CHEK2 Genomic and Proteomic Analyses Reveal Genetic Inactivation Or Endogenous Activation Across the 60 Cell Lines of the US National Cancer Institute

Oncogene (2012) 31, 403–418 & 2012 Macmillan Publishers Limited All rights reserved 0950-9232/12 www.nature.com/onc ORIGINAL ARTICLE CHEK2 genomic and proteomic analyses reveal genetic inactivation or endogenous activation across the 60 cell lines of the US National Cancer Institute

G Zoppoli1,2,8, S Solier1,8, WC Reinhold1, H Liu1,3, JW Connelly Jr4, A Monks4, RH Shoemaker5, OD Abaan6, SR Davis6, PS Meltzer6, JH Doroshow1,7 and Y Pommier1

1Laboratory of Molecular Pharmacology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA; 2Department of Internal Medicine (Di.M.I.), University of Genova, Genova, Italy; 3Division of Biomedical Statistics, and Informatics, Mayo Clinic, Rochester, MN, USA; 4Laboratory of Functional Genomics, SAIC Frederick Inc., NCI-Frederick, Frederick, MD, USA; 5Screening Technologies Branch, Developmental Therapeutics Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, National Institutes of Health, Frederick, MD, USA; 6Genetics Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA and 7Division of Cancer Treatment and Diagnosis, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA

CHEK2 encodes a serine/threonine kinase (Chk2) activated Introduction by ATM in response to DNA double-strand breaks. On the one hand, CHEK2 has been described as a tumor suppressor The cell-cycle checkpoint gene CHEK2 gene encodes with proapoptotic, cell-cycle checkpoint and mitotic func- Chk2, a serine/threonine kinase activated in response to tions. On the other hand, Chk2 is also commonly activated double-strand breaks generated by endogenous onco- (phosphorylated at T68) in cancers and precancerous lesions. genic activation, replication defects, ionizing radiations, Here, we report an extensive characterization of CHEK2 DNA-targeted chemotherapeutic agents and apoptosis across the panel of 60 established cancer cell lines from the (Bartek and Lukas, 2003; Ahn et al., 2004; Pommier NCI Anticancer Screen (the NCI-60) using genomic and et al., 2005; Harper and Elledge, 2007; Solier et al., proteomic analyses, including exon-specific mRNA expres- 2009). Chk2 activation is initiated by its phosphoryla- sion, DNA copy-number variation (CNV) by aCGH, exome tion at threonine-68 (T68) by the ataxia telangiectasia sequencing, as well as western blot analyses for total and mutated kinase, ATM (Ahn et al., 2000; Matsuoka activated (pT68-Chk2) Chk2. We show that the high et al., 2000) or other phosphatidyl-inositol-3 kinase- heterogeneity of Chk2 levels in cancer cells is primarily due family kinases (ataxia telangiectasia-related kinase to its inactivation (owing to low gene expression, alternative (ATR) and DNA-dependent protein kinase (DNA- splicing, point mutations, copy-number alterations and PK)) (Bartek and Lukas, 2003; Li and Stern, 2005; premature truncation) or reduction of protein levels. More- Pommier et al., 2006). T68 phosphorylation, in turn, over, we observe that a significant percentage of cancer cells induces Chk2 homodimerization and auto-phosphoryla- (12% of the NCI-60 and HeLa cells) show high endogenous tion in trans (Ahn and Prives, 2002; Ahn et al., 2002; Chk2 activation, which is always associated with p53 Schwarz et al., 2003; Li et al., 2008). Chk2 phosphor- inactivation, and which is accompanied by downregulation ylates the substrate proteins involved in cell-cycle arrest, of the Fanconi anemia and homologous recombination apoptosis, DNA-damage response and mitotic spindle pathways. We also report the presence of activated Chk2 assembly, including CDC25A, CDC25C, p53, E2F1, (pT68-Chk2) along with histone c-H2AX in centrosomes. BRCA1 and BRCA2 (Matsuoka et al., 1998; Chehab Oncogene (2012) 31, 403–418; doi:10.1038/onc.2011.283; et al., 2000; Hirao et al., 2000; Falck et al., 2001; Stevens published online 18 July 2011 et al., 2003; Ou et al., 2005; Pommier et al., 2005, 2006; Bahassi et al., 2008; Stolz et al., 2010). Keywords: Chk2; centrosome; H2AX; p53; BRCA1; The tumor-suppressor function of Chk2 stems from Fanconi anemia the epidemiological finding that Chk2 is inactivated by germline mutations in patients with Li–Fraumeni-like syndrome without p53 mutations (Bell et al., 1999) and from mouse genetic studies showing that knocking out Correspondence: Dr G Zoppoli, Avancorpo II Piano, Department of CHEK2 in mice (Hirao et al., 2002; Takai et al., 2002) Internal Medicine (Di.M.I.), V.le Benedetto XV, Room 223, 6, Genova 16132, Italy. increases tumor incidence when p53, ATM, BRCA1 or E-mail: [email protected] or Dr Y Pommier, Laboratory of Chk1 are inactivated together with Chk2 (Cao et al., Molecular Pharmacology, National Institutes of Health, Building 37, 2006; Niida et al., 2010). CHEK2 germline mutations Room 5068, Bethesda, MD 20892-4255, USA. have been identified in familial cases of breast cancer E-mail: [email protected] or 8These authors contributed equally to this work. (Meijers-Heijboer et al., 2002; Nevanlinna and Bartek, Received 22 December 2010; revised 16 May 2011; accepted 4 June 2011; 2006) and CHEK2 appears to be lost in more than published online 18 July 2011 50% of lung cancers (Stolz et al., 2010). In response to CHEK2 in the NCI-60 G Zoppoli et al 404 BRCA1 deficiency, activation of the ATM–Chk2–p53 expression analysis between cell lines with endogenously signaling pathway may contribute to the suppression of activated Chk2 and cell lines without such phenotype. neoplastic transformation, as shown in BRCA1 D11/D11, CHEK2À/À mouse models (Cao et al., 2006), which are viable but prone to the development of neoplasia. This finding suggests a role for Chk2 as a tumor Results suppressor in response to BRCA1 deficiency as well transcript levels exhibit broad expression range as a key activator of BRCA1 during mitosis (Stolz CHEK2 across the NCI-60 et al., 2010). However, Chk2 activation (pT68-Chk2) CHEK2 transcript levels were determined by combining is not always associated with apoptosis (Solier et al., 2009). pT68-Chk2 has recently been found to occur data generated from five different microarray platforms. Details on microarray quality control and z-score physiologically during mitosis as a critical step for transformations are included under Materials and BRCA1 phosphorylation on serine-988, which appears critical for maintaining chromosome number stability methods, and the data can be accessed at http:// discover.nci.nih.gov/cellminer/. Data sets yielded a total (Stolz et al., 2010). Endogenous T68-phosphorylated/ of 25 good-quality, highly correlated probe sets from activated Chk2 has been found in a wide range of both Affymetrix and Agilent chips, with an average cancers and precancerous lesions (Gorgoulis et al., Pearson’s correlation coefficient of 0.788 for all probe 2005), raising the possibility that Chk2 may in some sets and an average Pearson’s correlation coefficient of cases contribute to the carcinogenic process. In support 0.805 between the Agilent and Affymetrix probe sets. of this hypothesis, Chk2 inactivation by small interfer- Overall, the average normalized intensity for the ing RNA or small-molecule inhibitors is sufficient to kill Affymetrix probe sets was 5.32 (log intensity), with a ovarian cancer cell lines with endogenously activated 2 range of 3.19 log (9.1-fold variation) and an s.d. of 0.79 Chk2 (Jobson et al., 2009). Similarly, HEK-293 cells are 2 also killed after Chk2 antisense transfection (Yu et al., (see Figure 1). The ovarian cancer cell line OVCAR-3 showed the 2001). Moreover, Castedo et al. (2004) have shown that highest CHEK2 transcript levels (1.72 s.d.s above HeLa and HCT-116 cells can be sensitized to doxor- z ubicin by transfection with a dominant-negative Chk2 average for the -scored values), whereas the lung cancer cell line NCI-H226 showed the lowest (1.82 mutant. The molecular mechanisms that may determine s.d.s below average). A certain degree of tissue the ‘addiction’ of cancer cells to Chk2 are not presently specificity for CHEK2 mRNA expression was observed understood. One possibility is that Chk2 may suppress (Figure 1), with cell lines of hematopoietic origin apoptosis in p53-deficient cells not only by activating presenting above-average values (P 0.01, w2-test, two- the DNA-damage response and cell-cycle checkpoints, o sided), and CNS and renal lines being the lowest but also by promoting the release of survivin from P P 2 mitochondria (Ghosh et al., 2006). expressers ( o0.01 and o0.05, w -test, two-sided) (see also Figure 2a, left panel for mean-centered The NCI-60 panel consists of 60 cancer cell lines from representation). Cell lines derived from lung cancer nine tissues of origin: 6 from hematopoietic malignan- CHEK2 cies, 10 melanomas, 5 lines from breast, 6 from the CNS, samples showed high variability in transcript expression, ranging from very low (NCI-H226, 7 from colon, 9 from lung, 7 ovarian, 2 from prostate 1.82 s.d.s below the average for CHEK2 expression in and 8 from renal cancers. The NCI-60 panel was the NCI-60) to high intensities (NCI-H23, 0.89 s.d.s developed by the Developmental Therapeutics Program above average). These results demonstrate the high of the National Cancer Institute to screen and discover heterogeneity (approximately eight-fold) for CHEK2 novel anticancer drugs (Shoemaker, 2006; Holbeck expression across the NCI-60. et al., 2010). The NCI-60 panel also provides a unique aCGH analysis revealed that two cell lines with low database because of its extensive characterization for transcripts, melanoma SK-MEL-2 and lung cancer genome-wide gene expression across multiple platforms, NCI-H226, were hypo-diploid at the CHEK2 locus micro-RNA and protein expression (Scherf et al., 2000; Nishizuka et al., 2003; Bussey et al., 2006; Shankavaram (ch.22, cytoband 22q12.2) (see Supplementary Figure 1). On the other hand, in spite of the marked focal et al., 2007; Reinhold et al., 2010); gene copy number by amplification of the CHEK2 locus in the ovarian line array comparative genomic hybridization (aCGH) (Nishizuka et al., 2003); karyotypic aberrations by OVCAR-5, its transcript was scarcely expressed. spectral karyotyping (Roschke et al., 2003); oncogene mutations by capillary sequencing (Ikediobi et al., 2006) Novel CHEK2 point mutations in the NCI-60 and sensitivity to more than 400 000 natural and Next-generation sequencing and targeted resequencing synthetic compounds through in vitro toxicity screening are currently being performed across the NCI-60 to (Shoemaker, 2006; Holbeck et al., 2010; Reinhold et al., analyze all exons of every known gene (unpublished 2010). data; ongoing analysis). Here we only report our results In the present paper, we present the genome-wide and for CHEK2. Our analysis revealed 16 single-nucleotide proteomic analysis of the NCI-60 for CHEK2 mRNA variants in 11 cell lines (no short insertions or deletions expression, alternative splicing, copy-number alterations, were detected). Ten of these variants were further tested mutations, as well as total and activated (phosphory- by conventional capillary sequencing, and all of them lated) Chk2 protein levels, and perform differential gene were validated (Table 1). In agreement with previous

