Insight Into Bortezomib Focusing on Its Efficacy Against P-Gp-Positive
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Supplementary Materials
Supplementary Materials Identification of Compounds The connectivity map concept (C-Map) is based on gene expression profiles, also known as gene fingerprints, and is used to analyze similar effects of compounds and to find drugs for treating diseases [1]. The gene expression profiles in both the C-Map and the CLUE [2] websites were derived from the treatment of human cells with thousands of drugs. Therefore, the gene expression signatures of interest in any induced or organic cell state could be compared with one another to determine similar mechanisms or reverse signatures of drugs and shRNA. Pattern-matching algorithms were used to score each gene expression profile and provide strength of enrichment through query signatures. The results were ranked by “connectivity score (τ)”; a positive score of a signature denoted a similar effect, whereas a negative score indicated a contrary effect. A τ of 90 indicated that only 10% of all perturbations exhibited strong connectivity to the query [2]. Methodology of perturbagen classes (PCLs) To render the CLUE database relatively easy for users to quickly find the mechanism of action (MOA) of a target drug, codifying the class-level annotation required considerable effort. MOAs were adopted to identify groups of compounds with distinct chemical structures, and genetic perturbagens were grouped on the basis of their belonging to the same 1 gene family or being commonly targeted by the same compounds. Ultimately, CLUE named PCLs for their class-level annotations and further connected these cognate class members according to the results of L1000 connectivity analyses to predict the mechanism [2]. 2 A B 3 C D 4 E 5 Figure S1. -
Proteasome Subunit Beta Type 2 (PSMB2) Rabbit Polyclonal Antibody Product Data
OriGene Technologies, Inc. 9620 Medical Center Drive, Ste 200 Rockville, MD 20850, US Phone: +1-888-267-4436 [email protected] EU: [email protected] CN: [email protected] Product datasheet for TA332716 Proteasome subunit beta type 2 (PSMB2) Rabbit Polyclonal Antibody Product data: Product Type: Primary Antibodies Applications: IF, IHC, WB Recommended Dilution: WB 1:500 - 1:2000, IHC 1:50- 1:200, IF 1:50- 1:200 Reactivity: Human, Mouse, Rat Host: Rabbit Isotype: IgG Clonality: Polyclonal Immunogen: Recombinant protein of human PSMB2 Formulation: Store at -20°C (regular) and -80°C (long term). Avoid freeze / thaw cycles. Buffer: PBS with 0.02% sodium azide, 50% glycerol, pH7.3. Concentration: lot specific Purification: Affinity purification Conjugation: Unconjugated Storage: Store at -20°C as received. Stability: Stable for 12 months from date of receipt. Predicted Protein Size: 201 Gene Name: proteasome subunit beta 2 Database Link: NP_002785 Entrez Gene 26445 MouseEntrez Gene 29675 RatEntrez Gene 5690 Human P49721 This product is to be used for laboratory only. Not for diagnostic or therapeutic use. View online » ©2021 OriGene Technologies, Inc., 9620 Medical Center Drive, Ste 200, Rockville, MD 20850, US 1 / 3 Proteasome subunit beta type 2 (PSMB2) Rabbit Polyclonal Antibody – TA332716 Background: The proteasome is a multicatalytic proteinase complex with a highly ordered ring-shaped 20S core structure. The core structure is composed of 4 rings of 28 non-identical subunits; 2 rings are composed of 7 alpha subunits and 2 rings are composed of 7 beta subunits. Proteasomes are distributed throughout eukaryotic cells at a high concentration and cleave peptides in an ATP/ubiquitin-dependent process in a non-lysosomal pathway. -
TEAD4 Ensures Postimplantation Development by Promoting Trophoblast Self-Renewal: an Implication in Early Human Pregnancy Loss
