Pazopanib and lapatinib are two tyrosine kinase inhibitors that have been designed to inhibit the VEGF tyrosine kinase receptors 1, 2 and 3 (pazopanib), and the HER1 and HER2 receptors in a dual manner (lapatinib). Pazopanib has also been reported to mediate inhibitory effect on a selected panel of additional tyrosine kinases such as PDGFR and c-kit. Here, we report that pazopanib and lapatinib act synergistically to induce apoptosis of A549 non-small-cell lung cancer cells. Systematic assessment of the kinome revealed that both pazopanib and lapatinib inhibited dozens of different tyrosine kinases and that their combination could suppress the activity of some tyrosine kinases (such as c-Met) that were not or only partially affected by either of the two agents alone. We also found that pazopanib and lapatinib induced selective changes in the transcriptome of A549 cells, some of which were specific for the combination of both agents. Analysis of a panel of unrelated human carcinoma cell lines revealed a signature of 52 genes whose up- or downregulation reflected the combined action of pazopanib and lapatinib. Indeed, pazopanib and lapatinib exerted synergistic cytotoxic effects on several distinct non-small-cell lung cancer cells as well as on unrelated carcinomas. Altogether, these results support the contention that combinations of tyrosine kinase inhibitors should be evaluated for synergistic antitumor effects. Such combinations may lead to a ‘collapse’ of pro-survival signal transduction pathways that leads to apoptotic cell death.
The unwarranted survival of cancer cells relies on the constitutive activation of growth factor receptors, often tyrosine kinase receptors, that may be overactivated due to their overexpression, activating mutations and/or the continuous presence of their ligands. The continuous phosphorylation of their substrates on tyrosine residues then can improve the flux of metabolites through the plasma membrane (Flier et al., 1987), a process that is essential for anabolic reactions required for tumor cell growth (Edinger, 2007). In addition, receptor tyrosine kinases signal for growth (Hulit et al., 2002), inhibition of cell death (Barnes and Kumar, 2003) as well as increased motility and angiogenesis (Petit et al., 1997), thereby contributing to the phenotypic characteristics of cancer. For this reason, specific or general tyrosine kinase inhibitors have been developed for anticancer therapy, and spectacular progress has been achieved in the treatment of selected malignancies relying on the constitutive signaling of Bcr-Abl (chronic myeloid leukemia) (Druker et al., 2001), c-kit (gastrointestinal stromal tumor, GIST) (Sleijfer et al., 2008), HER2 (breast cancer) (Cameron and Stein, 2008) and HER1 (non-small-cell lung cancer, colorectal cancer, squamous cell head and neck cancer and pancreatic cancer) (Ciardiello and Tortora, 2008), among others (Noble et al., 2004). As a result, tyrosine kinase inhibitors are under close scrutiny for the targeted therapy of multiple distinct neoplasias.
Pazopanib (GW786034B) is a multitarget kinase inhibitor that blocks the VEGF tyrosine kinase receptors 1, 2 and 3 (VEGFR-1, -2 and -3), which have a key function in the regulation of normal and pathological angiogenesis (Harris et al., 2008). In addition, but to a lesser extent, pazopanib also inhibits PDGFR and c-kit (Kumar et al., 2007). In xenograft models, pazopanib inhibits the growth of a broad range of human tumors including colon, lung, breast, renal and prostate carcinomas, chondrosarcoma, leiomyosarcoma, melanoma, multiple myeloma and GIST (Kumar et al., 2007). Pazopanib is currently evaluated in a phase III clinical trial for the therapy of metastatic renal cell carcinoma (Sonpavde et al., 2008). Although VEGFR inhibitors are commonly thought to act through an effect on tumor endothelial cells, thus preventing neovascularization (Kerbel, 2008), it has become clear that tumor cells themselves can also express VEGFR isoforms at their surface (Donnem et al., 2007), and that they can receive trophic signals through VEGFR (Podar et al., 2006; Lee et al., 2007; Kerbel, 2008), implying that VEGFR antagonists may mediate cell-autonomous antitumor effects.
