Transcriptomic Response to 1,25-Dihydroxyvitamin D
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Pdf Sub-Classification of Patients with a Molecular Alteration Provides Better Response [57]
Theranostics 2021, Vol. 11, Issue 12 5759 Ivyspring International Publisher Theranostics 2021; 11(12): 5759-5777. doi: 10.7150/thno.57659 Research Paper Homeobox B5 promotes metastasis and poor prognosis in Hepatocellular Carcinoma, via FGFR4 and CXCL1 upregulation Qin He1, Wenjie Huang2, Danfei Liu1, Tongyue Zhang1, Yijun Wang1, Xiaoyu Ji1, Meng Xie1, Mengyu Sun1, Dean Tian1, Mei Liu1, Limin Xia1 1. Department of Gastroenterology, Institute of Liver and Gastrointestinal Diseases, Hubei Key Laboratory of Hepato-Pancreato-Biliary Diseases, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei Province, China. 2. Hubei Key Laboratory of Hepato-Pancreato-Biliary Diseases; Hepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology; Clinical Medicine Research Center for Hepatic Surgery of Hubei Province; Key Laboratory of Organ Transplantation, Ministry of Education and Ministry of Public Health, Wuhan, Hubei, 430030, China. Corresponding author: Dr. Limin Xia, Department of Gastroenterology, Institute of Liver and Gastrointestinal Diseases, Hubei Key Laboratory of Hepato-Pancreato-Biliary Diseases, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei Province, China; Phone: 86 27 6937 8507; Fax: 86 27 8366 2832; E-mail: [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: 2020.12.29; Accepted: 2021.03.17; Published: 2021.03.31 Abstract Background: Since metastasis remains the main reason for HCC-associated death, a better understanding of molecular mechanism underlying HCC metastasis is urgently needed. -
Figure S1. Representative Report Generated by the Ion Torrent System Server for Each of the KCC71 Panel Analysis and Pcafusion Analysis
Figure S1. Representative report generated by the Ion Torrent system server for each of the KCC71 panel analysis and PCaFusion analysis. (A) Details of the run summary report followed by the alignment summary report for the KCC71 panel analysis sequencing. (B) Details of the run summary report for the PCaFusion panel analysis. A Figure S1. Continued. Representative report generated by the Ion Torrent system server for each of the KCC71 panel analysis and PCaFusion analysis. (A) Details of the run summary report followed by the alignment summary report for the KCC71 panel analysis sequencing. (B) Details of the run summary report for the PCaFusion panel analysis. B Figure S2. Comparative analysis of the variant frequency found by the KCC71 panel and calculated from publicly available cBioPortal datasets. For each of the 71 genes in the KCC71 panel, the frequency of variants was calculated as the variant number found in the examined cases. Datasets marked with different colors and sample numbers of prostate cancer are presented in the upper right. *Significantly high in the present study. Figure S3. Seven subnetworks extracted from each of seven public prostate cancer gene networks in TCNG (Table SVI). Blue dots represent genes that include initial seed genes (parent nodes), and parent‑child and child‑grandchild genes in the network. Graphical representation of node‑to‑node associations and subnetwork structures that differed among and were unique to each of the seven subnetworks. TCNG, The Cancer Network Galaxy. Figure S4. REVIGO tree map showing the predicted biological processes of prostate cancer in the Japanese. Each rectangle represents a biological function in terms of a Gene Ontology (GO) term, with the size adjusted to represent the P‑value of the GO term in the underlying GO term database. -
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 -
SUPPLEMENTARY MATERIAL Bone Morphogenetic Protein 4 Promotes
