Y-Box Binding Protein 1 Is Up-Regulated in Proliferative Breast Cancer and Its Inhibition Deregulates the Cell Cycle
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Figure 2S 4 7 A - C 080125 CSCs 080418 CSCs - + IFN-a 48 h + IFN-a 48 h + IFN-a 72 h 6 + IFN-a 72 h 3 5 MRFI 4 2 3 2 1 1 0 0 MHC I MHC II MICA MICB ULBP-1 ULBP-2 ULBP-3 ULBP-4 MHC I MHC II MICA MICB ULBP-1 ULBP-2 ULBP-3 ULBP-4 7 B 13 080125 FBS - D 080418 FBS - + IFN-a 48 h 12 + IFN-a 48 h + IFN-a 72 h + IFN-a 72 h 6 080125 FBS 11 10 5 9 8 4 7 6 3 MRFI 5 4 2 3 2 1 1 0 0 MHC I MHC II MICA MICB ULBP-1 ULBP-2 ULBP-3 ULBP-4 MHC I MHC II MICA MICB ULBP-1 ULBP-2 ULBP-3 ULBP-4 Molecule Molecule FIGURE 4S FIGURE 5S Panel A Panel B FIGURE 6S A B C D Supplemental Results Table 1S. Modulation by IFN-α of APM in GBM CSC and FBS tumor cell lines. Molecule * Cell line IFN-α‡ HLA β2-m# HLA LMP TAP1 TAP2 class II A A HC§ 2 7 10 080125 CSCs - 1∞ (1) 3 (65) 2 (91) 1 (2) 6 (47) 2 (61) 1 (3) 1 (2) 1 (3) + 2 (81) 11 (80) 13 (99) 1 (3) 8 (88) 4 (91) 1 (2) 1 (3) 2 (68) 080125 FBS - 2 (81) 4 (63) 4 (83) 1 (3) 6 (80) 3 (67) 2 (86) 1 (3) 2 (75) + 2 (99) 14 (90) 7 (97) 5 (75) 7 (100) 6 (98) 2 (90) 1 (4) 3 (87) 080418 CSCs - 2 (51) 1 (1) 1 (3) 2 (47) 2 (83) 2 (54) 1 (4) 1 (2) 1 (3) + 2 (81) 3 (76) 5 (75) 2 (50) 2 (83) 3 (71) 1 (3) 2 (87) 1 (2) 080418 FBS - 1 (3) 3 (70) 2 (88) 1 (4) 3 (87) 2 (76) 1 (3) 1 (3) 1 (2) + 2 (78) 7 (98) 5 (99) 2 (94) 5 (100) 3 (100) 1 (4) 2 (100) 1 (2) 070104 CSCs - 1 (2) 1 (3) 1 (3) 2 (78) 1 (3) 1 (2) 1 (3) 1 (3) 1 (2) + 2 (98) 8 (100) 10 (88) 4 (89) 3 (98) 3 (94) 1 (4) 2 (86) 2 (79) * expression of APM molecules was evaluated by intracellular staining and cytofluorimetric analysis; ‡ cells were treatead or not (+/-) for 72 h with 1000 IU/ml of IFN-α; # β-2 microglobulin; § β-2 microglobulin-free HLA-A heavy chain; ∞ values are indicated as ratio between the mean of fluorescence intensity of cells stained with the selected mAb and that of the negative control; bold values indicate significant MRFI (≥ 2). -
Deregulated Gene Expression Pathways in Myelodysplastic Syndrome Hematopoietic Stem Cells
Leukemia (2010) 24, 756–764 & 2010 Macmillan Publishers Limited All rights reserved 0887-6924/10 $32.00 www.nature.com/leu ORIGINAL ARTICLE Deregulated gene expression pathways in myelodysplastic syndrome hematopoietic stem cells A Pellagatti1, M Cazzola2, A Giagounidis3, J Perry1, L Malcovati2, MG Della Porta2,MJa¨dersten4, S Killick5, A Verma6, CJ Norbury7, E Hellstro¨m-Lindberg4, JS Wainscoat1 and J Boultwood1 1LRF Molecular Haematology Unit, NDCLS, John Radcliffe Hospital, Oxford, UK; 2Department of Hematology Oncology, University of Pavia Medical School, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy; 3Medizinische Klinik II, St Johannes Hospital, Duisburg, Germany; 4Division of Hematology, Department of Medicine, Karolinska Institutet, Stockholm, Sweden; 5Department of Haematology, Royal Bournemouth Hospital, Bournemouth, UK; 6Albert Einstein College of Medicine, Bronx, NY, USA and 7Sir William Dunn School of Pathology, University of Oxford, Oxford, UK To gain insight into the molecular pathogenesis of the the World Health Organization.6,7 Patients with refractory myelodysplastic syndromes (MDS), we performed global gene anemia (RA) with or without ringed sideroblasts, according to expression profiling and pathway analysis on the hemato- poietic stem cells (HSC) of 183 