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Supporting Information Supporting Information Pratilas et al. 10.1073/pnas.0900780106 SI Text HER2) xenografts. In each of these analyses, all noncontrol Determination of Sensitivity to MEK Inhibition. Drug sensitivity probes (n ϭ 22,215) were rank-ordered according to the mag- assays were performed by using a 96-well plate and the Alamar nitude of their difference in expression after MEK inhibition Blue reagent (Invitrogen) as reported (1). The cells were treated compared with DMSO-treated controls, as measured by SAM- with PD0325901 (Pfizer) in a range of concentrations from 0.1 derived d-scores. The positions of the output genes in this signed to 500 nM (Fig. S1). ranking were then scored in a manner similar to that described by the Connectivity Map (2). This empirical and nonparametric Enrichment Analysis Over a Time Course of MEK Inhibition. Af- Kolmogorov-Smirnov-based statistic reflects an enrichment fymetrix U133A 2.0 array analysis of V600EBRAF, SkMel-28 cells, score that ranges from ϩ1toϪ1, where a score of 0 is a lack of at 0, 2, 8, and 24 h after MEK inhibition was completed as enrichment in either direction of expression, or graphically, a described (see Experimental Procedures). Robust multiarray av- random distribution of the output profile genes. Those with erage (RMA) was used to estimate the expression of probe sets. enrichment scores nearer to 1 indicated increasing correlation Each time point from2hto24wascompared with 0 h, and in between the output profile and the rank-ordered gene set from each comparison, we considered only probe sets with an expres- the experimental comparison. sion in log2 space greater than the first quartile of expression on each array. Thus, either time 0 or the time point under study in Oncomine Concepts Map. We performed Oncomine Concepts each comparison had to contribute an expression value exceed- analysis (OCM; www.oncomine.org/ocm) (3, 4) on the 36 probe ing this threshold before a fold change difference was consid- sets not identified as elements of consensus ERK signaling ered. We then generated a fold change difference in expression pathways (as shown in Fig. 2), from the signature of MEK between the 2 experimental time points: 0 and 2, 0 and 8, 0 and inhibition in mutant BRAF cells. Affymetrix probe set identi- 24 h. Genes were annotated and exported if the absolute value fiers for each of the 36 genes were converted to HUGO gene of its fold change was Ͼ2. symbols and batch-loaded to OCM for analysis. Gene concepts Down-regulated, or underexpressed, probe sets (n ϭ 63, 173, sharing significant overlap with this 36-gene set were identified and 187 at time points 2, 8, and 24 h respectively) were grouped and included concepts defined by drug sensitivity, gene expres- as belonging to 1 of 9 monitored classes of gene function as sion, and annotation concepts (Fig. S6). annotated by Gene Ontology (GO) (Table S1). They were selected to reflect the direction of expression of whole classes of MIAME Checklist. Type of experiment. This study used microarray genes relative to the phenomenological activity expected upon expression analysis to identify global changes in transcript al- MEK inhibition. We included both 1 positive control and 2 teration in response to MEK inhibition. Genes under ERK negative control annotations. The former was the homogenous control were identified in a panel of V600EBRAF and RTK- MAP kinase phosphatase activity annotation, containing only activated tumor cells and xenografts, using short-term inhibition members of the DUSP family of phosphatases. The latter two, of ERK activity by the MEK inhibitor PD0325901 (Pfizer). DNA replication and ribosome biogenesis, represent secondary Experimental factors. Cell lines growing in culture (n ϭ 12) and and tertiary function considerably downstream of the primary murine xenografts (n ϭ 2) were treated with the MEK inhibitor expected signaling effect of MEK inhibition. Each gene function PD0325901 or vehicle alone as control. Cell lines were treated annotation was tested for statistically significant enrichment with 50 nM PD0325901 or 0.1% DMSO for 8 h. Mice were (one-sided Fisher exact test) against this down-regulated gene treated with a single oral dose of PD0325901 (25 mg/kg) or set derived at each time point compared with0h(Fig. S2). vehicle alone and killed 8 h later. We found that the positive control annotation of MAPK Number of hybridizations performed in the experiment. A total of 36 phosphatase activity and genes involved in the regulation of hybridizations on oligonucleotide arrays (Affymetrix signal transduction were most significantly enriched at2hwith HG࿝U133A 2.0) were performed. the latter peaking at 8 h. Those genes with functional roles in Hybridization design. The Affymetrix single-color system was used. transcription factor activity, cell proliferation, and cell cycle Quality-control steps taken. Standard Affymetrix control recom- progression were maximally enriched at the 8-h time point, mendations