Combined Gene Expression Profiling and Rnai Screening in Clear Cell Renal Cell Carcinoma Identify PLK1 and Other Therapeutic Kinase Targets

Published OnlineFirst June 3, 2011; DOI: 10.1158/0008-5472.CAN-11-0076

Cancer Therapeutics, Targets, and Chemical Biology Research

Combined Gene Expression Profiling and RNAi Screening in Clear Cell Renal Cell Carcinoma Identify PLK1 and Other Therapeutic Kinase Targets

Yan Ding1, Dan Huang1, Zhongfa Zhang1, Josh Smith1, David Petillo1, Brendan D. Looyenga2, Kristin Feenstra3, Jeffrey P. MacKeigan2, Kyle A. Furge1,4, and Bin T. Teh1,5

Abstract In recent years, several molecularly targeted therapies have been approved for clear cell renal cell carcinoma (ccRCC), a highly aggressive cancer. Although these therapies significantly extend overall survival, nearly all patients with advanced ccRCC eventually succumb to the disease. To identify other molecular targets, we profiled gene expression in 90 ccRCC patient specimens for which tumor grade information was available. Gene set enrichment analysis indicated that cell-cycle–related genes, in particular, Polo-like kinase 1 (PLK1), were associated with disease aggressiveness. We also carried out RNAi screening to identify kinases and phosphatases that when inhibited could prevent cell proliferation. As expected, RNAi-mediated knockdown of PLK1 and other cell-cycle kinases was sufficient to suppress ccRCC cell proliferation. The association of PLK1 in both disease aggression and in vitro growth prompted us to examine the effects of a small-molecule inhibitor of PLK1, BI 2536, in ccRCC cell lines. BI 2536 inhibited the proliferation of ccRCC cell lines at concentrations required to inhibit PLK1 kinase activity, and sustained inhibition of PLK1 by BI 2536 led to dramatic regression of ccRCC xenograft tumors in vivo. Taken together, these findings highlight PLK1 as a rational therapeutic target for ccRCC. Cancer Res; 71(15); 1–10. 2011 AACR.

Introduction and pazopanib, which target the receptor tyrosine kinases of vascular endothelial growth factor and platelet-derived In 2010, in the United States, an estimated 58,000 people will growth factor, have recently been approved by the Food be diagnosed with, and 35,000 deaths will be attributed to, and Drug Administration for ccRCC therapy, but the cancers of the kidney and renal pelvis (1). Kidney cancer can responses are usually partial and most patients eventually be divided into several histologic subtypes, but the majority of experience progression (5, 6). Therapies directed against the the cases (about 75%) are of the clear cell renal cell carcinoma mTOR have also been used to treat advanced disease, but (ccRCC) subtype (2). Surgery offers the best opportunity to again most patients have disease progression (7). Thus, there cure localized ccRCC. However, most patients who experience remains a critical need for effective and specifically targeted recurrence after surgery or who have metastatic disease at the therapies for ccRCC. time of diagnosis will ultimately succumb to the disease. Gene expression profiling has been successfully used to find Immunotherapy with agents such as interleukin-2 (IL-2) has genes that are differentially expressed among RCC subtypes, been the only choice for metastatic renal cell carcinoma (RCC) correlated with chromosomal abnormalities, or correlated patients, with 7-8% of individuals showing complete remission with deregulated oncogenic pathways (8–10). However, find- following treatment (3, 4), but IL-2 is beneficial to only a small ing therapeutic targets from those lists of genes is still number of patients. New agents such as sunitinib, sorafenib, challenging. Genes whose expression varies with clinical para- meters such as tumor grade, stage, or survival duration may be more helpful in identifying molecular targets, but they require Authors' Affiliations: Laboratories of 1Cancer Genetics, 2Systemic Biol- ogy, 3Analytical Cellular and Molecular Microscopy, and 4Computational additional validation (11, 12). Biology, Van Andel Research Institute, Grand Rapids, Michigan; and The discovery of RNA interference (RNAi) and the advance 5NCCS-VARI Translational Research Laboratory, National Cancer Centre of technologies for using RNAi on large sets of genes in Singapore, Singapore mammalian cells—either siRNA or short hairpin RNA Note: Supplementary data for this article are available at Cancer Research (shRNA)—allow us to systematically interrogate gene func- Online (http://cancerres.aacrjournals.org/). tions at high throughput (13–16). Such an approach has Corresponding Author: Jeffrey P. MacKeigan or Kyle A. Furge or Bin T. Teh, Van Andel Research Institute, 333 Bostwick Avenue NE, Grand proven successful in the discovery of genes that were compo- Rapids, MI 49503. Phone: 1616-234-5296 (B.T.T.); Fax: 1616-234-5297; nents of the p53 tumor-suppressor pathway (13), of genes that E-mail: [email protected] or [email protected] or [email protected] when knocked down sensitize resistant cells to chemother- doi: 10.1158/0008-5472.CAN-11-0076 apeutic agents (15, 16), and of genes essential to the prolif- 2011 American Association for Cancer Research. eration of human mammary and colon cancer cells (17, 18).

