Supplementary Fig. S1

Total Page:16

File Type:pdf, Size:1020Kb

Load more

Supplementary Fig. S1 A All cancers (3.4%) PDAC (17.2%) CRC (1.1%) LAC (2.0%) G12 G12 G12 G12 G13 G13 G13 G13 Q61 Q61 Q61 Q61 84% N117 93% N117 68% N117 89% N117 A146 A146 A146 A146 G12S G12S G12S G12S G12R 17% G12R G12R 21% G12R 31% 28% G12C 35% G12C G12C G12C G12D G12D G12D G12D 42% G12A 43% G12A 44% G12A 13% 52% G12A G12V G12V G12V G12V G0/G1 B C S G2M 50 100 NS si K1 40 75 30 50 20 % cell cycle 25 % apoptotic cells apoptotic % 10 0 0 NS K1 NS K1 NS K1 NS K1 NS K1 NS K1 NS K1 NS K1 NS K1 NS K1 1 C 2 4 1 8 3 0 4 - . C- 8 -T3 K- C 4 3 2 3 0 a0 Ca P SN- P AN2 -1 4 A . -T -1 -8 N 4 5 sP 81 P C a0 I 18 P N K A C TC A P Pa A Hu P ATC4ATC5 P P M 2 8 u S P P AT A P P As a- A H P - P P A CC- CC MI T PaC T G12R Figure S1. KRASG12R is the third most prevalent mutation in PDAC. A, KRAS mutation frequency in PDAC, CRC and LAC. The top row provides the mutational frequency by amino acid position, and the bottom row provides the prevalence of G12 mutations in each cancer. B, Apoptosis assays of siRNA-transfected PDAC cells measured by Annexin V- FITC staining. Data are representative of two independent experiments. C, Cell cycle analyses of siRNA-transfected PDAC cells determined by staining with propidium iodide. At least 104 cells were collected for apoptosis and cell cycle assays, and data are representative of at least two independent experiments. Error bars, mean ± s.e.m. Supplementary Fig. S2 0.5 h 2 h 6 h 24 h A B * 200 ** Vector EV G12D RIE-1 G12V 150 G12R KRASG12D DAPI ; 100 ** KRASG12V * 50 FITC-Dextran *** Macropinocytotic index Macropinocytotic **** * ** KRASG12R 0 0.5 h 2 h 6 h 24 h RIE-1 CF I EV EV G12V G12V G12D G12R G12D G12R RIE-1 HA-KRAS HA-KRAS Vinculin Vinculin NIH 3T3 HPNE-DT Vector D Vector KRASG12D G Vector KRASG12D DAPI DAPI ; ; KRASG12D FITC-Dextran FITC-Dextran KRASG12V KRASG12V KRASG12R KRASG12V KRASG12R E H ** **** 20 30 **** *** 20 10 KRASG12R index 10 index 0 0 Macropinocytotic V V R Macropinocytotic E D 2 2 EV D 2V 2R NIH 3T312 1 1 HPNE-DT 12 1 1 G G G G G G Figure S2. Ectopic expression of KRASG12D and KRASG12V mutants elevate macropinocytosis in model systems. A, Time-dependent measurement of FITC-dextran labeled macropinosomes in KRAS- transformed RIE-1 cells. Macropinosomes, green; nuclei, blue, for the indicatedtime.Assayused 1 ml of 1:20 FITC-dextran/DMEM. B, Quantification of macropinocytosis index. Quantification performed with at least 50 cells per condition, and data are representative of two independent experiments. C, Immunoblot analysis of HA epitope-tagged KRAS expression levels in NIH/3T3 cells. D, FITC-dextran labeled macropinosomes in KRAS-transformed NIH/3T3 cells. E, Quantification of macropinocytotic index. Quantification of macropinocytosis index with at least 50 cells per condition, and data are representative of two independent experiments. F, Immunoblot analysis of HA epitope-tagged KRAS expression levels in HPNE-DT cells. G, FITC- dextran labeled macropinosomes in KRAS-transformed HPNE-DT cells. H, Quantification of macropinocytotic index. Quantification of macropinocytosis index with at least 50 cells per condition, and data are representative of three independent experiments. I, Brightfield microscopy images of RIE-1 cells transfected with KRAS mutants. Scale bar, 100 µm. For all data; ****P<0.0001, ***P<0.0002, **P<0.0021, *P<0.032, p values from Dunnett’s multiple comparison test after one-way ANOVA, comparing all lanes to G12R at each time point. Scale bar is 20 μm, unless otherwise noted. Error bars, mean ± s.e.m. Supplementary Fig. S3 A KRASG12R B HRASG12V HRASG12R (GMPPNP/Mg) SI SI SII T35 SII G12R G12V G12R E62 Q61 C D TM KRASG12R 100 WT: 52.25 C HRASG12R G12D: 57.25 C 80 G12V: 57.75 C G12R: 57.75 C 60 SII SI 40 Normalized G12R mGDP fluorescence 20 0 30 40 50 60 70 80 Temperature (C) Figure S3. KRASG12R structure is unique among G12 mutations. A, Overlay of the ribbon diagrams of KRASG12R (green) and HRASG12V (pink; PDB 3OIW). SI, light blue; SII, red. Stick models of G12V and G12R are shown. GMPPNP is shownwith phosphates colored orange. B, A ribbon diagram of the HRASG12R crystal structure with selected side chains represented as sticks. Carbons in Q61 and E62 are colored red, nitrogen is blue and oxygen light red. T35 carbons colored in light blue. Hydrogen bonds