Lapatinib (GW572016F) is an inhibitor of HER1 (ErbB1) and HER2 (ErbB2) (Wood et al., 2004). Preclinical studies have shown the growth-inhibitory activity of lapatinib, notably in cell lines that have become resistant against trastuzumab, a monoclonal antibody targeting HER2 (Konecny et al., 2006). Recently, lapatinib has been approved for treating HER2-positive metastatic breast cancer in combination with capecitabine (Geyer et al., 2006; Cameron and Stein, 2008). As a result, lapatinib can be expected to exert direct cytotoxic and cytostatic effects on tumor cells that are addicted to HER1 or HER2 or both (Press et al., 2008).
Pazopanib and lapatinib, when used in combination, have recently shown preliminary efficacy in patients with breast cancer (Sloan and Scheinfeld, 2008). Here, we report the unexpected finding that pazopanib and lapatinib with different spectrums of activity have a hyperadditive proapoptotic effect on a range of different cancer cell lines. In particular, pazopanib and lapatinib synergistically inhibit a selected set of tyrosine kinases and both agents synergistically influence the expression level of a limited set of genes. Altogether, our results describe how two tyrosine kinase inhibitors that target different branches of the kinome can cause a collapse of essential survival signals, thereby resulting in tumor cell apoptosis.
Results and discussion
Synergistic proapoptotic activity of pazopanib and lapatinib on A549 non-small-cell lung cancer cells
When different combinations of two distinct kinase inhibitors (pazopanib or lapatinib), an antimetabolite (pemetrexed) or a classical DNA-damaging agent (cisplatin) were preliminarily tested for their capacity to inhibit the growth of A549 non-small-cell lung cancer cells in vitro, we found that only the combination of pazopanib and lapatinib exerted a clear hyperadditive effect (Figure 1). We therefore chose a range of distinct concentrations of both agents to construct a rotatable 2 factors design matrix and tested them for their putative synergistic effect on the metabolic activity (tested by a tetrazolium salt conversion assay) on A549 cells (Figure 2a), thus constructing a model that estimates the synergism between pazopanib and lapatinib (Figure 2b), according to the response surface method. The full model showed no significance of any of the parameters, but retained the pazopanib/lapatinib interaction as significant (P<1E–3) after optimization by Akaike Information Criterion. The optimal model, containing lapatinib and pazopanib/lapatinib interaction, was then validated by a chessboard analysis in which different concentrations of both agents were combined in a systematic manner (Figure 2c), yielding a close correlation between the calculated and experimental values, especially when we considered the isodose curve at 10 μM (Figure 2d) that showed a higher effect of a combined treatment compared to a single treatment (at an identical amount of drug). Altogether, these results indicate that pazopanib and lapatinib have a synergistic antiproliferative activity on A549 cells. These synergistic effects were obtained at concentrations that were close to the clinically attainable concentrations of pazopanib (40–60 μg/ml) (Hurwitz et al., 2009) and of lapatinib (2.5 μg/ml) (Storniolo et al., 2008). However, the direct translation of these in vitro data to the clinics is difficult, given the fact that our cells are not grown in the presence of all the binding proteins that may bind these agents in human plasma. Attempts to perform the experiments in 50% human serum failed because the cells did not grow (not shown).
The combination of pazopanib and lapatinib yielded lower levels of tetrazolium conversion than each drug alone (Figures 1 and 2c) after beginning of the cultures, yielding values that were lower than before addition of the agents (T0), suggesting that at these concentrations they exerted cytotoxic rather than merely cytostatic effects. We therefore tested the capacity of both drugs, alone or in combination, to induce cell death. Indeed, the combination of pazopanib and lapatinib (but neither of two drugs alone) triggered apoptosis, as indicated by chromatin condensation (Figure 3a), the morphological feature that defines apoptotic cell death (Kroemer et al., 2009). Accordingly, pazopanib and lapatinib together (but neither alone) induced several biochemical hallmarks of apoptosis including the loss of the mitochondrial transmembrane potential and exposure of phosphatidylserine residues on the surface of the plasma membrane (Figure 3b), as well as DNA degradation leading to the accumulation of cells with a subdiploid DNA content (Figure 3c). The combination of pazopanib and lapatinib also induced a reduction in clonogenic survival of A549 cells, in conditions in which pazopanib and lapatinib alone had minor or no effects (Figure 3d).