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Here, we expand upon previous partial kinase library Cells and cell culture screening of ccRCC (19) by examining the effects on cell The A498, ACHN, Caki-1, and 786-O RCC cell lines were proliferation within the whole library of kinases and phos- obtained from the American Type Culture Collection. SN12C phatases. In addition, we used expression profiling data cells were kindly provided by Dr. George Vande Woude (Van þ carried out on 90 ccRCC samples for which we had tumor Andel Research Institute). 786-O cells (WT2, VHL ) and 786-O grade information. Combining these results identified a class cells (RC3, VHL ) were kindly provided by Dr. Michael Ohh of cell-cycle kinases, such as Polo-like kinase 1 (PLK1), as (University of Toronto). The cells were maintained in potential therapeutic targets for ccRCC. Dulbecco's modiﬁed Eagle's medium (Invitrogen) supplemen- ted with 10% FBS (Invitrogen), 100 IU/mL penicillin, and 100 Materials and Methods mg/mL streptomycin (Invitrogen) in a humidified incubator containing 5% CO2 at 37 C. Tissue collection and gene expression profiling Gene expression profiles from 90 ccRCC tumors and 13 Viability staining normal kidney samples were produced as previously described 786-O cells were plated at 2,000 cells per well in a 96-well (10, 20). This data has been deposited at the Gene Expression plate, and to 4 different wells were added 1 of 4 siRNAs Omnibus (GSE 17895). The kidney samples were obtained targeting a single gene. At 24 hours after transfection, the from the Cooperative Human Tissue Network, and approval cells were trypsinized and then transferred to a 6-well plate, was obtained from the Van Andel Research Institute Institu- where the cells were cultured for another 8 to 10 days. Finally, tional Review Board to study the samples. Gene expression the cells were fixed and stained with 1.5% (w/v) crystal violet analysis was conducted as previously described (21, 22). (15). The genes differentially expressed between the weakly aggressive group of tumors (grades I and II) and the highly Cell proliferation assay aggressive tumors (grade IV) were identified using the func- Cells were plated under the same conditions as the primary tion of the linear model for a series of arrays (lmFit) as stated screening. Twenty-four hours later, cells were either trans- in the limma package (23). fected with siRNAs or treated with BI 2536. Cells were further For Gene Ontology (GO) gene enrichment analysis, signifi- cultured for another 4 days and then cell proliferation was cant GO terms were calculated using the Fisher test (raw P assessed using either the MTS assay or the CellTiter-Glo value) or elim Fisher test (adjusted P value) as stated in the top Luminescent assay (Promega). GO package (24). Quantitative reverse transcriptase PCR Survival analysis Total RNA was isolated from 786-O cells 48 hours after Gene expression profiles from 179 ccRCC tumors, with transfection, followed by reverse transcription to cDNA using following survival duration after surgery, were used to carry universal primers and a TaqMan Gene Expression Cells-to-CT out survival analysis as previously described (25). kit (Applied Biosystems). The reverse transcriptase PCR (RT- PCR) reaction was carried out as previously described (15). Statistical analysis For all statistical analyses, values were expressed as mean Cell-cycle analysis SD, except that the relative gene expression values from Cells were incubated with either 10, 20, or 40 nmol/L BI microarrays were expressed as median median absolute 2536; 1:1,000 dilution of 0.1 N HCl (vehicle); or were left deviation (MAD; ref. 26). Values were compared using treatment naïve for 24 hours. Cell-cycle profiles were deter- Student's t-test; P < 0.05 was considered significant. mined by flow cytometric analysis as previously described (27). Nocodazole (0.1 mmol/L) was used as a positive control siRNA library screening and target identification for cell-cycle arrest at the G2–M phase. Custom siRNA human kinase and phosphatase library sets were designed and synthesized as previously described (15). Immunofluorescence of cultured cells Our validation data showed greater than 93% transfection Cell lines were grown on coverslips (Nunc Lab-Tek II efficiency in ccRCC cell lines, and this library has been Chamber Slide) for 24 hours and treated the same as in observed to induce, on average, greater than 80% knockdown cell-cycle analysis. The cells were stained with mouse anti- for each mRNA target species in our previously published a-tubulin antibody (1:500; Sigma) followed by addition of a study (15) and this article. Rhodamine Red-X-conjugated (1:200) antibody to mouse IgG. 786-O cells (WT2 or RC3) were seeded onto 96-well plates at 40,6-Diamidino-2-phenylindole (DAPI; 300 nmol/L) was used 1,000 cells per well. Twenty-four hours later, 10 mL of siRNA to highlight DNA. Fluorescently labeled cells were visualized and lipid (Oligofectamine; Invitrogen) mix was added to each using a confocal or fluorescence microscope. well. Cell viabilities were analyzed 4 days after transfection using the CellTiter 96 AQueous assay (MTS assay; Promega). Cell lysate and Western blotting analysis For proliferation analyses, B-score normalization was Cell lysates were prepared by washing cells with PBS and applied to primary screening MTS OD values to eliminate then following published methods (28), Western blotting plate-to-plate variability and well-position effects (26). was conducted as previously described (28), except that the