Oncogene CHEK2 in the NCI-60 G Zoppoli et al 405

Figure 1 CHEK2 mRNA varies widely across the NCI-60 and shows tissue-speciﬁc expression. (a) CHEK2 expression in the 60 cancer cell lines from the NCI-60 panel sorted by decreasing CHEK2 mRNA expression (z-score). Tissues of origin are color-coded (see bottom right). (b) A dot plot of CHEK2 expression. Cell lines are ordered on the x-axis as in panel a. Range, minimum, maximum and average intensity below the ﬁgure represent the mean log2 values for the Affymetrix probe sets.

sequencing, we confirmed the two previously described Analysis of transcription factors potentially involved point mutations, R145W and A247D, in the HCT-15 in CHEK2 transcriptional control colon line (Lee et al., 2001). The effect of codon changes The TRANSFAC database (Matys et al., 2006) provides on the protein were evaluated by using the SIFT analyses of transcription factors, their experimentally algorithm (Ng and Henikoff, 2003). A previously proven binding sites and potentially regulated genes. unknown missense CHEK2 mutation, E394K in the We used this database to determine putative CHEK2 SK-MEL-28 cell line, was predicted to be damaging transcription factors by correlating their transcript (Table 1). In light of the SIFT prediction and of the key profiles in the NCI-60 with those of CHEK2 (Supple- position of this mutation in the kinase domain of Chk2, mentary Figure 2). SP1, ELF1 and MYC showed a very the novel E394K missense mutation variant found in high correlation with CHEK2 transcripts (Po0.001 for melanoma SK-MEL-28 cells is likely to interfere with SP1 and ELF1,ando0.01 for MYC; Pearson’s correla- Chk2 activity. Together, exome sequencing revealed tion coefficient test r ¼ 0.53, 0.42 and 0.4, respectively; novel potentially inactivating CHEK2 mutations. Supplementary Figure 2). Other significantly correlated

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Figure 2 Relationship between CHEK2 mRNA and Chk2 protein levels across the NCI-60. (a) Mean-centered bar graphs showing intensities for CHEK2 transcript (left) and total Chk2 protein (right). The CHEK2 transcript values are z-score-normalized. r: Pearson’s correlation coefﬁcient between transcript and protein levels (0.36, Po0.01, two-sided). The bars are colored according to tissues of origin (see bottom left for legend). NA: not available. (b) A scatter plot of Chk2 protein versus transcript. The two outliers (HCT-15 and SK-MEL-28) discussed in the text are indicated. x-axis: Total protein levels (ratios to HeLa cell line). y-axis: CHEK2 transcript intensity (z-score).

