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2011 AACR OncoPanel Poster
 

2011 AACR OncoPanel Poster

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Tumor cell line profiling of eighteen cancer therapeutics to evaluate relationships between tumor genotypes and cancer cell sensitivities

Tumor cell line profiling of eighteen cancer therapeutics to evaluate relationships between tumor genotypes and cancer cell sensitivities

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    2011 AACR OncoPanel Poster 2011 AACR OncoPanel Poster Presentation Transcript

    • 2011 AACR 102nd Annual MeetingTitle: Tumor cell line profiling of eighteen cancertherapeutics to evaluate relationships betweentumor genotypes and cancer cell sensitivitiesAuthors: Yulia Y. Ovechkina, Christine ODay, Karen Marcoe, Robert Keyser, KarenBernards, Jessica Chesnut-Speelman, Phuong T.B. Nguyen, Jenny Mulligan, TeddyLin, Rodney Shively, Jim Hnilo, Brian Nelson. Ricerca Biosciences, LLC, Bothell,WA
    • Introduction In vitro cellular response profiling of tumor human cell lines has become awidely used approach for the targeted cancer therapeutics development. Correlationof the drug sensitivity and resistance cellular response with genomic data offers arobust and sensitive system for predicting clinical efficacy and identifying moreefficacious patient populations. We have developed a high throughput cellular approach to evaluate therelationship between tumor genotypes and drug sensitivity over 240 human tumorcell lines. A panel of eighteen cancer therapeutic agents was tested for proliferative,apoptotic and cell cycle arrest responses using multiplexed high content screeningwith automated fluorescence microscopy and image analysis based technology (GEHealthcare INCell Analyzer 1000). Growth index was measured using nuclear dye.Activated caspase 3 antibodies were used for the apoptosis induction detection.Phospho-histone H3 antibodies were used to measure the cell cycle block. Wegenerated cell line profiles to reveal drug sensitivity and resistance patterns andidentified examples of the genomic markers associated with a specific response. Thisapproach could provide insight into the mechanisms of enhanced susceptibility orresistance which in turn could be used for the optimization of the targeted cancertherapeutics.
    • 240_OncoPanel™ - Human Tumor Cell Line Profiling 240_OncoPanel™ - Cancer Types• 240 human tumor-derived cell Colon/GI 33 line panel from different origins Haematopoietic 29 with broad genetic Soft Tissue 20 Female GU 20 heterogeneity CNS 20• Cell lines are quality controlled Breast 20 (procured from ATCC and Skin 19 Lung 19 other banks) Pancreas 12• Sensitive High Content cellular Bladder 11 image analysis Kidney 10 Prostate 7 • High throughput (384 well plates) Liver 7 • Multiplexed data output Head and Neck 6 • 10 concentrations (in triplicates) Endocrine 6 Other 1
    • Available genetic informationmRNA expression data 50+ Gene Mutation datahttp://www.ebi.ac.uk/microarray-as/ae/files/E-MTAB-37 APC BRAF BRCA1 BRCA2Gene copy number and mRNA expression data CDH1 CDKN2A CTNNB1 CYLDhttps://cabig.nci.nih.gov/caArray_GSKdata/ ERBB2 FBXW7 FGFR3 FLCNSanger gene copy number data GNAS HRAS JAK2 KIThttp://www.sanger.ac.uk/genetics/CGP/translation/data/http://www.broadinstitute.org/cgi-bin/cancer/datasets.cgi MAP2K4 MLH1 MSH2 MSH6 NF1 NF2 NOTCH1 NPM1Sanger gene mutation datahttp://www.sanger.ac.uk/genetics/CGP/Celllines NTRK3 PALB2 PDGFRA PIK3C2A PTCH1 PTEN RB1 RETThe mutation data was obtained from the Sanger Institute CatalogueOf Somatic Mutations In Cancer web site, SMAD4 SMO SOCS1 STK11http://www.sanger.ac.uk/cosmic TP53 TSC1 TSC2 VHLBamford et al (2004) The COSMIC (Catalogue of Somatic Mutationsin Cancer) database and website. Br J Cancer, 91,355-358. CBFB EGFR FLT3 KRAS NRAS PIK3CA RUNX1 MYC
