DOCSLIB.ORG

Supplementary Table 1 Mean Viability Values for Each Cell Line for Each Compound Tested in the Small Molecule Screen

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Supplementary Table 1 Mean Viability Values for Each Cell Line for Each Compound Tested in the Small Molecule Screen Supplementary Table 1 Mean viability values for each cell line for each compound tested in the small molecule screen. A value of "1" represents a hypothetical, perfectly flat line (no effect). Drug GTL-16 GTL-16_A GTL-16_B GTL-16_C GTL-16_D GTL-16_E GTL-16_F GTL-16_G GTL-16_H GTL-16_I GTL-16_J GTL-16_K (S)-Citalopram Oxalate 0.94311374 0.98629332 0.95815778 0.9297682 0.94129628 0.97543865 0.92876703 0.94308692 0.97087634 0.92498189 1.03652668 2-Ethyl-2-thiopseudourea, HBr 0.9926737 1.02483487 1.04627788 1.01238942 1.01124644 0.99179834 1.03981841 1.03206468 1.07888484 0.95669609 1.03375137 1.00257194 2-methoxyestradiol 0.95743567 1.02442777 0.96874416 0.95701057 0.96000141 0.9319331 0.96175575 0.98632097 0.97543859 1.07065523 0.9810608 1.00528908 3-Isobutyl-1-methyl-xanthine 1.07753563 0.90621853 0.91486669 0.88967401 1.00929224 0.87712008 0.86304086 0.84795183 0.8218478 0.80844665 0.86385089 0.88111275 5-FU 0.5692879 0.58485568 0.59111845 0.66370136 0.60502565 0.52588075 0.61204398 0.55819142 0.57166713 0.44119668 0.61203408 0.61352444 6-aminonicotinimide 0.67580861 0.74962443 0.74297309 0.78548056 0.69875711 0.76253933 0.72148764 0.75038254 0.72102743 0.74534333 0.77091813 A-1331852 0.93531603 0.90417945 0.94313675 0.92505068 0.94545311 0.96834266 0.88789237 0.93844146 0.94623333 0.95265883 0.84359944 0.98073947 a-cyano-4-OH-cinnamate (CHCA) 0.9952172 0.98906165 0.99838293 1.01442099 0.99624294 1 0.98471749 1.0049547 1.02723098 0.9742409 0.9819023 1.0257504 A922500 0.87694919 0.97097522 0.94563395 0.96351612 0.90027344 0.97543859 0.95685369 0.99162376 0.97543859 0.99552864 0.97768879 0.90608144 ABT-199 1.16429579 1.08221138 1.0141027 0.99331677 1.10464954 1.02660263 1.04603684 1.02137256 1.02593267 0.99139178 1.0738945 1.0436343 ABT737 0.91664159 0.9923889 1.05407965 0.9700942 0.89283508 1.00871408 0.93230343 0.98689145 1.0286752 0.96533024 0.94891477 1.04316843 acetylsalicylic acid 1.01659238 0.9979338 0.94857973 1.01929474 1 0.96629065 0.97594625 0.96813035 0.99379772 0.94024408 1.0001055 1.01547849 Alitretinoin 0.98869127 1.03639805 0.97551936 0.97847396 0.98871243 0.95675898 0.96696025 0.95001709 0.9840253 1.06605625 0.97239363 1.04783285 Altace 0.87073982 1.03982008 0.99782932 0.96493018 0.84670079 0.94735545 0.96060789 0.97058862 0.99526423 1.06157458 0.98981637 0.96154916 Anagrelide HCI 1.05837071 1.07910013 1.0464623 1.05003238 1.09089124 1.08650148 1.03727293 1.03105056 1.06632137 1.05114949 1.0688504 Anastrazole 0.99115813 1.04960859 0.99801701 0.94947243 1.0236882 0.96336734 1.02696466 0.99695414 0.97759819 0.9885264 0.9747808 1.0182724 Antimycin A 0.76865405 0.73035717 0.65301722 0.7834608 0.78227186 0.72338969 0.69951057 0.74505854 0.71001744 0.72835344 0.7763648 Apocynin 0.97543859 0.99232286 1.00482845 1.0018357 0.98933357 0.98961926 0.96391517 0.99102676 0.96731085 1.028561 0.98263758 0.97668135 Atorvastatin 0.84320343 0.88637364 0.85761011 0.88786685 0.92744112 0.89492053 0.8989476 0.86354041 0.91969699 0.86774677 0.93828964 Azacitidine 0.68160683 0.76850802 0.78691721 0.73743463 0.7508415 0.92645198 0.88798296 0.80494529 0.85260504 0.78941232 0.78597897 0.80580533 AZD1480 1.05516684 0.5808388 0.5708518 0.59790021 