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Original Article Upregulation of HOXA13 As a Potential Tumorigenesis and Progression Promoter of LUSC Based on Qrt-PCR and Bioinformatics
Int J Clin Exp Pathol 2017;10(10):10650-10665 www.ijcep.com /ISSN:1936-2625/IJCEP0065149 Original Article Upregulation of HOXA13 as a potential tumorigenesis and progression promoter of LUSC based on qRT-PCR and bioinformatics Rui Zhang1*, Yun Deng1*, Yu Zhang1, Gao-Qiang Zhai1, Rong-Quan He2, Xiao-Hua Hu2, Dan-Ming Wei1, Zhen-Bo Feng1, Gang Chen1 Departments of 1Pathology, 2Medical Oncology, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, China. *Equal contributors. Received September 7, 2017; Accepted September 29, 2017; Epub October 1, 2017; Published October 15, 2017 Abstract: In this study, we investigated the levels of homeobox A13 (HOXA13) and the mechanisms underlying the co-expressed genes of HOXA13 in lung squamous cancer (LUSC), the signaling pathways in which the co-ex- pressed genes of HOXA13 are involved and their functional roles in LUSC. The clinical significance of 23 paired LUSC tissues and adjacent non-tumor tissues were gathered. HOXA13 levels in LUSC were detected by quantita- tive real-time polymerase chain reaction (qRT-PCR). HOXA13 levels in LUSC from The Cancer Genome Atlas (TCGA) and Oncomine were analyzed. We performed receiver operator characteristic (ROC) curves of various clinicopath- ological features of LUSC. Co-expressed of HOXA13 were collected from MEM, cBioPortal and GEPIA. The func- tions and pathways of the most reliable overlapped genes were achieved from the Gene Otology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases, respectively. The protein-protein interaction (PPI) net- works were mapped using STRING. HOXA13 in LUSC were markedly upregulated compared with those in the non- cancerous controls as demonstrated by qRT-PCR (LUSC: 0.330±0.360; CONTROLS: 0.155±0.142; P=0.021). -
Cyclin K Interacts with Β-Catenin to Induce Cyclin D1 Expression And
Theranostics 2020, Vol. 10, Issue 24 11144 Ivyspring International Publisher Theranostics 2020; 10(24): 11144-11158. doi: 10.7150/thno.42578 Research Paper Cyclin K interacts with β-catenin to induce Cyclin D1 expression and facilitates tumorigenesis and radioresistance in lung cancer Guojun Yao*, Jing Tang*, Xijie Yang, Ye Zhao, Rui Zhou, Rui Meng, Sheng Zhang, Xiaorong Dong, Tao Zhang, Kunyu Yang, Gang Wu and Shuangbing Xu Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China. *These authors contributed equally to this work. Corresponding author: Shuangbing Xu or Gang Wu, Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China. E-mail: [email protected] or [email protected]. © The author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/). See http://ivyspring.com/terms for full terms and conditions. Received: 2019.11.29; Accepted: 2020.08.24; Published: 2020.09.11 Abstract Rationale: Radioresistance remains the major cause of local relapse and distant metastasis in lung cancer. However, the underlying molecular mechanisms remain poorly defined. This study aimed to investigate the role and regulatory mechanism of Cyclin K in lung cancer radioresistance. Methods: Expression levels of Cyclin K were measured by immunohistochemistry in human lung cancer tissues and adjacent normal lung tissues. Cell growth and proliferation, neutral comet and foci formation assays, G2/M checkpoint and a xenograft mouse model were used for functional analyses. Gene expression was examined by RNA sequencing and quantitative real-time PCR. -
4-6 Weeks Old Female C57BL/6 Mice Obtained from Jackson Labs Were Used for Cell Isolation