TEAD4 ensures postimplantation development by promoting trophoblast self-renewal: An implication in early human pregnancy loss Biswarup Sahaa,1,2, Avishek Gangulya,1, Pratik Homea,b, Bhaswati Bhattacharyaa, Soma Raya, Ananya Ghosha, M. A. Karim Rumia,b, Courtney Marshb,c, Valerie A. Frenchc, Sumedha Gunewardenad, and Soumen Paula,b,c,3 aDepartment of Pathology and Laboratory Medicine, University of Kansas Medical Center, Kansas City, KS 66160; bInstitute for Reproduction and Perinatal Research, University of Kansas Medical Center, Kansas City, KS 66160; cDepartment of Obstetrics and Gynecology, University of Kansas Medical Center, Kansas City, KS 66160; and dDepartment of Molecular and Integrative Physiology, University of Kansas Medical Center, Kansas City, KS 66160 Edited by R. Michael Roberts, University of Missouri, Columbia, MO, and approved June 22, 2020 (received for review February 12, 2020) Early pregnancy loss affects ∼15% of all implantation-confirmed Studies in mutant mouse models showed that failure in pla- human conceptions. However, evolutionarily conserved molecular centation often leads to in utero embryonic death (6, 7). Therefore, mechanisms that regulate self-renewal of trophoblast progenitors impaired placentation due to defective development or function of and their association with early pregnancy loss are poorly under- trophoblast cell lineages is considered one of the major underlying stood. Here, we provide evidence that transcription factor TEAD4 causes of early pregnancy loss. Disruptions of trophoblast pro- ensures survival of postimplantation mouse and human embryos genitor differentiation and defective placentation have also been by controlling self-renewal and stemness of trophoblast progeni- implicated as probable causes of pregnancy-associated compli- tors within the placenta primordium. -
Targeting Cyclin-Dependent Kinase 9 and Myeloid Cell Leukaemia 1 in MYC-Driven B-Cell Lymphoma
Targeting cyclin-dependent kinase 9 and myeloid cell leukaemia 1 in MYC-driven B-cell lymphoma Gareth Peter Gregory ORCID ID: 0000-0002-4170-0682 Thesis for Doctor of Philosophy September 2016 Sir Peter MacCallum Department of Oncology The University of Melbourne Doctor of Philosophy Submitted in total fulfilment of the degree of Abstract Aggressive B-cell lymphomas include diffuse large B-cell lymphoma, Burkitt lymphoma and intermediate forms. Despite high response rates to conventional immuno-chemotherapeutic approaches, an unmet need for novel therapeutic by resistance to chemotherapy and radiotherapy. The proto-oncogene MYC is strategies is required in the setting of relapsed and refractory disease, typified frequently dysregulated in the aggressive B-cell lymphomas, however, it has proven an elusive direct therapeutic target. MYC-dysregulated disease maintains a ‘transcriptionally-addicted’ state, whereby perturbation of A significant body of evidence is accumulating to suggest that RNA polymerase II activity may indirectly antagonise MYC activity. Furthermore, very recent studies implicate anti-apoptotic myeloid cell leukaemia 1 (MCL-1) as a critical survival determinant of MYC-driven lymphoma. This thesis utilises pharmacologic and genetic techniques in MYC-driven models of aggressive B-cell lymphoma to demonstrate that cyclin-dependent kinase 9 (CDK9) and MCL-1 are oncogenic dependencies of this subset of disease. The cyclin-dependent kinase inhibitor, dinaciclib, and more selective CDK9 inhibitors downregulation of MCL1 are used -
Functional Gene Clusters in Global Pathogenesis of Clear Cell Carcinoma of the Ovary Discovered by Integrated Analysis of Transcriptomes
International Journal of Environmental Research and Public Health Article Functional Gene Clusters in Global Pathogenesis of Clear Cell Carcinoma of the Ovary Discovered by Integrated Analysis of Transcriptomes Yueh-Han Hsu 1,2, Peng-Hui Wang 1,2,3,4,5 and Chia-Ming Chang 1,2,* 1 Department of Obstetrics and Gynecology, Taipei Veterans General Hospital, Taipei 112, Taiwan; [email protected] (Y.-H.H.); [email protected] (P.-H.W.) 2 School of Medicine, National Yang-Ming University, Taipei 112, Taiwan 3 Institute of Clinical Medicine, National Yang-Ming University, Taipei 112, Taiwan 4 Department of Medical Research, China Medical University Hospital, Taichung 440, Taiwan 5 Female Cancer Foundation, Taipei 104, Taiwan * Correspondence: [email protected]; Tel.: +886-2-2875-7826; Fax: +886-2-5570-2788 Received: 27 April 2020; Accepted: 31 May 2020; Published: 2 June 2020 Abstract: Clear cell carcinoma of the ovary (ovarian clear cell carcinoma (OCCC)) is one epithelial ovarian carcinoma that is known to have a poor prognosis and a tendency for being refractory to treatment due to unclear pathogenesis. Published investigations of OCCC have