(Cnvs) in Hepatocellular Carcinoma; in Silico Analysis
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Supplementary Materials
Supplementary materials Supplementary Table S1: MGNC compound library Ingredien Molecule Caco- Mol ID MW AlogP OB (%) BBB DL FASA- HL t Name Name 2 shengdi MOL012254 campesterol 400.8 7.63 37.58 1.34 0.98 0.7 0.21 20.2 shengdi MOL000519 coniferin 314.4 3.16 31.11 0.42 -0.2 0.3 0.27 74.6 beta- shengdi MOL000359 414.8 8.08 36.91 1.32 0.99 0.8 0.23 20.2 sitosterol pachymic shengdi MOL000289 528.9 6.54 33.63 0.1 -0.6 0.8 0 9.27 acid Poricoic acid shengdi MOL000291 484.7 5.64 30.52 -0.08 -0.9 0.8 0 8.67 B Chrysanthem shengdi MOL004492 585 8.24 38.72 0.51 -1 0.6 0.3 17.5 axanthin 20- shengdi MOL011455 Hexadecano 418.6 1.91 32.7 -0.24 -0.4 0.7 0.29 104 ylingenol huanglian MOL001454 berberine 336.4 3.45 36.86 1.24 0.57 0.8 0.19 6.57 huanglian MOL013352 Obacunone 454.6 2.68 43.29 0.01 -0.4 0.8 0.31 -13 huanglian MOL002894 berberrubine 322.4 3.2 35.74 1.07 0.17 0.7 0.24 6.46 huanglian MOL002897 epiberberine 336.4 3.45 43.09 1.17 0.4 0.8 0.19 6.1 huanglian MOL002903 (R)-Canadine 339.4 3.4 55.37 1.04 0.57 0.8 0.2 6.41 huanglian MOL002904 Berlambine 351.4 2.49 36.68 0.97 0.17 0.8 0.28 7.33 Corchorosid huanglian MOL002907 404.6 1.34 105 -0.91 -1.3 0.8 0.29 6.68 e A_qt Magnogrand huanglian MOL000622 266.4 1.18 63.71 0.02 -0.2 0.2 0.3 3.17 iolide huanglian MOL000762 Palmidin A 510.5 4.52 35.36 -0.38 -1.5 0.7 0.39 33.2 huanglian MOL000785 palmatine 352.4 3.65 64.6 1.33 0.37 0.7 0.13 2.25 huanglian MOL000098 quercetin 302.3 1.5 46.43 0.05 -0.8 0.3 0.38 14.4 huanglian MOL001458 coptisine 320.3 3.25 30.67 1.21 0.32 0.9 0.26 9.33 huanglian MOL002668 Worenine -
Whole Genome Sequencing of Familial Non-Medullary Thyroid Cancer Identifies Germline Alterations in MAPK/ERK and PI3K/AKT Signaling Pathways
biomolecules Article Whole Genome Sequencing of Familial Non-Medullary Thyroid Cancer Identifies Germline Alterations in MAPK/ERK and PI3K/AKT Signaling Pathways Aayushi Srivastava 1,2,3,4 , Abhishek Kumar 1,5,6 , Sara Giangiobbe 1, Elena Bonora 7, Kari Hemminki 1, Asta Försti 1,2,3 and Obul Reddy Bandapalli 1,2,3,* 1 Division of Molecular Genetic Epidemiology, German Cancer Research Center (DKFZ), D-69120 Heidelberg, Germany; [email protected] (A.S.); [email protected] (A.K.); [email protected] (S.G.); [email protected] (K.H.); [email protected] (A.F.) 2 Hopp Children’s Cancer Center (KiTZ), D-69120 Heidelberg, Germany 3 Division of Pediatric Neurooncology, German Cancer Research Center (DKFZ), German Cancer Consortium (DKTK), D-69120 Heidelberg, Germany 4 Medical Faculty, Heidelberg University, D-69120 Heidelberg, Germany 5 Institute of Bioinformatics, International Technology Park, Bangalore 560066, India 6 Manipal Academy of Higher Education (MAHE), Manipal, Karnataka 576104, India 7 S.Orsola-Malphigi Hospital, Unit of Medical Genetics, 40138 Bologna, Italy; [email protected] * Correspondence: [email protected]; Tel.: +49-6221-42-1709 Received: 29 August 2019; Accepted: 10 October 2019; Published: 13 October 2019 Abstract: Evidence of familial inheritance in non-medullary thyroid cancer (NMTC) has accumulated over the last few decades. However, known variants account for a very small percentage of the genetic burden. Here, we focused on the identification of common pathways and networks enriched in NMTC families to better understand its pathogenesis with the final aim of identifying one novel high/moderate-penetrance germline predisposition variant segregating with the disease in each studied family. -