are shown as gray dashed lines. C, Overlay of the ribbon diagrams of HRASG12R (teal) with KRASG12R (green). All other coloring is the same as previous. D, Thermal denaturation of KRAS proteins as measured by mGDP binding. Supplementary Fig. S4 A B D KRAS KRAS E37G RAF RALGEF PI3K Vector G12D G12D/T35S G12D/E37G G12D/Y40C G12V G12V/T35S G12V/E37G G12V/Y40C C HA-KRAS KRAS 35 pERK 30 ERK 20 pAKT AKT 10 Vinculin 0 Macropinocytotic index Macropinocytotic RIE-1 S G C V EV D 7G 0C 37 40 35S 4 T35 T 3 G12 E Y G12 / /E /Y D/ D/ D/ V V V 12 E G12 G12 G12 G12 G G12 KRAS PDK1 mTORC2 PIP3 PI3Kα P P T308 AKT S473 mTORC1 PIP2 P P P P PRAS40 T246MDM2 S166FKHR T24 S6K T421 T389 F KRAS Effector WT G12D G12R CRAF-RBD 61.0 ± 0.53 nM 481 ± 10 nM 499 ± 23 nM RGL2-RA 3.52 ± 0.12 μM 5.28 ± 0.15 μM 4.47 ± 0.11 μM PLCε-RA 0.73 ± 0.04 μM 2.15 ± 0.20 μM 1.96 ± 0.19 μM PI3K 1.85 ± 0.07 μM 1.91 ± 0.20 μM No binding G12R G12R G12V G12V G12D G12D -FBS +FBS Figure S4. KRASG12R does not interact with p110α/p85 in vitro and in RIE-1 cells. A, Immunoblot analysis of RIE-1 cells transfected with HA epitope-tagged KRAS effector-specific mutants. Vinculin was used a total lysate control, and phospho-specific and total AKT and ERK levels were probed. B, A diagram of the expected signaling preference for the KRAS effector-specific mutants. C, Quantification of macropinocytosis in KRAS effector-specific mutants with at least 50 cells per condition, and data are representative of two independent experiments. Error bars, mean ± s.e.m. D, Heatmap of the relative RPPA intensity of 162 proteins in RIE-1 cells ectopically expressing KRAS mutants cultured in the absence or presence of serum. E, KRAS-PI3K effector signaling diagram displaying the expected phosphorylation sites downstream of PI3K activation in cells. F, Table of KRAS WT and mutant protein binding affinities to select effector RBD/RA domains and full length p110α/p85. Values were determined using the inhibition of nucleotide dissociation assay as described. All experiments were performed in triplicate or greater, and the results are the average binding affinity. Supplementary Fig. S5 A B **** NS **** 4.5 M1 si 3.0 M2 1.5 ** ** ** ** ** 1.0 ** ** Normalized 0.5 0.0 2D colony formation colony 2D AsPC-1 Pa04C A818.4 HuP-T3 PSN-1 PK-8 C AsPC-1 Pa04C A818.4 HuP-T3 PSN-1 PK-8 NS DAPI ; M1 siRNA FITC-Dextran M2 G12D G12V G12R Figure S5. KRASG12R cell lines are distinct from nonKRASG12R cell lines. A, Heatmap comparing RPPA protein phosphorylation/expression in KRASG12D and KRASG12R pancreas cancer cell lines under basal conditions. RPPA analysis of over 160 proteins cell lines with a native KRASG12R (6 cell lines, magenta) or non-KRASG12R (7 cell lines, cyan) mutation. B, 2D colony formation of MYC- silenced G12R-mutant PDAC. All cells were siRNA transfected for 48 h and allowed to proliferate for 10 days. Data are an average of four independent experiments. (***P<0.0002, **P<0.0021, *P<0.032, p values from Dunnett’s multiple comparison test after one-way ANOVA, comparing all lanes to NS for each treatment). Error bars, mean ± s.e.m. C,Imagesof FITC-dextran labeled macropinosomes with and without MYC silencing by siRNA. 70-kDa FITC-dextran, green; nuclei, blue. Scale bar, 20 μm. Supplementary Fig. S6 A DMSO Alpelisib IPI-549 Pictilisib B DMSO AsPC-1 30 AZD8186 G12D **** *** 20 * Pa04C G12V 10 0 A818.4 index Macropinocytotic AsPC-1Pa04C MIA A818.4 HuP- PSN-1 PK-8 TCC- PATC PATC G12R PaCa-2 T3 PAN2 43 50 G12R C Hup-T3 G12R PSN-1 G12R PK-8 G12R 5 TCC-PAN2 G12R D 4 3 PATC43 G12R 2 PATC50 Activity area 1 G12R 0 FITC-Dextran; DAPI E Figure S6. KRASG12R-mutant PDAC rely on p110γ for macropinocytosis and are sensitive to MEK/ERK inhibition. A, Images of FITC-dextran labeled macropinosomes of PDAC cell lines treated for 24 h with DMSO, alpelisib (p110α-selective inhibitor, 100 nM), IPI-549 (p110γ-selective inhibitor, 300 nM) or pictilisib (pan-p110 inhibitor, 1.5 µM) for 18 hrs. Images are representative from four independent experiments. B, Quantification of FITC-dextran labeled macropinosomes in PDAC cell lines treated for 18 h with DMSO or AZD8186 alpelisib (p110α/β/δ-selective inhibitor, 1.0 μM). C, Response to selumetinib (AZD6244) measured by IC50 values (in nM) in a pancreas cancer cell line panel.
Recommended publications
  • WO 2018/223101 Al 06 December 2018 (06.12.2018) W !P O PCT