www.intjdevbiol.com doi: 10.1387/ijdb.160040mk SUPPLEMENTARY MATERIAL corresponding to: Bone morphogenetic protein 4 promotes craniofacial neural crest induction from human pluripotent stem cells SUMIYO MIMURA, MIKA SUGA, KAORI OKADA, MASAKI KINEHARA, HIROKI NIKAWA and MIHO K. FURUE* *Address correspondence to: Miho Kusuda Furue. Laboratory of Stem Cell Cultures, National Institutes of Biomedical Innovation, Health and Nutrition, 7-6-8, Saito-Asagi, Ibaraki, Osaka 567-0085, Japan. Tel: 81-72-641-9819. Fax: 81-72-641-9812. E-mail: [email protected] Full text for this paper is available at: http://dx.doi.org/10.1387/ijdb.160040mk TABLE S1 PRIMER LIST FOR QRT-PCR Gene forward reverse AP2α AATTTCTCAACCGACAACATT ATCTGTTTTGTAGCCAGGAGC CDX2 CTGGAGCTGGAGAAGGAGTTTC ATTTTAACCTGCCTCTCAGAGAGC DLX1 AGTTTGCAGTTGCAGGCTTT CCCTGCTTCATCAGCTTCTT FOXD3 CAGCGGTTCGGCGGGAGG TGAGTGAGAGGTTGTGGCGGATG GAPDH CAAAGTTGTCATGGATGACC CCATGGAGAAGGCTGGGG MSX1 GGATCAGACTTCGGAGAGTGAACT GCCTTCCCTTTAACCCTCACA NANOG TGAACCTCAGCTACAAACAG TGGTGGTAGGAAGAGTAAAG OCT4 GACAGGGGGAGGGGAGGAGCTAGG CTTCCCTCCAACCAGTTGCCCCAAA PAX3 TTGCAATGGCCTCTCAC AGGGGAGAGCGCGTAATC PAX6 GTCCATCTTTGCTTGGGAAA TAGCCAGGTTGCGAAGAACT p75 TCATCCCTGTCTATTGCTCCA TGTTCTGCTTGCAGCTGTTC SOX9 AATGGAGCAGCGAAATCAAC CAGAGAGATTTAGCACACTGATC SOX10 GACCAGTACCCGCACCTG CGCTTGTCACTTTCGTTCAG Suppl. Fig. S1. Comparison of the gene expression profiles of the ES cells and the cells induced by NC and NC-B condition. Scatter plots compares the normalized expression of every gene on the array (refer to Table S3). The central line -
HOXB6 Homeo Box B6 HOXB5 Homeo Box B5 WNT5A Wingless-Type
5 6 6 5 . 4 2 1 1 1 2 4 6 4 3 2 9 9 7 0 5 7 5 8 6 4 0 8 2 3 1 8 3 7 1 0 0 4 0 2 5 0 8 7 5 4 1 1 0 3 6 0 4 8 3 7 4 7 6 9 6 7 1 5 0 8 1 4 1 1 7 1 0 0 4 2 0 8 1 1 1 2 5 3 5 0 7 2 6 9 1 2 1 8 3 5 2 9 8 0 6 0 9 5 1 9 9 2 1 1 6 0 2 3 0 3 6 9 1 6 5 5 7 1 1 2 1 1 7 5 4 6 6 4 1 1 2 8 4 7 1 6 2 7 7 5 4 3 2 4 3 6 9 4 1 7 1 3 4 1 2 1 3 1 1 4 7 3 1 1 1 1 5 3 2 6 1 5 1 3 5 4 5 2 3 1 1 6 1 7 3 2 5 4 3 1 6 1 5 3 1 7 6 5 1 1 1 4 6 1 6 2 7 2 1 2 e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S HOXB6 homeo box B6 HOXB5 homeo box B5 WNT5A wingless-type MMTV integration site family, member 5A WNT5A wingless-type MMTV integration site family, member 5A FKBP11 FK506 binding protein 11, 19 kDa EPOR erythropoietin receptor SLC5A6 solute carrier family 5 sodium-dependent vitamin transporter, member 6 SLC5A6 solute carrier family 5 sodium-dependent vitamin transporter, member 6 RAD52 RAD52 homolog S. -
Chromatin and Epigenetics Cross-Journal Focus Chromatin and Epigenetics
EMBO Molecular Medicine cross-journal focus Chromatin and epigenetics cross-journal focus Chromatin and epigenetics EDITORS Esther Schnapp Senior Editor [email protected] | T +49 6221 8891 502 Esther joined EMBO reports in October 2008. She was awarded her PhD in 2005 at the Max Planck Institute for Molecular Cell Biology and Genetics in Dresden, Germany, where she studied tail regeneration in the axolotl. As a post-doc she worked on muscle development in zebrafish and on the characterisation of mesoangioblasts at the Stem Cell Research Institute of the San Raffaele Hospital in Milan, Italy. Anne Nielsen Editor [email protected] | T +49 6221 8891 408 Anne received her PhD from Aarhus University in 2008 for work on miRNA processing in Joergen Kjems’ lab. As a postdoc she then went on to join Javier Martinez’ lab at IMBA in Vienna and focused on siRNA-binding proteins and non-conventional splicing in the unfolded protein response. Anne joined The EMBO Journal in 2012. Maria Polychronidou Editor [email protected] | T +49 6221 8891 410 Maria received her PhD from the University of Heidelberg, where she studied the role of nuclear membrane proteins in development and aging. During her post-doctoral work, she focused on the analysis of tissue-specific regulatory functions of Hox transcription factors using a combination of computational and genome-wide methods. Céline Carret Editor [email protected] | T +49 6221 8891 310 Céline Carret completed her PhD at the University of Montpellier, France, characterising host immunodominant antigens to fight babesiosis, a parasitic disease caused by a unicellular EMBO Apicomplexan parasite closely related to the malaria agent Plasmodium. -