    • 240_OncoPanel™ - Assay Workflow 240 human tumor cell line panel High Content Analysis O 100 H C NCH2 CH2 CH2 CH3 Cell proliferation POC 50 O N H N C OCH3 0 -11 -10 -9 -8 -7 -6 N 40 log [Vinblastine], M Compound Apoptosis Fold Induction 30 20 10 0 -11 -10 -9 -8 -7 -6 4 log [Vinblastine], M Cell cycle Fold Induction 3 2 1 0 -12 -11 -10 -9 -8 -7 log [Vinblastine], M 72 hrs High Throughput Screening Sensitive cells Resistant cells Genotype correlation analysis
    • Criteria for Positive ResponsesHigh Content Multiplexed Output• Cell proliferation measured by relative cell counts » EC50 is a concentration at the curve inflection point (parameter C) » IC50 is a concentration at 50% of maximal possible response » GI50 is a concentration needed to reduce the growth of treated cells to half that of untreated cells.  D Log GI50 is the log difference from the average GI50 value• Apoptosis: » >5-fold increase in activated caspase-3 signal indicates apoptosis induction• Cell cycle block: Cell Nuclei – blue; Apoptotic cells- » >2-fold increase in phospho-histone-3 indicates green ; Mitotic cells - red G2/M cell cycle block » <2-fold decrease in phospho-histone-3 indicates G1/S cell cycle block
    • Cancer therapeutic agents Sensitive Resistant Ratio of resistant Concentration Log GI50 Compound Synonym(s) Target(s) Source CAS No. response response mean GI50 mean to range, microM range mean GI50, GI50, microM sensitive GI50 mean BMS-387032 SNS-032 CDK2, 7 and 9 Selleck 345627-80-7 10 - 0.0003 0.15 1.45 10 2.1 Cl 1040 PD184352 Mek1/2 Selleck 212631-79-3 10 - 0.0003 0.18 4.43 25 3.1 PD0325901 N/A Mek1/2 Calbiochem 391210-10-9 30 - 0.001 0.06 15.53 259 4.5 PD173074 N/A FGFR1, FGFR3 Calbiochem 219580-11-7 5 - 0.0002 0.24 4.63 19 2.4 API-2 Triciribine AKT Tocris 35943-35-2 20 - 0.0006 0.38 12.79 34 2.8 EGFR, ErbB2, Erk-1/2 Sequoia Lapatinib Tykerb 388082-78-8 20 - 0.0006 0.28 9.26 33 3.4 and AKT Research BMS-536924 N/A IGF-1R Selleck 468740-43-4 10 - 0.0003 0.19 3.41 18 3 Sequoia Erlotinib Tarceva EGFR, ErbB2 183321-74-6 14 - 0.0004 0.15 4.48 30 3.2 Research Sequoia Geldanamycin N/A HSP-90 30562-34-6 5 - 0.0002 0.03 0.12 4 2.4 Research BRAF, PDGF, C-Kit, Sequoia Sorafenib Nexavar 284461-73-0 20 - 0.0006 0.29 4.33 15 2.6 VEGF Research BCR-ABL, SRC, Sequoia Dasatinib Sprycel 863127-77-9 5 - 0.0002 0.008 0.87 109 4.5 Ephrins, EGFR Research Aurora-A,-B,-C Sequoia VX-680 Tozasertib 639089-54-6 10 - 0.0003 0.06 2.23 37 3.3 kinases Research FLT3, PDGFRs, Sequoia Sunitinib Sutent 557795-19-4 20 - 0.0006 0.21 4.37 21 3.2 VEGFRs, Kit Research Sequoia Everolimus N/A mTOR 159351-69-6 10 - 0.0003 0.009 4.83 537 4.5 Research Sequoia Tandutinib N/A FLT3 ,PDGFR, KIT 387867-13-2 10 - 0.0003 0.22 4.58 21 2.8 Research Doxorubicin N/A topoisomerase II Calbiochem 25316-40-9 5 - 0.0002 0.005 0.04 8 2.8 Paclitaxel Taxol tubulin Calbiochem 33069-62-4 0.3 - 9.55E-06 0.001 0.009 9 3.5 PKC, PKA,PKG, p60v- Staurosporine N/A Calbiochem 62996-74-1 1 - 3.18E-05 0.003 0.025 8 2.4 src, CaM kinase IIMidpoint of the GI50 range was used to distinguish sensitive and resistant populations. The GI50 of the sensitive and resistant populationswas then averaged to produce the “sensitive and resistant response mean GI50”.
