAs fit into the known regulatory circuits underlying mune cells inappropriately respond to self-Ags and cause Th17 cell biology remains an important area of investigation.
    [Show full text]