PIM kinases are a potential prognostic biomarker and therapeutic target in neuroblastoma
Diede Brunen1, Romy C. de Vries1, Cor Lieftink1, Roderick L. Beijersbergen1, & René Bernards1*
1Division of Molecular Carcinogenesis and Cancer Genomics Center Netherlands, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam,
The Netherlands
Corresponding author: René Bernards
The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
E-mail: [email protected] Phone: +31 20 512 1952
Running title: PIM kinases: a potential therapeutic target in neuroblastoma
Keywords: PIM, neuroblastoma, NF1, screen, biomarker
Financial support: This study was supported by grants from the Dutch Cancer Society, the Center for Cancer Genomics, and Stand Up to Cancer (SU2C-AACR- DT0912).
The authors declare no competing financial interests
ABSTRACT
The majority of high-risk neuroblastoma patients are refractory to, or relapse on current treatment regimens, resulting in 5-year survival rates of less than 50%. This emphasizes the urgent need to identify novel therapeutic targets. Here, we report that high PIM kinase expression is correlated with poor overall survival. Treatment of neuroblastoma cell lines with the pan-PIM inhibitors AZD1208 or PIM-447 suppressed proliferation through inhibition of mTOR signaling. In a panel of neuroblastoma cell lines, we observed a marked binary response to PIM inhibition, suggesting that specific genetic lesions control responses to PIM inhibition. Using a genome-wide CRISPR-Cas9 genetic screen, we identified NF1 loss as the major resistance mechanism to PIM kinase inhibitors. Treatment with AZD1208 impaired the growth of NF1 wild type xenografts, while NF1 knock out cells were insensitive. Thus, our data indicate that PIM inhibition may be a novel targeted therapy in NF1 wild type neuroblastoma.
INTRODUCTION
Neuroblastoma is a pediatric malignancy originating from precursor cells of the sympathetic nervous system (1). It accounts for 8-10 percent of all childhood cancers and is the most common type of cancer diagnosed in infants (2). Tumor behavior is highly heterogeneous, varying from spontaneous regression to aggressive metastatic disease. Patients with high-risk tumors have a poor prognosis due to refractory or relapsed disease, with 5-year survival rates of less than 50 percent (3). Treatment options are mainly limited to surgery, radiation, chemotherapy, and stem cell transplantation (3). Unfortunately, compared to more common malignancies, relatively few targeted agents are being evaluated for the treatment of neuroblastoma. The only FDA-approved targeted therapy is a monoclonal antibody (dinutuximab) targeting the cell surface glycolipid GD2, which is administered in combination with granulocyte macrophage colony-stimulating factor (GM-CSF), interleukin-2 (IL-2), and 13-cis retinoic acid (isotretinoin) (4). It is therefore essential to identify novel targeted therapies for the treatment of neuroblastoma.
PIM serine/threonine kinases (PIM1, -2, and -3) are overexpressed in many hematological malignancies and several solid cancers (5). Due to a short half-life, the activity of these constitutively active kinases is mainly regulated at a transcriptional level by the JAK/STAT pathway (6-9). Many PIM kinase substrates are commonly regulated by AKT/mTOR signaling, including PRAS40 (10), TSC2 (11), 4EBP1 (12), the pro-apoptotic protein BAD (13-15), and the cell cycle regulating proteins p21CIP1
(16) and p27KIP1 (17). PIM kinases are highly homologous and share a unique hinge region that results in a distinct ATP binding site (9,18), which has led to the development of highly specific pan-PIM kinase inhibitors, such as AZD1208 (19) and PIM-447 (20). Furthermore, Pim1, Pim2, and Pim3 deficient mice are viable and only display mild phenotypic changes such as reduced body size, which might indicate a favorable toxicity profile for PIM kinase inhibitors in human patients (21).
Although PIM kinases are, thus far, mostly studied in hematological malignancies, an increasing number of reports demonstrate a role for these kinases in solid cancers. For instance, PIM1 was recently found to be overexpressed in triple- negative (TN) breast cancer, in which high mRNA expression correlated with poor clinical outcome (22,23). In addition, MYC-positive TN cell lines and patient-derived xenografts were found to be sensitive to PIM inhibitors. Here we explore PIM kinase inhibition as a potential strategy for the treatment of neuroblastoma.