transcription factors were GABPA/NRF-2 (Po0.01), to the HeLa cervical cancer cell line and mean-centered LIN9, LIN54, CTCF and FOXA1 (Po0.05). Although (Figure 2, right panel). Overall, the leukemia cell lines these data are only correlative, they suggest further present the highest Chk2 protein levels (4 out of 6 cell experimental confirmation for the possible role of SP1, lines, 67% around two-fold above average), whereas the ELF1 and MYC as CHEK2 transcription factors, and melanoma lines tend to be low (with 8 out of 9 tested cell the likely interaction of multiple transcription factors in lines below average). All the CNS lines also tend to have CHEK2 transcriptional regulation. low Chk2 protein levels (with the exception of SF-268), as do the lung cancer lines (6 out 9 lines below average). Correlation between CHEK2 transcript and Chk2 The transcript and total protein showed a significant protein levels overall positive correlation (Pearson’s correlation To assess the relationship between CHEK2 transcript coefficient ¼ 0.36, P ¼ 0.005; Figure 2b). Notable excep- and Chk2 protein levels, a western blot analysis was tions to this correlation are represented by the colorectal performed in the NCI-60. The results were normalized cancer cell line HCT-15 and the melanoma line SK-

Oncogene CHEK2 in the NCI-60 G Zoppoli et al 407 Table 1 All 10 validated CHEK2 coding region SNVs identiﬁed in the NCI-60 panel Cell line Varianta Gene:Exonb Known mutation/SNPc % SNVd Codon change AA change SIFT predictione

SK-MEL-28 chr22:27421777 CHEK2:12 None 32% GAA4AAA E394K DAMAGING HCT-15 chr22:27451242 CHEK2:4 None 33% CGG4TGG R145W DAMAGING HCT-15 chr22:27437949 CHEK2:7 None 39% GCC4GAC A247D DAMAGING OVCAR-4 chr22:27451016 CHEK2:5 None 26% CGT4TGT R181C TOLERATED KM12 chr22:27451349 CHEK2:4 None 48% GTG4GCG V109A TOLERATED ACHN chr22:27460458 CHEK2:2 rs1805129 100% GAA4GAG E41E None HT29 chr22:27460458 CHEK2:2 rs1805129 75% GAA4GAG E41E None KM12 chr22:27460458 CHEK2:2 rs1805129 64% GAA4GAG E41E None RPMI-8226 chr22:27460458 CHEK2:2 rs1805129 69% GAA4GAG E41E None SW-620 chr22:27460458 CHEK2:2 rs1805129 100% GAA4GAG E41E None

Abbreviations: SNV, single-nucleotide variant; NCI-60, the NCI-60 panel (comprising 60 established cancer cell lines from the NCI Anticancer Screen). Bold letters represent the predicted amino acid substitution based on the mutated codon. aAll the coordinates are in respect to human genome build 18 (hg18, March 2006). bThe exon numbers are calculated according to the SpliceCenter website (http://www.tigerteamconsulting.com/SpliceCenter/SpliceOverview.jsp), and the amino-acid position is calculated according to the protein canonical isoform a (NP 009125.1). cReports of the particular variant in the Catalogue of Somatic Mutations in Cancer (COSMIC) database (http://www.sanger.ac.uk/genetics/CGP/ cosmic/) or in the case of an rs number a known single-nucleotide polymorphism cataloged in dbSNP version 130. dThe value represents the percentage of unique reads containing the Single Nucleotide Variation. eSorting Intolerant From Tolerant: A prediction based on the effect of the non-synonymous amino-acid substitution on protein function (Ng and Henikoff, 2003).

MEL-28, both of which present high CHEK2 transcript quantitative PCR. A cell line with uniformly high levels but almost undetectable Chk2 protein by western CHEK2 transcript, colorectal HCT-116, was used as a blotting (Figures 2a and b). The low protein levels for reference against SK-OV-3. The results shown in the HCT-15 are due to the CHEK2 mutations R145W Figure 4a validate the results obtained by the exon and A247D (Lee et al., 2001) (see above and Table 1). array analysis. Notably, this CHEK2 transcript anomaly The SK-MEL-28 line also contains a deleterious was reﬂected by the absence of detectable Chk2 protein CHEK2 mutation, which causes an amino-acid sub- by western blot analysis in SK-OV-3 cells (see Figure 2a, stitution, E394K. This mutation is novel and further right panel). analyses are warranted to determine whether it destabi- Looking at individual exons for variable intensity lizes the Chk2 polypeptide. Overall, our results show indicative of potential splice variants across cell lines, that measuring the CHEK2 transcript may be a three probe sets, corresponding to exons 3, 6 and 11 (see suboptimal surrogate for Chk2 protein level estimation pink, green and blue arrowheads at the bottom of in cancer cells. Figure 3B), showed variable intensities across the NCI- 60 (with lower than average intensity in some of the CHEK2 exon analyses high-CHEK2-expresser lines and higher than average To assess potential alternative CHEK2 splice variants, intensity in low-CHEK2-expresser lines). These results we analyzed the Affymetrix GeneChip Human Exon 1.0 suggest the possible existence of CHEK2 splice variants ST (GH Exon 1.0 ST) exon microarray database from for those three exons (3, 6 and 11; validation experi- the NCI-60. Of the 28 probe sets across the CHEK2 ments for exon-3 are included below). Indeed, many cell transcript (1 to 4 probe sets per exon; mapping and lines showed a detectable signal for the probe set exon numbering are according to the SpliceCenter mapping to an additional exon (number 6 in Splice- Suite (http://www.tigerteamconsulting.com/SpliceCenter/ Center), part of an alternative splice variant (AY551301) SpliceOverview.jsp); Figure 3A), 22 showed a variance characterized by nonsense-mediated mRNA decay and 40.1 across the NCI-60. These probeset values were found in breast cancer specimens (Staalesen et al., 2004). clustered according to their normalized, median-cen- We also validated by semi-quantitative PCR (reverse tered expression (to account for the different variance of transcription (RT)–PCR) the retention of exon-3 each probe set) as shown in Figure 3B. Cluster analysis detected by exon array in some of the NCI-60 cells divided the NCI-60 into two main groups, the high- and (this exon is spliced in the canonical CHEK2 transcript low-CHEK2-expresser cell lines (Figure 3A, a and b, variant-1 (NM 007194.3, see Figure 3A)). Two lung respectively). In the low-expresser group, one cell line, cancer cell lines showing high exon-3 intensity in the ovarian SK-OV-3, clustered separately and presented an exon array analysis, NCI-H322M and NCI-H522, and aberrant decrease in transcript intensity after exon-11 two lines with low exon-3, leukemia SR and prostate (Figure 3B, purple staggered arrow at bottom right, and cancer PC-3, were tested for those experiments. Supplementary Figure 3c), suggesting the occurrence of Figure 4b shows that the four cell lines transcribe both a truncated message after that exon. transcript variant-1 and the exon-3-retaining transcript The potential premature truncation of CHEK2 variant-3 (NM 001005735.1). However, two of them, in transcript in SK-OV-3 ovarian cells was tested by good agreement with the exon array data, present a