    WO 2018/223101 Al 06 December 2018 (06.12.2018) W !P O PCT

    (12) INTERNATIONAL APPLICATION PUBLISHED UNDER THE PATENT COOPERATION TREATY (PCT) (19) World Intellectual Property Organization International Bureau (10) International Publication Number (43) International Publication Date WO 2018/223101 Al 06 December 2018 (06.12.2018) W !P O PCT (51) International Patent Classification: (71) Applicant: JUNO THERAPEUTICS, INC. [US/US]; 400 A 61K 35/1 7 (20 15.0 1) A 61P 35/00 (2006 .0 1) Dexter Ave. N., Suite 1200, Seattle, WA 98109 (US). (21) International Application Number: (72) Inventor: ALBERTSON, Tina; 400 Dexter Ave. N., Suite PCT/US2018/035755 1200, Seattle, WA 98109 (US). (22) International Filing Date: (74) Agent: AHN, Sejin et al; Morrison & Foerster LLP, 1253 1 0 1 June 2018 (01 .06.2018) High Bluff Drive, Suite 100, San Diego, CA 92130-2040 (US). (25) Filing Language: English (81) Designated States (unless otherwise indicated, for every (26) Publication Language: English kind of national protection available): AE, AG, AL, AM, (30) Priority Data: AO, AT, AU, AZ, BA, BB, BG, BH, BN, BR, BW, BY, BZ, 62/5 14,774 02 June 2017 (02.06.2017) US CA, CH, CL, CN, CO, CR, CU, CZ, DE, DJ, DK, DM, DO, 62/5 15,530 05 June 2017 (05.06.2017) US DZ, EC, EE, EG, ES, FI, GB, GD, GE, GH, GM, GT, HN, 62/521,366 16 June 2017 (16.06.2017) u s HR, HU, ID, IL, IN, IR, IS, JO, JP, KE, KG, KH, KN, KP, 62/527,000 29 June 2017 (29.06.2017) u s KR, KW, KZ, LA, LC, LK, LR, LS, LU, LY, MA, MD, ME, 62/549,938 24 August 2017 (24.08.2017) u s MG, MK, MN, MW, MX, MY, MZ, NA, NG, NI, NO, NZ, 62/580,425 0 1 November 2017 (01 .11.2017) u s OM, PA, PE, PG, PH, PL, PT, QA, RO, RS, RU, RW, SA, 62/593,871 0 1 December 2017 (01 .12.2017) u s SC, SD, SE, SG, SK, SL, SM, ST, SV, SY, TH, TJ, TM, TN, 62/596,764 08 December 2017 (08.12.2017) u s TR, TT, TZ, UA, UG, US, UZ, VC, VN, ZA, ZM, ZW.
  • Toward Personalized Treatment in Waldenström Macroglobulinemia