0.97274268 0.84303343 0.63504857 0.54799163 0.56712043 0.63054359 0.57492965 0.52439815 AZD5363 1.03660142 1.03264475 0.97480762 1.02342236 1.02716827 0.97283322 1.05016696 0.98566836 0.9744758 0.98173034 1.01834416 1.02222073 BAY 11-7821 0.83367866 0.82742381 0.8398239 0.75691718 0.79982984 0.76694465 0.76502866 0.76191229 0.76876932 0.79342228 0.82935077 0.84060133 Bay 11-7085 0.90183669 0.9032231 0.85297155 0.83557886 0.85814548 0.80442488 0.85277754 0.9507314 0.87015092 0.81668991 0.95939302 0.8565433 Belinostat 0.58585119 0.58984524 0.55198771 0.62311172 0.53826171 0.64547908 0.61591887 0.51412266 0.53659713 0.56087005 0.5439077 0.51004094 Benzofibrate 0.97543865 0.95768976 0.90309739 0.99303764 1.03130925 0.9988544 0.91316086 1.00974655 0.96932709 0.99157763 1.03401732 BI-D1870 1.00653481 1.06455576 1.08639479 1.03054297 0.95142496 1.08527851 1.04516876 1.05362809 1.04241431 0.97729003 1.072649 1.08245933 Bicalutamide 1.04075134 0.94048578 0.96631384 0.96081638 1.0026921 0.89953828 0.95612019 0.9370026 0.98999798 0.91997677 0.97406381 0.94326419 BIRB-796 0.9406845 0.88510805 0.86352462 0.88639754 1.03746033 0.88337725 0.89192021 0.852557 0.80451751 0.85053211 0.88485157 0.85409266 Bisindolylmaleimide I 0.79447883 0.77071041 0.78634983 0.75654894 0.70693886 0.68097818 0.89997333 0.85750604 0.80822361 0.75806242 0.73403537 0.75910336 BMS753 1.14387619 0.99524611 1.00422919 0.98119253 1.03567636 0.95755398 1.02452695 0.96526581 1.03066874 0.95993036 0.98410887 0.97190255 Bortezomib 0.42598787 0.36504528 0.54794055 0.48919612 0.41261989 0.50286382 0.49576858 0.47062629 0.50904244 0.52536148 0.52086037 0.48605648 Bosutinib 0.78732622 0.74653077 0.74716896 0.78953677 0.68061101 0.60852605 0.76187694 0.80148232 0.73061305 0.7210055 0.78231984 0.73420972 Brefeldin A 0.69975811 0.77177715 0.81760871 0.8136391 0.7243371 0.77431703 0.77843982 0.76636004 0.79764473 0.79391062 0.7757051 0.7513957 Bromopyruvic acid 1.01441431 1.02288449 0.97543859 1.00099742 1.01936913 0.99015832 0.97260034 1.03007793 0.98447269 1.01628029 0.98209924 1.01655972 BV6 0.95070201 0.80581135 0.79456836 0.76522732 0.89405626 0.72117794 0.81000656 0.78144783 0.75603807 0.7994858 0.80759579 0.83000571 BX795 0.8326326 0.80962682 0.79888809 0.86500263 0.7585631 0.93312925 0.81786305 0.76044267 0.77183384 0.73866659 0.82035542 0.80553973 BX912 0.70837396 0.58121341 0.5913499 0.60991174 0.66077471 0.78774565 0.62063599 0.56731081 0.57567203 0.57100946 0.56503338 0.56380934 Camptothecin 0.20894133 0.38259089 0.36735317 0.19042179 0.19720933 0.32078287 0.3279928 0.26670286 0.29759926 0.33057389 0.34511778 0.37134597 Canertinib 0.7510671 0.82200074 0.81215608 0.8408913 0.83382499 0.68709397 0.8789776 0.82378107 0.73406273 0.6547783 0.80781341 0.75155145 Capecitabine 1.07068443 1.02926111 1.0253768 1.06530011 1.01679039 0.93793541 1.02361035 0.98695672 1.00986755 1.0067296 0.98807853 1.08348918 Carboplatin 0.83013099 0.98302728 0.94078618 0.96377999 0.94137114 0.92602187 1.0379746 0.90051472 0.94743073 0.93390137 0.96844828 0.91597313 Cariporide 1.1018244 0.99898422 0.87974077 1.04940832 1.13230598 1.04628766 0.9695642 1.02885628 0.99153167 1.01112819 1.04479337 CCCP (carbonyl cyanide-3-chlorophenylhydrazone) 0.82035446 0.77923489 0.69563985 0.78734636 0.88130516 0.73593515 0.71261907 0.75006813 0.71850342 0.75384742 0.74381506 Celecoxib 1.11873269 0.87606305 0.9370687 0.90737754 0.96222585 0.92698979 0.95294422 0.87205005 0.9287219 0.88048339 0.93658185 0.91279942 Cemadotin 