Figure 7: Sensitive and resistant cell lines to VX-680 with genetic biomarkers.

The log of the difference from the average EC50 is plotted against the various cell lines. CTTNB1 mutations predominate in the most sensitive cells lines and tended to be of colon/GI origin. Those cell lines with CTTNB1 mutations that were resistant were not of colon origin. APC mutations tended to be intermediate/resistant with no APC mutations in the 50 most sensitive cell lines.

Figure 4: Sensitive and resistant cell lines to Erlotinib with genetic biomarkers.

The log of the difference from the average IC50 value was plotted against the 240 cell lines. Kras mutations correlated with resistance. Genetic analysis of mRNA data was not complete, but the few known cell lines that overexpress EGFR were identified as sensitive. Cell lines with EGFR mutations that were not sensitive also had mutations in the Ras/Raf pathway.

Figure 2. CVs in the nuclear channel were low. The CV of control wells was averaged over 3 independent experiments. Overall, 91% of cell lines had a CV of less than 20% and only 11 non-adherent cells had a CV greater than 25%.

All cells were grouped according to morphology and the CVs of the control wells were averaged and binned according to the range of CVs: a) adherent cells; b) semi-adherent cells; c) non-adherent cells.

Profiles of Contributing genes to sensitive/resistant PhenotyPe of 11 Different onCology theraPeutiC agents aCross 240 Cell lines.

O’Day, C., Ovechkina, Y., Marcoe, K.F., Keyser, R., Yoshino, K., Nguyen, P., Hnilo, J., Shively, R., Mulligan, J., Bernards, K., Chesnut-Speelman, J., Lin, T., and Wang, S.Ricerca Biosciences LLC – Bothell, WA, USA

PurPoseA number of targeted therapies have been shown to be effective in the treatment of cancer, such as Imatinib for treating chronic myelogenous leukemia, Erlotinib for non-small-cell lung cancers and Sorefinib for metastatic lung cancer. The sporadic sensitivity to these therapeutic agents has launched an investigation of correlation between cancer phenotype and genotype. We have developed an in vitro cellular assay to evaluate the relationship between tumor genotypes (Affymetrix SNP and gene expression chips and Sanger mutation data) and cancer cell sensitivity for over 240 human tumor cell lines. A panel of targeted therapeutics was used to show the usefulness of this in vitro approach for developing anticancer drugs. Data for nine of the eleven evaluated therapeutics is shown below. Data was not shown for Staurosporine, Paclitaxel or Doxorubicin in the interest of space.

MethoDsGrowth and assay conditions were established for all 240 cell lines. Compounds were added in half-log dilutions for 10 concentrations using tipless acoustic transfer with an Echo 550. An additional “time zero” (T0) plate also was seeded at the same density and analyzed for cell number on day one to determine the number of doublings. Seventy-two hours after compound addition, the cells were fixed and stained with antibodies for activated caspase-3 and phospho-histone H3. Nuclei were stained with DAPI. Cells were imaged with a 4X objective on an IN Cell Image Analyzer and analyzed with the Developer software tool. Data was plotted with in-house Math IQ graphing software using nonlinear regression analysis. Data was analyzed for cell count (% of control), fold induction of apoptosis (% of control) and fold induction or decrease in G2 (% of control). All data was normalized to control wells. Reference compound data was analyzed and pooled. Cell lines were binned to sensitive and resistant lines based on acceptable in vivo dosage levels or a marked delineation of sensitivity. Sensitive and resistant cell lines were then correlated to mutation spectrums to determine genes underlying the corresponding phenotype (Fig.1). Mutation data was used to analyze these cell lines. Analysis of expression and SNP data is currently underway.

ConClusions

Table 1. Multiplexed cytotoxicity assay parameters are robust. Intra-assay variability in EC50 of Staurosporine on HCT-116 over 10 independent experiments.

Cell line HCT-116 was propagated and plated in 10 different experiments. Reference compound controls were added in accord with our standard assay. Data was collected, analyzed, and averaged with standard deviations. Results are reported above.

Figure 1: Assay Workflow

Table 2: Panel of mutations generated from Sanger Database

Figure 1: Cells are plated in 384 wells and treated with inhibitor (staurosporine) for 72 hours. Cells were fixed and stained with anti-activated caspase 3 (green), anti-phospho-histone H3 (red) and DAPI for cell number (blue). All data is normalized to vehicle control wells and reported as % of control (nuclear count) or fold induction (apoptosis and cell cycle). Data is binned into sensitive and resistant cell lines and analyzed for genetic correlations.