MDS patients as compared with the the French–American–British classification, were subdivided HSC of 17 healthy controls. The most significantly deregulated based on the presence or absence of multilineage dysplasia. In pathways in MDS include interferon signaling, thrombopoietin addition, patients with RA with excess blasts (RAEB) were signaling and the Wnt pathways. Among the most signifi- subdivided into two categories, RAEB1 and RAEB2, based on the cantly deregulated gene pathways in early MDS are immuno- percentage of bone marrow blasts. -
Atlas Antibodies in Breast Cancer Research Table of Contents
ATLAS ANTIBODIES IN BREAST CANCER RESEARCH TABLE OF CONTENTS The Human Protein Atlas, Triple A Polyclonals and PrecisA Monoclonals (4-5) Clinical markers (6) Antibodies used in breast cancer research (7-13) Antibodies against MammaPrint and other gene expression test proteins (14-16) Antibodies identified in the Human Protein Atlas (17-14) Finding cancer biomarkers, as exemplified by RBM3, granulin and anillin (19-22) Co-Development program (23) Contact (24) Page 2 (24) Page 3 (24) The Human Protein Atlas: a map of the Human Proteome The Human Protein Atlas (HPA) is a The Human Protein Atlas consortium cell types. All the IHC images for Swedish-based program initiated in is mainly funded by the Knut and Alice the normal tissue have undergone 2003 with the aim to map all the human Wallenberg Foundation. pathology-based annotation of proteins in cells, tissues and organs expression levels. using integration of various omics The Human Protein Atlas consists of technologies, including antibody- six separate parts, each focusing on References based imaging, mass spectrometry- a particular aspect of the genome- 1. Sjöstedt E, et al. (2020) An atlas of the based proteomics, transcriptomics wide analysis of the human proteins: protein-coding genes in the human, pig, and and systems biology. mouse brain. Science 367(6482) 2. Thul PJ, et al. (2017) A subcellular map of • The Tissue Atlas shows the the human proteome. Science. 356(6340): All the data in the knowledge resource distribution of proteins across all eaal3321 is open access to allow scientists both major tissues and organs in the 3. -
Funkce CDK12 a CDK13 V Regulaci Transkripce Hana Paculová
MASARYKOVA UNIVERZITA PŘÍRODOVĚDECKÁ FAKULTA ÚSTAV BIOCHEMIE Funkce CDK12 a CDK13 v regulaci transkripce Disertační práce Hana Paculová Školitel: Mgr. Jiří Kohoutek, Ph.D Brno 2018 Bibliogra cký záznam Autorka: Mgr. Hana Paculová Prrodovedecáá aaául,a鏈 Maaarkáova unvverv,a Úa,av bvochemve Název práce: Funáce CDK12 a CDK13 v regulacv ,ranaárvpce Studijní program: Bvochemve Studijní obor: Bvochemve Školitel: Mgr. Jvr Kohou,eá鏈 Ph.D Akademický rok: 2017/2018 Po et stran: 89 Klí ová slova: Ckálvn-dependen,n ávnaaa鏈 CDK12鏈 ,ranaárvpce鏈 RNA polkmeraaa II鏈 raáovvna vaječnáů鏈 CHK1 Bibliographic entry Author: Mgr. Hana Paculová Facul,k oa acvence鏈 Maaarká unvverav,k Department of Biochemistry Title oF dissertation: CDK12 and CDK13 aunc,von vn ,ranacrvp,von regula,von Degree programme: Bvochemva,rk Field oF study: Bvochemva,rk Supervisor: Mgr. Jvr Kohou,eá鏈 Ph.D Academic year: 2017/2018 Number oF pages: 89 Keywords: Ckclvn-dependen ávnaae鏈 CDK12鏈 ,ranacrvp,von鏈 RNA polkmeraae II鏈 ovarvan cancer鏈 CHK1 Abstrakt Ckálvn-dependen,n ávnaaa 12 (CDK12) je ,ranaárvpčn ávnaaa鏈 á,erá rd expreav avých clových genů ,m鏈 že