    Toward Personalized Treatment in Waldenström Macroglobulinemia

    | INDOLENT LYMPHOMA:HOW UNDERSTANDING DISEASE BIOLOGY IS INFLUENCING CLINICAL DECISION-MAKING | Toward personalized treatment in Waldenstrom¨ macroglobulinemia Jorge J. Castillo and Steven P. Treon Bing Center for Waldenstrom¨ Macroglobulinemia, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA Waldenstrom¨ macroglobulinemia (WM) is a rare lymphoma with 1000 to 1500 new patients diagnosed per year in the United States. Patients with WM can experience prolonged survival times, which seem to have increased in the last decade, but relapse is inevitable. The identification of recurrent mutations in the MYD88 and CXCR4 genes has opened avenues of research to better understand and treat patients with WM. These developments are giving way to per- sonalized treatment approaches for these patients, focusing on increasing depth and duration of response alongside lower toxicity rates. In the present document, we review the diagnostic differential, the clinical manifestations, and the pathological and genomic features of patients with WM. We also discuss the safety and efficacy data of alkylating agents, proteasome inhibitors, monoclonal antibodies, and Bruton tyrosine kinase inhibitors in patients with WM. Finally, we propose a genomically driven algorithm for the treatment of WM. The future of therapies for WM appears bright and hopeful, but we should be mindful of the cost-effectiveness and long-term toxicity of novel agents. Diagnostic considerations Learning Objectives The differential diagnosis of WM includes immunoglobulin M (IgM) • To understand recent advances on the biology of Waldenstrom¨ monoclonal gammopathy of undetermined significance; other macroglobulinemia IgM-secreting lymphomas, especially marginal zone lymphoma (MZL); • To review available and investigational agents for the treat- and the rare IgM multiple myeloma (MM).
  • Tanibirumab (CUI C3490677) Add to Cart

    Tanibirumab (CUI C3490677) Add to Cart

    5/17/2018 NCI Metathesaurus Contains Exact Match Begins With Name Code Property Relationship Source ALL Advanced Search NCIm Version: 201706 Version 2.8 (using LexEVS 6.5) Home | NCIt Hierarchy | Sources | Help Suggest changes to this concept Tanibirumab (CUI C3490677) Add to Cart Table of Contents Terms & Properties Synonym Details Relationships By Source Terms & Properties Concept Unique Identifier (CUI): C3490677 NCI Thesaurus Code: C102877 (see NCI Thesaurus info) Semantic Type: Immunologic Factor Semantic Type: Amino Acid, Peptide, or Protein Semantic Type: Pharmacologic Substance NCIt Definition: A fully human monoclonal antibody targeting the vascular endothelial growth factor receptor 2 (VEGFR2), with potential antiangiogenic activity. Upon administration, tanibirumab specifically binds to VEGFR2, thereby preventing the binding of its ligand VEGF. This may result in the inhibition of tumor angiogenesis and a decrease in tumor nutrient supply. VEGFR2 is a pro-angiogenic growth factor receptor tyrosine kinase expressed by endothelial cells, while VEGF is overexpressed in many tumors and is correlated to tumor progression. PDQ Definition: A fully human monoclonal antibody targeting the vascular endothelial growth factor receptor 2 (VEGFR2), with potential antiangiogenic activity. Upon administration, tanibirumab specifically binds to VEGFR2, thereby preventing the binding of its ligand VEGF. This may result in the inhibition of tumor angiogenesis and a decrease in tumor nutrient supply. VEGFR2 is a pro-angiogenic growth factor receptor
  • WO 2017/173206 Al 5 October 2017 (05.10.2017) P O P C T