mainly focused only on individual genes and lack of systematic integrated research to analyze the pathogenesis of OCCC in a genome-wide perspective. Thus, we conducted an integrated analysis using transcriptome datasets from a public domain database to determine genes that may be implicated in the pathogenesis involved in OCCC carcinogenesis. We used the data obtained from the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO) DataSets. We found six interactive functional gene clusters in the pathogenesis network of OCCC, including ribosomal protein, eukaryotic translation initiation factors, lactate, prostaglandin, proteasome, and insulin-like growth factor. -
Cyclin A1 Rabbit Pab
Leader in Biomolecular Solutions for Life Science Cyclin A1 Rabbit pAb Catalog No.: A14529 Basic Information Background Catalog No. The protein encoded by this gene belongs to the highly conserved cyclin family, whose A14529 members are characterized by a dramatic periodicity in protein abundance through the cell cycle. Cyclins function as regulators of CDK kinases. Different cyclins exhibit distinct Observed MW expression and degradation patterns which contribute to the temporal coordination of 52kDa each mitotic event. The cyclin encoded by this gene was shown to be expressed in testis and brain, as well as in several leukemic cell lines, and is thought to primarily function in Calculated MW the control of the germline meiotic cell cycle. This cyclin binds both CDK2 and CDC2 47kDa/52kDa kinases, which give two distinct kinase activities, one appearing in S phase, the other in G2, and thus regulate separate functions in cell cycle. This cyclin was found to bind to Category important cell cycle regulators, such as Rb family proteins, transcription factor E2F-1, and the p21 family proteins. Multiple transcript variants encoding different isoforms Primary antibody have been found for this gene. Applications WB Cross-Reactivity Mouse, Rat Recommended Dilutions Immunogen Information WB 1:500 - 1:2000 Gene ID Swiss Prot 8900 P78396 Immunogen A synthetic peptide corresponding to a sequence within amino acids 350-450 of human CCNA1 (NP_001104515.1). Synonyms CCNA1;CT146;cyclin-A1 Contact Product Information www.abclonal.com Source Isotype Purification Rabbit IgG Affinity purification Storage Store at -20℃. Avoid freeze / thaw cycles. Buffer: PBS with 0.02% sodium azide,50% glycerol,pH7.3. -
Correction1 4784..4785
Correction Correction: PCI-24781 Induces Caspase and Reactive Oxygen Species-Dependent Apoptosis In the article on PCI-24781 induces caspase and reactive oxygen species-dependent apoptosis published in the May 15, 2009 issue of Clinical Cancer Research, there was an error in Table 1. Down-regulated genes were incorrectly labeled as up-regulated genes. The correct table appears here. Bhalla S, Balasubramanian S, David K, et al. PCI-24781 induces caspase and reactive oxygen species-dependent apoptosis through NF-nB mechanisms and is synergistic with bortezomib in lymphoma cells. Clin Cancer Res 2009;15:3354–65. Table 1. Selected genes from expression analysis following 24-h treatment with PCI-24781, bortezomib, or the combination (in Ramos cells) Accn # Down-regulated genes 0.25 Mmol/L PCI/3 nmol/L Bor Name PCI-24781 Bortezomib Combination* Cell cycle-related NM_000075 Cyclin-dependent kinase 4 (CDK4) 0.49 0.83 0.37 NM_001237 Cyclin A2 (CCNA2) 0.43 0.87 0.37 NM_001950 E2F transcription factor 4, p107/p130-binding (E2F4) 0.48 0.79 0.40 NM_001951 E2F transcription factor 5, p130-binding (E2F5) 0.46 0.98 0.43 NM_003903 CDC16 cell division cycle 16 homolog (S cerevisiae) (CDC16) 0.61 0.78 0.43 NM_031966 Cyclin B1 (CCNB1) 0.55 0.90 0.43 NM_001760 Cyclin D3 (CCND3) 0.48 1.02 0.46 NM_001255 CDC20 cell division cycle 20 homolog (S cerevisiae; CDC20) 0.61 0.82 0.46 NM_001262 Cyclin-dependent kinase inhibitor 2C (p18, inhibits CDK4; CDKN2C) 0.61 1.15 0.56 NM_001238 Cyclin E1 (CCNE1) 0.56 1.05 0.60 NM_001239 Cyclin H (CCNH) 0.74 0.90 0.64 NM_004701 -
Genome-Wide Transcript and Protein Analysis Reveals Distinct Features of Aging in the Mouse Heart