aoaaorkluje RNA polkmeraau II v průbehu elongačn aáe ,ranaárvpce. CDK12 je apojena do neáolváa bunečných preceaů鏈 což ahrnuje odpoveď na pošáoen DNA鏈 vývoj a bunečnou dvaerencvacv a aea,rvh mRNA. CDK12 bkla popaána jaáo jeden genů鏈 á,eré jaou čaa,o mu,ovánk v hvgh-grade aerónm ovarválnm áarcvnomu鏈 nvcméne vlvv ,ech,o mu,ac na aunácv CDK12 a jejvch role v áarcvnogenev dopoaud nebkla a,anovena. Zjva,vlv jame鏈 že ve,švna mu,ac CDK12鏈 á,eré bklk naleenk v nádorech鏈 brán vk,voren áomplexu CDK12 a Ckálvnem K a vnhvbuj ávnaaovou aá,vvv,u CDK12. -
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. -
Microrna Pharmacoepigenetics: Posttranscriptional Regulation Mechanisms Behind Variable Drug Disposition and Strategy to Develop More Effective Therapy
1521-009X/44/3/308–319$25.00 http://dx.doi.org/10.1124/dmd.115.067470 DRUG METABOLISM AND DISPOSITION Drug Metab Dispos 44:308–319, March 2016 Copyright ª 2016 by The American Society for Pharmacology and Experimental Therapeutics Minireview MicroRNA Pharmacoepigenetics: Posttranscriptional Regulation Mechanisms behind Variable Drug Disposition and Strategy to Develop More Effective Therapy Ai-Ming Yu, Ye Tian, Mei-Juan Tu, Pui Yan Ho, and Joseph L. Jilek Department of Biochemistry & Molecular Medicine, University of California Davis School of Medicine, Sacramento, California Received September 30, 2015; accepted November 12, 2015 Downloaded from ABSTRACT Knowledge of drug absorption, distribution, metabolism, and excre- we review the advances in miRNA pharmacoepigenetics including tion (ADME) or pharmacokinetics properties is essential for drug the mechanistic actions of miRNAs in the modulation of Phase I and development and safe use of medicine. Varied or altered ADME may II drug-metabolizing enzymes, efflux and uptake transporters, and lead to a loss of efficacy or adverse drug effects. Understanding the xenobiotic receptors or transcription factors after briefly introducing causes of variations in drug disposition and response has proven the characteristics of miRNA-mediated posttranscriptional gene dmd.aspetjournals.org critical for the practice of personalized or precision medicine. The regulation. Consequently, miRNAs may have significant influence rise of noncoding microRNA (miRNA) pharmacoepigenetics and on drug disposition and response. Therefore, research on miRNA pharmacoepigenomics has come with accumulating evidence sup- pharmacoepigenetics shall not only improve mechanistic under- porting the role of miRNAs in the modulation of ADME gene standing of variations in pharmacotherapy but also provide novel expression and then drug disposition and response. -
Profiling Data
Compound Name DiscoveRx Gene Symbol Entrez Gene Percent Compound Symbol Control Concentration (nM) JNK-IN-8 AAK1 AAK1 69 1000 JNK-IN-8 ABL1(E255K)-phosphorylated ABL1 100 1000 JNK-IN-8 ABL1(F317I)-nonphosphorylated ABL1 87 1000 JNK-IN-8 ABL1(F317I)-phosphorylated ABL1 100 1000 JNK-IN-8 ABL1(F317L)-nonphosphorylated ABL1 65 1000 JNK-IN-8 ABL1(F317L)-phosphorylated ABL1 61 1000 JNK-IN-8 ABL1(H396P)-nonphosphorylated ABL1 42 1000 JNK-IN-8 ABL1(H396P)-phosphorylated ABL1 60 1000 JNK-IN-8 ABL1(M351T)-phosphorylated ABL1 81 1000 JNK-IN-8 ABL1(Q252H)-nonphosphorylated ABL1 100 1000 JNK-IN-8 ABL1(Q252H)-phosphorylated ABL1 56 1000 JNK-IN-8 ABL1(T315I)-nonphosphorylated ABL1 100 1000 JNK-IN-8 ABL1(T315I)-phosphorylated ABL1 92 