    • Multiplexed high content approach provides insight into the drugmechanisms of action PD0325901 treated Colo829 cell line PD173074 treated KatoIII cell line Cell proliferation Cell proliferation Apoptosis Apoptosis Cell cycle Cell cycle
    • Multiplexed high content approach provides insight into the drugmechanisms of action Lapatinib treated CHL-1 cell line BMS-536924 treated HT-29 cell line Cell proliferation Cell proliferation Apoptosis Apoptosis Cell cycle Cell cycle
    • Multiplexed high content approach provides insight into the drugmechanisms of action BMS-387032 treated MV-4-11 cell line API-2 treated T47D cell line Cell proliferation Cell proliferation Apoptosis Apoptosis Cell cycle Cell cycle
    • IC50 vs GI50 profiles across 240 cell lines PD0325901 Lapatinib BMS-387032 100.000 100.000 10.00 10.000 10.000 IC50, microM IC50, microM IC50, microM 1.000 1.00 1.000 0.100 0.100 0.010 0.10 0.010 0.001 0.000 0.001 0.01 0.000 0.001 0.010 0.100 1.000 10.000 100.000 0.001 0.010 0.100 1.000 10.000 100.000 0.01 0.10 1.00 10.00 GI50, m icroM GI50, m icroM GI50, m icroMIC50 PD173074 BMS-536924 API-2 (Triciribine) 10.00 10.00 100.00 IC50, microM 10.00 IC50, microM IC50, microM 1.00 1.00 1.00 0.10 0.10 0.10 0.01 0.01 0.01 0.01 0.10 1.00 10.00 0.01 0.10 1.00 10.00 0.01 0.10 1.00 10.00 100.00 GI50, m icroM GI50, m icroM GI50, m icroM Sensitive GI50 Resistant
    • IC50 vs GI50 profiles across 240 cell lines Erlotinib CL 1040 Sorafenib 100 10 100 10 1 10 IC50, microM IC50, microM IC50, microM 1 0.1 1 0.1 0.01 0.1 0.01 0.001 0.01 0.001 0.01 0.1 1 10 100 0.001 0.01 0.1 1 10 0.01 0.1 1 10 100 GI50, microM GI50, microM GI50, microMIC50 Dasatinib VX-680 Everolimus 10 10 10 1 1 1 IC50, microM IC50, microM IC50, microM 0.1 0.1 0.1 0.01 0.01 0.001 0.01 0.001 0.0001 0.0001 0.001 0.00001 0.0001 0.001 0.01 0.1 1 10 0.001 0.01 0.1 1 10 0.0001 0.001 0.01 0.1 1 10 GI50, microM GI50, microM GI50, microM Sensitive GI50 Resistant
    • IC50 vs GI50 profiles across 240 cell lines Sunitinib Tandutinib Doxorubicin 100 10 1 10 0.1 IC50, microM IC50, microM IC50, microM 1 1 0.01 0.1 0.001 0.01 0.1 0.0001 0.01 0.1 1 10 100 0.01 0.1 1 10 0.0001 0.001 0.01 0.1 1 GI50, microM GI50, microM GI50, microMIC50 Paclitaxel Staurosporine Geldanamycin 1 1 10 0.1 0.1 1 IC50, microM IC50, microM IC50, microM 0.01 0.01 0.1 0.001 0.001 0.01 0.0001 0.00001 0.0001 0.001 1.00E-05 1.00E-04 1.00E-03 1.00E-02 1.00E-01 1.00E+00 0.0001 0.001 0.01 0.1 1 0.001 0.01 0.1 1 10 GI50, microM GI50, microM GI50, microM Sensitive GI50 Resistant
    • GI50 values across 240 cell line panel PD0325901 Lapatinib BMS-387032 100.000 100.000 10.00 10.000 10.000GI50, microM GI50, microM GI50, microM GI50, microM 1.00 1.000 1.000 0.100 0.100 0.10 0.010 0.010 0.001 0.001 0.01 0 20 40 60 80 100 120 140 160 180 200 220 240 0 20 40 60 80 100 120 140 160 180 200 220 240 0 20 40 60 80 100 120 140 160 180 200 220 240 PD173074 BMS-536924 API-2 (Triciribine) 10.00 10.00 100.00 10.00 GI50, microM GI50, microM GI50, microM 1.00 1.00 1.00 0.10 0.10 0.10 0.01 0.01 0.01 0 20 40 60 80 100 120 140 160 180 200 220 240 0 20 40 60 80 100 120 140 160 180 200 220 240 0 20 40 60 80 100 120 140 160 180 200 220 240 Sensitive 240 cell lines Resistant
