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Items: 1 to 20 of 78

1.

Systematic identification of combinatorial drivers and targets in cancer cell lines.

Tabchy A, Eltonsy N, Housman DE, Mills GB.

PLoS One. 2013;8(4):e60339. doi: 10.1371/journal.pone.0060339. Epub 2013 Apr 5. Erratum in: PLoS One. 2013;8(5). doi:10.1371/annotation/85d86c29-4ba6-4bf0-94f6-2977b3e1c792.

2.
3.

Whole-Exome Sequencing of Metastatic Cancer and Biomarkers of Treatment Response.

Beltran H, Eng K, Mosquera JM, Sigaras A, Romanel A, Rennert H, Kossai M, Pauli C, Faltas B, Fontugne J, Park K, Banfelder J, Prandi D, Madhukar N, Zhang T, Padilla J, Greco N, McNary TJ, Herrscher E, Wilkes D, MacDonald TY, Xue H, Vacic V, Emde AK, Oschwald D, Tan AY, Chen Z, Collins C, Gleave ME, Wang Y, Chakravarty D, Schiffman M, Kim R, Campagne F, Robinson BD, Nanus DM, Tagawa ST, Xiang JZ, Smogorzewska A, Demichelis F, Rickman DS, Sboner A, Elemento O, Rubin MA.

JAMA Oncol. 2015 Jul;1(4):466-74. doi: 10.1001/jamaoncol.2015.1313.

4.

Identification of molecular subtypes of gastric cancer with different responses to PI3-kinase inhibitors and 5-fluorouracil.

Lei Z, Tan IB, Das K, Deng N, Zouridis H, Pattison S, Chua C, Feng Z, Guan YK, Ooi CH, Ivanova T, Zhang S, Lee M, Wu J, Ngo A, Manesh S, Tan E, Teh BT, So JB, Goh LK, Boussioutas A, Lim TK, Flotow H, Tan P, Rozen SG.

Gastroenterology. 2013 Sep;145(3):554-65. doi: 10.1053/j.gastro.2013.05.010. Epub 2013 May 14.

PMID:
23684942
5.

Development of candidate genomic markers to select breast cancer patients for dasatinib therapy.

Moulder S, Yan K, Huang F, Hess KR, Liedtke C, Lin F, Hatzis C, Hortobagyi GN, Symmans WF, Pusztai L.

Mol Cancer Ther. 2010 May;9(5):1120-7. doi: 10.1158/1535-7163.MCT-09-1117. Epub 2010 Apr 27.

6.

Array analysis for potential biomarker of gemcitabine identification in non-small cell lung cancer cell lines.

Zhang HH, Zhang ZY, Che CL, Mei YF, Shi YZ.

Int J Clin Exp Pathol. 2013 Aug 15;6(9):1734-46. eCollection 2013.

7.

Unequal prognostic potentials of p53 gain-of-function mutations in human cancers associate with drug-metabolizing activity.

Xu J, Wang J, Hu Y, Qian J, Xu B, Chen H, Zou W, Fang JY.

Cell Death Dis. 2014 Mar 6;5:e1108. doi: 10.1038/cddis.2014.75.

8.

Multi-omic measurement of mutually exclusive loss-of-function enriches for candidate synthetic lethal gene pairs.

Wappett M, Dulak A, Yang ZR, Al-Watban A, Bradford JR, Dry JR.

BMC Genomics. 2016 Jan 19;17:65. doi: 10.1186/s12864-016-2375-1.

9.

CGPredictor: a systematic integrated analytic tool for mining and examining genome-scale cancer independent prognostic epigenetic marker panels.

Cheng WS, Chiang JH.

BMC Syst Biol. 2013;7 Suppl 6:S10. doi: 10.1186/1752-0509-7-S6-S10. Epub 2013 Dec 13.

10.

Chemical genomics and emerging DNA technologies in the identification of drug mechanisms and drug targets.

Olsen LC, Færgeman NJ.