Taken together, these results indicate that pazopanib and lapatinib have synergistic cytotoxic effects on the survival of A549 cells that may be explained by the induction of apoptotic cell death.
Hyperadditive effects of pazopanib and lapatinib on the kinome and the transcriptome of A549 cells
Pazopanib and lapatinib have been developed as inhibitors of the VEGFR and HER1/HER2 receptors, respectively. The ensemble of kinases, the kinome, is organized in a network of interacting cascades with multiple cross talks (Manning et al., 2002; Johnson and Hunter, 2005). To study the effects of pazopanib and lapatinib on the kinome, we generated lysates from A549 cells that had been preincubated with pazopanib or lapatinib or both for 12 h—well before any kind of cytotoxic activity can be detected (data not shown)—and applied these lysates to peptides immobilized on glass slides. The activity of kinases contained in the lysate was then monitored by detecting phosphotyrosine residues using specific antibodies that were visualized by means of an immunochemical method (Figure 4a). Both lapatinib and pazopanib alone inhibited multiple kinases. The combination of both inhibitors yielded a hyperadditive effect on some kinase activities (Figure 4b; Supplementary Table S1), meaning that lapatinib and pazopanib in combination inhibited some tyrosine kinase activities (such as c-Met kinase) down to background levels, although each of the inhibitors alone had marginal or partial effects on their activity (Figure 4b; Table 1). These results indicate that pazopanib and lapatinib can provoke the ‘collapse’ of selected portions of the kinome, if they act concomitantly. In this context, it is particularly interesting that the combination of lapatinib and pazopanib led to a complete inhibition of c-Met. Indeed, it has been reported that c-Met inhibition—together with EGFR inhibition—has a synergistic antiproliferative effect on non-small-cell lung cancer cell lines in vitro, including the A549 cells that were used in our experiments (Puri and Salgia, 2008). Moreover c-Met inhibition alone suppresses the proliferation of A549 cells that were xenografted on immunodeficient mice (Puri et al., 2007), underscoring that the inhibition of c-Met likewise contributes to the synergistic activity of lapatinib and pazopanib. Whether additional kinases that co-inhibited by lapatinib and pazopanib may contribute to their synergistic cytotoxicity remains elusive. However, it appears that the combined inhibition of lapatinib- and pazopanib-sensitive kinases can lead to the pronounced inhibition of several kinases with known pro-survival activities (see Concluding remarks).
To further evaluate the functional impact of pazopanib and lapatinib on non-small-cell lung cancer cells, we evaluated the consequences of pazopanib and lapatinib on the transcriptome. The expression analyses were again performed at 12 h, using concentrations of lapatinib and pazopanib that cause 50% of the cells to enter an early phase of apoptosis at 24 h (defined by the collapse of the mitochondrial transmembrane potential) (Castedo et al., 2002). This design was chosen based on the fact that at 12 h less than 10% of the cells had entered early apoptosis in response to the combination of both agents. We reasoned that it would be important to define transcriptome changes that occur during the proapoptotic signaling phase rather than those occurring during the execution of the apoptotic program (Castedo et al., 2006; Vitale et al., 2007; de La Motte Rouge et al., 2007), when RNAs (Houge et al., 1995; Nadano and Sato, 2000) and the death-associated bioenergetic collapse (Thompson et al., 2004; Klawitter et al., 2009) may affect the transcriptome in a nonspecific manner. Microarray analyses revealed that pazopanib and lapatinib, given together, influenced the expression of a selected set of genes that were not affected by either of the tyrosine kinase inhibitors alone (Figure 5a). A total of 174 RNA species that were overexpressed or downregulated after the combination treatment were not influenced in the same manner by either pazopanib or lapatinib alone (Figure 5b; Table 2; Supplementay Table S2). These analyses hence suggest that selective combination effects of pazopanib and lapatinib may predict their synergistic toxicity on non-small-cell lung cancer cells.