Methods Mice: 4-6 weeks old female C57BL/6 mice obtained from Jackson labs were used for cell isolation. Female Foxp3-IRES-GFP reporter mice (1), backcrossed to B6/C57 background for 10 generations, were used for the isolation of naïve CD4 and naïve CD8 cells for the RNAseq experiments. The mice were housed in pathogen-free animal facility in the La Jolla Institute for Allergy and Immunology and were used according to protocols approved by the Institutional Animal Care and use Committee. Preparation of cells: Subsets of thymocytes were isolated by cell sorting as previously described (2), after cell surface staining using CD4 (GK1.5), CD8 (53-6.7), CD3ε (145- 2C11), CD24 (M1/69) (all from Biolegend). DP cells: CD4+CD8 int/hi; CD4 SP cells: CD4CD3 hi, CD24 int/lo; CD8 SP cells: CD8 int/hi CD4 CD3 hi, CD24 int/lo (Fig S2). Peripheral subsets were isolated after pooling spleen and lymph nodes. T cells were enriched by negative isolation using Dynabeads (Dynabeads untouched mouse T cells, 11413D, Invitrogen). After surface staining for CD4 (GK1.5), CD8 (53-6.7), CD62L (MEL-14), CD25 (PC61) and CD44 (IM7), naïve CD4+CD62L hiCD25-CD44lo and naïve CD8+CD62L hiCD25-CD44lo were obtained by sorting (BD FACS Aria). Additionally, for the RNAseq experiments, CD4 and CD8 naïve cells were isolated by sorting T cells from the Foxp3- IRES-GFP mice: CD4+CD62LhiCD25–CD44lo GFP(FOXP3)– and CD8+CD62LhiCD25– CD44lo GFP(FOXP3)– (antibodies were from Biolegend). In some cases, naïve CD4 cells were cultured in vitro under Th1 or Th2 polarizing conditions (3, 4). -
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Supplementary Figure S1. Results of flow cytometry analysis, performed to estimate CD34 positivity, after immunomagnetic separation in two different experiments. As monoclonal antibody for labeling the sample, the fluorescein isothiocyanate (FITC)- conjugated mouse anti-human CD34 MoAb (Mylteni) was used. Briefly, cell samples were incubated in the presence of the indicated MoAbs, at the proper dilution, in PBS containing 5% FCS and 1% Fc receptor (FcR) blocking reagent (Miltenyi) for 30 min at 4 C. Cells were then washed twice, resuspended with PBS and analyzed by a Coulter Epics XL (Coulter Electronics Inc., Hialeah, FL, USA) flow cytometer. only use Non-commercial 1 Supplementary Table S1. Complete list of the datasets used in this study and their sources. GEO Total samples Geo selected GEO accession of used Platform Reference series in series samples samples GSM142565 GSM142566 GSM142567 GSM142568 GSE6146 HG-U133A 14 8 - GSM142569 GSM142571 GSM142572 GSM142574 GSM51391 GSM51392 GSE2666 HG-U133A 36 4 1 GSM51393 GSM51394 only GSM321583 GSE12803 HG-U133A 20 3 GSM321584 2 GSM321585 use Promyelocytes_1 Promyelocytes_2 Promyelocytes_3 Promyelocytes_4 HG-U133A 8 8 3 GSE64282 Promyelocytes_5 Promyelocytes_6 Promyelocytes_7 Promyelocytes_8 Non-commercial 2 Supplementary Table S2. Chromosomal regions up-regulated in CD34+ samples as identified by the LAP procedure with the two-class statistics coded in the PREDA R package and an FDR threshold of 0.5. Functional enrichment analysis has been performed using DAVID (http://david.abcc.ncifcrf.gov/) -
Supp Table 1.Pdf
Upregulated genes in Hdac8 null cranial neural crest cells fold change Gene Symbol Gene Title 134.39 Stmn4 stathmin-like 4 46.05 Lhx1 LIM homeobox protein 1 31.45 Lect2 leukocyte cell-derived chemotaxin 2 31.09 Zfp108 zinc finger protein 108 27.74 0710007G10Rik RIKEN cDNA 0710007G10 gene 26.31 1700019O17Rik RIKEN cDNA 1700019O17 gene 25.72 Cyb561 Cytochrome b-561 25.35 Tsc22d1 TSC22 domain family, member 1 25.27 4921513I08Rik RIKEN cDNA 4921513I08 gene 24.58 Ofa oncofetal antigen 24.47 B230112I24Rik RIKEN cDNA B230112I24 gene 23.86 Uty ubiquitously transcribed tetratricopeptide repeat gene, Y chromosome 22.84 D8Ertd268e DNA segment, Chr 8, ERATO Doi 268, expressed 19.78 Dag1 Dystroglycan 1 19.74 Pkn1 protein kinase N1 18.64 Cts8 cathepsin 8 18.23 1500012D20Rik RIKEN cDNA 1500012D20 gene 18.09 Slc43a2 solute carrier family 43, member 2 17.17 Pcm1 Pericentriolar material 1 17.17 Prg2 proteoglycan 2, bone marrow 17.11 LOC671579 hypothetical protein LOC671579 17.11 Slco1a5 solute carrier organic anion transporter family, member 1a5 17.02 Fbxl7 F-box and leucine-rich repeat protein 7 17.02 Kcns2 K+ voltage-gated channel, subfamily S, 2 16.93 AW493845 Expressed sequence AW493845 16.12 1600014K23Rik RIKEN cDNA 1600014K23 gene 15.71 Cst8 cystatin 8 (cystatin-related epididymal spermatogenic) 15.68 4922502D21Rik RIKEN cDNA 4922502D21 gene 15.32 2810011L19Rik RIKEN cDNA 2810011L19 gene 15.08 Btbd9 BTB (POZ) domain containing 9 14.77 Hoxa11os homeo box A11, opposite strand transcript 14.74 Obp1a odorant binding protein Ia 14.72 ORF28 open reading -