0.81740808 0.8573339 0.8568216 0.93641597 0.77537167 0.82901448 0.8414433 0.78843892 0.81153262 0.80342633 0.75642872 0.86246282 Cerulenin 0.79705918 0.87305528 0.79146135 0.80968487 0.79773712 0.78913617 0.80886656 0.80827105 0.83226705 0.8867746 0.85166657 0.86195236 CGK733 0.79042548 0.76854265 0.77987552 0.76550132 0.73111457 0.80862498 0.79618257 0.76800966 0.81612039 0.79762948 0.80335754 0.77891046 CGP60474 0.87239724 0.9119454 0.90213031 0.88764507 0.89206308 0.85745806 0.88436276 0.85193402 0.82045639 0.82383811 0.82102573 0.82253671 CHIR-99021 0.5828234 0.66965628 0.62213451 0.66182125 0.57654351 0.59000897 0.59886163 0.60789955 0.58976889 0.6733073 0.63413531 0.63290143 Chlorambucil 0.89733434 0.95284444 0.94750434 0.90158272 0.9428677 0.91256434 1.03503537 0.87303466 0.9277299 0.91080809 0.93689883 0.95691967 Chlorpromazone 0.75541717 0.98476666 1.0515728 0.90970254 0.71548563 0.85036635 0.97543859 0.98435044 0.95917183 0.97153389 0.98460901 1.08553421 CHR2797 0.94654739 0.87775087 0.93137068 0.89211506 0.89894849 0.78941768 0.87208623 0.87887788 0.86117679 0.89835125 0.90167201 0.91642159 Ciclofenac 0.96623486 0.77217293 0.71118975 0.73915017 0.84422112 0.7380017 0.80333006 0.65155786 0.64903492 0.67986989 0.73579526 0.74646413 Cisplatin 0.95600808 0.96731192 0.99548155 0.99059349 0.99338919 0.88061142 1.02301145 0.96743989 1.01899421 0.96915877 0.94874859 1.112728 Clofarabine 1.01809669 0.95282352 0.90600961 0.94427979 0.98169041 0.8818633 0.95967597 0.92659581 0.90833884 0.97295755 0.98265064 0.93756026 Clopidogrel bisulfate 1.19351304 0.99234265 1.03127456 1.05109465 0.98515803 1.02755177 0.89117992 0.95169306 1.01534867 1.04056871 0.99059594 0.97543859 Coumadin 1.01434469 1.05241323 1.09439468 1.05259717 0.99200523 1.02085912 1.0704186 1.06527376 1.05223489 1.0801872 1.06524324 1.01449585 CP100356 0.6555329 0.85908645 0.83995026 0.79265374 0.80409306 0.77705431 0.83131158 0.85033226 0.82632738 0.90492851 0.86411977 0.86386293 Cyclophosphamide 1.06944931 1.02101398 1.02411282 1.04312098 1.00670624 0.88926482 1.03625488 1.00134182 0.98421937 1.00694931 1.0006274 1.10068035 CYM5442 0.80616331 0.97543859 0.99240255 1.00453186 0.79247022 0.97429889 0.99702585 1.02511632 1.03009224 0.9933849 1 0.96919751 Cytarabine 0.74090928 0.71297586 0.65775532 0.70986426 0.60572392 0.69052368 0.84219593 0.61489236 0.65672958 0.65666699 0.71609515 0.55362391 Cytochalasin D 0.84181362 0.77303553 0.83960438 0.77226877 0.67960167 0.70588487 0.76513737 0.72352082 0.70135921 0.73986787 0.74505955 0.76076967 D-erythro-Sphingosine N-Octanoyl 1.01438236 1.00347221 0.97543859 1.02364767 0.97303784 1.00117862 1.02272499 1.0395484 0.97543859 1.03981674 1.01552594 1.03742456 Darifenacin 0.54694915 0.62165582 0.53592509 0.50163603 0.5776239 0.5956884 0.61470634 0.49524888 0.50098801 0.49259189 0.58787286 0.54652232 Dasatinib 1.15710568 1.00784969 1.05186403 1.07799315 1.05721724
Load more

Recommended publications
  • Methods for Predicting the Survival Time of Patients Suffering from a Lung Cancer