Evidence for a Functional Role of Epigenetically Regulated Midcluster HOXB Genes in the Development of Barrett Esophagus
Evidence for a functional role of epigenetically regulated midcluster HOXB genes in the development of Barrett esophagus Massimiliano di Pietroa, Pierre Lao-Sirieixa, Shelagh Boyleb, Andy Cassidyc, Dani Castillod, Amel Saadic, Ragnhild Eskelandb,1, and Rebecca C. Fitzgeralda,2 aMedical Research Council Cancer Cell Unit, Hutchison Medical Research Council Research Centre, CB2 0XZ Cambridge, United Kingdom; bMedical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, EH4 2XU Edinburgh, United Kingdom; cCancer Research United Kingdom, Cambridge Research Institute, Li Ka Shing Centre, CB2 0RE Cambridge, United Kingdom; and dSection of Gastrointestinal Surgery, Hospital Universitari del Mar, Universitat Autónoma de Barcelona, 08003 Barcelona, Spain Edited* by Walter Fred Bodmer, Weatherall Institute of Molecular Medicine, Oxford University, Oxford, United Kingdom, and approved April 18, 2012 (received for review October 17, 2011) Barrett esophagus (BE) is a human metaplastic condition that is the CDXs on their own are sufficient to induce an intestinal pheno- only known precursor to esophageal adenocarcinoma. BE is charac- type in the mouse esophagus. terized by a posterior intestinal-like phenotype in an anterior organ An intestinal-like epithelium in the esophagus is reminiscent of and therefore it is reminiscent of homeotic transformations, which homeotic transformations, which have been linked to mutations of can occur in transgenic animal models during embryonic develop- HOX genes (10). The 39 human HOX genes are divided into four ment as a consequence of mutations in HOX genes. In humans, clusters (HOXA, HOXB, HOXC, and HOXD) and have a collin- acquired deregulation of HOX genes during adulthood has been ear expression during development along the anterior-posterior linked to carcinogenesis; however, little is known about their role (A-P) axis, whereby 3′ end genes are activated earlier and are more in the pathogenesis of premalignant conditions. -
UC San Diego UC San Diego Electronic Theses and Dissertations
UC San Diego UC San Diego Electronic Theses and Dissertations Title Insights from reconstructing cellular networks in transcription, stress, and cancer Permalink https://escholarship.org/uc/item/6s97497m Authors Ke, Eugene Yunghung Ke, Eugene Yunghung Publication Date 2012 Peer reviewed|Thesis/dissertation eScholarship.org Powered by the California Digital Library University of California UNIVERSITY OF CALIFORNIA, SAN DIEGO Insights from Reconstructing Cellular Networks in Transcription, Stress, and Cancer A dissertation submitted in the partial satisfaction of the requirements for the degree Doctor of Philosophy in Bioinformatics and Systems Biology by Eugene Yunghung Ke Committee in charge: Professor Shankar Subramaniam, Chair Professor Inder Verma, Co-Chair Professor Web Cavenee Professor Alexander Hoffmann Professor Bing Ren 2012 The Dissertation of Eugene Yunghung Ke is approved, and it is acceptable in quality and form for the publication on microfilm and electronically ________________________________________________________________ ________________________________________________________________ ________________________________________________________________ ________________________________________________________________ Co-Chair ________________________________________________________________ Chair University of California, San Diego 2012 iii DEDICATION To my parents, Victor and Tai-Lee Ke iv EPIGRAPH [T]here are known knowns; there are things we know we know. We also know there are known unknowns; that is to say we know there -