A Yeast Bifc-Seq Method for Genome-Wide Interactome Mapping
bioRxiv preprint doi: https://doi.org/10.1101/2020.06.16.154146; this version posted June 17, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. 1 A yeast BiFC-seq method for genome-wide interactome mapping 2 3 Limin Shang1,a, Yuehui Zhang1,b, Yuchen Liu1,c, Chaozhi Jin1,d, Yanzhi Yuan1,e, 4 Chunyan Tian1,f, Ming Ni2,g, Xiaochen Bo2,h, Li Zhang3,i, Dong Li1,j, Fuchu He1,*,k & 5 Jian Wang1,*,l 6 1State Key Laboratory of Proteomics, Beijing Proteome Research Center, National 7 Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing 102206, 8 China; 2Department of Biotechnology, Beijing Institute of Radiation Medicine, 9 Beijing 100850, China; 3Department of Rehabilitation Medicine, Nan Lou; 10 Department of Key Laboratory of Wound Repair and Regeneration of PLA, College 11 of Life Sciences, Chinese PLA General Hospital, Beijing 100853, China; 12 Correspondence should be addressed to F.H. ([email protected]) and J.W. 13 ([email protected]). 14 * Corresponding authors. 15 E-mail:[email protected] (Fuchu He),[email protected] (Jian Wang) 16 a ORCID: 0000-0002-6371-1956. 17 b ORCID: 0000-0001-5257-1671 18 c ORCID: 0000-0003-4691-4951 19 d ORCID: 0000-0002-1477-0255 20 e ORCID: 0000-0002-6576-8112 21 f ORCID: 0000-0003-1589-293X 22 g ORCID: 0000-0001-9465-2787 23 h ORCID: 0000-0003-3490-5812 24 i ORCID: 0000-0002-3477-8860 25 j ORCID: 0000-0002-8680-0468 26 k ORCID: 0000-0002-8571-2351 27 l ORCID: 0000-0002-8116-7691 28 Total word counts:4398 (from “Introduction” to “Conclusions”) 29 Total Keywords: 5 bioRxiv preprint doi: https://doi.org/10.1101/2020.06.16.154146; this version posted June 17, 2020. -
A Trafficome-Wide Rnai Screen Reveals Deployment of Early and Late Secretory Host Proteins and the Entire Late Endo-/Lysosomal V
bioRxiv preprint doi: https://doi.org/10.1101/848549; this version posted November 19, 2019. 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 4.0 International license. 1 A trafficome-wide RNAi screen reveals deployment of early and late 2 secretory host proteins and the entire late endo-/lysosomal vesicle fusion 3 machinery by intracellular Salmonella 4 5 Alexander Kehl1,4, Vera Göser1, Tatjana Reuter1, Viktoria Liss1, Maximilian Franke1, 6 Christopher John1, Christian P. Richter2, Jörg Deiwick1 and Michael Hensel1, 7 8 1Division of Microbiology, University of Osnabrück, Osnabrück, Germany; 2Division of Biophysics, University 9 of Osnabrück, Osnabrück, Germany, 3CellNanOs – Center for Cellular Nanoanalytics, Fachbereich 10 Biologie/Chemie, Universität Osnabrück, Osnabrück, Germany; 4current address: Institute for Hygiene, 11 University of Münster, Münster, Germany 12 13 Running title: Host factors for SIF formation 14 Keywords: siRNA knockdown, live cell imaging, Salmonella-containing vacuole, Salmonella- 15 induced filaments 16 17 Address for correspondence: 18 Alexander Kehl 19 Institute for Hygiene 20 University of Münster 21 Robert-Koch-Str. 4148149 Münster, Germany 22 Tel.: +49(0)251/83-55233 23 E-mail: [email protected] 24 25 or bioRxiv preprint doi: https://doi.org/10.1101/848549; this version posted November 19, 2019. 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 4.0 International license. -
Identification of Hub Genes Associated with Prognosis, Diagnosis, Immune