    WO 2017/173206 Al 5 October 2017 (05.10.2017) P O P C T

    (12) INTERNATIONAL APPLICATION PUBLISHED UNDER THE PATENT COOPERATION TREATY (PCT) (19) World Intellectual Property Organization I International Bureau (10) International Publication Number (43) International Publication Date WO 2017/173206 Al 5 October 2017 (05.10.2017) P O P C T (51) International Patent Classification: CA 94121 (US). HUBBARD, Robert; 7684 Marker Road, A61K 31/52 (2006.01) C07D 473/02 (2006.01) San Diego, CA 92087 (US). MIKOLON, David; 6140 A61K 31/505 (2006.01) C07D 473/26 (2006.01) Calle Empinada, San Diego, CA 92120 (US). RAYMON, A61K 31/519 (2006.01) C07D 473/32 (2006.01) Heather; 3520 Vista de la Orilla, San Diego, CA 921 17 (US). SHI, Tao; 4650 Tarantella Lane, San Diego, CA (21) International Application Number: 92130 (US). TRAN, Tam, M.; 8953 Libra Drive, San PCT/US20 17/025252 Diego, CA 92126 (US). TSUJI, Toshiya; 4171 Donald (22) International Filing Date: Court, San Diego, CA 921 17 (US). WONG, Lilly, L.; 871 3 1 March 2017 (3 1.03.2017) Viva Court, Solana Beach, CA 92075 (US). XU, Suichan; 9650 Deer Trail Place, San Diego, CA 92127 (US). ZHU, (25) Filing Language: English Dan; 4432 Calle Mar De Armonia, San Diego, CA 92130 (26) Publication Language: English (US). (30) Priority Data: (74) Agents: BRUNER, Michael, J. et al; Jones Day, 250 Ve- 62/3 17,412 1 April 2016 (01.04.2016) US sey Street, New York, NY 10281-1047 (US). (71) Applicant: SIGNAL PHARMACEUTICALS, LLC (81) Designated States (unless otherwise indicated, for every [US/US]; 10300 Campus Point Drive, Suite 100, San kind of national protection available): AE, AG, AL, AM, Diego, CA 92121 (US).
  • Physiologically Based Pharmacokinetic Modeling in Regulatory Decision‐Making at the European Medicines Agency

    Physiologically Based Pharmacokinetic Modeling in Regulatory Decision‐Making at the European Medicines Agency

    ARTICLES Physiologically Based Pharmacokinetic Modeling in Regulatory Decision-Making at the European Medicines Agency E Luzon1, K Blake1, S Cole2,3,4, A Nordmark4,5, C Versantvoort3,6 and E Gil Berglund3,5 Physiologically based pharmacokinetic (PBPK) modeling is a valuable tool in drug development and regulatory assessment, as it offers the opportunity to simulate the pharmacokinetics of a compound, with a mechanistic understanding, in a variety of populations and situations. This work reviews the use and impact of such modeling in selected regulatory procedures submitted to the European Medicines Agency (EMA) before the end of 2015, together with its subsequent reflection in public documents relating to the assessment of these procedures. It is apparent that the reference to PBPK modeling in regulatory public documents underrepresents its use. A positive trend over time of the number of PBPK models submitted is shown, and in a number of cases the results of these may impact the decision- making process or lead to recommendations in the product labeling. These results confirm the need for regulatory guidance in this field, which is currently under development by the EMA. Study Highlights WHAT IS THE CURRENT KNOWLEDGE ON THE WHAT THIS STUDY ADDS TO OUR KNOWLEDGE TOPIC? þ This is the first work presenting the situation in the Europe- þ PBPK is a cutting-edge technology that is increasingly being an Union and confirms what was detected by the FDA is a applied to drug development to address various aspects related global trend. to clinical pharmacology. Previous works by the FDA acknowl- HOW THIS MIGHT CHANGE CLINICAL PHARMA- edge its use in regulatory submissions in the US, but so far there COLOGY OR TRANSLATIONAL SCIENCE is no analysis of the European perspective.
  • Drug Name Plate Number Well Location % Inhibition, Screen Axitinib 1 1 20 Gefitinib (ZD1839) 1 2 70 Sorafenib Tosylate 1 3 21 Cr

    Drug Name Plate Number Well Location % Inhibition, Screen Axitinib 1 1 20 Gefitinib (ZD1839) 1 2 70 Sorafenib Tosylate 1 3 21 Cr

    Drug Name Plate Number Well Location % Inhibition, Screen Axitinib 1 1 20 Gefitinib (ZD1839) 1 2 70 Sorafenib Tosylate 1 3 21 Crizotinib (PF-02341066) 1 4 55 Docetaxel 1 5 98 Anastrozole 1 6 25 Cladribine 1 7 23 Methotrexate 1 8 -187 Letrozole 1 9 65 Entecavir Hydrate 1 10 48 Roxadustat (FG-4592) 1 11 19 Imatinib Mesylate (STI571) 1 12 0 Sunitinib Malate 1 13 34 Vismodegib (GDC-0449) 1 14 64 Paclitaxel 1 15 89 Aprepitant 1 16 94 Decitabine 1 17 -79 Bendamustine HCl 1 18 19 Temozolomide 1 19 -111 Nepafenac 1 20 24 Nintedanib (BIBF 1120) 1 21 -43 Lapatinib (GW-572016) Ditosylate 1 22 88 Temsirolimus (CCI-779, NSC 683864) 1 23 96 Belinostat (PXD101) 1 24 46 Capecitabine 1 25 19 Bicalutamide 1 26 83 Dutasteride 1 27 68 Epirubicin HCl 1 28 -59 Tamoxifen 1 29 30 Rufinamide 1 30 96 Afatinib (BIBW2992) 1 31 -54 Lenalidomide (CC-5013) 1 32 19 Vorinostat (SAHA, MK0683) 1 33 38 Rucaparib (AG-014699,PF-01367338) phosphate1 34 14 Lenvatinib (E7080) 1 35 80 Fulvestrant 1 36 76 Melatonin 1 37 15 Etoposide 1 38 -69 Vincristine sulfate 1 39 61 Posaconazole 1 40 97 Bortezomib (PS-341) 1 41 71 Panobinostat (LBH589) 1 42 41 Entinostat (MS-275) 1 43 26 Cabozantinib (XL184, BMS-907351) 1 44 79 Valproic acid sodium salt (Sodium valproate) 1 45 7 Raltitrexed 1 46 39 Bisoprolol fumarate 1 47 -23 Raloxifene HCl 1 48 97 Agomelatine 1 49 35 Prasugrel 1 50 -24 Bosutinib (SKI-606) 1 51 85 Nilotinib (AMN-107) 1 52 99 Enzastaurin (LY317615) 1 53 -12 Everolimus (RAD001) 1 54 94 Regorafenib (BAY 73-4506) 1 55 24 Thalidomide 1 56 40 Tivozanib (AV-951) 1 57 86 Fludarabine
  • Related Kinases (VRK) Bound to Small-Molecule Inhibitors Identifies Different P-Loop Conformations