Synergistic anticancer activity of pazopanib and lapatinib on multiple carcinoma cell lines
On the basis of aforementioned results, we suspected that the transcriptome effects of pazopanib and lapatinib might indicate synergistic cytotoxic activities of both tyrosine kinase inhibitors. We therefore validated the set of 174 mRNAs (Figure 5b) whose expression level is up- or downregulated by pazopanib and lapatinib in A549 cells on a panel of distinct carcinoma cells representing non-small-cell lung cancer (H1975 carrying an EGFR mutation abolishing erlotinib-mediated antiproliferative effects and H1299 with mutated p53), gastric cancer (AGS) and colon cancer (HCT116). A significant fraction of the mRNA species (33%) identified in the initial A549 screen were modulated in the same manner by the combination of pazopanib and lapatinib (but not by other chemotherapeutic agents such as cisplatin, or drug combinations; data not shown) in all the cell lines (Figure 5c; Supplementary Table S3), suggesting that pazopanib and lapatinib might exert synergistic effects on multiple different malignancies. Among the 58 genes that were induced specifically by the combination regimen in all cell lines, several have previously been involved in apoptotic signaling, in particular p53 (Pietsch et al., 2008), PHLDA1 (also known as T-cell-death-associated gene 51, TDAG51) (Hayashida et al., 2006; Joo et al., 2007; Oberst et al., 2008) and RHOT1 (ras homolog gene family, member T1; also known as mitochondrial Rho; Miro1) (Fransson et al., 2003). Indeed, we observed that the combination of pazopanib and lapatinib was able to kill the five carcinoma cell lines included in the transcriptome analysis, as well as ovarian (SKOV3) and cervix cancer cells (HeLa), yielding highly significant synergistic effects of both compounds as compared to each of them alone (Figure 5d; Supplementary Table S4). In conclusion, pazopanib and lapatinib may cooperate to mediate generally cytotoxic effect on multiple carcinomas.
We report here the unexpected finding that the use of tyrosine kinase inhibitors designed to inhibit HER1/HER2 and VEGFR can exert synergistic cytotoxic effects on a variety of carcinoma cell lines. Synergistic anticancer effects are potentially interesting for the clinical application of drugs, following the dual aim of reducing side effects (by reducing the concentration of the agents used for anticancer therapy) and improving therapeutic efficacy (by obtaining systemic lethal effects on tumor cells). It has been shown in the past that inhibition of HER1 can induce cell death in HER1-dependent cancer cells (Helfrich et al., 2006), and it has also been shown that inhibition of VEGFR can exert direct (cell-autonomous) effects on VEGFR-expressing tumor cells, beyond the angiostatic (non-cell-autonomous) effects of VEGFR inhibitors on endothelial cells (Fan et al., 2005; Bianco et al., 2008; Simiantonaki et al., 2008; Sini et al., 2008). Here, we show that pazopanib and lapatinib together are much more potent in their antiproliferative and proapoptotic activities than either of the two agents alone. In support of these findings, a recent article reported a supraadditive effect of a dual HER1/VEGFR inhibition (gefitinib+AZD2171) in head and neck cancer xenografts (Bozec et al., 2007) and preliminary data in patients with breast cancer suggested clinical activity of pazopanib and lapatinib when administered as a combination (Sloan and Scheinfeld, 2008). However, it would be premature to conclude that the specific inhibition of HER1, HER2 and VEGFR has a synergistic effect. Indeed, both pazopanib and lapatinib are not uniquely specific inhibitors of HER1/HER2 and VEGFR, respectively, and rather inhibit multiple tyrosine kinases (Karaman et al., 2008). Although we did not assess the complete repertoire of tyrosine kinases targeted directly by these agents, the characterization of the kinome influenced by pazopanib and lapatinib suggests that both agents can inhibit (directly or indirectly) 50–100 different tyrosine kinase