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primary antibody was mouse antiphosphorylated histone H3 for example, the GO terms "mitosis" (GO:0007067, raw P ¼ (Ser10). 4.30 10 13, adjusted P ¼ 4.30 10 13) and "cell-cycle phase" (GO:0022403, raw P ¼ 1.60 10 13, adjusted P ¼ Xenograft models 0.024; Supplementary Table S3 and Supplementary Fig. S1). All animal studies were in compliance with VARI Institu- The GO term "cell cycle" (GO:0007049) was the highest level tional Animal Care and Use Committee (IACUC) policies. Six- of parent node for these 6 related significant nodes, and it week-old female BALB/c nu/nu nude mice (Charles River) was itself also significantly related to aggressiveness (raw were given subcutaneous injections of 3 106 786-O, A498, P ¼ 2.3 10 12, adjusted P ¼ 0.11; Supplmentary Fig. S1 Caki-1, or SN12C cells in the right flank. Tumor size was and Supplementary Table S3). Within the GO term "cell measured as previously described (27). cycle," 117 genes were identified as being associated with aggressiveness, representing 10.1% (117/1,159) of the aggres- Tumor growth study siveness-related genes (Fig. 1A). Thus, genes associated When tumors had grown to an average volume of 200 to 300 with the cell cycle were strongly associated with ccRCC mm3, mice were separated into 2 groups of 5 animals. For 1 aggressiveness. treatment cycle, 1 group received an intratumoral injection of When the analysis was conducted using the Molecular BI 2536 either once or twice per day on 2 consecutive days per Function GO categories, one of the significant related nodes week, at a dosage of 50 mg/kg per injection; the vehicle control was the GO term "kinase activity" (GO:0016301; raw P ¼ 4.14 group received 0.1 N HCl. The mice received 3 to 4 treatment 10 3, adjusted P ¼ 0.19), which is the parent node of GO terms cycles before sacrifice. of "protein kinase activity" (GO:0004672, P ¼ 5.97 10 3, adjusted P ¼ 0.38) and "protein serine/threonine kinase Target modulation study activity" (GO:0004674, raw P ¼ 3.35 10 3, adjusted P ¼ When tumors had grown to an average volume of 400 to 500 3.35 10 3). Another significant enriched GO term was "ATP mm3, tumor-bearing mice were separated into 2 groups of 5 binding" (GO:0005524, raw P ¼ 3.61 10 3; adjusted P ¼ 4.30 animals. Then, the mice were treated twice on the first day and 10 3), which includes 661 kinases (Supplementary Table S4 once on the following day by intratumoral injection of BI 2536 and Supplementary Fig. S2). Seventy-two genes in the GO term (50 mg/kg per injection) or of 0.1 N HCl. Six hours after the "kinase activity" were identified as being associated with third treatment, the mice were sacrificed. aggressiveness, representing 6.21% (72/1,159) of the aggres- Immunohistochemical staining for phosphorylated histone siveness-related genes (Fig. 1A). These results highlight the H3 (Ser10) was carried out as described (20). Phosphorylated importance of kinases in ccRCC aggressiveness. histone H3 (Ser10) antibody (Cell Signaling) was used at a There was an overlap of 101 genes between the "cell cycle" dilution of 1:50. The quantification of proliferation index was and the "kinase activity" GO terms. Of the overlapped genes, also carried out as previously described (20). 19.8% (20/101) were significantly related with disease aggressiveness, and 85% (17/20) of those were serine/threonine Results kinases (Supplementary Fig. S3). In particular, PLK1, Aurora kinase B (AURKB), and cyclin-dependent kinase 1 (CDK1) are Genes associated with aggressive ccRCC 3 representatives of these 20 cell-cycle–related kinases (CCRK; Gene expression profiling was carried out on 90 ccRCC Fig. 1B). The significance of these kinases is supported by patient samples for which tumor grade information was patient survival analysis using another cohort of 179 patients available (Supplementary Table S1). To identify individual (Fig. 1C and Supplementary Fig. S4). genes whose expression is associated with tumor aggressiveness, we first filtered out genes that did not show much Importance of cell-cycle kinases for ccRCC cell line difference among the patients, using 1.414 (log2 value <0.5) proliferation in vitro as the cutoff for interquartile expression levels. This left about We used a cell-based assay to identify genes that were half the genes (9,824/18,185) as candidates for further analysis. essential to ccRCC cell proliferation, and we carried out a Then, we classified the patients into 2 groups, weakly aggres- high-throughput siRNA screen targeting the whole kinome and sive (grades I and II) and highly aggressive (grade IV). A linear phosphatome using an isogenic pair of ccRCC cell lines, 786-O þ model was used to identify genes differentially expressed (RC3, VHL ) and 786-O (WT2, VHL ; ref. 30), trying to find between these 2 groups. We identified 1,159 genes as being targets specific required for VHL-mutated cell proliferation. significantly associated with aggressiveness when highly Each cell line was transfected with 4 unique siRNA duplexes expressed [False Discovery Rate (FDR) <0.2 and fold change targeting each of 678 known and putative kinases and 198 >1; Fig. 1A and Supplementary Table S2]. known and putative phosphatases in a 1-gene/1-well format on 96-well microtiter plates. The transfection efficiency was High expression of cell-cycle–related kinases is greater than 93% (Supplementary Fig. S5). At 96 hours after associated with tumor aggressiveness transfection, cell proliferation was measured using an MTS To place the individual genes into biological context, a gene assay, which measures the activity of reductase enzymes enrichment analysis approach based on GO was used (29). in living cells (31). Raw absorbance values were normalized When the Biological Process GO categories were examined, 6 to internal reference control samples on each plate to permit out of the top 10 GO terms were associated with the cell cycle, plate-to-plate comparisons, and each well was assigned a