    Related Kinases (VRK) Bound to Small-Molecule Inhibitors Identifies Different P-Loop Conformations

    Structural characterization of human Vaccinia- Related Kinases (VRK) bound to small-molecule inhibitors identifies different P-loop conformations Rafael M. Couñago1,2*, Charles K. Allerston3, Pavel Savitsky3, Hatylas Azevedo4, Paulo H Godoi1,5, Carrow I. Wells6, Alessandra Mascarello4, Fernando H. de Souza Gama4, Katlin B. Massirer1,2, William J. Zuercher6, Cristiano R.W. Guimarães4 and Opher Gileadi1,3 1. Structural Genomics Consortium, Universidade Estadual de Campinas — UNICAMP, Campinas, SP, Brazil. 2. Centro de Biologia Molecular e Engenharia Genética, Universidade Estadual de Campinas, Campinas, SP, Brazil. 3. Structural Genomics Consortium and Target Discovery Institute, Nuffield Department of Clinical Medicine, University of Oxford, UK. 4. Aché Laboratórios Farmacêuticos SA, Guarulhos, SP, Brazil. 5. Department of Biochemistry and Tissue Biology, Institute of Biology, State University of Campinas, Campinas, Brazil. 6. Structural Genomics Consortium, UNC Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, NC, USA. *Correspondence to Rafael M. Couñago: [email protected] (RMC) Supplementary information 1 SUPPLEMENTARY METHODS PKIS results analyses - hierarchical cluster analysis (HCL) A hierarchical clustering (HCL) analysis was performed to group kinases based on their inhibition patterns across the compounds. The average distance clustering method was employed, using sample tree selection and sample leaf order optimization. The distance metric used was the Pearson correlation and the HCL analysis was performed in the TmeV software 1. SUPPLEMENTARY REFERENCES 1 Saeed, A. I. et al. TM4: a free, open-source system for microarray data management and analysis. BioTechniques 34, 374-378, (2003). SUPPLEMENTARY FIGURES LEGENDS Supplementary Figure S1: Hierarchical clustering analysis of PKIS data. Hierarchical clustering analysis of PKIS data.
  • Sarcoma Metabolomics: Current Horizons and Future Perspectives