    THETWO TORTOITUUSN 20180252720A1ULLUM HOLATIN ( 19) United States (12 ) Patent Application Publication ( 10) Pub . No. : US 2018 / 0252720 A1 DIEU -NOSJEAN et al. (43 ) Pub. Date : Sep . 6 , 2018 (54 ) METHODS FOR PREDICTING THE Publication Classification SURVIVAL TIME OF PATIENTS SUFFERING (51 ) Int . Ci. FROM A LUNG CANCER GOIN 33 /574 ( 2006 .01 ) (71 ) Applicants : INSERM (INSTITUT NATIONAL ( 52 ) U . S . CI. DE LA SANTE ET DE LA CPC .. GOIN 33 /57423 (2013 . 01) ; GOIN 2800/ 52 RECHERCHE MEDICALE ) , Paris ( 2013 . 01 ) (FR ) ; UNIVERSITE PARIS DESCARTES , Paris ( FR ) ; SORBONNE UNIVERSITE , Paris (57 ) ABSTRACT (FR ) ; UNIVERSITE PARIS DIDEROT - PARIS 7 , Paris ( FR ) ; The present invention relates to methods for predicting the ASSISTANCE survival time of patients suffering from a lung cancer . In PUBLIQUE -HOPITAUX DE PARIS particular , the present invention relates to a method for (ADHP ) , Paris (FR ) predicting the survival time of a subject suffering from a lung cancer comprising the steps of i) quantifying the ( 72 ) Inventors: Marie - Caroline DIEU - NOSJEAN , density of regulatory T ( Treg ) cells in a tumor tissue sample Paris (FR ) ; Wolf Herdman obtained from the subject, ii ) quantifying the density of one FRIDMAN , Paris ( FR ) ; Catherine further population of immune cells selected from the group SAUTES - FRIDMAN , Paris ( FR ) ; consisting of TLS -mature DC or TLS - B cells or Tconv cells , Priyanka DEVI, Paris (FR ) CD8 + T cells or CD8 + Granzyme - B + T cells in said tumor tissue sample , iii ) comparing the densities quantified at steps (21 ) Appl. No. : 15/ 754 , 640 i ) and ii ) with their corresponding predetermined reference values and iv ) concluding that the subject will have a short ( 22 ) PCT Filed : Aug .
    [Show full text]
  • Lonidamine Induces Apoptosis in Drug-Resistant Cells Independently of the P53 Gene
    Lonidamine induces apoptosis in drug-resistant cells independently of the p53 gene. D Del Bufalo, … , A Sacchi, G Zupi J Clin Invest. 1996;98(5):1165-1173. https://doi.org/10.1172/JCI118900. Research Article Lonidamine, a dichlorinated derivative of indazole-3-carboxylic acid, was shown to play a significant role in reversing or overcoming multidrug resistance. Here, we show that exposure to 50 microg/ml of lonidamine induces apoptosis in adriamycin and nitrosourea-resistant cells (MCF-7 ADR(r) human breast cancer cell line, and LB9 glioblastoma multiform cell line), as demonstrated by sub-G1 peaks in DNA content histograms, condensation of nuclear chromatin, and internucleosomal DNA fragmentation. Moreover, we find that apoptosis is preceded by accumulation of the cells in the G0/G1 phase of the cell cycle. Interestingly, lonidamine fails to activate the apoptotic program in the corresponding sensitive parental cell lines (ADR-sensitive MCF-7 WT, and nitrosourea-sensitive LI cells) even after long exposure times. The evaluation of bcl-2 protein expression suggests that this different effect of lonidamine treatment in drug-resistant and -sensitive cell lines might not simply be due to dissimilar expression levels of bcl-2 protein. To determine whether the lonidamine-induced apoptosis is mediated by p53 protein, we used cells lacking endogenous p53 and overexpressing either wild-type p53 or dominant-negative p53 mutant. We find that apoptosis by lonidamine is independent of the p53 gene. Find the latest version: https://jci.me/118900/pdf
    [Show full text]
  • Effect of Lonidamine on Systemic Therapy of DB-1 Human Melanoma Xenografts with Temozolomide KAVINDRA NATH 1, DAVID S