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Figure 3 Exon array analysis of CHEK2 transcript in the NCI-60 reveals novel splice variants and premature transcript truncation in the ovarian cancer cell line SK-OV-3. (A) The three RefSeq CHEK2 isoforms (bold letters) and alternative transcripts are shown. Exons are numbered according to SpliceCenter; the black and gray boxes represent translated and untranslated exons, respectively. (B) A CIM showing median-centered probe set levels for CHEK2 exons in the NCI-60 clustered by normalized intensity. Right and left: Cell line names. Bottom: Probeset IDs. Purple arrow: SK-OV-3 cell line. Pink arrowhead: Exon-3. Green arrowhead: Exon-6. Blue arrowhead: Exon-11. a: High-CHEK2-expresser cell line cluster. b: Low-CHEK2-expresser cell line cluster.

more intense slower migrating band, consistent with blot quantitations are plotted in Figure 5b (left panel). higher levels of the longer CHEK2 transcript retaining Seven of the NCI-60 lines showed consistently high exon-3. These data demonstrate the presence of multiple pT68-Chk2 levels: the leukemia/multiple myeloma CHEK2 isoforms and splice variants co-existing in the RPMI-8226; the three lung cancer lines, EKVX, HOP- same cell populations in the NCI-60. 92 and NCI-H322M; the two ovarian cancer lines OVCAR-3 and OVCAR-4; and the renal cancer line RXF-393, which together with OVCAR-3, presented the Chk2 is constitutively phosphorylated in p53-deﬁcient highest basal levels of pT68-Chk2 among the NCI-60, cell lines comparable or greater than HeLa. Notably, all the 12 To determine the extent of endogenous Chk2 activation cancer cell lines characterized as being p53 wild-type in the NCI-60, lysates from each of the 60 cell lines were (data from the IARC p53 database (http://www- subjected to western blot analysis with a phospho- p53.iarc.fr/)) showed almost undetectable levels of speciﬁc antibody against the T68 residue of Chk2 (pT68- pT68-Chk2 (dotted arrows in Figure 5b). Overall, these Chk2) (Figure 5a and Supplementary Figure 4). While results demonstrate the value of phosphoproteomic performing these experiments, testing the cervical cancer analyses, as pT68-Chk2 levels are not correlated with HeLa cell line revealed consistently high endogenous total Chk2 protein levels (Figure 5b, right panel; pT68-Chk2 levels, which led us to use the HeLa cell line Supplementary Figure 4; also see Figure 2a, right as a reference and normalization parameter for pT68- panel). They also demonstrate the absence of high Chk2 levels across the NCI-60. The pT68-Chk2 western endogenous Chk2 activation in wild-type p53 cells.

Oncogene CHEK2 in the NCI-60 G Zoppoli et al 409 H2AX phosphorylated at S139), which is a sensitive marker of double-strand breaks (Bonner et al., 2008), in cells co-stained with pT68-Chk2. g-H2AX presented focal and diffuse nuclear staining in the cells with activated Chk2 (Figure 6a and Supplementary Figure 5). In HeLa cells, which show high endogenous pT68-Chk2 activation, the pT68-Chk2 signal mostly colocalized with g-H2AX in interphase cells (see Figure 6a, upper panel; representative image in Supplementary Figure 5, upper panel). Also, centrosomal pT68-Chk2 colocalized with g-H2AX in interphase cells. In mitotic cells (see Figure 6a, upper panel; representative image in Supple- mentary Figure 5, lower panel), the pT68-Chk2 signal tended to be excluded from the DNA, remained in centrosomes and did not colocalize with g-H2AX, which remained within the condensed chromatin. Similar results were obtained in the other three high- pT68- Chk2 cell lines: OVCAR-3, OVCAR-4 and RXF-393 (Figure 6a). To identify the kinase implicated in the endogenous phosphorylation of Chk2, we pretreated HeLa cells with KU55933 or NU7441. At the concentrations used, KU55933 and NU7441 are highly specific inhibitors of ATM and DNA-PK, respectively (Hickson et al., 2004; Leahy et al., 2004). The ATM inhibitor strongly decreased pT68-Chk2 phosphorylation, whereas the DNA-PK inhibitor showed a weaker effect, and both together completely suppressed pT68-Chk2 phosphorylation (Figure 7a). To look for downstream substrates of Chk2, we compared the phosphorylation levels of CDC25A, CDC25C and BRCA1 in HeLa and HCT116 Figure 4 Exon-3 retention in cancer cell lines and premature cells. Although CDC25C phosphorylation at S216 was truncation of SK-OV-3 are confirmed by independent PCR experiments. (a) Quantitative PCR showing premature truncation greater in HeLa cells, this was not the case for the of the SK-OV-3 transcript compared with the HCT116 transcript. phosphorylation intensities of CDC25A at S123 or The primers used are CHEK2 E4s, CHEK2 E5as, CHEK2 E15s BRCA1 at S988 (Figure 7b). and CHEK2 E16as. The y-axis corresponds to the SK-OV-3/ To determine whether there is a correlation between HCT116 ratio in percent. (b) RT–PCR showing retention of CHEK2 exon-3 in NCI-H322M, NCI-H522, SR and PC-3 cell Chk2 activation and chromosome instability or ploidy, lines. CHEK2 mRNA was analyzed by RT–PCR using CHEK2 we correlated pT68-Chk2 with spectral karyotyping E2s and CHEK2 E4 as primers. b2-Microglobulin (b2) mRNA was alterations for each of the 60 cell lines (Roschke et al., used as a standardizing control. 2003). Overall, we found a statistically significant correlation between pT68-Chk2 levels and the number of chromosomal rearrangements per cell (Pearson’s Relationship between DNA damage, chromosomal product–moment correlation ¼ 0.29, Po0.05, two- instability and Chk2 activation by ATM tailed). All seven cell lines with high pT68-Chk2 showed Immunofluorescence analyses showed that activated/ higher than average chromosomal rearrangements. phosphorylated Chk2 is nuclear (diffuse and focal Conversely, all cells with low chromosomal rearrange- patterns). We also found that pT68-Chk2 is concen- ments showed low pT68-Chk2 (see Supplementary trated in the centrosomes of both interphase and mitotic Figure 6). These data demonstrate a positive correlation cells (Figure 6 and Supplementary Figure 5), which is between activated Chk2 and chromosomal instability. consistent with prior reports (Tsvetkov et al., 2003; Zhang et al., 2007). In the cell lines that scored low for pT68-Chk2 by western blotting (HCT116, HT29 cells; Downregulation of homologous recombination and see Figure 5), immunofluorescence nuclear staining for Fanconi anemia pathway genes in Chk2-activated cells pT68-Chk2 was reduced in comparison with the high- The potential impact of endogenous Chk2 activation pT68-Chk2 cell lines (HeLa, RFX-393, OVCAR-3 and was analyzed by transcriptome profiling of the five OVCAR-4; Figures 6a and b). However, the pT68-Chk2 highest-pT68-Chk2 cell lines, comparing them with five centrosomal staining remained visible in the low-pT68–– tissue-matched, low-pT68-Chk2 and p53-matched defi- Chk2 cells (Figure 6b). cient cell lines. Two-sided t-tests revealed 176 genes To determine whether cells with activated Chk2 differentially expressed with statistical significance display high levels of DNA damage, we looked at (Po0.01) in the two groups (high- versus low-pT68- g-H2AX staining (g-H2AX corresponds to histone Chk2). The clustered intensity map for those genes is