    • GI50 values across 240 cell line panel Erlotinib CL 1040 Sorafenib 100 100 100 10 10 10GI50, microM GI50, microM GI50, microM GI50, microM 1 1 1 0.1 0.1 0.1 0.01 0.01 0.01 0.001 0.001 0.001 0.0001 0.0001 0.0001 0 20 40 60 80 100 120 140 160 180 200 220 240 0 20 40 60 80 100 120 140 160 180 200 220 240 0 20 40 60 80 100 120 140 160 180 200 220 240 Dasatinib VX-680 Everolimus 100 100 100 10 10 10 GI50, microM 1 GI50, microM GI50, microM 1 1 0.1 0.1 0.1 0.01 0.01 0.01 0.001 0.001 0.001 0.0001 0.0001 0.0001 0 20 40 60 80 100 120 140 160 180 200 220 240 0 20 40 60 80 100 120 140 160 180 200 220 240 0 20 40 60 80 100 120 140 160 180 200 220 240 Sensitive 240 cell lines Resistant
    • GI50 values across 240 cell line panel Sunitinib Tandutinib Doxorubicin 100 100 100 10 10 10GI50, microM GI50, microM GI50, microM GI50, microM 1 1 1 0.1 0.1 0.1 0.01 0.01 0.01 0.001 0.001 0.001 0.0001 0.0001 0.0001 0 20 40 60 80 100 120 140 160 180 200 220 240 0 20 40 60 80 100 120 140 160 180 200 220 240 0 20 40 60 80 100 120 140 160 180 200 220 240 Paclitaxel Staurosporine Geldanamycin 1.00E+00 100 100 1.00E-01 10 10 GI50, microM GI50, microM GI50, microM 1 1 1.00E-02 0.1 0.1 1.00E-03 0.01 0.01 1.00E-04 0.001 0.001 1.00E-05 0.0001 0.0001 0 20 40 60 80 100 120 140 160 180 200 220 240 0 20 40 60 80 100 120 140 160 180 200 220 240 0 20 40 60 80 100 120 140 160 180 200 220 240 Sensitive 240 cell lines Resistant
    • Chemosensitivity profiles ranked by the D GI50 value across 240 cell lines PD0325901 Lapatinib BMS-387032 -3.0 -3.00 -1.00 -2.5 -2.50D Log GI50, microM -2.0 -0.50 -2.00 D Log GI50, microM D Log GI50, microM D Log GI50, microM -1.5 0.00 -1.0 -1.50 -0.5 -1.00 0.50 0.0 0.5 -0.50 1.00 1.0 0.00 1.5 1.50 0.50 2.0 2.5 1.00 2.00 PD173074 BMS-536924 API-2 (Triciribine) -2.50 -2.50 -2.50 -2.00 -2.00 -2.00 D Log GI50, microM D Log GI50, microM -1.50 D Log GI50, microM -1.50 -1.50 -1.00 -1.00 -1.00 -0.50 -0.50 0.00 -0.50 0.00 0.50 0.00 0.50 1.00 0.50 1.00 1.50 Sensitive 240 cell lines Resistant
    • Chemosensitivity profiles ranked by the D GI50 value across 240 cell lines Erlotinib CL 1040 Sorafenib -3.00 -2.50 -2.50 -2.50 -2.00 -2.00D Log GI50, microM D Log GI50, microM D Log GI50, microM -2.00 D Log GI50, microM -1.50 -1.50 -1.50 -1.00 -1.00 -1.00 -0.50 -0.50 -0.50 0.00 0.00 0.00 0.50 0.50 0.50 1.00 1.00 1.00 Dasatinib VX-680 Everolimus -3.00 -2.50 -3.00 -2.50 -2.50 -2.00 -2.00 -2.00 D Log GI50, microM D Log GI50, microM D Log GI50, microM -1.50 -1.50 -1.50 -1.00 -1.00 -0.50 -1.00 -0.50 0.00 -0.50 0.00 0.50 0.50 1.00 0.00 1.00 1.50 1.50 0.50 2.00 2.00 2.50 1.00 2.50 Sensitive 240 cell lines Resistant