Lei et al. Human Genomics (2021) 15:39 https://doi.org/10.1186/s40246-021-00341-4 PRIMARY RESEARCH Open Access Identification of hub genes associated with prognosis, diagnosis, immune infiltration and therapeutic drug in liver cancer by integrated analysis Xinyi Lei1, Miao Zhang2, Bingsheng Guan1, Qiang Chen3, Zhiyong Dong1* and Cunchuan Wang1* Abstract Background: Liver cancer is one of the most common cancers and causes of cancer death worldwide. The objective was to elucidate novel hub genes which were benefit for diagnosis, prognosis, and targeted therapy in liver cancer via integrated analysis. Methods: GSE84402, GSE101685, and GSE112791 were filtered from the Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) were identified by using the GEO2R. The GO and KEGG pathway of DEGs were analyzed in the DAVID. PPI and TF network of the DEGs were constructed by using the STRING, TRANSFAC, and Harmonizome. The relationship between hub genes and prognoses in liver cancer was analyzed in UALCAN based on The Cancer Genome Atlas (TCGA). The diagnostic value of hub genes was evaluated by ROC. The relationship between hub genes and tumor-infiltrate lymphocytes was analyzed in TIMER. The protein levels of hub genes were verified in HPA. The interaction between the hub genes and the drug were identified in DGIdb. Results: In total, 108 upregulated and 60 downregulated DEGs were enriched in 148 GO terms and 20 KEGG pathways. The mRNA levels and protein levels of CDK1, HMMR, PTTG1, and TTK were higher in liver cancer tissues compared to normal tissues, which showed excellent diagnostic and prognostic value. CDK1, HMMR, PTTG1, and TTK were positively correlated with tumor-infiltrate lymphocytes, which might involve tumor immune response. -
Whole Genome Sequencing Reveals a Frameshift Mutation and a Large
Raggio et al. Human Genomics (2021) 15:28 https://doi.org/10.1186/s40246-021-00328-1 PRIMARY RESEARCH Open Access Whole genome sequencing reveals a frameshift mutation and a large deletion in YY1AP1 in a girl with a panvascular artery disease Víctor Raggio1, Nicolas Dell’Oca1, Camila Simoes2, Alejandra Tapié1, Conrado Medici3, Gonzalo Costa3, Soledad Rodriguez1, Gonzalo Greif4, Estefania Garrone5, María Laura Rovella5, Virgina Gonzalez5, Margarita Halty6, Gabriel González3, Jong-Yeon Shin7, Sang-Yoon Shin7, Changhoon Kim8, Jeong-Sun Seo7,9, Martin Graña2, Hugo Naya2,10 and Lucia Spangenberg2,11* Abstract Background: Rare diseases are pathologies that affect less than 1 in 2000 people. They are difficult to diagnose due to their low frequency and their often highly heterogeneous symptoms. Rare diseases have in general a high impact on the quality of life and life expectancy of patients, which are in general children or young people. The advent of high-throughput sequencing techniques has improved diagnosis in several different areas, from pediatrics, achieving a diagnostic rate of 41% with whole genome sequencing (WGS) and 36% with whole exome sequencing, to neurology, achieving a diagnostic rate between 47 and 48.5% with WGS. This evidence has encouraged our group to pursue a molecular diagnosis using WGS for this and several other patients with rare diseases. Results: We used whole genome sequencing to achieve a molecular diagnosis of a 7-year-old girl with a severe panvascular artery disease that remained for several years undiagnosed. We found a frameshift variant in one copy and a large deletion involving two exons in the other copy of a gene called YY1AP1. -
Multi-Cancer Molecular Signatures and Their Interrelationships