1000 JNK-IN-8 ABL1(Y253F)-phosphorylated ABL1 71 1000 JNK-IN-8 ABL1-nonphosphorylated ABL1 97 1000 JNK-IN-8 ABL1-phosphorylated ABL1 100 1000 JNK-IN-8 ABL2 ABL2 97 1000 JNK-IN-8 ACVR1 ACVR1 100 1000 JNK-IN-8 ACVR1B ACVR1B 88 1000 JNK-IN-8 ACVR2A ACVR2A 100 1000 JNK-IN-8 ACVR2B ACVR2B 100 1000 JNK-IN-8 ACVRL1 ACVRL1 96 1000 JNK-IN-8 ADCK3 CABC1 100 1000 JNK-IN-8 ADCK4 ADCK4 93 1000 JNK-IN-8 AKT1 AKT1 100 1000 JNK-IN-8 AKT2 AKT2 100 1000 JNK-IN-8 AKT3 AKT3 100 1000 JNK-IN-8 ALK ALK 85 1000 JNK-IN-8 AMPK-alpha1 PRKAA1 100 1000 JNK-IN-8 AMPK-alpha2 PRKAA2 84 1000 JNK-IN-8 ANKK1 ANKK1 75 1000 JNK-IN-8 ARK5 NUAK1 100 1000 JNK-IN-8 ASK1 MAP3K5 100 1000 JNK-IN-8 ASK2 MAP3K6 93 1000 JNK-IN-8 AURKA AURKA 100 1000 JNK-IN-8 AURKA AURKA 84 1000 JNK-IN-8 AURKB AURKB 83 1000 JNK-IN-8 AURKB AURKB 96 1000 JNK-IN-8 AURKC AURKC 95 1000 JNK-IN-8 -
Gene Expression Signature–Based Prognostic Risk Score in Patients with Primary Central Nervous System Lymphoma
Published OnlineFirst August 20, 2012; DOI: 10.1158/1078-0432.CCR-12-0596 Clinical Cancer Imaging, Diagnosis, Prognosis Research Gene Expression Signature–Based Prognostic Risk Score in Patients with Primary Central Nervous System Lymphoma Atsushi Kawaguchi1, Yasuo Iwadate2, Yoshihiro Komohara3, Masakazu Sano4, Koji Kajiwara5, Naoki Yajima4, Naoto Tsuchiya4, Jumpei Homma4, Hiroshi Aoki4, Tsutomu Kobayashi4, Yuko Sakai7, Hiroaki Hondoh6, Yukihiko Fujii4, Tatsuyuki Kakuma1, and Ryuya Yamanaka7 Abstract Purpose: Better understanding of the underlying biology of primary central nervous system lymphomas (PCNSL) is critical for the development of early detection strategies, molecular markers, and new therapeutics. This study aimed to define genes associated with survival of patients with PCNSL. Experimental Design: Expression profiling was conducted on 32 PCNSLs. A gene classifier was developed using the random survival forests model. On the basis of this, prognosis prediction score (PPS) using immunohistochemical analysis is also developed and validated in another data set with 43 PCNSLs. Results: We identified 23 genes in which expressions were strongly and consistently related to patient survival. A PPS was developed for overall survival (OS) using a univariate Cox model. Survival analyses using the selected 23-gene classifiers revealed a prognostic value for high-dose methotrexate (HD-MTX) and HD- MTX–containing polychemotherapy regimen–treated patients. Patients predicted to have good outcomes by the PPS showed significantly longer survival than those with poor predicted outcomes (P < 0.0001). PPS using immunohistochemical analysis is also significant in test (P ¼ 0.0004) and validation data set (P ¼ 0.0281). The gene-based predictor was an independent prognostic factor in a multivariate model that included clinical risk stratification (P < 0.0001). -
Application of a MYC Degradation
SCIENCE SIGNALING | RESEARCH ARTICLE CANCER Copyright © 2019 The Authors, some rights reserved; Application of a MYC degradation screen identifies exclusive licensee American Association sensitivity to CDK9 inhibitors in KRAS-mutant for the Advancement of Science. No claim pancreatic cancer to original U.S. Devon R. Blake1, Angelina V. Vaseva2, Richard G. Hodge2, McKenzie P. Kline3, Thomas S. K. Gilbert1,4, Government Works Vikas Tyagi5, Daowei Huang5, Gabrielle C. Whiten5, Jacob E. Larson5, Xiaodong Wang2,5, Kenneth H. Pearce5, Laura