    • Chemosensitivity profiles ranked by the D GI50 value across 240 cell lines Sunitinib Tandutinib Doxorubicin -2.50 -2.50 -2.00 -2.00 -2.00 -1.50D Log GI50, microM -1.50 D Log GI50, microM D Log GI50, microM D Log GI50, microM -1.50 -1.00 -1.00 -1.00 -0.50 -0.50 -0.50 0.00 0.00 0.00 0.50 0.50 1.00 0.50 1.00 1.50 1.00 1.50 Paclitaxel Staurosporine Geldanamycin -2.50 -1.50 -1.50 -2.00 -1.00 -1.50 -1.00 D Log GI50, microM D Log GI50, microM D Log GI50, microM -1.00 -0.50 -0.50 -0.50 0.00 0.00 0.00 0.50 0.50 1.00 0.50 1.00 1.50 2.00 1.00 1.50 Sensitive 240 cell lines Resistant
    • Raf/Ras mutations are associated with sensitivity to Mek inhibitor, PD0325901, whilePIK3CA and RB mutations correlate with resistance -3.0 PD0325901 -2.5 -2.0 D Log GI50, microM -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0 2.5 Sensitive Resistant Raf/Ras mutations PIK3CA mutations RB1 mutations The log difference from the average GI50 value is plotted across the 240 cell lines
    • Raf/Ras mutations are associated with sensitivity to Mek inhibitor, CL 1040, while PIK3CAand RB mutations correlate with resistance CL 1040 -2.50 -2.00 D Log GI50, microM -1.50 -1.00 -0.50 0.00 0.50 1.00 Sensitive Resistant Raf/Ras mutations PIK3CA mutations RB1 mutations The log difference from the average GI50 value is plotted across the 240 cell lines
    • PIK3CA mutations are associated with sensitivity to Everolimus, while KRASmutations confer resistance Everolimus -4.00 -3.00 D Log GI50, microM -2.00 -1.00 0.00 1.00 2.00 3.00 Sensitive Resistant PIK3CA mutations PIK3CA and KRAS KRAS mutations mutations The log difference from the average GI50 value is plotted across the 240 cell lines
    • Ephrin type-A7 & A3 receptor mRNA overexpression and BCR-ABL translocationare associated with sensitivity to Dasatinib Dasatinib -3.00 -2.50 -2.00 D Log GI50, microM -1.50 -1.00 -0.50 0.00 0.50 1.00 1.50 2.00 2.50 Sensitive Resistant EphA7 & EphA3 mRNA BCR-ABL translocation overexpression The log difference from the average GI50 value is plotted across the 240 cell lines
    • CDKN2A mutations are associated with sensitivity to CDK inhibitor, BMS-387032,while CCND2 amplification correlates with resistance -1.00 BMS-387032 -0.50 D Log GI50, microM 0.00 0.50 1.00 1.50 2.00 Sensitive Resistant CDKN2A mutation CCND2 (Cyclin D2) copy number amplification The log difference from the average GI50 value is plotted across the 240 cell lines
    • AKT2 amplification and PTEN mutations are associated with resistance to AKTinhibitor, API-2 (Triciribine) -2.50 API-2 (Triciribine) -2.00 D Log GI50, microM -1.50 -1.00 -0.50 0.00 0.50 1.00 1.50 Sensitive Resistant PTEN mutation AKT2 copy number amplification The log difference from the average GI50 value is plotted across the 240 cell lines