activities independently, at least at the relatively high concentrations used here. Indeed, emerging clinical data are suggesting the benefit of high-dose pulse treatments of tyrosine kinase inhibitors in combination with other molecules in cancer patients (Chien et al., 2008; Riely et al., 2009). Thus, at concentrations that should be therapeutically relevant, both pazopanib and lapatinib can influence multiple kinases, well beyond the narrow range of activities that has been defined for them (VEGFR-1, -2, -3; PDGFR and c-kit for pazopanib, and HER1 and HER2 for lapatinib). Of note, the combination of pazopanib and lapatinib suppressed the activity of some kinases by 100% although each kinase inhibitor on its own exerted only partial effects. This is true, in particular, for c-Met, a kinase whose activity was completely extinguished by pazopanib and lapatinib. Inhibition of c-Met has been shown to exert cytotoxic effects on A549 cells (Puri et al., 2007), suggesting that c-Met inhibition might explain some of the synergy of the pazopanib/lapatinib combination. How this ‘combined’ blockade of c-Met is achieved remains unknown. However, it is possible that the inhibition of other kinases may indirectly affect c-Met (Peruzzi and Bottaro, 2006; Comoglio et al., 2008). However, beyond c-Met, the complete inhibition of FGFR, ZAP70, ALK and FAK activation that we observed in the condition of combined treatment can also have proapoptotic effects (Golubovskaya et al., 2002; Danilov et al., 2005; Mourali et al., 2006; Calandrella et al., 2007). Of note, lapatinib has previously shown a dose- and time-dependent effect on phosphoproteins such as FOXO3A and its target protein p27 (Hegde et al., 2007). It is not known how such time-dependent effects would affect our observations.
Before any signs of apoptosis were detectable, pazopanib and lapatinib induced a major change in the transcriptome leading to the specific induction of a panel of proapoptotic mRNA species that was first retrieved among A549 cells and then validated on a series of additional non-small-cell lung cancers and a diverse array of unrelated carcinoma cell lines. Although the exact molecular mechanisms that link the extinction of tyrosine kinase activities to changes in gene expression remain elusive, these results point to the possibility to identify biomarkers that predict a therapeutic response induced by pazopanib together with lapatinib, as well as giving new insight as to better understand the hyperadditive action of both tyrosine kinase inhibitors. Anyhow, our data support further implementation of clinical trials associating lapatinib and pazopanib at various schedules and dosages in different cancers.
Materials and methods
Cell lines and culture
All cell lines were purchased from the ATCC cell collection. A549 and AGS cells were grown in F12-K medium from Gibco-Invitrogen (Carlsbad, CA, USA) containing L-glutamine, supplemented with 10% fetal calf serum (FCS), 100 U/ml penicillin G sodium and 100 μg/ml streptomycin sulfate. H1299 and H1975 cells were maintained in RPMI 1640 medium with GlutaMAX supplemented with 10% FCS and antibiotics (as above). HCT116 and SKOV3 cells were grown in McCoy’s 5A medium supplemented with 10% FCS. HeLa cells were grown in Dulbecco’s modified Eagle’s medium (DMEM) supplemented with 10% FCS, 100 U/ml penicillin, 100 mg/ml streptomycin and hygromycin B (125 mg/ml) under 5% CO2. For proliferation assays, all cell lines were cultured in DMEM/F12 (1:1) with L-glutamine but no phenol red supplemented with 10% FCS and 100 U/ml penicillin, 100 mg/ml streptomycin.
Pazopanib (GW786034B) and lapatinib (GW572016F) were obtained from GlaxoSmithKline (Brentford, UK) and dissolved in neat dimethyl sulfoxide (DMSO) at 10 mM and conserved in small aliquots at −20 °C. All experiments were designed to obtain an equal amount of DMSO in every well. Cisplatin (CDDP) was dissolved in DMSO at 100 mM, and pemetrexed (Alimta, Eli Lilly, Indianapolis, IN, USA) was diluted at 10 mM in water and conserved as aliquots at −20 °C.