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Figure 5 Proteomic analysis of total and phosphorylated (pT68) Chk2 shows high endogenous levels of Chk2 activation in several cancer cell lines across the NCI-60. (a) Representative western blot pictures of pT68-Chk2 in the NCI-60. The colored bars correspond to the tissues of origin (see legend at the bottom). HeLa cells were used as positive control and to calculate the Chk2 phosphorylation ratios in the NCI-60. (b) Quantitation of pT68-Chk2 (left) and total Chk2 (right) protein levels in the NCI-60. The colored bars represent the means of the ratios between the western blot intensities of the individual cell lines and the HeLa reference loading, after normalization by b-actin loading. The colors represent the tissues of origin (see also Figure 1). The dotted arrows indicate known p53 wild-type cancer cell lines. NA: not available.

shown in Figure 8A. Among the genes with down- Discussion regulated expression, a significant number codes for proteins involved in DNA recombination, replication In this study, we used a series of genomic and proteomic and repair (FANCA, FANCG, FANCL, BRCA2, assays to characterize the CHEK2 gene and its protein RAD51C, EME1 and RECQL5 being the most rele- product in the 60 cell lines of the NCI (NCI-60 panel). vant), and centromere organization (Figure 8B). Intrigu- Our analysis reveals the relatively high frequency of ingly, several of these downregulated genes are parts of Chk2 heterogeneity in cancer cells, either by inactivation the Fanconi anemia pathway or related to homologous or endogenous activation/phosphorylation. We show recombination (Po0.05 for statistically significant en- that inactivation can result from several mechanisms, richment using Ingenuity Pathway Analysis; see Supple- including point mutations, haplo-insufficiency, alterna- mentary Figure 7). Among the upregulated genes in the tive splicing, premature truncation of CHEK2 transcript high-pT68-Chk2 lines, a significant number encodes for or reduced protein levels. Endogenous activation cellular stress response and immunological disease measured by phosphoproteomic analyses with a pT68- factors (Figure 8B). One of them, CDKN2A/p14ARF,is Chk2-specific antibody was also detected in approxi- strongly upregulated in the high-pT68-Chk2 lines mately 12% of the cell lines and in HeLa cells, always in (P ¼ 0.0051, t-test, two-sided), consistent with prior a p53-deficient cellular milieu. studies suggesting a role of CDKN2A/p14ARF in promot- In normal human tissues, Chk2 is widely expressed in ing Chk2 activation through Tip60-dependent acetyla- proliferating, renewing cell populations, whereas being tion and activation of ATM (Sun et al., 2005; Eymin undetectable or cytoplasmic in resting or terminally et al., 2006). differentiated cells (Bartek et al., 2001; Lukas et al., 2001).

Oncogene CHEK2 in the NCI-60 G Zoppoli et al 411

Figure 6 pT68-Chk2 tends to be linked to DNA damage and localizes to centrosomes. (a) pT68-Chk2 and g-H2AX confocal immunoﬂuorescence staining in high-pT68-Chk2 cell lines (HeLa, RXF-393, OVCAR-3, OVCAR-4). pT68-Chk2 was labeled in pink, g-H2AX in green and nuclei were stained in blue with DAPI. Scale bars: 10 mm. (b) pT68-Chk2 and g-H2AX confocal immunoﬂuorescence staining in low-pT68-Chk2 cell lines (HCT116, HT29). pT68-Chk2 was labeled in pink, g-H2AX in green and nuclei were stained in blue with DAPI. Scale bars: 10 mm.

Our results show that, despite an overall correlation CHEK2 mRNA levels. HCT-15 is a typical example between transcript and total protein levels, 19 of the where CHEK2 mRNA is among the highest in the NCI- NCI-60 cell lines (approximately 1/3) show relatively 60 panel whereas there is no detectable Chk2 protein. low Chk2 protein levels in spite of higher than average Consistent with the existing literature (Lee et al., 2001),