    • FGFR protein family overexpression is associated with sensitivity to FGFR inhibitor,PD173074, while EGFR overexpression correlates with resistance -2.50 PD173074 -2.00 D Log GI50, microM -1.50 -1.00 -0.50 0.00 0.50 Sensitive Resistant FGFR protein family mRNA EGFR mRNA FGFR overexpression in Ras/Raf or overexpression overexpression PIK3CA mutation background The log difference from the average GI50 value is plotted across the 240 cell lines
    • Raf/Ras, PIK3CA and PTEN mutations correlate with resistance to FGFR inhibitor, PD173074 -2.50 PD173074 -2.00 D Log GI50, microM -1.50 -1.00 -0.50 0.00 0.50 Sensitive Resistant Raf/Ras mutations PIK3CA mutations PTEN mutations The log difference from the average GI50 value is plotted across the 240 cell lines
    • EGFR overexpression is associated with sensitivity to EGFR inhibitor, Lapatinib, whileRaf/Ras, PIK3CA or PTEN mutations may confer resistance to the EGFR overexpressing celllines -3.00 Lapatinib -2.50 D Log GI50, microM -2.00 -1.50 -1.00 -0.50 0.00 0.50 1.00 Sensitive Resistant EGFR mRNA EGFR overexpression in Raf/Ras, PIK3CA or overexpression PTEN mutation background The log difference from the average GI50 value is plotted across the 240 cell lines
    • Raf/Ras, PIK3CA and PTEN mutations may correlate with resistance to EGFRinhibitor, Lapatinib -3.00 Lapatinib -2.50 D Log GI50, microM -2.00 -1.50 -1.00 -0.50 0.00 0.50 1.00 Sensitive Resistant Raf/Ras mutations PIK3CA mutations PTEN mutations The log difference from the average GI50 value is plotted across the 240 cell lines
    • EGFR overexpression is associated with resistance to IGF-1R inhibitor, BMS-536924 -2.50 BMS-536924 -2.00 D Log GI50, microM -1.50 -1.00 -0.50 0.00 0.50 1.00 Sensitive Resistant EGFR overexpression in EGFR mRNA EGFR mutation background overexpression The log of the difference from the average GI50 value is plotted across the 240 cell lines
    • K-Ras, PIK3CA and PTEN mutations may correlate with resistance to IGF-1Rinhibitor, BMS-536924 -2.50 BMS-536924 -2.00 D Log GI50, microM -1.50 -1.00 -0.50 0.00 0.50 1.00 Sensitive Resistant K-Ras mutations PIK3CA mutations PTEN mutations The log difference from the average GI50 value is plotted across the 240 cell lines
    • ConclusionsWe generated chemosensitivity profiles over 240 cell lines to reveal drugsensitivity and resistance patterns and identified markers associated with aspecific response. It was found that Raf/Ras mutations confer sensitivity to MEKinhibitors, PD0325901 and Cl 1040, while PIK3CA and RB mutations wereassociated with resistance. Resistance to IGF-1R, FGFR, and EGFR inhibitorscorrelated with PI3K/PTEN/Akt or Raf/Ras pathway activation. EGFR mRNAoverexpression was associated with resistance to FGFR and IGF-1R inhibitors.Resistance to AKT inhibitor, API-2 (Triciribine), was associated with PTENmutations and amplification of AKT. PIK3CA mutations were associated withsensitivity to Everolimus, while KRAS mutations confer resistance. Dasatinibsensitivity was associated with BCR-ABL translocation and Ephrin type-A7 andA3 receptor mRNA overexpression.