MATERIALS AND METHODS
Patient cohort
Data from two independent neuroblastoma microarray datasets were derived from the online tool R2 (http://r2.amc.nl). The Versteeg dataset consisted of 88 samples and has previously been described. The Kocak dataset consisted of 643 samples, of which for 476 samples follow-up data was available and were therefore used for the analysis. Patient characteristics are described in Supplementary Table S1. Patient studies were conducted in compliance with the Helsinki declaration (http://www.wma.net/en/30publications/10policies/b3/).
Cell culture, transfection, and lentiviral transduction
HEK293, HT230, SK-N-SH, NB90-4, NB90-6, NB90-9, NB69, SK-N-AS, and SK-N-
BE cell lines were cultured in Dulbecco’s Modified Eagle Medium (DMEM). LAN5, CLB-MA, GI-ME-N, and KELLY cell lines were cultured in Roswell Park Memorial Institute (RPMI) 1640. IMR32 was cultured in Minimum Essential Medium (MEM). SH-SY5Y was cultured in DMEM/F12 medium. Medium was supplemented with 8% fetal calf serum (FCS), 1% glutamine, and 1% penicillin/streptomycin, and cells were grown at 37°C and 5% CO2. Cell lines were available within the Netherlands Cancer Institute, were STR profiled when reference STR data was available for the particular
cell line, and all cell lines were routinely tested by PCR for mycoplasma contamination and found negative.
PEI transfection of HEK293 cells was used to produce lentiviral supernatant. Target cells were seeded 1 day before infection. Lentivirus was added to the medium in the presence of 5 µg/ml polybrene. Cells were selected for successful lentiviral integration using 2 µg/ml puromycin. For individual knockout of genes, the following gRNAs were cloned into the lentiCRISPR version 2.1 (LC2.1) vector by Gibson cloning:
gNT 5’-ACGGAGGCTAAGCGTCGCAA -3’
gNF1 #1 5’-TCTTTAGTCGCATTTCTACC-3’
gNF1 #2 5’-ACACTGGAAAAATGTCTTGC-3’ gTSC1 5’-ATGAAAGAGTGCGTACACAC-3’ gDEPDC5 #1 5’-TGTTAATGTCGTAGACCCTA-3’
gDEPDC5 #2 5’- GGAACACTTGAGTCACAGTC-3’ gPTEN 5’-ACCGCCAAATTTAATTGCAG-3’ gSTK11 5’- GAAGGGGAGCTACGCCATCC-3’
CRISPR-Cas9 resistance screen
The genome-wide GECKO version 2 library A – consisting of 65,383 gRNAs in lentiviral vectors – was used to infect KELLY cells with 200-fold coverage. After 48 hours, viral supernatant was replaced by medium containing puromycin to select for infected cells. 48 hours after puromycin selection, cells were harvested, a T0 sample was taken, and the rest of the cells were reseeded and cultured in the absence or presence of drug in 2 biological replicates for 30 days, followed by genomic DNA isolation using the DNAeasy Blood & Tissue Kit (Qiagen). gRNA sequences were amplified using Phusion High Fidelity DNA polymerase (Thermo Scientific) by performing a 2 step PCR amplification: (1) 98°C, 2 min; (2) 98°C, 30s; (3) 60°C, 30 s;
(4) 72°C, 1 min; (5) to step 2, 20 cycles (PCR1) or 15 cycles (PCR2); (6) 72°C, 5
min; (7) 4°C. 2 μl of the pooled PCR1 product was used for the subsequent PCR2 reaction. The abundance of each gRNA in the treated versus untreated pools was determined by Illumina next generation sequencing. Statistical analysis was performed using DESeq version 1.8.3. We considered gRNAs with a Log2 fold change ≥ 5 and an adjusted p-value ≤ 0.1 as hits (adjusted for multiple testing using the Benjamini Hochberg procedure). Since several of the hits were gRNA’s targeting negative regulators of AKT/mTOR signaling, we used these gRNAs for subsequent validation experiments. The data of the CRISPR screen can be found in Supplementary Table S2.