Multi-cancer molecular signatures and their interrelationships Wei-Yi Cheng1, Tai-Hsien Ou Yang1, Hui Shen2, Peter W. Laird2, Dimitris Anastassiou1 and the Cancer Genome Atlas Research Network 1Columbia Initiative in Systems Biology and Department of Electrical Engineering, Columbia University, New York, NY, USA 2USC Epigenome Center, Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA. Corresponding Author Dimitris Anastassiou, Columbia Initiative in Systems Biology and Department of Electrical Engineering, Columbia University, 1312S.W.Mudd Building, – Mail Code 4712, 500 West 120th Street, USA. Phone:+1212854-3113; E-mail: [email protected] This is version 2. A previous version of the same article appears at http://arxiv.org/pdf/1306.2584v1.pdf dated June 11, 2013. Please note: The pan-cancer molecular signatures disclosed in this article are the results of applying our data mining algorithm to the rich TCGA “pancan12” data sets from twelve different cancer types. These signatures have been identified as patterns, without any indication about their arXiv:1306.2584v2 [q-bio.QM] 11 Jul 2013 role or potential usefulness. We believe that each of them represents an important biomolecular event in cancer. We invite the cancer research community to contact us and help us interpret each of these pan-cancer signatures, and to investigate them for potential applications in diagnostic, prognostic and therapeutic products applicable to multiple cancer types. There will be additional versions of this article and we expect that the final version will contain many co-authors. 1 Although cancer is known to be characterized by several unifying biological hallmarks, systems biology has had limited success in identifying molecular signatures present in in all types of cancer. -
Single-Cell Genomics
Single-Cell Genomics Exploring new applications in microfluidics Mark Lynch April 10, 2019 Agenda 1. Microfluidics solutions for single-cell analysis 2. Single-cell total RNA sequencing 3. Single-cell high-throughput (HT) RNA expression and protein sequencing (REAP-seq) 4. Creating single-cell microenvironments 2 Microfluidic solutions for single-cell analysis Cellular analysis cell by cell The single-cell revolution is only beginning Science special issue, A Fantastic Voyage in Science, 2018 Breakthrough of the Year, Genomics, 2017 published in December 4 Driving those advances are techniques for isolating thousands of intact cells from living organisms, efficiently sequencing expressed genetic material in each cell and using computers, or labeling the cells, to reconstruct their relationships in space and time. That technical trifecta ‘will transform the next decade of research,’ says Nikolaus Rajewsky, a systems biologist at the Max Delbrück Center for Molecular Medicine in Berlin. —Elizabeth Pennisi, writing in ‘Science’ about the 2018 Breakthrough of the Year 5 Creating a cell atlas The only way to identify and understand all cells in a tissue Three cell-based approaches: 1. Classification 2. Characterization 3. Context 6 The benefit Individual cells behave differently from the average of many cells Modified from Dominguez et al. Journal of Immunological Methods (2014) 7 Cell characterization Deep profiling of cells to study multiple modes Stuart and Satija. Nature Reviews Genetics (2019) 8 Microfluidics Integrated fluidic circuit -
Chromatin Conformation Links Distal Target Genes to CKD Loci