    ANTICANCER RESEARCH 37 : 3413-3421 (2017) doi:10.21873/anticanres.11708 Effect of Lonidamine on Systemic Therapy of DB-1 Human Melanoma Xenografts with Temozolomide KAVINDRA NATH 1, DAVID S. NELSON 1, JEFFREY ROMAN 1, MARY E. PUTT 2, SEUNG-CHEOL LEE 1, DENNIS B. LEEPER 3 and JERRY D. GLICKSON 1 Departments of 1Radiology and 2Biostatistics & Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, U.S.A.; 3Department of Radiation Oncology, Thomas Jefferson University, Philadelphia, PA, U.S.A. Abstract. Background/Aim: Since temozolomide (TMZ) is stages. However, following recurrence with metastasis, the activated under alkaline conditions, we expected lonidamine prognosis is poor. Mutationally-activated BRAF is found in (LND) to have no effect or perhaps diminish its activity, but 40-60% of all melanomas with most common substitution of initial results suggest it may actually enhance either or both valine to glutamic acid at codon 600 (p. V600E) (3). Overall short- and long-term activity of TMZ in melanoma xenografts. survival is approaching two years using agents that target this Materials and Methods: Cohorts of 5 mice with subcutaneous mutation (4, 5). MEK, RAS and other signal transduction xenografts ~5 mm in diameter were treated with saline inhibitors, in combination with mutant BRAF inhibitors, have (control (CTRL)), LND only, TMZ only or LND followed by been used to deal with melanoma resistance to these agents TMZ at t=40 min (time required for maximal tumor (6). Treatment with anti-programmed death-1 (PD-1) acidification). Results: Mean tumor volume for LND+TMZ for checkpoint inhibitor immunotherapy currently produces the period between 6 and 26 days was reduced compared to durable response in about 25% of melanoma patients (7-10).
    [Show full text]
  • Targeting the Mitochondrial Metabolic Network: a Promising Strategy in Cancer Treatment
    International Journal of Molecular Sciences Review Targeting the Mitochondrial Metabolic Network: A Promising Strategy in Cancer Treatment Luca Frattaruolo y , Matteo Brindisi y , Rosita Curcio, Federica Marra, Vincenza Dolce and Anna Rita Cappello * Department of Pharmacy, Health and Nutritional Sciences, University of Calabria, Via P. Bucci, 87036 Rende (CS), Italy; [email protected] (L.F.); [email protected] (M.B.); [email protected] (R.C.); [email protected] (F.M.); [email protected] (V.D.) * Correspondence: [email protected] These authors contributed equally and should be considered co-first authors. y Received: 31 July 2020; Accepted: 19 August 2020; Published: 21 August 2020 Abstract: Metabolic reprogramming is a hallmark of cancer, which implements a profound metabolic rewiring in order to support a high proliferation rate and to ensure cell survival in its complex microenvironment. Although initial studies considered glycolysis as a crucial metabolic pathway in tumor metabolism reprogramming (i.e., the Warburg effect), recently, the critical role of mitochondria in oncogenesis, tumor progression, and neoplastic dissemination has emerged. In this report, we examined the main mitochondrial metabolic pathways that are altered in cancer, which play key roles in the different stages of tumor progression. Furthermore, we reviewed the function of important molecules inhibiting the main mitochondrial metabolic processes, which have been proven to be promising anticancer candidates in recent years. In particular, inhibitors of oxidative phosphorylation (OXPHOS), heme flux, the tricarboxylic acid cycle (TCA), glutaminolysis, mitochondrial dynamics, and biogenesis are discussed. The examined mitochondrial metabolic network inhibitors have produced interesting results in both preclinical and clinical studies, advancing cancer research and emphasizing that mitochondrial targeting may represent an effective anticancer strategy.