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A B C 350 *** 100 Expression analysis AURKB AURKB (18185 genes) 300 80 250 60 n = 90 200 150 40 Deregulated in ccRCC n = 89 (9824 genes) 100 20 Survival (%)

Relative mRNA (%) Relative 50 0 0 Associated with grade NG1G2G3G4 0 5 10 15 20 (1159 genes) 500 ** 100 (y) 400 CDK 80 CDK

300 60 n = 90

40 200 n = 89 Cell-cycle– Kinase

related 100 Survival (%) 20 (72 genes)

(117 genes) mRNA (%) Relative 0 0 N G1G2G3G4 0 5 10 15 20 (y) 250 * 100 PLK1 200 PLK1 Cell-cycle–related 80 kinases (20 genes) 150 60 n = 90

100 40 n = 89 50 Survival (%) 20

Relative mRNA (%) Relative 0 0 N G1G2G3G4 0 5 10 15 20 n = 13 3 32 39 16 (y)

Figure 1. Increased expression of CCRK is associated with advanced ccRCC. A, schematic showing the gene selection criteria to identify classes of genes associated with high-grade ccRCC. On the basis of gene expression profiling data, genes that were upregulated in ccRCC relative to nondiseased tissue were filtered to identify those that were differentially expressed between low- and high-grade tumors (see Material and Methods). Gene enrichment analysis revealed the importance of both cell cycle-related genes and protein kinases in high-grade ccRCC. B, relative gene expression levels of the CCRK Aurora kinase B (AURKB), CDK1, and PLK1 in nondiseased kidney tissue (N) and ccRCC tumors that are grouped according to tumor grades (G1, G2, G3, and G4). The relative gene expression values are expressed as median MAD. *, P < 0.05; **, P < 0.01; ***, P < 0.001. C, expression of genes shown in (B) in 179 ccRCC samples. The tumor samples were separated into 2 groups based on higher-than-average expression (black) or lower-than-average expression (grey) and evaluated for differences in patient cancer-specific survival using the Kaplan–Meier method.

B-score after normalization of the position effects (26). vidually in the 786-O, A498, ACHN, Caki-1, and SN12C cell Although we started with the idea of finding synthetic lethal lines. To rule out potential assay effects, proliferation rates genes, we did not find such targets except for the genes which were measured by quantitation of ATP levels (CellTiter-Glo) have been reported before (19). Next, we used the average B- rather than by reductase activity (32). All ccRCC cell lines score from these 2 cell lines to choose positive hits regardless of showed a similar requirement, regardless of VHL status, for VHL status (Supplementary Table S5). the NME3, PLK1, CCRK, NADK, PCTK3, deoxyguanosine kinase In this screen, siRNAs having an average B-score of less than (DGUOK), and glucokinase (GCK) genes for cell survival in vitro 3 were defined as proliferation genes for ccRCC (Fig. 2A). (Fig. 2C and Supplementary Fig. S6A). Overall, we identified 35 kinases, including PLK1, nonmeta- To confirm these results, 786-O cells were transfected with 4 static cells 3 (NME3), CCRK, NAD kinase (NADK), and siRNAs individually targeting 1 of 5 different kinases. The cells PCTAIRE protein kinase 3 (PCTK3), as well as 2 phosphatases, were transferred to 6-well plates and allowed to grow for 8 to protein phosphatase 1 regulatory (inhibitor) subunit 3F 10 days and then were stained with crystal violet to visualize (PPP1R3F) and 6-phosphofructo-2-kinase/fructose-2,6-bipho- the relative number of cell colonies (Fig. 2D and Supplemen- sphatase 2 (PFKFB2). To get a functional overview of these tary Fig. S6B). At the same time, the mRNA levels for the data, the genes were classified according to function; the kinases were measured using quantitative PCR (Q-PCR) fol- majority of hits were metabolic and cell-cycle kinases and lowing knockdown by single siRNAs (Fig. 2E and Supplemen- phosphatases (Fig. 2B). tary Fig. S6C). The results were consistent, showing that the A subset of these genes was selected for further study. To effective siRNAs were targeting their specific targets and that a rule out potential off-target and cell line effects of the siRNA decrease of candidate gene expression was associated with screen, each gene was targeted with 4 different siRNAs indi- decreased cell proliferation. In summary, we identified 37