E. Herring1,4, Lee M. Graves1,2,4, Stephen V. Frye2,5, Michael J. Emanuele1,2, Adrienne D. Cox1,2,6, Channing J. Der1,2* Stabilization of the MYC oncoprotein by KRAS signaling critically promotes the growth of pancreatic ductal adeno- carcinoma (PDAC). Thus, understanding how MYC protein stability is regulated may lead to effective therapies. Here, we used a previously developed, flow cytometry–based assay that screened a library of >800 protein kinase inhibitors and identified compounds that promoted either the stability or degradation of MYC in a KRAS-mutant PDAC cell line. We validated compounds that stabilized or destabilized MYC and then focused on one compound, Downloaded from UNC10112785, that induced the substantial loss of MYC protein in both two-dimensional (2D) and 3D cell cultures. We determined that this compound is a potent CDK9 inhibitor with a previously uncharacterized scaffold, caused MYC loss through both transcriptional and posttranslational mechanisms, and suppresses PDAC anchorage- dependent and anchorage-independent growth. We discovered that CDK9 enhanced MYC protein stability 62 through a previously unknown, KRAS-independent mechanism involving direct phosphorylation of MYC at Ser . -
Anti-EGFR Monoclonal Antibodies and EGFR Tyrosine Kinase Inhibitors As Combination Therapy for Triple-Negative Breast Cancer
www.impactjournals.com/oncotarget/ Oncotarget, Vol. 7, No. 45 Research Paper Anti-EGFR monoclonal antibodies and EGFR tyrosine kinase inhibitors as combination therapy for triple-negative breast cancer Abderrahim El Guerrab1,2, Mahchid Bamdad2,3, Fabrice Kwiatkowski1, Yves-Jean Bignon1,2,*, Frédérique Penault-Llorca1,2,*, Corinne Aubel1,2 1Centre Jean Perrin - ERTICa-EA4677, BP392, 63011 Clermont-Ferrand Cedex, France 2Clermont Université - Université d’Auvergne - ERTICa-EA4677, Faculté de Médecine, BP38, 63001 Clermont-Ferrand Cedex, France 3Clermont Université - Université d’Auvergne - ERTICa-EA4677, Institut Universitaire de Technologie, Département Génie Biologique, Ensemble Universitaire des Cézeaux, BP86, 63172 Aubière Cedex, France *These authors have contributed equally to this work Correspondence to: Yves-Jean Bignon, email: [email protected] Keywords: triple-negative breast cancer, epidermal growth factor receptor, anti-EGFR targeted therapy, cytotoxicity, cell cycle Received: November 09, 2015 Accepted: August 22, 2016 Published: September 15, 2016 ABSTRACT Triple-negative breast cancer (TNBC) is characterized by overexpression of epidermal growth factor receptor (EGFR) and activation of its downstream signaling pathways. Dual targeting of EGFR using one monoclonal antibody (mAb; cetuximab or panitumumab) and one tyrosine kinase inhibitor (EGFR-TKI; gefitinib or erlotinib) is a potential therapeutic approach. We investigated the effect of these therapies in EGFR-expressing TNBC cell lines that do or do not harbor the main activating mutations of EGFR pathways. Cell lines were sensitive to EGFR-TKIs, whereas mAbs were active only in MDA-MB-468 (EGFR amplification) and SUM-1315 (KRAS and PTEN wild-type) cells. MDA-MB-231 (KRAS mutated) and HCC-1937 (PTEN deletion) cells were resistant to mAbs. -
Teaching an Old Dog New Tricks: Reactivated Developmental Signaling Pathways Regulate ABCB1 and Chemoresistance in Cancer