bioRxiv preprint doi: https://doi.org/10.1101/2020.08.28.272260; this version posted April 21, 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. Genome-wide transcript and protein analysis reveals distinct features of aging in the mouse heart Isabela Gerdes Gyuricza1, Joel M. Chick2, Gregory R. Keele1, Andrew G. Deighan1, Steven C. Munger1, Ron Korstanje1, Steven P. Gygi3, Gary A. Churchill1 1The Jackson Laboratory, Bar Harbor, Maine 04609 USA; 2Vividion Therapeutics, San Diego, California 92121, USA; 3Harvard Medical School, Boston, Massachusetts 02115, USA Corresponding author: [email protected] Key words for online indexing: Heart Aging Transcriptomics Proteomics eQTL pQTL Stoichiometry ABSTRACT Investigation of the molecular mechanisms of aging in the human heart is challenging due to confounding factors, such as diet and medications, as well limited access to tissues. The laboratory mouse provides an ideal model to study aging in healthy individuals in a controlled environment. However, previous mouse studies have examined only a narrow range of the genetic variation that shapes individual differences during aging. Here, we analyzed transcriptome and proteome data from hearts of genetically diverse mice at ages 6, 12 and 18 months to characterize molecular changes that occur in the aging heart. Transcripts and proteins reveal distinct biological processes that are altered through the course of natural aging. Transcriptome analysis reveals a scenario of cardiac hypertrophy, fibrosis, and reemergence of fetal gene expression patterns. -
Immuno-Oncology Panel 4 (Direct-MRM MS, Pending)
Immuno-Oncology panel 4 (direct-MRM MS, pending) (397 analytes pending validation) Gene Symbol Target protein name UniProt ID (& link) Modification* *blanks mean the assay detects the ABCE1 ATP-binding cassette sub-family E member 1 P61221 non-modified peptide sequence ABCE1 ATP-binding cassette sub-family E member 1 P61221 ABI1 Abl interactor 1 Q8IZP0 ABI1 Abl interactor 1 Q8IZP0 AKT1 RAC-alpha serine/threonine-protein kinase P31749 AKT1 RAC-alpha serine/threonine-protein kinase P31749 ANXA1 Annexin A1 P04083 ANXA4 annexin A4 P09525 ANXA5 Annexin A5 P08758 ANXA5 Annexin A5 P08758 ANXA6 annexin A6 P08133 B2M Beta-2-microglobulin P61769 B2M Beta-2-microglobulin P61769 BCAP31 B-cell receptor-associated protein 31 P51572 BCAP31 B-cell receptor-associated protein 31 P51572 BCL2 Apoptosis regulator Bcl-2 P10415 BCL2L1 Bcl-2-like protein 1 Q07817 BCL2L11 Bcl-2-like protein 11 O43521 BCL2L11 Bcl-2-like protein 11 O43521 BCL2L2 Bcl-2-like protein 2 Q92843 BCL2L2 Bcl-2-like protein 2 Q92843 BCL3 B-cell lymphoma 3 protein P20749 BCL3 B-cell lymphoma 3 protein P20749 BID BH3-interacting domain death agonist P55957 BID BH3-interacting domain death agonist P55957 BNIP3L BCL2/adenovirus E1B 19 kDa protein-interacting protein 3-like O60238 BNIP3L BCL2/adenovirus E1B 19 kDa protein-interacting protein 3-like O60238 BPGM Bisphosphoglycerate mutase P07738 BPGM Bisphosphoglycerate mutase P07738 BST2 Bone marrow stromal antigen 2 Q10589 BST2 Bone marrow stromal antigen 2 Q10589 C1QA Complement C1q subcomponent subunit A P02745 C1QA Complement C1q subcomponent -
Supplementary Table 2
Supplementary Table 2. Differentially Expressed Genes following Sham treatment relative to Untreated Controls Fold Change Accession Name Symbol 3 h 12 h NM_013121 CD28 antigen Cd28 12.82 BG665360 FMS-like tyrosine kinase 1 Flt1 9.63 NM_012701 Adrenergic receptor, beta 1 Adrb1 8.24 0.46 U20796 Nuclear receptor subfamily 1, group D, member 2 Nr1d2 7.22 NM_017116 Calpain 2 Capn2 6.41 BE097282 Guanine nucleotide binding protein, alpha 12 Gna12 6.21 NM_053328 Basic helix-loop-helix domain containing, class B2 Bhlhb2 5.79 NM_053831 Guanylate cyclase 2f Gucy2f 5.71 AW251703 Tumor necrosis factor receptor superfamily, member 12a Tnfrsf12a 5.57 NM_021691 Twist homolog 2 (Drosophila) Twist2 5.42 NM_133550 Fc receptor, IgE, low affinity II, alpha polypeptide Fcer2a 4.93 NM_031120 Signal sequence receptor, gamma Ssr3 4.84 NM_053544 Secreted frizzled-related protein 4 Sfrp4 4.73 NM_053910 Pleckstrin homology, Sec7 and coiled/coil domains 1 Pscd1 4.69 BE113233 Suppressor of cytokine signaling 2 Socs2 4.68 NM_053949 Potassium voltage-gated channel, subfamily H (eag- Kcnh2 4.60 related), member 2 NM_017305 Glutamate cysteine ligase, modifier subunit Gclm 4.59 NM_017309 Protein phospatase 3, regulatory subunit B, alpha Ppp3r1 4.54 isoform,type 1 NM_012765 5-hydroxytryptamine (serotonin) receptor 2C Htr2c 4.46 NM_017218 V-erb-b2 erythroblastic leukemia viral oncogene homolog Erbb3 4.42 3 (avian) AW918369 Zinc finger protein 191 Zfp191 4.38 NM_031034 Guanine nucleotide binding protein, alpha 12 Gna12 4.38 NM_017020 Interleukin 6 receptor Il6r 4.37 AJ002942 -