Supplementary Information Method CLEAR-CLIP. Mouse Keratinocytes
Supplementary Information Method CLEAR-CLIP. Mouse keratinocytes of the designated genotype were maintained in E-low calcium medium. Inducible cells were treated with 3 ug/ml final concentration doxycycline for 24 hours before performing CLEAR-CLIP. One 15cm dish of confluent cells was used per sample. Cells were washed once with cold PBS. 10mls of cold PBS was then added and cells were irradiated with 300mJ/cm2 UVC (254nM wavelength). Cells were then scraped from the plates in cold PBS and pelleted by centrifugation at 1,000g for 2 minutes. Pellets were frozen at -80oC until needed. Cells were then lysed on ice with occasional vortexing in 1ml of lysis buffer (50mM Tris-HCl pH 7.4, 100mM NaCl, 1mM MgCl2, 0.1 mM CaCl2, 1% NP-40, 0.5% Sodium Deoxycholate, 0.1% SDS) containing 1X protease inhibitors (Roche #88665) and RNaseOUT (Invitrogen #10777019) at 4ul/ml final concentration. Next, TurboDNase (Invitrogen #AM2238, 10U), RNase A (0.13ug) and RNase T1 (0.13U) were added and samples were incubated at 37oC for 5 minutes with occasional mixing. Samples were immediately placed on ice and then centrifuged at 16,160g at 4oC for 20 minutes to clear lysate. 25ul of Protein-G Dynabeads (Invitrogen #10004D) were used per IP. Dynabeads were pre-washed with lysis buffer and pre- incubated with 3ul of Wako Anti-Mouse-Ago2 (2D4) antibody. The dynabead/antibody mixture was added to the lysate and rocked for 2 hours at 4oC. All steps after the IP were done on bead until samples were loaded into the polyacrylamide gel. -
Palmitic Acid Effects on Hypothalamic Neurons
bioRxiv preprint doi: https://doi.org/10.1101/2021.08.03.454666; this version posted August 4, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. Running title: Oleic and palmitic acid effects on hypothalamic neurons Concentration-dependent change in hypothalamic neuronal transcriptome by the dietary fatty acids: oleic and palmitic acids Fabiola Pacheco Valencia1^, Amanda F. Marino1^, Christos Noutsos1, Kinning Poon1* 1Department of Biological Sciences, SUNY Old Westbury, Old Westbury NY, United States ^Authors contributed equally to this work *Corresponding Author: Kinning Poon 223 Store Hill Rd Old Westbury, NY 11568, USA 1-516-876-2735 [email protected] bioRxiv preprint doi: https://doi.org/10.1101/2021.08.03.454666; this version posted August 4, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. Abstract Prenatal high-fat diet exposure increases hypothalamic neurogenesis events in embryos and programs offspring to be obesity-prone. The molecular mechanism involved in these dietary effects of neurogenesis are unknown. This study investigated the effects of oleic and palmitic acids, which are abundant in a high-fat diet, on the hypothalamic neuronal transcriptome and how these changes impact neurogenesis events. The results show differential effects of low and high concentrations of oleic or palmitic acid treatment on differential gene transcription. -
G Protein-Coupled Receptors
G PROTEIN-COUPLED RECEPTORS Overview:- The completion of the Human Genome Project allowed the identification of a large family of proteins with a common motif of seven groups of 20-24 hydrophobic amino acids arranged as α-helices. Approximately 800 of these seven transmembrane (7TM) receptors have been identified of which over 300 are non-olfactory receptors (see Frederikson et al., 2003; Lagerstrom and Schioth, 2008). Subdivision on the basis of sequence homology allows the definition of rhodopsin, secretin, adhesion, glutamate and Frizzled receptor families. NC-IUPHAR recognizes Classes A, B, and C, which equate to the rhodopsin, secretin, and glutamate receptor families. The nomenclature of 7TM receptors is commonly used interchangeably with G protein-coupled receptors (GPCR), although the former nomenclature recognises signalling of 7TM receptors through pathways not involving G proteins. For example, adiponectin and membrane