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A B 6 6 3

3 0 Others Cell cycle 0 n = 12 n = 8 −3 −3 − - 6

−6 EPHB2 DGUOK −9 AATK Metabolic - (B-score) NADK - n = 2 L PCTK3 2 (B-score) − ipid, n = 6 − - 9 Calcium, 12 - NME3 Relative proliferation Relative

−12 n proliferation Relative −15 Apoptosis,MAPK n = = 4 PLK1 PLK1 n = 3 −15 NME3 −18

Lipid

Others Control

Cell cycle Metabolic C D 125 siPLK1 100 siRNA siPLK1 siNME3 * * 75 * * * * * ** * C 12 * * * ** 50 * *** * S 34 25 Proliferation (%) Proliferation 0 S 1234 S 1234 S 1234 S 1234 S 1234 E 125 siNME3 125 PLK1 125 NME3 100 * * * 100 100 * * * * * * 75 75 75 * * * 50 * 50 50 25 25 25 Proliferation (%) Proliferation 0 mRNA (%) Relative 0 mRNA (%) Relative 0 S 1234 S 1234 S 1234 S 1234 S 1234 S 1 2 3 4 S 1 2 3 4 786-O A498 ACHN Caki-1 SN12C

Figure 2. siRNA screen to identify kinases and phosphatases important for ccRCC proliferation. A, 786-O (RC3, VHL) and 786-O (WT2, VHLþ) cells were transfected with siRNAs directed against known and putative human phosphastases (n ¼ 198) and kinases (n ¼ 678). Cells were incubated for 96 hours and proliferation was measured using the MTS assay. The B-score for each siRNA is plotted (see Materials and Methods). The top 37 genes are shown in light grey. B, The 37 top genes are classified by their known functions (left), and the B-scores for groups with more than 4 genes are graphed; the median B-score is indicated by the bar. C, proliferation of human ccRCC cell lines was measured using a CellTiter-Glo assay with a nonsilencing scrambled siRNA control (S) and 4 different siRNA duplexes (1, 2, 3, and 4) targeting the indicated gene. The relative numbers of cells were normalized to lipid-only controls (not plotted). *, P < 0.05. D, 786-O cell proliferation was measured 8 to 10 days after the introduction of a lipid-only control (C), a nonsilencing scrambled control (S), or an siRNA duplex (1, 2, 3, or 4) targeting the indicated gene. Cells were fixed and stained with crystal violet. E, 786-O cells were treated as in D. After 48 hours, total RNA was isolated, and primers were designed to specifically amplify the indicated genes.

Q-PCR reactions used TaqMan Gene Expression assays and the comparative Ct method for relative expression. The data were normalized to the expression of nonsilencing scrambled siRNA controls (S). genes, including PLK1, that are important to ccRCC cell line (Supplementary Fig. S7). We previously examined the role of proliferation in vitro (Table 1). the Aurora kinases in ccRCC, showing that inhibition of this class of kinases suppresses the growth of ccRCC (25). Here, we Inhibition of PLK1 function suppresses ccRCC cell used the small-molecule inhibitor of PLK1, BI 2536, which has proliferation in vitro recently become available, to examine the effects of PLK1 The combined results of the aggressiveness analysis and the inhibition on ccRCC. The cell lines 786-O, A498, ACHN, Caki-1, cell line proliferation screening indicated that cell-cycle– and SN12C were treated for 96 hours with concentrations of BI related genes were important to both disease progression 2536 from 5 to 80 nmol/L (Fig. 3A). These concentrations were and cell proliferation. Specifically, we found that 3 kinases previously reported to inhibit PLK1 kinase activity in vitro (33, (AURKB, PLK1, and JAK3) were identified in both data sets 34). BI 2536 suppressed the proliferation of the ccRCC cell

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Table 1. Functional categories of in vitro proliferation kinases and phosphatases