Oncogene CHEK2 in the NCI-60 G Zoppoli et al 412 study, we identified a novel CHEK2 transcript in the SK-OV-3 ovarian cell line, characterized by premature truncation after exon-11. Other splicing variations appear likely at exons 3, 6 and 11, based on our exon array expression analyses and validation by PCR for exon-3. Exon-6 is normally not included in the canonical CHEK2 isoforms (Staalesen et al., 2004), but its presence, albeit at low absolute intensity, in some cancer cell lines suggests that it might be retained as an undescribed Chk2 minor isoform along with canonical transcript variants. Thus, our results from the NCI-60 consolidate the rationale for using exon array platforms to detect splice variants in tumors. A recent study reported that Chk2 is lost in more than 50% of lung cancer tissues (Stolz et al., 2010). In line with these results, we observed lower than average total Chk2 levels in 6 out of 9 lung cancer cell lines (66%). The lung cancer cell line NCI-H226 is also the lowest CHEK2 expresser across the NCI-60. Interestingly, we also found three lung cancer lines (EKVX, HOP-92 and NCI-H322M) with high levels of activated pT68-Chk2. The pT68-Chk2 modification was not investigated in the recent publication linking Chk2 and BRCA1 with chromosome stability in cancer cells (Stolz et al., 2010). Chk2 phosphorylation at T68 by ATM, DNA-PK or/ and ATR is the first step toward its activation in response to DNA damage (Ahn et al., 2000). Several studies have reported high levels of endogenous activation of Chk2 in pre-neoplastic and early cancerous lesions (Bartkova et al., 2005; Gorgoulis et al., 2005; Fan et al., 2006; Nuciforo et al., 2007). Later on in the carcinogenesis process, Chk2 phosphorylation is vari- ably maintained (Hirao et al., 2000; Bartkova et al., 2001, 2004; DiTullio et al., 2002; Sullivan et al., 2002; Figure 7 Chk2 is phosphorylated by both ATM and DNA-PK. Hattori et al., 2004; Ribeiro-Silva et al., 2006; Albert (a) HeLa cells were treated with an ATM inhibitor (ATM-i) et al., 2007; Kim et al., 2009). This Chk2 activation has (KU55933) and/or a DNA-PK inhibitor (DNA-PK-i) (NU7441) (10 mM for 4 h). pT68-Chk2 was analyzed by western blotting. generally been interpreted as a cellular response to GAPDH was used as loading control. (b) Study of some Chk2 oncogenic stress and endogenous DNA lesions that substrates in HCT116 and HeLa cells. pS123-CDC25A, total drive cells toward p53-mediated apoptosis (Antoni et al., CDC25A, pS216-CDC25C, total CDC25C, pS988-BRCA1, total 2007; Bartkova et al., 2010). Our study demonstrates BRCA1 and pT68-Chk2 T68 were examined by western blotting. GAPDH was used as loading control. high endogenous pT68-Chk2 (activated Chk2) in seven of the NCI-60 cell lines (approximately 12%), as well as in the HeLa cells. Our data indicate that activated/ phosphorylated Chk2 tends to be linked to endogenous we confirmed that this cell line harbors a bi-allelic gene DNA damage in interphase cells- in response to ATM mutation in CHEK2, R145W within the forkhead- (and DNA-PK). In a recent study, Sedelnikova and associated (FHA) domain of one allele and A247D in Bonner (2006) studied endogenous g-H2AX foci in a the kinase domain of the other. As a result, one allele is wide range of untreated cancer cell lines. That study not transcribed, whereas the other generates an inactive, shows that some cell lines, such as MDA-MB-231 with rapidly degraded protein product. Exome sequencing high g-H2AX foci, fail to show high pT68-Chk2. This of the NCI-60 revealed a novel, undescribed and could be due to the fact that the Chk2 pathway may not potentially deleterious Chk2 mutation (E394K) in the be functional in some of the cells that accumulate melanoma SK-MEL-28 cell line (see Table 1). endogenous DNA lesions. Three canonical CHEK2 isoforms are usually described We also found a high pT68-Chk2 signal in centro- in the literature (http://www.tigerteamconsulting.com/ somes, which colocalizes with g-H2AX in interphase SpliceCenter/ArrayCheck). However, more than 90 patho- cells. Our observation regarding the centrosomal activa- logical CHEK2 splice variants have been reported in tion of Chk2 is consistent with prior reports showing breast cancer (Staalesen et al., 2004), and it has been pT68-Chk2 in centrosomes (Tsvetkov et al., 2003; suggested that these isoforms, co-existing with physio- Zhang et al., 2007). Concerning g-H2AX, its focal and logical ones, could exert a dominant-negative effect in diffuse patterns have been mentioned previously (Zhao neoplastic diseases (Berge et al., 2010). In the present et al., 2007, 2008), but our study is the first to show its

Oncogene CHEK2 in the NCI-60 G Zoppoli et al 413

Figure 8 Fanconi anemia and homologous recombination genes are downregulated in cells with activated (phosphorylated) Chk2 and p53 deficiency. (A) A CIM of genes differentially expressed in the five highest-pT68-Chk2 cancer cell lines from the NCI-60 (highlighted with a red bar on the right) and in five tissue-matched, p53-deficient and low-pT68-Chk2 cancer cell lines (highlighted with a green bar on the left). (B) Relevant genes up- and downregulated in pT68-Chk2-activated cells (light red and blue boxes, respectively). centrosomal localization. It is noteworthy that some et al., 2004; Ghosh et al., 2006; Jobson et al., 2009). other DNA-damage response proteins have been re- In line with these reports, Chk2 has recently been shown ported in centrosomes: Chk1, ATM and ATR (Zhang to regulate SIRT1 expression by phosphorylating HuR et al., 2007). Whether the concentration and colocaliza- (Abdelmohsen et al., 2007) and to reduce chromosomal tion of g-H2AX and pT68-Chk2 in centrosomes is attachment to kinetochores by phosphorylating BRCA1 related to DNA damage remains questionable. How- (Stolz et al., 2010). ever, it is interesting to note that the cells with high Our observations that cancer cells with high endo- activated/phosphorylated Chk2 were also those with the genous activated Chk2 also show downregulated Fan- greatest number of chromosomal rearrangements. coni anemia and homologous recombination pathways Of interest, none of the NCI-60 cell lines with (as seen by gene expression microarrays (see Figure 8) proficient p53 function showed detectable levels of and western blotting (see Figure 7b)), together with an activated Chk2. This observation holds true also for elevated number of chromosomal rearrangements (see HeLa cells, which, while being genetically p53 wild-type, Supplementary Figure 6), suggests a role for Chk2 in the are infected by human papilloma virus, which inacti- control of cell proliferation when DNA-damage repair vates p53 (Yee et al., 1985), owing to its degradation by pathways are altered. Our data may also point toward a the viral protein E6 (Kessis et al., 1993). Although rationale for Chk2 inhibition in cancers with an intrinsic several studies have linked Chk2 to p53 activation in deficiency in the aforementioned pathways. apoptosis and senescence induction (Gire et al., 2004; The detection of high pT68-Chk2 in p53-deficient Powers et al., 2004; Rogoff et al., 2004; Pommier et al., lines is suggestive of the dependence of such cells on 2005; Antoni et al., 2007), other studies have shown that activated Chk2. The consequence of Chk2 inactivation/ Chk2 exerts p53-independent effects (Stevens et al., depletion in cells with high levels of this kinase is an 2003; Yang et al., 2006; Zhou et al., 2007; Solier and antiproliferative effect (Jobson et al., 2009). Jobson Pommier, 2009; Solier et al., 2009; Stolz et al., 2010) that et al. showed that PV1019, a potent and selective may even promote cell survival (Yu et al., 2001; Castedo inhibitor of Chk2, exerts antiproliferative activity in