Curr Top Med Chem. 2012;12(12):1331-45. Review.

PMID:
22690680
11.

Prediction of drug sensitivity and drug resistance in cancer by transcriptional and proteomic profiling.

Alaoui-Jamali MA, Dupré I, Qiang H.

Drug Resist Updat. 2004 Aug-Oct;7(4-5):245-55. Review.

PMID:
15533762
12.

Combining phenotypic and proteomic approaches to identify membrane targets in a 'triple negative' breast cancer cell type.

Rust S, Guillard S, Sachsenmeier K, Hay C, Davidson M, Karlsson A, Karlsson R, Brand E, Lowne D, Elvin J, Flynn M, Kurosawa G, Hollingsworth R, Jermutus L, Minter R.

Mol Cancer. 2013 Feb 13;12:11. doi: 10.1186/1476-4598-12-11.

13.

A molecularly annotated platform of patient-derived xenografts ("xenopatients") identifies HER2 as an effective therapeutic target in cetuximab-resistant colorectal cancer.

Bertotti A, Migliardi G, Galimi F, Sassi F, Torti D, Isella C, Corà D, Di Nicolantonio F, Buscarino M, Petti C, Ribero D, Russolillo N, Muratore A, Massucco P, Pisacane A, Molinaro L, Valtorta E, Sartore-Bianchi A, Risio M, Capussotti L, Gambacorta M, Siena S, Medico E, Sapino A, Marsoni S, Comoglio PM, Bardelli A, Trusolino L.

Cancer Discov. 2011 Nov;1(6):508-23. doi: 10.1158/2159-8290.CD-11-0109. Epub 2011 Sep 2.

14.

Platforms for biomarker analysis using high-throughput approaches in genomics, transcriptomics, proteomics, metabolomics, and bioinformatics.

Merrick BA, London RE, Bushel PR, Grissom SF, Paules RS.

IARC Sci Publ. 2011;(163):121-42. Review.

PMID:
22997859
15.

In silico analyses for the discovery of tuberculosis drug targets.

Chung BK, Dick T, Lee DY.

J Antimicrob Chemother. 2013 Dec;68(12):2701-9. doi: 10.1093/jac/dkt273. Epub 2013 Jul 9. Review.

PMID:
23838951
16.

Cellular fingerprints: a novel approach using large-scale cancer cell line data for the identification of potential anticancer agents.

Füllbeck M, Dunkel M, Hossbach J, Daniel PT, Preissner R.

Chem Biol Drug Des. 2009 Nov;74(5):439-48. doi: 10.1111/j.1747-0285.2009.00883.x. Epub 2009 Oct 2.

PMID:
19799613
17.

Inferring synthetic lethal interactions from mutual exclusivity of genetic events in cancer.

Srihari S, Singla J, Wong L, Ragan MA.

Biol Direct. 2015 Oct 1;10:57. doi: 10.1186/s13062-015-0086-1.

18.

Integrative bioinformatic analyses of an oncogenomic profile reveal the biology of endometrial cancer and guide drug discovery.

Wong HS, Juan YS, Wu MS, Zhang YF, Hsu YW, Chen HH, Liu WM, Chang WC.

Oncotarget. 2016 Feb 2;7(5):5909-23. doi: 10.18632/oncotarget.6716.

19.

Discovery of novel drugs for promising targets.

Martell RE, Brooks DG, Wang Y, Wilcoxen K.

Clin Ther. 2013 Sep;35(9):1271-81. doi: 10.1016/j.clinthera.2013.08.005. Review.

PMID:
24054704
20.

Candidate biomarkers of response to an experimental cancer drug identified through a large-scale RNA interference genetic screen.

Mullenders J, von der Saal W, van Dongen MM, Reiff U, van Willigen R, Beijersbergen RL, Tiefenthaler G, Klein C, Bernards R.

Clin Cancer Res. 2009 Sep 15;15(18):5811-9. doi: 10.1158/1078-0432.CCR-09-0261. Epub 2009 Sep 1.

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