Accession Symbol Description B-score Notes Number

Metabolic NM_002513 NME3 Nonmetastatic cells 3 14.46 NM_023018 NADK NAD kinase 6.23 NM_001929 DGUOK Deoxyguanosine kinase 4.90 NM_000162 GCK Glucokinase 4.39 NM_182471 PKM2 Pyruvate kinase, muscle 4.23 NM_006212 PFKFB2 6-Phosphofructo-2-kinase/fructose- 3.65 2,6-biphosphatase 2 Cell cycle NM_005030 PLK1 Polo-like kinase 1 (Drosophila) 13.33 NM_002596 PCTK3 PCTAIRE protein kinase 3 7.02 NM_004217 AURKB Aurora kinase B 4.31 NM_001261 CDK9 Cyclin-dependent kinase 9 (CDC2-related kinase) 4.08 NM_012119 CCRK Cell-cycle–related kinase 3.90 NM_003390 WEE1 WEE1 homolog (S. pombe) 3.77 NM_003137 SRPK1 SFRS protein kinase 1 3.64 NM_003157 NEK4 NIMA (never in mitosis gene a)-related kinase 4 3.37 Lipid signaling pathway NM_020126 SPHK2 Sphingosine kinase 2 4.21 NM_004570 PIK3C2G Phosphoinositide-3-kinase, class 2, gamma polypeptide 4.12 NM_005026 PIK3CD Phosphoinositide-3-kinase, catalytic, delta polypeptide 3.44 NM_024779 PIP5K2C Phosphatidylinositol-4-phosphate 5-kinase, 3.23 type II, gamma MAPK signaling pathway NM_004759 MAPKAPK2 Mitogen-activated protein kinase-activated 3.31 protein kinase 2 NM_004579 MAP4K2 Mitogen-activated protein kinase kinase 3.11 kinase kinase 2 NM_001654 ARAF v-raf murine sarcoma 3,611 viral oncogene 3.03 homolog Apoptosis AB014541 AATK Apoptosis-associated tyrosine kinase 5.28 NM_006712 FASTK FAST kinase 3.14 Calcium signaling pathway NM_018584 CaMKIINalpha Calcium/calmodulin-dependent protein kinase II 3.36 NM_006383 CIB2 Calcium and integrin binding family member 2 3.40 Others NM_017449 EPHB2 EPH receptor B2 4.81 Ephrin signaling pathway NM_003215 TEC tec protein tyrosine kinase 4.43 None receptor protein tyrosine kinase NM_015112 MAST2 Microtubule-associated serine/threonine kinase 2 3.64 Microtubule NM_006374 STK25 Serine/threonine kinase 25 (STE20 homolog, yeast) 3.50 Stress NM_005246 FER fer (fps/fes-related) tyrosine kinase 3.50 Cell adhesion (phosphoprotein NCP94) NM_005975 PTK6 PTK6 protein tyrosine kinase 6 3.38 None receptor protein kinase NM_033215 PPP1R3F Protein phosphatase 1, regulatory (inhibitor) 3.38 Unknown subunit 3F NM_182948 PRKACB Protein kinase, cAMP-dependent, catalytic, beta 3.23 cAMP signaling pathway NM_000215 JAK3 Janus kinase 3 (a protein tyrosine kinase, 3.03 JAK-STAT leukocyte) NM_001954 DDR1 Discoidin domain receptor family, member 1 3.20 Receptor tyrosine kinase XM_055866 LMTK3 Lemur tyrosine kinase 3 3.95 Unknown NM_032017 MGC4796 Ser/Thr-like kinase 3.18 Unknown

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A C BI 2536 120 786-O A498 100 ACHN Aph 40 nmol/L 20 nmol/L Starve Control Buffer Hydr Noc 80 Caki-1 10 nmol/L pHistone H3 60 SN12C α-Tubulin 786-O 40 pHistone H3 Proliferation (%) 20 α-Tubulin Caki-1 0 0 5 10 20 40 80 BI 2536 (nmol/L) B D 786-O Caki-1

70 ∗ Control 60 786-O ∗ 50 ∗ ∗ Caki-1 40 ∗

–M (%) ∗ 2 30 G BI 2536 20 10 50 40 786-O 0 30 Caki-1 Noc 20 Buffer Control cells (%) 10 10 nmol/L20 nmol/L40 nmol/L

"Polo" in mitotic 0 BI 2536 Buffer Control 10 nmol/L20 nmol/L 40 nmol/L BI 2536

Figure 3. Inhibition of PLK1 by the drug BI 2536 suppresses in vitro cell proliferation. A, the indicated ccRCC-derived cell lines were treated with BI 2536 for 96 hours, and proliferation was measured using the CellTiter-Glo assay. At least 3 experiments were run, each in triplicate. Results are expressed as a percentage of the proliferation of control cells treated with vehicle (1:1,000 dilution of 0.1 N HCl in medium). B, effects of BI 2536 on cell-cycle distribution. The cells were treated with medium alone (control); a 1:1,000 dilution of 0.1 N HCl in medium (buffer); 10, 20, or 40 nmol/L BI 2536; or nocodazole (0.1 mmol/L) for 24 hours. *, P < 0.05. C, BI 2536 induced an M-phase block. Control, buffer, and BI 2536 treatments were as in B; other treatments were medium with only 0.1% FBS (Starve); 1 mmol/L hydroxyurea (Hydr); or 0.5 mmol/L aphidicolin (Aph) for 24 hours. The positive control for phosphorylated histone H3 was 0.1 mmol/L nocodazole (Noc). D, effects of BI 2536 on chromosome alignment. Cells were treated as in B but without nocodazole. Cell response was analyzed by confocal imaging following staining for a-tubulin (red) and DNA (blue). The photos show images of the aberrant alignment of chromosomes ("Polo") after treatment with 40 nmol/L BI 2536. Scale bars, 5 mm. The graph shows the percentage of cells with aberrant chromosome alignment relative to all of the M-phase cells in each treatment. All error bars are standard deviations from 3 independent experiments.