All cell lines were analyzed for:

1. Mutation data (Available on most cell lines. Twenty two % of the cell lines did not have mutation data.)

2. SNP analysis (Affymetrix SNP 500K array)

3. Gene expression data (Affymetrix U133 plus 2.0 array)

Genetic data was generated in house, through the CABIG site and the Sanger site. All data was normalized through RMA normalization Gene copy number and mRNA expression data.

https://cabig.nci.nih.gov/caArray_GSKdata/

50+ Gene Mutation data

http://www.sanger.ac.uk/genetics/CGP/Celllines

“The mutation data was obtained from the Sanger Institute Catalogue Of Somatic Mutations In Cancer web site, http://www.sanger.ac.uk/cosmic Bamford et al (2004) The COSMIC (Catalogue of Somatic Mutations in Cancer) database and website. Br J Cancer, 91,355-358.”

a) b) c)

Figure 5: Sensitive and resistant cell lines to CL-1040 with genetic biomarkers.

The log of the difference from the average EC50 value was plotted against the various cell lines. Ras/Raf mutations predominated in the sensitive cells and RB mutations conferred resistance. The one Braf mutation that was not sensitive, harbored a G464V mutation rather than the activating V600E mutation.

Figure 6: RB mutations and Ras/Raf activation are competing processes.

Cells harboring a Ras/Raf activating mutation, activate CDK cyclin and ERK, which phosphorylate RB. Phosphorylated RB dissociates from the transcription complex and E2F is able to transcribe RNA and translate proteins needed for entry to S phase. However, if RB is mutated, E2F is constitutively activated and MEK inhibition is not able to inhibit transcription. Hence, Rb mutations confer resistance to CL-1040.

G464V

EndocrineLiverLungStomach

and colon

Table 3: Colon/GI cancers with CTNNB1 mutations are sensitive to Aurora inhibition. CTNNB1 mutations made up 4 of the 5 most sensitive cell lines in the 32 colon/GI cancers shown below. B-catenin mRNA levels are being examined for over-expression. APC mutations predominate in the resistant cells but APC mutations are thought to be mutually exclusive of CTNNB1 mutations. Other genes found through expression analysis might give a more complete picture of this sensitivity.

Summary of Erlotinib•Krasmutationsconferresistancetotreatment

•3EGFRmutationswerepresentinthe240celllines.Onewassensitiveand the two others were intermediate/resistant because of Ras/Raf mutations

Summary of CL-1040 Braf mutations clearly predominate in the sensitive cell lines

•15ofthe30mostsensitivecelllineshadBrafmutations

•Noneofthe30mostresistantcelllineshadBrafmutations

•OnesomewhatresistantBrafmutationwasaG464Vratherthanthetypical V600E mutation

Ras mutations had a positive correlation with sensitive cells but weaker than Braf

•Allofthe30mostsensitivecelllinescontainedBraforRasmutations

•1outofthe30mostresistantcelllineshadaRasmutation

Rb mutations appear exclusively in the resistant cell lines

•8ofthe30mostresistantcelllineshadaRbmutation

•0ofthe30mostsensitivecelllineshadaRbmutation

•RbproteinintersectstheRas/RafpathwayatCDK-cyclincontrolofSphase transcription

Summary of VX-680CTNNB1 mutations predominate in the sensitive cell lines

•4outofthe33colon/GIcelllineshaveaCTTNB1mutationandthesemutations are 4 of the 5 most sensitive cell lines to VX-680

•5ofthe8CTNNB1mutationsoccurinthesensitivecelllinesdeterminedto have a GI50 of 0.005 to 0.025; One CTNNB1 mutated cell line is in the resistant category

•4ofthe4coloncancerswithCTTNB1mutationsaresensitive

APC mutations do not exist in the sensitive lines but predominate in the intermediate/resistant cell lines

•0ofthe30mostsensitivecelllineshaveAPCmutations.

•2 of the 30 most resistant cell lines have APC mutations. APCmutations may be in the resistant/intermediate cell lines because they are exclusive of CTNNB1 mutation

Sensitive

Intermediate

Resistant

Figure 3: Distribution plot of sensitive and resistant cell lines.

EC50 values were plotted against IC50 values for many of the 240 cell lines. For some agents that generated incomplete growth inhibition (GI), GI50 values or max % growth inhibition was plotted against the EC50 values (Fig. 3a. and i). Sensitive cell lines were selected by a clear demarcation from the others such as in figures 3b, c, e, f, and g. For Geldanamycin (Fig. 3d) all cell lines responded over a small range but a few were resistant. For Dasatinib (Fig. 3c) CML lines were most sensitive. However, a subset of the cell lines did not demonstrate good growth inhibition when results were adjusted for the number of cells plated. Similarly, with Everolimus (Fig 3a) two groups of sensitive and resistant cells were apparent but of the sensitive lines, some showed poor growth inhibition when results were adjusted for the number of cells plated. CL-1040 did not show a clear demarcation between sensitive and resistant and thus cutoff was made based on in vivo dosage levels.

Data will be further validated by correlating genes from expression analysis and gene copy number. Analysis of this data is currently in progress.