Integrative Analysis of Single-Cell Genomics Data by Coupled Nonnegative Matrix Factorizations
Integrative analysis of single-cell genomics data by coupled nonnegative matrix factorizations Zhana Durena,b,1, Xi Chena,b,1, Mahdi Zamanighomia,b,c,1, Wanwen Zenga,b,d, Ansuman T. Satpathyc, Howard Y. Changc, Yong Wange,f, and Wing Hung Wonga,b,c,2 aDepartment of Statistics, Stanford University, Stanford, CA 94305; bDepartment of Biomedical Data Science, Stanford University, Stanford, CA 94305; cCenter for Personal Dynamic Regulomes, Stanford University, Stanford, CA 94305; dMinistry of Education Key Laboratory of Bioinformatics, Bioinformatics Division and Center for Synthetic & Systems Biology, Department of Automation, Tsinghua University, 100084 Beijing, China; eAcademy of Mathematics and Systems Science, Chinese Academy of Sciences, 100080 Beijing, China; and fCenter for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, 650223 Kunming, China Contributed by Wing Hung Wong, June 14, 2018 (sent for review April 4, 2018; reviewed by Andrew D. Smith and Nancy R. Zhang) When different types of functional genomics data are generated on Approach single cells from different samples of cells from the same hetero- Coupled NMF. We first introduce our approach in general terms. geneous population, the clustering of cells in the different samples Let O be a p1 by n1 matrix representing data on p1 features for n1 should be coupled. We formulate this “coupled clustering” problem units in the first sample; then a “soft” clustering of the units in as an optimization problem and propose the method of coupled this sample can be obtained from a nonnegative factorization nonnegative matrix factorizations (coupled NMF) for its solution. O = W1H1 as follows: The ith column of W1 gives the mean The method is illustrated by the integrative analysis of single-cell vector for the ith cluster of units, while the jth column of H1 gives RNA-sequencing (RNA-seq) and single-cell ATAC-sequencing (ATAC- the assignment weights of the jth unit to the different clusters. -
Consequences of Hoxb1 Duplication in Teleost Fish
EVOLUTION & DEVELOPMENT 9:6, 540–554 (2007) Consequences of Hoxb1 duplication in teleost fish Imogen A. Hurley,a Jean-Luc Scemama,b and Victoria E. Princea,c,Ã aDepartment of Organismal Biology and Anatomy, The University of Chicago, 1027 East 57th Street, IL 60637, USA bDepartment of Biology, Howell Science Complex, East Carolina University, Greenville, NC 27858, USA cCommittees on Developmental Biology, Neurobiology and Evolutionary Biology, The University of Chicago, 1027 East 57th Street, Chicago, IL 60637, USA ÃAuthor for correspondence (email: [email protected]) SUMMARY Vertebrate evolution is characterized by gene bass. Consistent with this theory, we found that the ancestral and genome duplication events. There is strong evidence that Hoxb1 expression pattern is subdivided between duplicate a whole-genome duplication occurred in the lineage leading to genes in a largely similar fashion in zebrafish, medaka, and the teleost fishes. We have focused on the teleost hoxb1 striped bass. Further, our analysis of hoxb1 genes reveals that duplicate genes as a paradigm to investigate the conse- sequence changes in cis-regulatory regions may underlie sub- quences of gene duplication. Previous analysis of the functionalization in all teleosts, although the specific changes duplicated zebrafish hoxb1 genes suggested they have vary between species. It was previously shown that zebrafish subfunctionalized. The combined expression pattern of the hoxb1 duplicates have also evolved different functional two zebrafish hoxb1 genes recapitulates the expression capacities. We used misexpression to compare the functions pattern of the single Hoxb1 gene of tetrapods, possibly due of hoxb1 duplicates from zebrafish, medaka and striped bass. to degenerative changes in complementary cis-regulatory Unexpectedly, we found that some biochemical properties, elements of the duplicates. -