Lee et al. Cancer Drug Resist 2021;4:424-52 Cancer DOI: 10.20517/cdr.2020.114 Drug Resistance Review Open Access Teaching an old dog new tricks: reactivated developmental signaling pathways regulate ABCB1 and chemoresistance in cancer Wing-Kee Lee, Frank Thévenod Institute for Physiology, Pathophysiology and Toxicology, ZBAF, Witten/Herdecke University, Witten 58453, Germany. Correspondence to: Prof. Wing-Kee Lee, Institute for Physiology, Pathophysiology and Toxicology, Witten/Herdecke University, Stockumer Strasse 12, Witten 58453, Germany. E-mail: [email protected] How to cite this article: Lee WK, Thévenod F. Teaching an old dog new tricks: reactivated developmental signaling pathways regulate ABCB1 and chemoresistance in cancer. Cancer Drug Resist 2021;4:424-52. http://dx.doi.org/10.20517/cdr.2020.114 Received: 11 Dec 2020 First Decision: 27 Jan 2021 Revised: 6 Feb 2021 Accepted: 20 Feb 2021 Available online: 19 Jun 2021 Academic Editor: Godefridus J. Peters Copy Editor: Yue-Yue Zhang Production Editor: Yue-Yue Zhang Abstract Oncogenic multidrug resistance (MDR) is a multifactorial phenotype intimately linked to deregulated expression of detoxification transporters. Drug efflux transporters, particularly the MDR P-glycoprotein ABCB1, represent a central mechanism by which not only chemotherapeutic drugs are extruded or sequestered to prevent drug delivery to their intracellular targets, but also for inhibiting apoptotic cell death cues, such as removal of proapoptotic signals. Several cell populations exhibiting the MDR phenotype co-exist within a tumor, such as cells forming the bulk tumor cell mass, cancer stem cells, and cancer persister cells. The key to regulation of ABCB1 expression is the cellular transcriptional machinery. -
Prognosis Value of RBBP8 Expression in Plasma Cell Myeloma
Cancer Gene Therapy https://doi.org/10.1038/s41417-018-0069-3 ARTICLE Prognosis value of RBBP8 expression in plasma cell myeloma 1 2 3 4 5 1 1 1 Weilong Zhang ● Ying Song ● Xue He ● Xiaoni Liu ● Ye Zhang ● Zuozhen Yang ● Ping Yang ● Jing Wang ● 1 4 3 4 1 Kai Hu ● Weiyou Liu ● Xiuru Zhang ● Xiaoliang Yuan ● Hongmei Jing Received: 30 July 2018 / Revised: 30 October 2018 / Accepted: 2 November 2018 © The Author(s) 2019. This article is published with open access Abstract Plasma cell myeloma (PCM) secretes monoclonal immunoglobulin (Ig) by clonal plasma cells of abnormal proliferation in the bone marrow. As PCM is incurable, it is necessary to find new biomarkers to predict the prognosis and recurrence of PCM. The relationship between cancer and RBBP8 has not been fully studied. The role of RBBP8 in tumorigenesis remains inconsistent. We described the expression of RBBP8 in the gene expression profile of 1930 PCM samples (1878 PCM patients) from seven independent data sets. We analyzed the relationship between RBBP8 and survival prognosis, recurrence, and treatment response in patients with PCM, and the biological significance of RBBP8 in PCM. The gene expression level of RBBP8 was significantly related to the International staging system (ISS) grade of PCM (P = 0.0012). RBBP8 expression in different molecular subtypes was different (P < 2.2e-16). High RBBP8 expression is associated with 1234567890();,: 1234567890();,: poor survival in PCM (P < 0.0001). High expression of RBBP8 indicates that PCM patients are more likely to relapse (P = 0.0078). The biological significance of RBBP8 in PCM is related to the cell cycle (P < 0.05).