Focus on Prostate Cancer
International Journal of Molecular Sciences Article Integrated Analysis to Study the Relationship between Tumor-Associated Selenoproteins: Focus on Prostate Cancer , Francesca Capone y, Andrea Polo y, Angela Sorice y, Alfredo Budillon * z , and Susan Costantini * z Unità di Farmacologia Sperimentale-Laboratori di Mercogliano, Istituto Nazionale Tumori “Fondazione G. Pascale”—IRCCS, 80131 Napoli, Italy; [email protected] (F.C.); [email protected] (A.P.); [email protected] (A.S.) * Correspondence: [email protected] (A.B.); [email protected] (S.C.); Tel.: +39-081-590-3292 (A.B.); +39-0825-191-1729 (S.C.) Capone F., Polo A. and Sorice A. contributed equally to this work. y Budillon A. and Costantini S. are co-senior authors of this article. z Received: 31 July 2020; Accepted: 11 September 2020; Published: 13 September 2020 Abstract: Selenoproteins are proteins that contain selenium within selenocysteine residues. To date, twenty-five mammalian selenoproteins have been identified; however, the functions of nearly half of these selenoproteins are unknown. Although alterations in selenoprotein expression and function have been suggested to play a role in cancer development and progression, few detailed studies have been carried out in this field. Network analyses and data mining of publicly available datasets on gene expression levels in different cancers, and the correlations with patient outcome, represent important tools to study the correlation between selenoproteins and other proteins present in the human interactome, and to determine whether altered selenoprotein expression is cancer type-specific, and/or correlated with cancer patient prognosis. Therefore, in the present study, we used bioinformatics approaches to (i) build up the network of interactions between twenty-five selenoproteins and identify the most inter-correlated proteins/genes, which are named HUB nodes; and (ii) analyze the correlation between selenoprotein gene expression and patient outcome in ten solid tumors. -
Cyclin-Dependent Kinase Control of Motile Ciliogenesis
RESEARCH ARTICLE Cyclin-dependent kinase control of motile ciliogenesis Eszter K Vladar1,2,3*, Miranda B Stratton4, Maxwell L Saal2,3, Glicella Salazar-De Simone5, Xiangyuan Wang6, Debra Wolgemuth6, Tim Stearns4,7, Jeffrey D Axelrod1 1Department of Pathology, Stanford University School of Medicine, Stanford, United States; 2Division of Pulmonary Sciences and Critical Care Medicine, Department of Medicine, University of Colorado School of Medicine, Aurora, United States; 3Department of Cell and Developmental Biology, University of Colorado School of Medicine, Aurora, United States; 4Department of Biology, Stanford University, Stanford, United States; 5Center for Radiological Research, Columbia University Medical Center, New York, United States; 6Department of Genetics & Development, Columbia University Medical Center, New York, United States; 7Department of Genetics, Stanford University School of Medicine, Stanford, United States Abstract Cycling cells maintain centriole number at precisely two per cell in part by limiting their duplication to S phase under the control of the cell cycle machinery. In contrast, postmitotic multiciliated cells (MCCs) uncouple centriole assembly from cell cycle progression and produce hundreds of centrioles in the absence of DNA replication to serve as basal bodies for motile cilia. Although some cell cycle regulators have previously been implicated in motile ciliogenesis, how the cell cycle machinery is employed to amplify centrioles is unclear. We use transgenic mice and primary airway epithelial cell culture to show that Cdk2, the kinase responsible for the G1 to S phase transition, is also required in MCCs to initiate motile ciliogenesis. While Cdk2 is coupled with cyclins E and A2 during cell division, cyclin A1 is required during ciliogenesis, contributing to an *For correspondence: alternative regulatory landscape that facilitates centriole amplification without DNA replication.