BASIC RESEARCH www.jasn.org Chromatin Conformation Links Distal Target Genes to CKD Loci Maarten M. Brandt,1 Claartje A. Meddens,2,3 Laura Louzao-Martinez,4 Noortje A.M. van den Dungen,5,6 Nico R. Lansu,2,3,6 Edward E.S. Nieuwenhuis,2 Dirk J. Duncker,1 Marianne C. Verhaar,4 Jaap A. Joles,4 Michal Mokry,2,3,6 and Caroline Cheng1,4 1Experimental Cardiology, Department of Cardiology, Thoraxcenter Erasmus University Medical Center, Rotterdam, The Netherlands; and 2Department of Pediatrics, Wilhelmina Children’s Hospital, 3Regenerative Medicine Center Utrecht, Department of Pediatrics, 4Department of Nephrology and Hypertension, Division of Internal Medicine and Dermatology, 5Department of Cardiology, Division Heart and Lungs, and 6Epigenomics Facility, Department of Cardiology, University Medical Center Utrecht, Utrecht, The Netherlands ABSTRACT Genome-wide association studies (GWASs) have identified many genetic risk factors for CKD. However, linking common variants to genes that are causal for CKD etiology remains challenging. By adapting self-transcribing active regulatory region sequencing, we evaluated the effect of genetic variation on DNA regulatory elements (DREs). Variants in linkage with the CKD-associated single-nucleotide polymorphism rs11959928 were shown to affect DRE function, illustrating that genes regulated by DREs colocalizing with CKD-associated variation can be dysregulated and therefore, considered as CKD candidate genes. To identify target genes of these DREs, we used circular chro- mosome conformation capture (4C) sequencing on glomerular endothelial cells and renal tubular epithelial cells. Our 4C analyses revealed interactions of CKD-associated susceptibility regions with the transcriptional start sites of 304 target genes. Overlap with multiple databases confirmed that many of these target genes are involved in kidney homeostasis. -
Identification of Hub Genes Associated with Hepatocellular Carcinoma Prognosis by Bioinformatics Analysis
Journal of Cancer Therapy, 2021, 12, 186-207 https://www.scirp.org/journal/jct ISSN Online: 2151-1942 ISSN Print: 2151-1934 Identification of Hub Genes Associated with Hepatocellular Carcinoma Prognosis by Bioinformatics Analysis Xi Zhang*, Xiaojun Luo*, Wenbin Liu, Ai Shen# Department of Hepatobiliary and Pancreatic Tumor Center, Chongqing University Cancer Hospital, Chongqing, China How to cite this paper: Zhang, X., Luo, Abstract X.J., Liu, W.B. and Shen, A. (2021) Identi- fication of Hub Genes Associated with He- Objective: This study aimed to identify hub genes that are associated with patocellular Carcinoma Prognosis by Bio- hepatocellular carcinoma (HCC) prognosis by bioinformatics analysis. Me- informatics Analysis. Journal of Cancer The- thods: Data were collected from the Gene Expression Omnibus (GEO) and rapy, 12, 186-207. https://doi.org/10.4236/jct.2021.124019 The Cancer Genome Atlas (TCGA) liver HCC datasets. The robust rank ag- gregation algorithm was used in integrating the data on differentially expressed Received: March 23, 2021 genes (DEGs). Online databases DAVID 6.8 and REACTOME were used for Accepted: April 26, 2021 gene ontology and pathway enrichment analysis. R software version 3.5.1, Cy- Published: April 29, 2021 toscape, and Kaplan-Meier plotter were used to identify hub genes. Results: Copyright © 2021 by author(s) and Six GEO datasets and the TCGA liver HCC dataset were included in this Scientific Research Publishing Inc. analysis. A total of 151 upregulated and 245 downregulated DEGs were iden- This work is licensed under the Creative tified. The upregulated DEGs most significantly enriched in the functional Commons Attribution International License (CC BY 4.0). -
Identification of Pathogenic YY1AP1 Splice Variants in Siblings with Grange Syndrome by Whole Exome Sequencing