Protein lysate preparation and western blot analysis
Cells were lysed using RIPA buffer containing 150 mM NaCl, 50 mM Tris pH 8.0, 1% NP-40, 0.5% sodium deoxycholate, and 0.1% SDS supplemented with protease inhibitors (Complete, Roche) and phosphatase inhibitor cocktails II and III (Sigma). Samples were equalized by measuring relative protein concentrations using Pierce™ BCA Protein Assay Kit (ThermoFisher). Bolt® LDS Sample Buffer (ThermoFisher) and 10X Bolt® Sample Reducing Agent (ThermoFisher) were added, lysates were boiled for 10 minutes, and equal amounts of sample were subjected to SDS gel electrophoresis followed by western blotting. Primary antibodies against HSP90 (sc- 7947), GAPDH (sc-20357), p-ERK1/2 (sc-7383), ERK1 (sc-93), ERK2 (sc-154),
STAT5 (sc-835), and MYC (sc-40) were purchased from Santa Cruz. Antibody against NF1 (A300-140A) was purchased from Bethyl Laboratories. Antibodies against clPARP (#5625), PIM1 (#3247), PIM2 (#4730), PIM3 (#4165), pSTAT3
(#9145), STAT3 (#4904), pSTAT5 (#4322), N-MYC (#9405), p-AKT (#4060), AKT
(#2920), p-S6 (#2215), S6 (#2217), p-4EBP1 (#9456), 4EBP1 (#9452), STK11
(#3050), PTEN (#9559), and TSC1 (#4906) were from Cell Signaling. Secondary antibodies were obtained from Bio-Rad Laboratories. AZD1208 and MK2206 were purchased from Selleckchem. Cobimetinib was purchased from ApexBio. PIM-447
was purchased from MedChem Express.
CellTiter-Blue viability assay.
Respectively 625 (GI-ME-N), 800 (HT230), 2,000 (IMR32), 3,000 (NB69), 5,000 (NB90-6, SK-N-SH, SH-SY5Y, SK-N-BE, SK-N-AS, KELLY, NB90-4), 10,000 (NB90-
9), 15,000 (LAN5, CLB-MA) cells per well were seeded in a 96-well plate. After 24 hours, drugs were added to the medium in 2-fold serial dilutions using a HP Direct Digital Dispenser. After 5 days of culture CellTiter-Blue (Promega) was added. The conversion of resazurin into resorufin was measured by using an EnVision Multilabel Reader. Treatment with 10 μM phenyl arsenic oxide – resulting in complete cell death – was used as a baseline for viability. Non-linear regression analysis in GraphPad Prism v6.0 was used for curve fitting.
RNA interference and quantitative RT-PCR.
KELLY cells (10,000 cells/well) and SH-SY5Y (4,000 cells/well) were seeded in triplicates in in a 96-well plate. After 24 hours, cells were transfected with Dharmacon siGENOME SMARTPool siRNAs against PIM1 (M-003923-00), PIM2 (M-005359-00),
PIM3 (M-032287-02), or Non-Targeting siRNA Pool #1 (D-001206-13) using DharmaFECT1 (#T-2001) (KELLY) or Lipofectamine RNAiMax (#13778075). 10 μM phenyl arsenic oxide – resulting in complete cell death – was used as a baseline for viability. After 5 days of culture, viability was measured using CellTiter-Blue (Promega) as described above.
To determine the level of knock down, 5.105 KELLY cells/well and 1.106 SH- SY5Y cells/well were seeded in a 6-well plate. After 24 hours, cells were transfected as previously indicated. After 48 hours, RNA was isolated using a ISOLATE II RNA Mini Kit (Bioline, # BIO-52073). Subsequent cDNA synthesis was performed using Maxima Universal First Strand cDNA Synthesis Kit (Thermo scientific, # K1661).
The 7500 Fast Real-Time PCR System from Applied Biosystems was used to
measure mRNA levels. mRNA expression levels were normalized to expression of RPL-13. The following primer sequences were used in the SYBR Green master mix: RPL-13_forward 5’-GAGACAGTTCTGCTGAAGAACTGAA-3’;
RPL-13_reverse 5’-TCCGGACGGGCATGAC-3’; PIM1_forward 5’-CGACATCAAGGACGAAAACATC-3’; PIM1_reverse 5’- ACTCTGGAGGGCTATACACTC-3’; PIM2_forward 5’-TCGAGGCCGAGTATCGACT-3’; PIM2_reverse 5’-ATTCCGGGGAATCACTTTG-3’; PIM3_forward 5’-CTGCTCAAGGACACGGTCTACAC-3’; PIM3_reverse 5’-CCCCACACACCATATCGTAGAGA-3’;
Colony formation assay
Respectively 20,000 (NB90-4, NB90-6, NB90-9, GI-ME-N, HT230), 40,000 (NB69, SK-N-BE, SK-N-AS, SK-N-SH, KELLY), 100,000 (IMR32, CLB-MA, LAN5, SH-SY5Y)
cells/well were seeded in 6-well plates and cultured both in the absence and presence of drugs as indicated. When untreated cells reached confluency, cells were washed with PBS, fixed with 4% formaldehyde, and stained with 0.1% crystal violet. For SH-SY5Y and SK-N-SH, non-targeting cells were stained at a later time point (when untreated well reached confluence) than NF1 KO cells, since the latter grew significantly faster.