    [Show full text]
  • Nath, K., Guo, L., Nancolas, B., Nelson, D. S., Shestov, A. A., Lee, S- C., Roman, J., Zhou, R., Leeper, D
    Nath, K., Guo, L., Nancolas, B., Nelson, D. S., Shestov, A. A., Lee, S- C., Roman, J., Zhou, R., Leeper, D. B., Halestrap, A. P., Blair, I. A., & Glickson, J. D. (2016). Mechanism of antineoplastic activity of lonidamine. Biochimica et Biophysica Acta (BBA) - Reviews on Cancer, 1866(2), 151-162. https://doi.org/10.1016/j.bbcan.2016.08.001 Peer reviewed version License (if available): CC BY-NC-ND Link to published version (if available): 10.1016/j.bbcan.2016.08.001 Link to publication record in Explore Bristol Research PDF-document This is the accepted author manuscript (AAM). The final published version (version of record) is available online via Elsevier at http://dx.doi.org/10.1016/j.bbcan.2016.08.001. Please refer to any applicable terms of use of the publisher. University of Bristol - Explore Bristol Research General rights This document is made available in accordance with publisher policies. Please cite only the published version using the reference above. Full terms of use are available: http://www.bristol.ac.uk/red/research-policy/pure/user-guides/ebr-terms/ Mechanism of Antineoplastic Activity of Lonidamine Kavindra Nath1, Lili Guo2, Bethany Nancolas3, David S. Nelson1, Alexander A Shestov1, Seung-Cheol Lee1, Jeffrey Roman1, Rong Zhou1, Dennis B. Leeper4, Andrew P. Halestrap3, Ian A. Blair2 and Jerry D. Glickson1 Departments of Radiology1 and Center of Excellence in Environmental Toxicology, and Department of Systems Pharmacology and Translational Therapeutics2, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA 19104, USA, School of Biochemistry3, Biomedical Sciences Building, University of Bristol, BS8 1TD, UK.
    [Show full text]
  • 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
    [Show full text]
  • Exploring the Anti-Leukemic Effect of the Combination Treatment with Valproic Acid, Lonidamine and Mycophenolate Mofetil in Acute Myeloid Leukemia
    P a g e | 1 Exploring the anti-leukemic effect of the combination treatment with Valproic acid, Lonidamine and Mycophenolate mofetil in acute myeloid leukemia Carina Hinrichs Master`s Degree This thesis is submitted in partial fulfilment of the requirements for the degree of Master of Science in Medical Biology – Medical Cell Biology. The work was conducted at Section for Hematology, Clinical Institute II, University of Bergen. Department of Biomedicine and Department of Clinical Science University of Bergen, Norway June 2015 1 P a g e | 2 Acknowledgement I would like to first and foremost sincerely acknowledge my head supervisor Dr. Rakel Brendsdal Forthun for inviting me to the Translational Hematology and Oncology Group at the Department of Clinical Science and University of Bergen. Not only has her continued support and encouragement kept me motivated and saved a lot of sleepless nights, but her scientific knowledge and thoroughly proofreading also inspired me to strive for a better understanding of my thesis and cancer research. I would also like to thank my co-supervisor Professor Bjørn Tore Gjertsen for including me into his research group and into the scientific environment. I truly appreciate the way Bjørn Tore Gjertsen has guided me through my studies and the attention he has given me and my work. I am most thankful to all of the colleagues of the Gjertsen laboratory for their good advises, technical help and especially for lighten up the scientific workplace. Wenche Eilifsen and Siv Lise Bedringaas are appreciated for their helping hand they have given me when I was “lost” in the laboratory.
    [Show full text]
  • Multistage Delivery of Active Agents
    111111111111111111111111111111111111111111111111111111111111111111111111111111 (12) United States Patent (io) Patent No.: US 10,143,658 B2 Ferrari et al. (45) Date of Patent: Dec. 4, 2018 (54) MULTISTAGE DELIVERY OF ACTIVE 6,355,270 B1 * 3/2002 Ferrari ................. A61K 9/0097 AGENTS 424/185.1 6,395,302 B1 * 5/2002 Hennink et al........ A61K 9/127 (71) Applicants:Board of Regents of the University of 264/4.1 2003/0059386 Al* 3/2003 Sumian ................ A61K 8/0241 Texas System, Austin, TX (US); The 424/70.1 Ohio State University Research 2003/0114366 Al* 6/2003 Martin ................. A61K 9/0097 Foundation, Columbus, OH (US) 424/489 2005/0178287 Al* 8/2005 Anderson ............ A61K 8/0241 (72) Inventors: Mauro Ferrari, Houston, TX (US); 106/31.03 Ennio Tasciotti, Houston, TX (US); 2008/0280140 Al 11/2008 Ferrari et al. Jason Sakamoto, Houston, TX (US) FOREIGN PATENT DOCUMENTS (73) Assignees: Board of Regents of the University of EP 855179 7/1998 Texas System, Austin, TX (US); The WO WO 2007/120248 10/2007 Ohio State University Research WO WO 2008/054874 5/2008 Foundation, Columbus, OH (US) WO WO 2008054874 A2 * 5/2008 ............... A61K 8/11 (*) Notice: Subject to any disclaimer, the term of this OTHER PUBLICATIONS patent is extended or adjusted under 35 U.S.C. 154(b) by 0 days. Akerman et al., "Nanocrystal targeting in vivo," Proc. Nad. Acad. Sci. USA, Oct. 1, 2002, 99(20):12617-12621. (21) Appl. No.: 14/725,570 Alley et al., "Feasibility of Drug Screening with Panels of Human tumor Cell Lines Using a Microculture Tetrazolium Assay," Cancer (22) Filed: May 29, 2015 Research, Feb.