lines in a dose-dependent manner with IC50 values of 2 to 20 treated for 24 hours with 10, 20, or 40 nmol/L BI 2536, stained nmol/L, which are consistent with the values found for other with propidium iodide, and analyzed by flowcytometry for cell lines (33, 34). effects on the cell cycle (Fig. 3B). Cells treated with nocodazole PLK1 has been shown to be critical for mitotic entry, were used as a control population blocked at G2–M phase. centrosome maturation, and cytokinesis (35). The loss of As expected, the cells treated with BI 2536 accumulated at PLK1 function (via either knockdown or small-molecule inhi- G2–M, which is consistent with the function of PLK1 in early bitors) results in a metaphase block in which cells fail to mitotic entry. Sustained evidence indicates that the level of assemble a functional bipolar spindle; instead, mitotic chro- histone H3 phosphorylated on serine 10 (pH3) correlates with mosomes become arranged in a circular fashion around a proliferation rate and that the intracellular pattern of pH3 monopolar spindle, termed a "Polo" spindle (33, 35, 36). To staining differentiates between stages of mitosis (37), so next confirm that BI 2536 was inhibiting PLK1 function at con- we examined both pH3 levels and the chromosome orienta- centrations that inhibited in vitro proliferation, cells were tion. Compared with either nontreated or buffer controls, BI

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A C pHistone H3 786-O H&E 2,400 ) 3 Vehicle 1,800 BI 2536

1,200 Control

600

Tumor volume (mm 0 33 43 53 63 (Days postimplantation) BI 2536 B 1,800 A498 ) 3 1,500 D 30 Vehicle 1,200 BI 2536 ** 900 20 600 10 300 Tumor volume (mm

0 Mitotic cells/field 28 38 48 58 68 0 (Days postimplantation) Control BI 2536

Figure 4. Inhibition of PLK1 by BI 2536 suppressed in vivo tumor growth. A, BI 2536 inhibited the growth of 786-O xenograft tumors. When xenograft tumors were 200 to 300 mm3, they were treated with vehicle (0.1 N HCl, filled squares) or 50 mg/kg BI 2536 (empty triangles) by intratumoral injection (arrows). The treatment cycle was 1 injection per day for 2 consecutive days each week for 2 weeks; it then changed to 2 injections per day for 2 consecutive days each week for another 3 weeks. B, BI 2536 treatment at 2 injections per day for 2 consecutive days inhibited the growth of A498 xenograft tumors. C, when 786-O tumors were 400 to 500 mm3, they were injected (intratumorally) either with vehicle control (0.1 N HCl) or 50 mg/kg BI 2536 3 times, twice the first day and once the following day. The treated tumor tissues were excised 6 hours after the final injection, and either immunostained with antibodies to the mitotic marker phosphorylated histone H3 or stained with hematoxylin and eosin (H&E). Cells with aberrant alignment chromosomes are indicated by arrows. Scale bars, 20 mm. Boxes at the lower left of the bottom images are enlargements of the small box in each image. D, mitotic cells (as described in C) positive for phosphorylated histone H3, were calculated using 5 fields from each of 3 separate tumors. **, P < 0.01.

2536-treated cells had increased levels of pH3, reaching the this protocol, tumors were allowed to grow to 200 mm3, level found in cells treated with nocodazole (Fig. 3C). Cells and then 50 mg/kg BI 2536 was injected intratumorally were also stained with a-tubulin, followed by secondary anti- according to the dosing schedule. After 2 cycles of treatment, body conjugated with Rhodamine Red-X, and chromosomes no effect on tumor growth was observed. We speculated that were visualized with DAPI. Confocal images of the cells the tumor was not responsive because of the incomplete treated with BI 2536 showed the Polo chromosomal pheno- inhibition of PLK1 function. Thus, in subsequent treatments, type. The number of cells with the Polo phenotype was 50 mg/kg of BI 2536 was injected twice a day (100 mg/kg total substantially increased in the BI 2536 treatment group relative per day), once at 7:00 AM and then at 5:00 PM, for 2 to controls, indicating that the inhibition of PLK1 function consecutive days in a week. Somewhat surprisingly, the results in an M-phase block that is associated with decreased tumors significantly regressed upon this BI 2536 treatment cellular proliferation (Fig. 3D). (Fig. 4A), and we repeatedly observed similar effects on both 786-O (data not shown) and A498 ccRCC xenografts (Fig. 4B). Sustained inhibition of PLK1 function inhibits ccRCC To confirm that BI 2536 inhibited PLK1 function using the tumor growth in vivo twice-a-day schedule in vivo, a target modulation study was 786-O, A498, Caki-1, or SN12C cells were subcutaneously carried out. 786-O cells were subcutaneously implanted in implanted in nude mice and treated with BI 2536. Following nude mice, tumors were allowed to grow to 400 to 500 mm3, the published literature (34), we initially used intravenous and then the mice were treated by intratumoral injection 3 injection of 50 mg/kg BI 2536 and a "2 days on, 5 days off" times, twice in the first day and once in the following day, weekly dosing schedule; we observed only minor inhibition using 50 mg/kg BI 2536 per injection. The mice were sacrificed effects on Caki-1 and SN12C xenograft tumors and no effects 6 hours after the final injection. The tumor tissues were on 786-O and A498 tumors (Supplementary Fig. S8). collected and examined for pH3 and for chromosome align- Then, we used the same treatment schedule, but we applied ment (Fig. 4C and D). Compared with the vehicle control BI 2536 to 786-O xenografts by intratumoral injection. Under group, pH3 and aberrations in chromosome alignment were