Oncogene CHEK2 in the NCI-60 G Zoppoli et al 414 OVCAR-3 and OVCAR-4 cell lines (two lines showing Malaysia). The alignments were further processed by using high levels of activated Chk2). Moreover, they observed a GATK pipeline (http://www.broadinstitute.org/gsa/wiki/ that downregulation of Chk2 (by small interfering index.php/Main_Page). The candidate variants in CHEK2 RNA) in the OVCAR-4 cell line also causes growth were amplified by PCR and subjected to conventional capil- inhibition. Thus, Chk2 inhibition can produce antipro- lary sequencing on an ABI 3730 DNA Analyzer (Applied liferative activity in cancer cells with endogenously Biosystems, Pleasanton, CA, USA). activated Chk2. It is worth mentioning that detecting activated Chk2 in cancer may also have a prognostic mRNA processing and microarray analysis value, as shown in squamous-cell carcinoma of the mRNA extraction, purification, quality control, microarray esophagus (Sarbia et al., 2007), where Chk2 activation hybridization, profiling and quality assessment have been in tumor specimens correlates with response to neo- described elsewhere (Nishizuka et al., 2003; Reinhold et al., 2010). The microarray data sets used to generate z-score adjuvant radio-chemotherapy. profiles for the gene transcripts in the NCI-60 are down- In conclusion, the biology of Chk2 remains complex, loadable from our relational database CellMiner (http:// multifaceted and fast evolving. Our study provides discover.nci.nih.gov/cellminer/loadDownload.do) and from information on the relationship between different the GEO data repository (accession numbers GSE22821, genomic and proteomic parameters related to Chk2 in GSE5846, GSE5949, GSE5720). cancer cells, and on the broad spectrum of variation in these parameters using the NCI-60 as a systems biology Quantitation of gene transcript expression using five microarray model. Measuring Chk2 expression and activation in platforms—development of the z-scored transcript data set tumors is likely relevant for translational research. On Transcript expression data for the NCI-60 were generated the one hand, Chk2 acts as a tumor suppressor both in from five microarray platforms that have been used for gene germinal and somatic cells, and its loss is likely to expression analysis in the NCI-60: Affymetrix Human Genome contribute to the inactivation of p53 and BRCA1. On U95 (HG-U95; B60 000 features; Affymetrix Inc., Santa Clara, the other hand, Chk2 activation by DNA damage CA, USA) (Supplementary Table 1). (Shankavaram et al., B (double-strand breaks) can be measured readily using 2007), Human Genome U133 (HG-U133a and b; 44 000 pT68-Chk2 antibodies and could be used prior to features) (Shankavaram et al., 2007), Human Genome U133 Plus 2.0 (HG-U133 Plus 2.0; B47 000 features), Agilent WHG therapy to identify tumors with endogenous DNA (Reinhold et al., 2010) and Affymetrix GeneChip Human damage and genomic instability. During therapy, Exon 1.0 ST (GH Exon 1.0 ST; B850 000 features) (Nishizuka activated Chk2 may also be useful to measure the et al., 2003). Further details on mRNA processing and micro- DNA-damaging and apoptotic effects of anticancer array analysis for the aforementioned data sets have been treatments. provided elsewhere (Pfister et al., 2009; Gmeiner et al., 2010). To generate gene transcript expression values, non-degenerate probes (as determined by SpliceCenter (http://www.tigerteam consulting.com/SpliceCenter/SpliceOverview.jsp)) from the five Materials and methods platforms with an intensity range of X1.2 log2 and with a Pearson’s correlation coefficient with other probes X0.60 were Cell lines used. Probes passing these quality criteria were used to The NCI-60 panel of cancer cell lines was obtained from determine a z-score value for gene transcript intensities as the NCI Developmental Therapeutics Program and grown in follows: the mean for each probe intensity value across the NCI- RPMI-1640 (Lonza Walkersville Inc., Walkersville, MD, USA) 60 was subtracted from that probe value in individual samples, with 10% fetal calf serum (Atlantic Biologicals Corp., Miami, and divided by its s.d. z-scores were then averaged to generate a FL, USA) and 2 mML-glutamine (Invitrogen Corp., Frederick, consensus gene transcription profile across all the five platforms MD, USA) as described previously (Scherf et al., 2000). The used for such analysis. cervix carcinoma HeLa cell line was obtained from ATCC (Rockville, MD, USA). Exon array analysis of CHEK2 transcript After feature extraction, pre-processing and normalization of Chemicals Affymetrix GeneChip Human Exon 1.0. ST arrays according The DNA-PK kinase inhibitor (NU7441 ¼ DNA-PK-i) and to Partek default specifications, non-degenerate probe sets (as the ATM kinase inhibitor (KU55933 ¼ ATM-i) were from defined in SpliceCenter) for CHEK2 were normalized accord- Tocris Bioscience (Ellisville, MO, USA). ing to the robust z-score method: the median of the expression of a given probe set in the NCI-60 was subtracted from the individual values for that probe set, and divided by the High-throughput sequencing, data analysis and validation normalized inter-quartile range (that is, the inter-quartile A manuscript is under preparation, which will describe the range multiplied by a factor of 0.7413, which makes it details and the overall results of the high-throughput sequen- comparable to a s.d.). The resulting values, after median- cing and data analysis. Briefly, the whole exome of the NCI-60 centering, were used to generate a clustered image map (CIM panel of cell lines was sequenced by using the SureSelect for short) of probe set expression. Human Whole Exome capture kit (Agilent Inc., Germantown, MD, USA) according to the manufacturers’ protocol, followed by 2 Â 80-bp paired-end reads using the Illumina Genome aCGH analysis Analyzer IIx (Illumina Inc., San Diego, CA, USA). Base For aCGH analysis, samples from the NCI-60 were prepared calling was performed by using the standard Illumina pipeline and analyzed with NimbleGen 385K aCGH chips (NimbleGen followed by alignment to the reference human genome build HG18 CGH 385K WG Tiling v2.0; NimbleGen Systems Inc., hg18 using Novoalign (Novocraft Technologies, Selangor, Madison, WI, USA) according to the manufacturer’s specifications