Mouse xenografts
8 weeks old male/female NMRI nude mice were housed in a specific pathogen-free facility in individually ventilated cages at the Animal Core Facilities of The Netherlands Cancer Institute. All mouse experiments were performed in compliance with protocols approved by the local Animal Ethics Committee, which conform to institutional and national regulatory standards on experimental animal usage. KELLY cells in PBS/matrigel mixture were subcutaneously implanted into the flanks of mice
(1.106 cells were used in the 90 mg/kg experiment and 5.106 cells were used in the 30 mg/kg experiment). When tumor size reached ~80 mm3 (90 mg/kg experiment) or
~200 mm3 (30mg/kg experiment), mice were randomly assigned and treated once daily with 30 or 90 mg/kg AZD1208 by oral gavage. Control group received vehicle (0.5% hydroxypropyl methylcellulose and 0.1% Tween 80). All groups were composed of 8 mice, although not all mice formed tumors. In the 90 mg/kg AZD1208 experiment, the groups consisted therefore of respectively 7 (gNT vehicle), 6 (gNT AZD1208), 7 (gNF1 #1 vehicle), 7 (gNF1 #1 AZD1208), 7 (gNF1 #2 vehicle), and 7 (gNF1 #2 AZD1208) mice. Grubbs’ analysis was used to exclude outliers. Tumor volume was measured three times per week with calipers and calculated as tumor volume = (length × width2) × 0.5.
Statistical analysis
Kaplan-Meier survival curves were compared using a log-rank test in GraphPad Prism v6.0. Hazard ratios were calculated using both a univariate and multivariate Cox regression analysis in IBM SPSS Statistics version 21. Statistical analysis of PIM expression in MYCN amplified vs MYCN non-amplified tumors was performed using two-tailed equal variance Student’s t-tests in GraphPad Prism v6.0. PIM expression levels of each tumor stage were compared to stage 4 tumors using a one-way ANOVA test with Dunnett correction for multiple comparisons in GraphPad Prism v6.0. Differences in viability upon PIM knock down were analyzed using a one- way ANOVA test with Dunnett correction for multiple comparisons in GraphPad Prism v6.0. The mean ± standard error (SEM) is shown in figures. A p value of less than 0.05 was considered statistically significant and is denoted by *. p ≤ 0.01 is denoted by **, p ≤ 0.001 by ***, and p ≤ 0.0001 by ****.
RESULTS
High PIM expression is associated with poor clinical outcome
To determine whether PIM expression is associated with survival in neuroblastoma patients, we analyzed microarray data from a large cohort (n=476) of neuroblastoma patients (24). We classified patients using median PIM expression as a cut-off value (Fig. 1A-C). Interestingly, high expression of either PIM1, -2, or -3 was significantly correlated with poor overall survival in this cohort. Since PIM kinases are highly redundant, we hypothesized that patients with low expression of all PIM genes would have a better overall survival than patients with high expression of at least one of the PIMs. This classifier further improved the separation between patients with good and poor overall survival (Fig. 1D). To determine whether high PIM expression is a prognostic biomarker, we calculated hazard ratio’s using a Cox regression analysis (Table 1). Importantly, high expression of at least one of the three PIM kinases versus low expression of all PIMs was significantly associated with poor overall survival in a multivariate model and is therefore a potential prognostic biomarker.