Cell proliferation assay
For proliferation assays, 25 × 103 cells per ml were seeded in triplicates in 96-well plates (2500 cells per well) 18 h before the treatment with pazopanib, lapatinib, cisplatin and/or pemetrexed at concentrations varying from 5 to 40 μM. Treatments were prolonged for 48 or 72 h before the assessment of end-point cell proliferation. As recommended by Monks et al. (1991), cell proliferation was quantified at time zero (T0, the time at which the drugs were added) and at end point (T48 or T72, 48 and 72 h after T0) by means of a colorimetric assay, which measures the conversion of the colorless tetrazolium salt WST-1 (4-[3-(4-iodophenyl)-2-(4-nitrophenyl)-2H-5-tetrazolio]-1,3-benzene disulfonate) to formazan (λ=450 nm) catalysed by cellular dehydrogenases. For this, the Cell Proliferation Reagent WST-1 (Roche Applied Science, Penzberg, Germany) was used.
Assessment of apoptosis and cell-cycle distribution
A549 cells were incubated in triplicate wells for 72 h with 8 μM of pazopanib, or 10 μM of lapatinib or both. These concentrations were chosen for their cytotoxic effect on A549 cells in the proliferation assays (loss of cells compared to T0). Apoptotic cells were quantified by cytofluorometric analysis using a FACSVantage apparatus (Becton Dickinson, Mountain View, CA, USA) as described previously (Zamzami and Kroemer, 2004). Thus, after trypsination, cells were washed and then stained with propidium iodide (PI; 1 μg/ml; Sigma, Steinheim, Germany) and with either DiOC6(3) (3,3-dihexyloxacarbocyanine iodide; 40 nM; Molecular Probes, Eugene, OR, USA) for 15 min at 37 °C to determine the mitochondrial transmembrane potential, or the Annexin V antibody (BD Pharmingen, San Diego, CA, USA) as recommended by the manufacturer. For cell-cycle analyses, cells were harvested, washed and stained with Hoechst 33342 (10 μg/ml; Invitrogen) followed by an incubation period of 30 min at room temperature. Subsequently cell-cycle distribution was determined by cytofluorometric analysis.
Microscopic evaluation of dying cells
For microscopic evaluation, A549 cells were seeded on LabTek slides (Nalge Nunc, Naperville, IL, USA), previously treated with polylysine. After 72 h of drug treatment (8 μm of pazopanib, 10 μM of lapatinib or both) the LabTek slides were centrifuged and cells stained with Hoechst 33342 (10 μg/ml) and PI (1 μg/ml). Slides were mounted and cells were evaluated under a Leica Microsystems (Wetzlar, Germany) confocal microscope.
A549 cells were incubated in triplicate for 72 h with 8 μM of pazopanib, or 10 μM of lapatinib or both, and washed with growth medium before long-term incubation. Clones were stained in crystal violet according to standard procedures after 14 days of incubation. Only clones representing more than 50 cells were counted.
Extraction of RNA and whole-cell lysate preparations
Cells were seeded at 50 000 cells per ml in six-well plates (2 ml per well) in duplicate. Each cell line was treated after 18 h of cell culture stabilization. For kinome and transcription analysis, the treatment duration was 12 h (before the appearance of apoptotic effects) using drug concentrations that demonstrated cytotoxic effect on all cell lines (20 μM pazopanib and 10 μM lapatinib). In controls, drugs were replaced with medium containing DMSO at equivalent concentrations. For kinase assays, whole-cell lysates were prepared according to standard established protocols. Briefly, the cells were washed three times in cold phosphate-buffered saline, solubilized with cell lysis buffer (Cell Signaling Technology, Boston, MA, USA) and gently homogenized. After 30 min on ice, cellular fragments were precipitated at 10 000 r.p.m. in a cold centrifuge and the quantification of the protein concentration was determined by the DC protein assay (Bio-Rad, Hercules, CA, USA). For transcriptome analysis, cultures were stopped at T12 by addition of 400 μl of RLT buffer (Qiagen, Hilden, Germany). RNAs were extracted using RNeasy Micro Kit (Qiagen) according to the manufacturer’s recommendations. Briefly, 350 μl of lysate was collected from each well. RNAs were precipitated with equal volume of ethanol 80% and placed into spin columns. After centrifugation RNAs were washed with RW1 reagent and treated with DNase for 15 min at room temperature. After washes, RNAs were eluted with 14 μl of RNase-free distilled water, quantified and qualified with Nanodrop ND-1000 spectrometer and Bioanalyser-2100 (Agilent, Santa Clara, CA, USA).