    [Show full text]
  • Interstitial Photodynamic Therapy Using 5-ALA for Malignant Glioma Recurrences
    cancers Article Interstitial Photodynamic Therapy Using 5-ALA for Malignant Glioma Recurrences Stefanie Lietke 1,2,† , Michael Schmutzer 1,2,† , Christoph Schwartz 1,3, Jonathan Weller 1,2 , Sebastian Siller 1,2 , Maximilian Aumiller 4,5 , Christian Heckl 4,5 , Robert Forbrig 6, Maximilian Niyazi 2,7, Rupert Egensperger 8, Herbert Stepp 4,5 , Ronald Sroka 4,5 , Jörg-Christian Tonn 1,2, Adrian Rühm 4,5,‡ and Niklas Thon 1,2,*,‡ 1 Department of Neurosurgery, University Hospital, LMU Munich, 81377 Munich, Germany 2 German Cancer Consortium (DKTK), Partner Site Munich, 81377 Munich, Germany 3 Department of Neurosurgery, University Hospital Salzburg, Paracelsus Medical University Salzburg, 5020 Salzburg, Austria 4 Laser-Forschungslabor, LIFE Center, University Hospital, LMU Munich, 81377 Munich, Germany 5 Department of Urology, University Hospital, LMU Munich, 81377 Munich, Germany 6 Institute for Clinical Neuroradiology, University Hospital, LMU Munich, 81377 Munich, Germany 7 Department of Radiation Oncology, University Hospital, LMU Munich, 81377 Munich, Germany 8 Center for Neuropathology and Prion Research, University Hospital, LMU Munich, 81377 Munich, Germany * Correspondence: [email protected]; Tel.: +49-89-4400-0 † Both authors contributed equally. ‡ This study is guided by AR and NT equally thus both serve as shared last authors. Citation: Lietke, S.; Schmutzer, M.; Schwartz, C.; Weller, J.; Siller, S.; Simple Summary: Malignant glioma has a poor prognosis, especially in recurrent situations. Intersti- Aumiller, M.; Heckl, C.; Forbrig, R.; tial photodynamic therapy (iPDT) uses light delivered by implanted light-diffusing fibers to activate Niyazi, M.; Egensperger, R.; et al. a photosensitizing agent to induce tumor cell death. This study examined iPDT for the treatment Interstitial Photodynamic Therapy of malignant glioma recurrences.
    [Show full text]
  • Antigen Binding Protein and Its Use As Addressing Product for the Treatment of Cancer
    (19) TZZ 58Z9A_T (11) EP 2 589 609 A1 (12) EUROPEAN PATENT APPLICATION (43) Date of publication: (51) Int Cl.: 08.05.2013 Bulletin 2013/19 C07K 16/28 (2006.01) (21) Application number: 11306416.6 (22) Date of filing: 03.11.2011 (84) Designated Contracting States: (72) Inventors: AL AT BE BG CH CY CZ DE DK EE ES FI FR GB •Beau-Larvor, Charlotte GR HR HU IE IS IT LI LT LU LV MC MK MT NL NO 74520 Jonzier Epagny (FR) PL PT RO RS SE SI SK SM TR • Goetsch, Liliane Designated Extension States: 74130 Ayze (FR) BA ME (74) Representative: Regimbeau (83) Declaration under Rule 32(1) EPC (expert 20, rue de Chazelles solution) 75847 Paris Cedex 17 (FR) (71) Applicant: PIERRE FABRE MEDICAMENT 92100 Boulogne-Billancourt (FR) (54) Antigen binding protein and its use as addressing product for the treatment of cancer (57) The present invention relates to an antigen bind- of Axl, being internalized into the cell. The invention also ing protein, in particular a monoclonal antibody, capable comprises the use of said antigen binding protein as an of binding specifically to the protein Axl as well as the addressing product in conjugation with other anti- cancer amino and nucleic acid sequences coding for said pro- compounds,such as toxins, radio- elements ordrugs, and tein. From one aspect, the invention relates to an antigen the use of same for the treatment of certain cancers. binding protein, or antigen binding fragments, capable of binding specifically to Axl and, by inducing internalization EP 2 589 609 A1 Printed by Jouve, 75001 PARIS (FR) EP 2 589 609 A1 Description [0001] The present invention relates to a novel antigen binding protein, in particular a monoclonal antibody, capable of binding specifically to the protein Axl as well as the amino and nucleic acid sequences coding for said protein.