We also determined the level of PIM expression across all tumor stages (Fig. 1E-G). PIM1 and -2 expression was significantly higher in stage 4 tumors compared to the other stages. Stage 4 disease indicates the occurrence of metastasis to distant lymph nodes and organs. Stage 4S represents ‘special neuroblastoma’: these metastatic tumors often spontaneously regress and therefore have favorable prognosis. We furthermore found statistically significant differential expression of PIM2 and -3 between MYCN amplified and non-amplified tumors (Fig. 1H). The same trends between PIM expression and outcome were observed in a second cohort of 88 patients (Supplementary Fig. S1) (25), but not all differences reached statistical significance, most likely due to the smaller cohort size.
PIM kinases are a potential therapeutic target in neuroblastoma
To investigate PIM kinases as a potential therapeutic target in neuroblastoma, we first analyzed PIM protein levels in a panel of 14 neuroblastoma cell lines (Fig. 2A). The majority of cell lines expressed high levels of PIM1 and -3 and to a lesser extent PIM2. We observed no differential PIM expression between MYCN amplified and non-amplified cell lines. Furthermore, several cell lines displayed high phospho- STAT3 levels — one of the upstream regulators of PIM.
To determine the dependency of neuroblastoma cells on PIM kinases, we performed siRNA-mediated depletion of PIM1, -2, or -3 in KELLY and SH-SY5Y cell lines (Fig. 2B-C; Supplementary Fig. S2A-B). Even though PIM kinases are described to be redundant, suppression of PIM1 was sufficient to reduce the viability of both cell lines. This is in line with findings in triple-negative breast cancer, in which PIM1 knockdown was sufficient to reduce cell viability (22,23). We next investigated whether high PIM expression can be exploited therapeutically by treating all 14 cell lines with the selective pan-PIM inhibitor AZD1208 in both a short-term CellTiter-Blue cell viability assay (Supplementary Fig. S2C-D) and a long-term colony formation assay (Fig. 2D). Interestingly, approximately one third of the cell lines responded to treatment, whereas the other cell lines were resistant. We did not observe a clear correlation between PIM protein levels and PIM inhibitor sensitivity, possibly due to the relative small number of cell lines (Fig. 2A; Fig 2D). We validated these results by repeating the colony formation assays with another pan-PIM inhibitor (PIM-447) in 3 AZD1208-sensitive and 3 AZD1208-resistant cell lines (Fig. S2E-F).
To gain insights into the biochemical differences underlying these responses,
we treated 3 sensitive and 3 resistant cell lines with 2 μM AZD1208 for 0, 4, 24, and 48 hours and analyzed the activity of downstream components of PIM signaling (Fig. 2E). Only sensitive cell lines demonstrated reduced phosphorylation of p-70, S6, and
4EBP1 upon AZD1208 treatment, while MYC protein levels remained unaffected upon treatment. Again, we observed similar responses upon treatment with PIM-447 (Supplementary Fig. S2G).
CRISPR-Cas9 screen identifies genes whose loss confers PIM inhibitor resistance
The binary response of the neuroblastoma cell lines to the PIM inhibitors suggests the presence of an underlying mutation that confers resistance, which might be used as a biomarker for response. To identify genes whose loss renders cells insensitive to AZD1208 treatment, we performed a loss-of-function genome-wide CRISPR-Cas9 genetic screen (Fig. 3A). We infected the PIM inhibitor sensitive KELLY cell line with lentivirus containing the GECKO library A (containing 3 gRNAs for each gene), cultured cells in the presence or absence of 2 μM AZD1208 for 30 days, followed by genomic DNA isolation, PCR amplification of the gRNAs, and next generation sequencing. To assess the efficacy of our screen, we analyzed the abundance of gRNAs targeting non-essential and essential genes in the untreated cells versus time point zero (T0) (Supplementary Fig. S3). Whereas the relative abundance of gRNAs targeting non-essential genes remained stable over time, gRNAs targeting essential genes were depleted in the untreated cells compared to T0, thus validating the screen. Next, we analyzed which gRNAs were enriched in the treated versus untreated samples (Supplementary Table S2). Interestingly, within this list of 28 hits, we found a gRNA targeting the RAS-GAP NF1 and gRNAs targeting negative regulators of the AKT/mTOR pathway PTEN, TSC1, DEPDC5, and STK11 to be significantly enriched (Fig. 3B; Supplementary Table S2). We validated these hits by creating polyclonal knockout cell lines, in which we subsequently determined the response to AZD1208 using colony formation assays (Fig. 3C). Whereas KELLY cells infected with a non-targeting gRNA remained sensitive to AZD1208, knockout of either of the hit genes conferred resistance to PIM inhibitor treatment. Knockout was
assessed by western blot analysis if respective antibodies were available (Fig. 3D). Since all hit genes are known to regulate mTOR signaling, we analyzed the activity of S6 and 4EBP1 upon AZD1208 treatment in the context of the particular knockouts (Fig. 3D). Similar to our observations in neuroblastoma cell lines that are intrinsically resistant to PIM inhibitor treatment (Fig. 2D), knockout of the genes identified in the genetic screen resulted in persistent mTOR signaling upon PIM inhibition.