Oncogene CHEK2 in the NCI-60 G Zoppoli et al 415 (http://www.nimblegen.com/products/lit/cgh_userguide_v6p0.pdf) (Santa Cruz Biotechnology, Santa Cruz, CA, USA). Signals (Nishizuka et al., 2003). The experiment did not include HT29. were revealed by autoradiography using the Enhanced Chemi- In brief, 1.5 mg of genomic DNA from cancer cell lines and luminescence detection kit (Pierce, Rockford, IL, USA). The from human male reference samples were purified, labeled relative band intensities were determined by densitometry by using Cy3-Random and Cy5-Random Nonamers respectively, using the Labworks 4.0 Imaging Acquisition and Analysis and hybridized to NimbleGen arrays. NimbleGen pairs files software (UVP Laboratory productsdivers, Upland, CA, USA). were then loaded in Partek 6.4 (Partek Inc., St Louis, MO, The protein expression data for each cell line was replicated in USA) for further analysis. at least three independent experiments. The primary antibodies used are as follows: anti-b-actin Quantitative PCR (Millipore), anti-pS988-BRCA1 (#sc-12888; Santa Cruz Biotech- The cell lines HCT-116 and SKOV-3 were washed in nology), anti-BRCA1 (#MS110; Calbiochem, EMD Biosciences, phosphate-buffered saline (PBS). RNA extraction was per- San Diego, CA, USA), anti-pS123-CDC25A (#AP3045a; formed with the Nucleospin RNA II kit (Macherey-Nagel, ABGENT, San Diego, CA, USA), anti-CDC25A (#sc-7389; Bethlehem, PA, USA). An aliquot of 1 mg of RNA was reverse- Santa Cruz Biotechnology), anti-pS216-CDC25C (#9528; transcribed by using a reverse transcription kit (Promega, Cell Signaling, Danvers, MA, USA), anti-CDC25C (#cc26; Madison, WI, USA). Real-time PCR was performed with Calbiochem), anti-pT68-Chk2 (#2661; Cell Signaling), anti- the SYBR Green PCR Master Mix (Applied Biosystems, Chk2 ((#2662; Cell Signaling), anti-g-H2AX (#05-636; Upstate, Carlsbad, CA, USA) on the ABI 7900 thermocycler (Applied Temecula, CA, USA) and anti-GAPDH (glyceraldehyde-3- Biosystems). The expression level of the gene of interest phosphate dehydrogenase) (#2118; Cell Signaling). was normalized by the b2-microglobulin RNA level of the same sample. The reaction mixtures contained 5 mlof2Â Immunofluorescence microscopy Quantitect SYBR-Green PCR Master Mix and 2 ml of reverse- Cells were washed with PBS; fixed with 2% formaldehyde in transcriptase-generated cDNA (diluted by 10) in a final volume PBS for 20 min; washed with PBS; fixed and permeabilized of 10 ml containing primers (Proligo, Paris, France) at 125 nM. with cold (À20 1C) 70% ethanol for 20 min; washed with PBS; ÀDDCt Relative gene expression was expressed as 2 (DDCt ¼ blocked with 8% bovine serum albumin in PBS for 1 h; washed DCt(sample)ÀDCt(calibrator); DCt ¼ Ct(gene)ÀCt(b2-microglobulin)). The with PBS; incubated with the first antibody (pT68-Chk2; 1/500 primer sequences are listed in Supplementary Table 2. dilution; g-H2AX, 1/500 dilution) in 1% bovine serum albumin in PBS for 2 h; washed with PBS; incubated with RT–PCR the secondary antibody conjugated with Alexa Fluor-488 or The OneStep RT–PCR kit (Qiagen, Valencia, CA, USA) was 568 for 1 h at RT; washed with PBS and mounted by using the Vectashield mounting medium with DAPI (40,6-diamidino- used under the following conditions: 1 Â buffer, 400 mM of each dNTP, 0.6 mM of each primer, 2 ml of enzyme mix and 2-phenylindole) to counterstain the DNA (Vector Laboratories, 1 mg of template RNA in a total volume of 50 ml. RNA Inc., Burlingame, CA, USA). Confocal images were sequentially was reverse-transcribed for 30 min at 50 1C; the initial PCR acquired with the Zeiss AIM software on a Zeiss LSM 510 NLO step was activated by heating for 15 min at 95 1C before Confocal system (Carl Zeiss Inc., Thornwood, NY, USA). the PCR (1-min denaturation at 94 1C, 1-min annealing at 60 1C, 1-min extension at 72 1C, 32 cycles) by using a MJ Pathway analysis Research PTC-200 Thermo Cycler (MJ Research, Reno, Gene expression data were analyzed for pathway enrichment NV, USA). The PCR products were analyzed on agarose gels. by Ingenuity Pathways Analysis (Ingenuity Systems, Redwood The amplified DNA fragments were stained with ethidium City, CA, USA). bromide and fluorescence was detected by video-camera imaging using the Quantity One software (Bio-Rad, Hercules, Statistical analyses CA, USA). The primer sequences are listed in Supplementary Agilent output text files were analyzed by using Agilent Table 2. GeneSpring GX 10.0 (Agilent Technologies, Santa Clara, CA, USA), whereas Affymetrix CEL files and NimbleGen pairs Western blotting files were analyzed by using the Partek software (Partek Inc.). Whole-cell lysates were prepared from logarithmically growing All data sets were processed and normalized, before z-score populations of the NCI-60 human tumor cell line panel. transformation, according to the default options of the Approximately 1 Â 107 cells were lysed with 1 Â RIPA buffer software used, with the exception of normalization for the (Millipore, Billerica, MA, USA) or in buffer containing 1% Affymetrix data (GCRMA for all platforms) and probe sodium dodecyl sulfate, 10 mM Tris–HCl (pH 7.4), supple- summarization for gene copy number analysis for the mented with protease inhibitors (Roche Applied Science, NimbleGen data (minimum 15 probes for any gene). The data Indianapolis, IN, USA) and phosphatase inhibitors (Sigma were then loaded into R for further analysis (http://www. Chemical Co., St Louis, MO, USA). Total protein concen- R-project.org). Unpaired t-tests with equal variance assumption trations were determined using the Bio-Rad Protein Assay were applied for differential gene expression between high- (Bio-Rad Laboratories Inc., Hercules, CA, USA). Equal pT68-Chk2 cells and low-pT68 cells, retaining genes significant amounts of proteins were boiled for 5 min in Tris-glycine- at a Po0.01 (two-tailed). Robust z-score transformation was sodium dodecyl sulfate sample buffer (Invitrogen, Carlsbad, used to normalize exon probe set data. CIMs were generated CA, USA) or heated at 70 1C for 10 min in lithium dodecyl with the CIMMiner tool, available freely on our Genomics and sulfate sample buffer (Invitrogen), separated by Tris-glycine or Bioinformatics Group website (http://discover.nci.nih.gov/). Tris-acetate polyacrylamide gels (Invitrogen) and electroblotted The ‘1-Pearson’ method was used for exon CIM and for onto nitrocellulose membranes (Bio-Rad). The membranes differential gene expression CIM. The clustering method was were saturated with milk, incubated overnight at 4 1C with average linkage for both types of CIM. In pathway analyses primary antibodies, washed and then incubated for 45 min with Ingenuity, processes and pathways were considered with secondary antibodies: peroxidase-conjugated goat anti- significantly enriched when having a Po0.05. Western blot mouse IgG or peroxidase-conjugated goat anti-rabbit IgG triplicates were normalized to the b-actin content of each

Oncogene CHEK2 in the NCI-60 G Zoppoli et al 416 membrane and the ratio with HeLa cell lysate was calculated. Molecular Targets and Cancer Therapeutics (Boston, 15–19 Individual outliers in triplicates were removed by using the November 2009) and at the 101st AACR Annual Meeting Grubbs’ test and the means for the remaining values were (Washington DC, 17–21 April 2010). We thank Sven Bilke, generated. R was used for statistical analysis and for graphics Yuan Jiang, Marbin Pineda, Robert Walker and Yuelin Zhu generation. Figures were finalized with Adobe Design Suit for technical help in next-generation sequencing and data Standard CS3. analysis, and Jaleisa Turner for help in capillary sequencing. We also thank Margot Sunshine (LMP BioInformatics Groups) for invaluable work and technical help. GZ thanks Dr P Blandini for insightful suggestions on the possible Conflict of interest consequences of Chk2 activation in cancer treatment. Fund- ing: This work was supported by the Center for Cancer The authors declare no conflict of interest. Research, Intramural Program of the National Cancer Institute, and by the Division of Cancer Treatment and Diagnosis, Extramural Program of the National Cancer Acknowledgements Institute (National Institutes of Health), and by AIRC MFAG grant no. 10570 (GZ). GZ was also supported by a PhD The present data were in part presented in abstract form at fellowship grant (XXIII Ciclo) from the University of Genova the 21st EORTC-NCI-AACR International Symposium on (Genova, Italy).

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