    [Show full text]
  • Targeted Delivery of Drugs and Genes Using Polymer Nanocarriers for Cancer Therapy
    International Journal of Molecular Sciences Review Targeted Delivery of Drugs and Genes Using Polymer Nanocarriers for Cancer Therapy Wentao Xia, Zixuan Tao, Bin Zhu, Wenxiang Zhang , Chang Liu , Siyu Chen * and Mingming Song * School of Life Science and Technology, China Pharmaceutical University, Nanjing 211198, China; [email protected] (W.X.); [email protected] (Z.T.); [email protected] (B.Z.); [email protected] (W.Z.); [email protected] (C.L.) * Correspondence: [email protected] (S.C.); [email protected] (M.S.); Tel.: +86-25-8618-5645 (M.S.) Abstract: Cancer is one of the primary causes of worldwide human deaths. Most cancer patients receive chemotherapy and radiotherapy, but these treatments are usually only partially efficacious and lead to a variety of serious side effects. Therefore, it is necessary to develop new therapeutic strategies. The emergence of nanotechnology has had a profound impact on general clinical treatment. The application of nanotechnology has facilitated the development of nano-drug delivery systems (NDDSs) that are highly tumor selective and allow for the slow release of active anticancer drugs. In recent years, vehicles such as liposomes, dendrimers and polymer nanomaterials have been considered promising carriers for tumor-specific drug delivery, reducing toxicity and improving biocompatibility. Among them, polymer nanoparticles (NPs) are one of the most innovative methods of non-invasive drug delivery. Here, we review the application of polymer NPs in drug delivery, gene therapy, and early diagnostics for cancer therapy. Citation: Xia, W.; Tao, Z.; Zhu, B.; Keywords: polymer nanocarriers; cancer therapy; drug delivery Zhang, W.; Liu, C.; Chen, S.; Song, M.
    [Show full text]
  • Analytics for Improved Cancer Screening and Treatment John
    Analytics for Improved Cancer Screening and Treatment by John Silberholz B.S. Mathematics and B.S. Computer Science, University of Maryland (2010) Submitted to the Sloan School of Management in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Operations Research at the MASSACHUSETTS INSTITUTE OF TECHNOLOGY September 2015 ○c Massachusetts Institute of Technology 2015. All rights reserved. Author................................................................ Sloan School of Management August 10, 2015 Certified by. Dimitris Bertsimas Boeing Leaders for Global Operations Professor Co-Director, Operations Research Center Thesis Supervisor Accepted by . Patrick Jaillet Dugald C. Jackson Professor Department of Electrical Engineering and Computer Science Co-Director, Operations Research Center 2 Analytics for Improved Cancer Screening and Treatment by John Silberholz Submitted to the Sloan School of Management on August 10, 2015, in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Operations Research Abstract Cancer is a leading cause of death both in the United States and worldwide. In this thesis we use machine learning and optimization to identify effective treatments for advanced cancers and to identify effective screening strategies for detecting early-stage disease. In Part I, we propose a methodology for designing combination drug therapies for advanced cancer, evaluating our approach using advanced gastric cancer. First, we build a database of 414 clinical trials testing chemotherapy regimens for this cancer, extracting information about patient demographics, study characteristics, chemother- apy regimens tested, and outcomes. We use this database to build statistical models to predict trial efficacy and toxicity outcomes. We propose models that use machine learning and optimization to suggest regimens to be tested in Phase II and III clinical trials, evaluating our suggestions with both simulated outcomes and the outcomes of clinical trials testing similar regimens.
    [Show full text]