Received: 17 May 2018 Revised: 23 October 2018 Accepted: 27 October 2018 DOI: 10.1002/ajmg.a.60700 CLINICAL REPORT Identification of pathogenic YY1AP1 splice variants in siblings with Grange syndrome by whole exome sequencing Matthias Rath1 | Stefanie Spiegler1 | Tim M. Strom2,3 | Johannes Trenkler4 | Peter Michael Kroisel5 | Ute Felbor1 1Department of Human Genetics, University Medicine Greifswald, and Interfaculty Institute Grange syndrome is an autosomal recessive condition characterized by arterial occlusions and of Genetics and Functional Genomics, hypertension. Syndactyly, brachydactyly, bone fragility, heart defects, and learning disabilities have University of Greifswald, Greifswald, Germany also been reported. Loss-of-function variants in YY1AP1 have only recently been associated with 2 Institute of Human Genetics, Technische Grange syndrome. YY1AP1 encodes for the transcription coactivator yin yang 1-associated protein Universität München, Munich, Germany 1 which regulates smooth muscle cell proliferation and differentiation. We here report on three 3Institute of Human Genetics, Helmholtz Zentrum München, Neuherberg, Germany siblings with steno-occlusive arterial disorder and syndactyly in two of them. Whole exome 4Institute of Neuroradiology, Kepler University sequencing including near-splice regions led to the identification of two intronic YY1AP1 variants Hospital, Linz, Austria which were predicted to interfere with normal splicing. Sanger sequencing demonstrated 5Institute of Human Genetics, Medical compound-heterozygosity in all affected siblings. RT-PCR analyses confirmed skipping of exon University of Graz, Austria 6 on one allele and exonization of 22 bp in intron 6 on the other. This is the first report of biallelic Correspondence YY1AP1 variants in noncoding regions and just the second family with multiple affected siblings. -
Upstream Open Reading Frames Cause Widespread Reduction of Protein Expression and Are Polymorphic Among Humans
Upstream open reading frames cause widespread reduction of protein expression and are polymorphic among humans Sarah E. Calvoa,b,c,d,1, David J. Pagliarinia,b,c,1, and Vamsi K. Moothaa,b,c,2 aBroad Institute of MIT and Harvard, Cambridge, MA 02142; bCenter for Human Genetic Research, Massachusetts General Hospital, Boston, MA 02114; cDepartment of Systems Biology, Harvard Medical School, Boston, MA 02115; and dDivision of Health Sciences and Technology, Harvard–MIT, Cambridge, MA 02139 Edited by Jonathan Weissman, University of California, San Francisco, CA, and accepted by the Editorial Board March 18, 2009 (received for review October 29, 2008) Upstream ORFs (uORFs) are mRNA elements defined by a start codon in the 5 UTR that is out-of-frame with the main coding sequence. A cap 5’ UTR main coding sequence 3’ UTR polyA Although uORFs are present in approximately half of human and AUG AUG AUG mouse transcripts, no study has investigated their global impact on AAAAAA protein expression. Here, we report that uORFs correlate with signif- uORF uORF icantly reduced protein expression of the downstream ORF, based on analysis of 11,649 matched mRNA and protein measurements from 4 B # Transcripts with: Human Mouse published mammalian studies. Using reporter constructs to test 25 annotated 5' UTR 23775 18663 selected uORFs, we estimate that uORFs typically reduce protein ≥1 uORF 11670 8253 expression by 30–80%, with a modest impact on mRNA levels. We ≥2 uORFs 6268 4197 additionally identify polymorphisms that alter uORF presence in 509 ≥1 uORF fully upstream 9879 6935 human genes. Finally, we report that 5 uORF-altering mutations, ≥1 uORF overlapping CDS 4275 2872 GENETICS detected within genes previously linked to human diseases, dramat- Median Length (nt): ically silence expression of the downstream protein.