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Inhibition of PLK1 Suppressed the Growth of ccRCC

increased in BI 2536-treated cells. Together, these results in vitro and in vivo. However, one of the most notable results showed that sustained inhibition of the PLK1 function in vivo of this work was that a twice-a-day schedule is required for the by BI 2536 can suppress ccRCC tumor growth. in vivo effects of BI 2536. This result may indicate that for cell- cycle kinase inhibitors to cause ccRCC tumor regression, the Discussion function of the kinases needs to be inhibited for a longer duration than is needed by, for example, receptor tyrosine This study integrated both gene expression profiling and kinase inhibitors. We speculate that to induce cell death or RNAi screening data to identify genes involved in ccRCC apoptosis in ccRCC, the function of PLK1 needs to be sup- development and progression. Consistent with cancer being pressed for a certain period, highlighting the need for careful a disease of uncontrolled proliferation, we found an enrich- selection of delivery schedules for this class of drugs in clinical ment of cell-cycle–related processes when genes associated trials for ccRCC. with tumor grade were examined for deregulated biological We also indentified a series of proliferation genes for ccRCC; pathways. However, the appearance of kinase-related genes in in particular, NME3 (also known as DR-nm23) seemed to the molecular function analysis was not initially expected, potently suppress the growth of these cells when knocked because ccRCC renal tumors have not been reported to down. NME3 belongs to the nm23 gene family having a contain specific kinase-associated pathway activation induced common nucleoside diphosphate kinase activity (46). NME3 by either gene mutation or focal amplification (33, 38, 39). has been shown to either inhibit or promote cell differentia- On the basis of the gene expression results and the gen- tion or apoptosis when highly expressed in different cell types eration of several potent small-molecule kinase inhibitors, we (47). Genes from the same family have been shown to be carried out an RNAi screen to identify kinases and phospha- closely related to metastasis (48). Whether the kinase activity tases that were required for the growth of ccRCC cell lines. of NME3 is required for ccRCC cell proliferation could be a Both our expression analysis and our siRNA proliferation fruitful area for further study. screen highlighted the importance of cell-cycle–related genes like PLK1 and AURKB in ccRCC. PLK1 is a serine–threonine Disclosure of Potential Conflicts of Interest kinase that plays a key role in mitotic entry, centrosome The authors declare that no conflicts of interest exist. maturation, and cytokinesis (35). Consistent with our finding that PLK1 is overexpressed in high-grade kidney cancers, Acknowledgments PLK1 has been found overexpressed in many other solid tumor types (40), including breast cancer (41) and colorectal We thank Lisa DeCamp, Vivarium Operations, Van Andel Research Institute, for help with the animal experiments; Eric Hudson from the Laboratory of cancer (42). As we report here for ccRCC, preclinical studies Analytical, Cellular, and Molecular Microscopy, Van Andel Research Institute, have also shown promising results in other solid cancers, for help in confocal imaging; Aikseng Ooi for scientific discussions; Sabrina including breast cancer and colorectal cancer (34, 43), by Noyes for administrative assistance, and David Nadziejka for reading and correcting the manuscript. We thank the Cooperative Human Tissue Network either knocking down PLK1 via siRNA/shRNA or inhibiting (CHTN) of the National Cancer Institute for providing samples for analysis. PLK1 function via small-molecular inhibitors. Several PLK1 The costs of publication of this article were defrayed in part by the payment inhibitors have been evaluated or ongoing against solid of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact. tumors in the clinical setting (44, 45). Our data reported here and previously (25) clearly show that inhibition of PLK1 or Received January 10, 2011; revised May 12, 2011; accepted June 01, 2011; AURKB function can suppress ccRCC tumor growth both published OnlineFirst June 3, 2011.

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OF10 Cancer Res; 71(15) August 1, 2011 Cancer Research

Combined Gene Expression Profiling and RNAi Screening in Clear Cell Renal Cell Carcinoma Identify PLK1 and Other Therapeutic Kinase Targets

Yan Ding, Dan Huang, Zhongfa Zhang, et al.

Cancer Res Published OnlineFirst June 3, 2011.

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