progestin receptors have some sequence homology to 7TM receptors but signal independently of G-proteins and appear to reside in membranes in an inverted fashion compared to conventional GPCR. Additionally, the NPR-C natriuretic peptide receptor has a single transmembrane domain structure, but appears to couple to G proteins to generate cellular responses. The 300+ non-olfactory GPCR are the targets for the majority of drugs in clinical usage (Overington et al., 2006), although only a minority of these receptors are exploited therapeutically. Signalling through GPCR is enacted by the activation of heterotrimeric GTP-binding proteins (G proteins), made up of α, β and γ subunits, where the α and βγ subunits are responsible for signalling. The α subunit (tabulated below) allows definition of one series of signalling cascades and allows grouping of GPCRs to suggest common cellular, tissue and behavioural responses. -
Supplementary Table 1
Supplementary Table 1. Large-scale quantitative phosphoproteomic profiling was performed on paired vehicle- and hormone-treated mTAL-enriched suspensions (n=3). A total of 654 unique phosphopeptides corresponding to 374 unique phosphoproteins were identified. The peptide sequence, phosphorylation site(s), and the corresponding protein name, gene symbol, and RefSeq Accession number are reported for each phosphopeptide identified in any one of three experimental pairs. For those 414 phosphopeptides that could be quantified in all three experimental pairs, the mean Hormone:Vehicle abundance ratio and corresponding standard error are also reported. Peptide Sequence column: * = phosphorylated residue Site(s) column: ^ = ambiguously assigned phosphorylation site Log2(H/V) Mean and SE columns: H = hormone-treated, V = vehicle-treated, n/a = peptide not observable in all 3 experimental pairs Sig. column: * = significantly changed Log 2(H/V), p<0.05 Log (H/V) Log (H/V) # Gene Symbol Protein Name Refseq Accession Peptide Sequence Site(s) 2 2 Sig. Mean SE 1 Aak1 AP2-associated protein kinase 1 NP_001166921 VGSLT*PPSS*PK T622^, S626^ 0.24 0.95 PREDICTED: ATP-binding cassette, sub-family A 2 Abca12 (ABC1), member 12 XP_237242 GLVQVLS*FFSQVQQQR S251^ 1.24 2.13 3 Abcc10 multidrug resistance-associated protein 7 NP_001101671 LMT*ELLS*GIRVLK T464, S468 -2.68 2.48 4 Abcf1 ATP-binding cassette sub-family F member 1 NP_001103353 QLSVPAS*DEEDEVPVPVPR S109 n/a n/a 5 Ablim1 actin-binding LIM protein 1 NP_001037859 PGSSIPGS*PGHTIYAK S51 -3.55 1.81 6 Ablim1 actin-binding -
Multi-Functionality of Proteins Involved in GPCR and G Protein Signaling: Making Sense of Structure–Function Continuum with In
Cellular and Molecular Life Sciences (2019) 76:4461–4492 https://doi.org/10.1007/s00018-019-03276-1 Cellular andMolecular Life Sciences REVIEW Multi‑functionality of proteins involved in GPCR and G protein signaling: making sense of structure–function continuum with intrinsic disorder‑based proteoforms Alexander V. Fonin1 · April L. Darling2 · Irina M. Kuznetsova1 · Konstantin K. Turoverov1,3 · Vladimir N. Uversky2,4 Received: 5 August 2019 / Revised: 5 August 2019 / Accepted: 12 August 2019 / Published online: 19 August 2019 © Springer Nature Switzerland AG 2019 Abstract GPCR–G protein signaling system recognizes a multitude of extracellular ligands and triggers a variety of intracellular signal- ing cascades in response. In humans, this system includes more than 800 various GPCRs and a large set of heterotrimeric G proteins. Complexity of this system goes far beyond a multitude of pair-wise ligand–GPCR and GPCR–G protein interactions. In fact, one GPCR can recognize more than one extracellular signal and interact with more than one G protein. Furthermore, one ligand can activate more than one GPCR, and multiple GPCRs can couple to the same G protein. This defnes an intricate multifunctionality of this important signaling system. Here, we show that the multifunctionality of GPCR–G protein system represents an illustrative example of the protein structure–function continuum, where structures of the involved proteins represent a complex mosaic of diferently folded regions (foldons, non-foldons, unfoldons, semi-foldons, and inducible foldons). The functionality of resulting highly dynamic conformational ensembles is fne-tuned by various post-translational modifcations and alternative splicing, and such ensembles can undergo dramatic changes at interaction with their specifc partners. -