    Sarcoma Metabolomics: Current Horizons and Future Perspectives

    cells Review Sarcoma Metabolomics: Current Horizons and Future Perspectives Miguel Esperança-Martins 1,2,3,* , Isabel Fernandes 1,3,4 , Joaquim Soares do Brito 4,5, Daniela Macedo 6, Hugo Vasques 4,7, Teresa Serafim 2, Luís Costa 1,3,4 and Sérgio Dias 2,4 1 Centro Hospitalar Universitário Lisboa Norte, Medical Oncology Department, Hospital Santa Maria, 1649-028 Lisboa, Portugal; [email protected] (I.F.); [email protected] (L.C.) 2 Vascular Biology & Cancer Microenvironment Lab, Instituto de Medicina Molecular João Lobo Antunes, Faculdade de Medicina, Universidade de Lisboa, 1649-028 Lisboa, Portugal; tserafi[email protected] (T.S.); [email protected] (S.D.) 3 Translational Oncobiology Lab, Instituto de Medicina Molecular João Lobo Antunes, Faculdade de Medicina, Universidade de Lisboa, 1649-028 Lisboa, Portugal 4 Faculdade de Medicina, Universidade de Lisboa, 1649-028 Lisboa, Portugal; [email protected] (J.S.d.B.); [email protected] (H.V.) 5 Centro Hospitalar Universitário Lisboa Norte, Orthopedics and Traumatology Department, Hospital Santa Maria, 1649-028 Lisboa, Portugal 6 Medical Oncology Department, Hospital Lusíadas Lisboa, 1500-458 Lisboa, Portugal; [email protected] 7 General Surgery Department, Instituto Português de Oncologia de Lisboa Francisco Gentil, 1099-023 Lisboa, Portugal * Correspondence: [email protected] Abstract: The vast array of metabolic adaptations that cancer cells are capable of assuming, not Citation: Esperança-Martins, M.; only support their biosynthetic activity, but also fulfill their bioenergetic demands and keep their Fernandes, I.; Soares do Brito, J.; intracellular reduction–oxidation (redox) balance. Spotlight has recently been placed on the en- Macedo, D.; Vasques, H.; Serafim, T.; ergy metabolism reprogramming strategies employed by cancer cells to proliferate.
  • Proteasome Inhibitors for the Treatment of Multiple Myeloma

    Proteasome Inhibitors for the Treatment of Multiple Myeloma

    cancers Review Proteasome Inhibitors for the Treatment of Multiple Myeloma Shigeki Ito Hematology & Oncology, Department of Internal Medicine, Iwate Medical University School of Medicine, Yahaba-cho 028-3695, Japan; [email protected]; Tel.: +81-19-613-7111 Received: 27 December 2019; Accepted: 19 January 2020; Published: 22 January 2020 Abstract: Use of proteasome inhibitors (PIs) has been the therapeutic backbone of myeloma treatment over the past decade. Many PIs are being developed and evaluated in the preclinical and clinical setting. The first-in-class PI, bortezomib, was approved by the US food and drug administration in 2003. Carfilzomib is a next-generation PI, which selectively and irreversibly inhibits proteasome enzymatic activities in a dose-dependent manner. Ixazomib was the first oral PI to be developed and has a robust efficacy and favorable safety profile in patients with multiple myeloma. These PIs, together with other agents, including alkylators, immunomodulatory drugs, and monoclonal antibodies, have been incorporated into several regimens. This review summarizes the biological effects and the results of clinical trials investigating PI-based combination regimens and novel investigational inhibitors and discusses the future perspective in the treatment of multiple myeloma. Keywords: multiple myeloma; proteasome inhibitors; bortezomib; carfilzomib; ixazomib 1. Introduction Multiple myeloma (MM) remains an incurable disease. Over the last ten years, the availability of new drugs, such as the proteasome inhibitors (PIs), the immunomodulatory drugs (IMiDs), the monoclonal antibodies (MoAbs), and the histone deacetylase inhibitors, have greatly advanced the treatment and improved the survival of patients with MM [1–3]. Proteasome inhibition has emerged as a crucial therapeutic strategy in the treatment of MM.
  • Efficacy and Safety Results from a Phase 1B/2, Multicenter, Open-Label

    Efficacy and Safety Results from a Phase 1B/2, Multicenter, Open-Label

    Leukemia Research 83 (2019) 106172 Contents lists available at ScienceDirect Leukemia Research journal homepage: www.elsevier.com/locate/leukres Research paper Efficacy and safety results from a phase 1b/2, multicenter, open-label study of oprozomib and dexamethasone in patients with relapsed and/or T refractory multiple myeloma ⁎ Parameswaran Haria, , Claudia E. Paba-Pradab, Peter M. Voorheesc, John Fryed, Yu-Lin Changd, Philippe Moreaue,Jeffrey Zonderf, Ralph Bocciag, Kenneth H. Shainh a Medical College of Wisconsin, Milwaukee, WI, USA b Dana-Farber Cancer Institute, Boston, MA, USA c Levine Cancer Institute, Atrium Health, Charlotte, NC, USA d Onyx Pharmaceuticals, Inc., an Amgen subsidiary, South San Francisco, CA, USA e University Hospital, Nantes, France f Barbara Ann Karmanos Cancer Institute, Detroit, MI, USA g Center for Cancer and Blood Disorders, Bethesda, MD, USA h Moffitt Cancer Center, Tampa, FL, USA ARTICLE INFO ABSTRACT Keywords: Oprozomib is an oral proteasome inhibitor with activity in multiple myeloma (MM). Our phase 1b/2 study Oprozomib examined the safety and efficacy of oprozomib with dexamethasone in patients with relapsed and refractory MM. Oral proteasome inhibitor Oprozomib was administered with a 5/14 or 2/7 schedule with dexamethasone. Phase 1b primary objectives Dexamethasone were to determine the maximum tolerated dose (MTD) and recommended phase 2 dose (RP2D) of oprozomib; Multiple myeloma phase 2 primary objectives were to determine overall response rate (ORR) and safety/tolerability of the RP2D. Maximum tolerated dose Between July 2, 2013, and August 29, 2016, data were available on 65 enrolled patients (5/14 schedule, n = 19; 2/7 schedule, n = 46).
  • Ehealth DSI [Ehdsi V2.2.2-OR] Ehealth DSI – Master Value Set