Increased Expression of Homeobox 5 Predicts Poor Prognosis: a Potential Therapeutic Target for Glioma
Increased expression of homeobox 5 predicts poor prognosis: A potential therapeutic target for glioma Chengran Xu First Aliated Hospital of China Medical University Jinhai Huang First Aliated Hospital of China Medical University Yi Yang First Aliated Hospital of China Medical University Lun Li Anshan Hospital of the First Hospital of China Medical University Guangyu Li ( [email protected] ) First Aliated Hospital of China Medical University Research Article Keywords: HOXB5, glioma, TCGA, CGGA, angiogenesis, IL-6/JAK-STAT3, Immune Inltration Posted Date: April 7th, 2021 DOI: https://doi.org/10.21203/rs.3.rs-376213/v1 License: This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License Page 1/16 Abstract Background: The homeobox gene 5 (HOXB5) encodes a transcription factor that regulates the central nervous system embryonic development. Of note, its expression pattern and prognostic role in glioma remain unelucidated. This study aimed to identify the relationship between HOXB5 and glioma by investigating the HOXB5 expression data from the The Cancer Genome Atlas (TCGA) and The Genotype Tissue Expression (GTEx) databases and validating the obtained data using the Chinese Glioma Genome Atlas (CGGA) database. Kaplan-Meier and univariate cox regression analyses were performed to assess the prognostic value of HOXB5. The key functions and signaling pathways of HOXB5 were analyzed using GSEA and GSVA. Immune inltration was calculated using Microenvironment Cell Populations- counter (MCP-counter), single-sample Gene Set Enrichment Analysis (ssGSEA), and ESTIMATE algorithms. Result: HOXB5 expression was elevated in glioma tissues. The increased levels of HOXB5 were signicantly correlated with a higher WHO grade and aggressive cancer phenotypes. -
Robles JTO Supplemental Digital Content 1
Supplementary Materials An Integrated Prognostic Classifier for Stage I Lung Adenocarcinoma based on mRNA, microRNA and DNA Methylation Biomarkers Ana I. Robles1, Eri Arai2, Ewy A. Mathé1, Hirokazu Okayama1, Aaron Schetter1, Derek Brown1, David Petersen3, Elise D. Bowman1, Rintaro Noro1, Judith A. Welsh1, Daniel C. Edelman3, Holly S. Stevenson3, Yonghong Wang3, Naoto Tsuchiya4, Takashi Kohno4, Vidar Skaug5, Steen Mollerup5, Aage Haugen5, Paul S. Meltzer3, Jun Yokota6, Yae Kanai2 and Curtis C. Harris1 Affiliations: 1Laboratory of Human Carcinogenesis, NCI-CCR, National Institutes of Health, Bethesda, MD 20892, USA. 2Division of Molecular Pathology, National Cancer Center Research Institute, Tokyo 104-0045, Japan. 3Genetics Branch, NCI-CCR, National Institutes of Health, Bethesda, MD 20892, USA. 4Division of Genome Biology, National Cancer Center Research Institute, Tokyo 104-0045, Japan. 5Department of Chemical and Biological Working Environment, National Institute of Occupational Health, NO-0033 Oslo, Norway. 6Genomics and Epigenomics of Cancer Prediction Program, Institute of Predictive and Personalized Medicine of Cancer (IMPPC), 08916 Badalona (Barcelona), Spain. List of Supplementary Materials Supplementary Materials and Methods Fig. S1. Hierarchical clustering of based on CpG sites differentially-methylated in Stage I ADC compared to non-tumor adjacent tissues. Fig. S2. Confirmatory pyrosequencing analysis of DNA methylation at the HOXA9 locus in Stage I ADC from a subset of the NCI microarray cohort. 1 Fig. S3. Methylation Beta-values for HOXA9 probe cg26521404 in Stage I ADC samples from Japan. Fig. S4. Kaplan-Meier analysis of HOXA9 promoter methylation in a published cohort of Stage I lung ADC (J Clin Oncol 2013;31(32):4140-7). Fig. S5. Kaplan-Meier analysis of a combined prognostic biomarker in Stage I lung ADC.