After determination of protein concentrations in cell lysates, these (200 μg per array) were applied on CelluSpot Tyrosine-kinase substrates I microarrays (Intavis Bioanalytical Instruments, Koeln, Germany) in tyrosine kinase buffer (Cell Signaling Technology) with 1% bovine serum albumin for 1 h and 30 min at room temperature. The microarray slides were then incubated with antibodies specific for tyrosine phosphopeptides (horseradish-peroxidase-conjugated mouse monoclonal anti-phosphotyrosine antibody (R&D Systems, Minneapolis, MN, USA) before revelation by means of ECL Detection kit (Amersham Pharmacia, Pittsburgh, PA, USA) and Hyperfilm X-ray films (Amersham Pharmacia). Quantification of spots was performed using a camera in the Syngene GBox (Ozyme, Saint Quentin en Yvelines, France) and its associated image software.
Gene expression analysis
Gene expression analysis was performed by dual-color competitive hybridization on Agilent 4 × 44K gene expression microarrays, according to the manufacturer’s recommendations. Briefly, 500 ng of RNA, extracted as previously described, was transcribed into cDNA. cRNA probes were synthesized with T7 RNA polymerase and labeled by incorporation of CTP-cyanine 3 for untreated control cells and CTP-cyanine 5 for treated cells. Each treated cell line was hybridized against its corresponding untreated control overnight at 65 °C. After washes, slides were digitized into the Agilent scanner station. Quality controls and ratio calculation were performed with Feature Extraction software (Agilent), and data were transferred into R software for statistical analysis.
Calculations and statistical analysis
The analysis of the effect of drug treatments on cell survival was performed by calculating an inhibition index (called ‘Effect’) from the absorbance measurements (optical density, OD), after blank deduction, as follows (Monks et al., 1991):
This transformation has the advantage of giving values from 0 to 200 that are increasing directly in relation to the effect due to each treatment condition. If the score equals 0, the effect is null (control condition). If the score is 100, the number of cell is equivalent to T0 (OD.treated=OD × T0), meaning there is a complete cytostatic effect. Finally, if the score is between 100 and 200, the effect is cytotoxic.
Research of significant growth inhibition effects was performed with R software (version 2.6.1, 2007-11-26) by using a response surface method where the full model was initially supposed to be of the form:
To compare drug effects between different cell lines, we calculated the index of Bliss (Bliss, 1939). First, an inhibition score was calculated as above, taking values between 0 and 200. The expected effect of the combination was then estimated from each separate drug effect: EExp=EPaz+ELap−(EPaz.ELap) and a ratio Observed/Expected was calculated. An index=1 indicates an additive effect, whereas index<0 and >1 indicate, respectively, antagonistic and synergistic effect of the combination.
To identify a specific gene expression signature associated with the pazopanib/lapatinib combination on A549 cell lines, we used a limma procedure (Wettenhall and Smyth, 2004). An initial filtering was applied to include only sequences that were significantly modified (P<10−3) in each treatment condition (in both duplicates). The A549 pazopanib/lapatinib signature was then studied on other cell lines by using a sam procedure (Wu, 2006). The q-value calculation was used as false discovery rate procedure control, according to Storey and Tibshirani (2003).
Conflict of interest
The authors declare no conflict of interest.
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GK received grants from Ligue Nationale contre le Cancer (équipe labellisée), Agence Nationale de Recherche, Institut National contre le Cancer, Cancéropôle Ile-de France, European Union (Active p53, ApoSys, ChemoRes, DeathTrain, RIGHT, TransDeath) and Fondation pour la Recherche Médicale.
Supplementary Information accompanies the paper on the Oncogene website (http://www.nature.com/onc)
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Olaussen, K., Commo, F., Tailler, M. et al. Synergistic proapoptotic effects of the two tyrosine kinase inhibitors pazopanib and lapatinib on multiple carcinoma cell lines. Oncogene 28, 4249–4260 (2009). https://doi.org/10.1038/onc.2009.277
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