were used. Quality assessment of cRNA was per- whereas genes responsible for cell-to-cell signaling and regula- formed on the RNA 6000 NanoAssay by using a Bioanalyzer tion of transcription from the polymerase II promoter were 2100 (Agilent). maximally enriched at 2 h. We found that genes involved in 2 Origin of the biological sample and its characteristics. Human cell lines processes related to the proliferation of all cells, DNA replica- (SkMel-1, SkMel-5, SkMel-19, SkMel-28) were provided by A. tion and ribosome biogenesis, were maximally enriched at 24 h. Houghton; MALME3M, Colo205, HT29, BT474, SkBr3, MDA- We therefore decided that this latter time point would likely MB-468, A431, and NCI-H1650 were obtained from ATCC. reflect largely secondary effects and not those directly affected Murine xenografts were established in athymic mice by using by suppression of ERK signaling. These data formed the justi- 5–10 ϫ 106 cells per mouse prepared in a 1:1 mixture of fication for investigating a panel of cell lines after an 8-h cells/Matrigel basement membrane and injected s.c. exposure to MEK inhibitor. Protocol for preparing the hybridization extract. Total cellular RNA was extracted from harvested cells or excised xenografts by using Rank Order Analysis. To further assess the significance of the 52 the Qiagen RNeasy extraction kit and methods provided by the genes identified as comprising the ERK output profile in mutant manufacturer. BRAF tumor cell lines, we determined their position in a list of Labeling protocols. Standard Affymetrix protocols (Affymetrix all genes rank-ordered by magnitude of change in expression GeneChip Expression Analysis) were used. after MEK inhibition, in 3 other systems treated with the MEK Protocol and conditions used during hybridization. Standard Af- inhibitor. These included the RTK cell lines (n ϭ 5) and fymetrix protocols (Affymetrix GeneChip Expression Analysis) SkMel-28 (V600EBRAF) and BT474 (WTBRAF, amplified were used. Pratilas et al. www.pnas.org/cgi/content/short/0900780106 1of11 Type of scanning hardware and software used. Microarrays were cell line and xenograft data in both experimental conditions and scanned by using a high-numerical aperture and flying objective subsequently log base 2 transformed. The time-course analysis (FOL) lens in the GS300 scanner (Affymetrix) and quantified by using data were quantified and normalized with Robust Multiarray GeneChip Operating Software version 1.4 (GCOS; Affymetrix). Average (RMA). All statistical analyses were performed in R Type of image analysis software used. GeneChip Operating Software software. version 1.4 (GCOS; Affymetrix) was used. Array design. Platform type was Affymetrix oligonucleotide array. The complete output of the image analysis before data selection and Surface and coating specifications were glass. The arrays used in transformation (spot quantitation matrices). Original Affymetrix out- ࿝ put files (.CEL files) were used. this study, Affymetrix HG U133Av2 are commercially available Data selection and transformation procedures. GeneChip Operating (Affymetrix). For features and reporters on the array see Software version 1.4 was used for signal quantification of both www.affymetrix.com. 1. Solit DB, et al. (2006) BRAF mutation predicts sensitivity to MEK inhibition. Nature 4. Rhodes DR, et al. (2007) Molecular concepts analysis links tumors, pathways, mecha- 439:358–362. nisms, and drugs. Neoplasia 9:443–454. 2.LambJ,etal. (2006) The Connectivity map: Using gene-expression signatures to 5. Benjamini Y, Hochberg Y (1995) Controlling the false discovery rate: A practical and connect small molecules, genes, and disease. Science 313:1929–1935. powerful approach to multiple testing. J R Stat Soc Ser B 57:289–300. 3. Tomlins SA, et al. (2007) Integrative molecular concept modeling of prostate cancer progression. Nat Genet 39:41–51. Pratilas et al. www.pnas.org/cgi/content/short/0900780106 2of11 Fig. S1. Sensitivity of the panel of cell lines to MEK inhibition. The IC50 of the MEK inhibitor PD0325901 is shown for each of the cell lines used in the panel, segregated by BRAF mutation status: V600E (gray) or WT (blue). Pratilas et al. www.pnas.org/cgi/content/short/0900780106 3of11 Fig. S2. Enrichment of gene function over a time course of MEK inhibition of a V600EBRAF cell line. (A) Nine classes of genes are plotted by functional annotation related to downstream pathway activities. The gene content of each is derived from only those genes whose expression is down-regulated at the plotted time point (x axis) relative to 0 h with a fold change Ͼ2. Plotted on the y axis is the Ϫlog10 of the P value for the enrichment of each class at each time point (one-sided Fisher exact test). (B) For the selected time point (8 h), the aggregate expression of those genes in A are plotted in each functional annotation. Aggregate expression is the mean Z-score of expression. Pratilas et al. www.pnas.org/cgi/content/short/0900780106 4of11 Fig.
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