Convergent Molecular, Cellular, and Cortical Neuroimaging Signatures of Major Depressive Disorder
Convergent molecular, cellular, and cortical neuroimaging signatures of major depressive disorder Kevin M. Andersona,1, Meghan A. Collinsa, Ru Kongb,c,d,e,f, Kacey Fanga, Jingwei Lib,c,d,e,f, Tong Heb,c,d,e,f, Adam M. Chekroudg,h, B. T. Thomas Yeob,c,d,e,f,i, and Avram J. Holmesa,g,j aDepartment of Psychology, Yale University, New Haven, CT 06520; bDepartment of Electrical and Computer Engineering, National University of Singapore, Singapore; cCentre for Sleep and Cognition, National University of Singapore, Singapore; dClinical Imaging Research Centre, National University of Singapore, Singapore; eN.1 Institute for Health, National University of Singapore, Singapore; fInstitute for Digital Medicine, National University of Singapore, Singapore; gDepartment of Psychiatry, Yale University, New Haven, CT 06520; hSpring Health, New York, NY 10001; iGraduate School for Integrative Sciences and Engineering, National University of Singapore, Singapore; and jDepartment of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114 Edited by Huda Akil, University of Michigan, Ann Arbor, MI, and approved August 12, 2020 (received for review May 5, 2020) Major depressive disorder emerges from the complex interactions detail. To date, there have been few opportunities to directly of biological systems that span genes and molecules through cells, explore the depressive phenotype across levels of analysis—from networks, and behavior. Establishing how neurobiological pro- genes and molecules through cells, circuits, networks, and cesses coalesce to contribute to depression requires a multiscale behavior—simultaneously (14). approach, encompassing measures of brain structure and function In vivo neuroimaging has identified depression-related corre- as well as genetic and cell-specific transcriptional data. -
Transcriptional Silencing of Long Noncoding RNA GNG12-AS1 Uncouples Its Transcriptional and Product-Related Functions.” Nature Communications 7 (1): 10406
Transcriptional silencing of long noncoding RNA GNG12- AS1 uncouples its transcriptional and product-related functions The Harvard community has made this article openly available. Please share how this access benefits you. Your story matters Citation Stojic, L., M. Niemczyk, A. Orjalo, Y. Ito, A. E. M. Ruijter, S. Uribe- Lewis, N. Joseph, et al. 2016. “Transcriptional silencing of long noncoding RNA GNG12-AS1 uncouples its transcriptional and product-related functions.” Nature Communications 7 (1): 10406. doi:10.1038/ncomms10406. http://dx.doi.org/10.1038/ncomms10406. Published Version doi:10.1038/ncomms10406 Citable link http://nrs.harvard.edu/urn-3:HUL.InstRepos:26318707 Terms of Use This article was downloaded from Harvard University’s DASH repository, and is made available under the terms and conditions applicable to Other Posted Material, as set forth at http:// nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of- use#LAA ARTICLE Received 4 Sep 2015 | Accepted 8 Dec 2015 | Published 2 Feb 2016 DOI: 10.1038/ncomms10406 OPEN Transcriptional silencing of long noncoding RNA GNG12-AS1 uncouples its transcriptional and product-related functions Lovorka Stojic1, Malwina Niemczyk1, Arturo Orjalo2,w, Yoko Ito1, Anna Elisabeth Maria Ruijter1, Santiago Uribe-Lewis1, Nimesh Joseph1, Stephen Weston3, Suraj Menon1, Duncan T. Odom1, John Rinn4, Fanni Gergely1 & Adele Murrell1,3 Long noncoding RNAs (lncRNAs) regulate gene expression via their RNA product or through transcriptional interference, yet a strategy to differentiate these two processes is lacking. To address this, we used multiple small interfering RNAs (siRNAs) to silence GNG12-AS1,a nuclear lncRNA transcribed in an antisense orientation to the tumour-suppressor DIRAS3.