    Ehealth DSI [Ehdsi V2.2.2-OR] Ehealth DSI – Master Value Set

    MTC eHealth DSI [eHDSI v2.2.2-OR] eHealth DSI – Master Value Set Catalogue Responsible : eHDSI Solution Provider PublishDate : Wed Nov 08 16:16:10 CET 2017 © eHealth DSI eHDSI Solution Provider v2.2.2-OR Wed Nov 08 16:16:10 CET 2017 Page 1 of 490 MTC Table of Contents epSOSActiveIngredient 4 epSOSAdministrativeGender 148 epSOSAdverseEventType 149 epSOSAllergenNoDrugs 150 epSOSBloodGroup 155 epSOSBloodPressure 156 epSOSCodeNoMedication 157 epSOSCodeProb 158 epSOSConfidentiality 159 epSOSCountry 160 epSOSDisplayLabel 167 epSOSDocumentCode 170 epSOSDoseForm 171 epSOSHealthcareProfessionalRoles 184 epSOSIllnessesandDisorders 186 epSOSLanguage 448 epSOSMedicalDevices 458 epSOSNullFavor 461 epSOSPackage 462 © eHealth DSI eHDSI Solution Provider v2.2.2-OR Wed Nov 08 16:16:10 CET 2017 Page 2 of 490 MTC epSOSPersonalRelationship 464 epSOSPregnancyInformation 466 epSOSProcedures 467 epSOSReactionAllergy 470 epSOSResolutionOutcome 472 epSOSRoleClass 473 epSOSRouteofAdministration 474 epSOSSections 477 epSOSSeverity 478 epSOSSocialHistory 479 epSOSStatusCode 480 epSOSSubstitutionCode 481 epSOSTelecomAddress 482 epSOSTimingEvent 483 epSOSUnits 484 epSOSUnknownInformation 487 epSOSVaccine 488 © eHealth DSI eHDSI Solution Provider v2.2.2-OR Wed Nov 08 16:16:10 CET 2017 Page 3 of 490 MTC epSOSActiveIngredient epSOSActiveIngredient Value Set ID 1.3.6.1.4.1.12559.11.10.1.3.1.42.24 TRANSLATIONS Code System ID Code System Version Concept Code Description (FSN) 2.16.840.1.113883.6.73 2017-01 A ALIMENTARY TRACT AND METABOLISM 2.16.840.1.113883.6.73 2017-01
  • Withdrawal Assessment Report for Jenzyl, INN: RIDAFOROLIMUS

    Withdrawal Assessment Report for Jenzyl, INN: RIDAFOROLIMUS

    3 December 2012 EMA/774827/2012 Committee for Medicinal Products for Human Use (CHMP) Withdrawal Assessment report for Jenzyl International non-proprietary name: Ridaforolimus Procedure no EMEA/H/C/2259 Note Assessment report as adopted by the CHMP with all information of a commercially confidential nature deleted. This withdrawal Assessment Report is based on the latest assessment report adopted by the CHMP with all information of a commercially confidential nature deleted. This should be read in conjunction with the “Questions and Answers” document on the withdrawal of the application: the Assessment Report may not include all available information on the product if the CHMP assessment of the latest submitted information was still ongoing at the time of the withdrawal of the application. 7 Westferry Circus ● Canary Wharf ● London E14 4HB ● United Kingdom Telephone +44 (0)20 7418 8400 Facsimile +44 (0)20 7418 8613 E -mail [email protected] Website www.ema.europa.eu An agency of the European Union © European Medicines Agency, 2013. Reproduction is authorised provided the source is acknowledged. 1. RECOMMENDATION Based on the CHMP review of the data and the Applicant’s response to the CHMP LOQ on quality, safety and efficacy, the CHMP considers that the application for Jenzyl, an orphan medicinal product, in the treatment metastatic soft tissue sarcoma or bone sarcoma as maintenance therapy for patients who have completed at least 4 cycles of chemotherapy without evidence of disease progression in adult and paediatric patients aged 13 through 17 years with weight over 100 pounds or 45.4 kilograms). is not approvable since "major objections" still remain, which preclude a recommendation for marketing authorisation at the present time.