NF1 protein expression is a potential predictive biomarker for PIM inhibitor treatment
NF1 protein is estimated to be lost in approximately 1 out of 3 neuroblastoma tumors (26), whereas mutations in PTEN, TSC1, DEPDC5, and STK11 rarely occur or have not been reported in neuroblastoma. Therefore, we analyzed the cell line panel for NF1 protein levels to investigate whether NF1 loss could be a potential biomarker to predict PIM inhibitor resistance (Fig. 3E). 5 out of 14 cell lines demonstrated complete loss of NF1 and were resistant to AZD1208. Furthermore, the resistant cell line SK-N-AS demonstrated partial loss of NF1, which has previously been reported, and in addition carries an NRASQ61 mutation (26). The cell lines IMR32, NB90-6, and CLB-MA were resistant to AZD1208 despite being NF1 wild type, which suggests that other genes can also modulate the response to PIM inhibitors. Consistent with a causal role for NF1 in PIM inhibitor resistance, all AZD1208 sensitive cell lines in the panel expressed NF1 protein.
To further assess the effect of NF1 loss on AZD1208 sensitivity, we created NF1 knockout cells using 2 different gRNAs in KELLY, SH-SY5Y, and SK-N-SH cell lines. These NF1 knockout cells were subsequently treated with AZD1208 or PIM-
447 in a colony formation assay (Fig. 4A-D; Supplementary Fig. S4A-B). In concordance with the initial results, NF1 loss induced resistance to both AZD1208 and PIM-447. To gain insights into the biochemical response underlying the resistance, we treated control and NF1 knockout cell lines with AZD1208 for 0, 4, 24,
and 48 hours (Fig. 4E; Supplementary Fig. S4C-D). In line with NF1 being a negative regulator of RAS, we observed strong phosphorylation of downstream ERK and AKT in NF1 knockout cells. Whereas PIM inhibition suppressed phosphorylation of S6 and 4EBP1 in cell lines infected with a non-targeting gRNA, their activity was maintained upon NF1 loss.
Since NF1 knock out cells display increased activation of both MAPK and AKT, we wondered whether the addition of a MEK or AKT inhibitor could alleviate resistance to PIM inhibitors. To assess the potential of this combination strategy, we co-treated control and NF1 knock out KELLY, SH-SY5Y, and SK-N-SH cells with AZD1208, the MEK inhibitor cobimetinib, or the AKT inhibitor MK2206 (27)(Supplementary Fig. S5A-C). Interestingly, MEK inhibitor treatment sensitized NF1 knockout cell lines to AZD1208 in KELLY and SH-SY5Y cells. SK-N-SH cells displayed increased sensitivity to cobimetinib mono-treatment upon NF1 loss, and therefore demonstrated no additional benefit of PIM inhibitor treatment. While AKT inhibition partially alleviated resistance in KELLY cells, it did not restore PIM inhibitor sensitivity in SH-SY5Y or SK-N-SH cell lines, suggesting that MAPK activation is the main driver of resistance upon NF1 loss. We subsequently investigated whether dual PIM/MEK inhibitor treatment could also prevent resistance to PIM inhibition in the ‘naturally’ NF1 deficient cell lines from our cell line panel (Figure S5D-F). However, in line with a previous report (28), these NF1 deficient cells were highly sensitive to MEK inhibitor mono-treatment, due to a dependency on MAPK signaling, which was not enhanced by AZD1208.
To validate the efficacy of PIM kinase inhibition in neuroblastoma in vivo, we subcutaneously injected control and NF1 knockout KELLY cells into nude mice, and treated mice once daily with vehicle, 30 mg/kg AZD1208, or 90 mg/kg AZD1208 (Fig. 4F; Supplementary Fig. S6A-D). High dose AZD1208 did not affect mouse body weight (Supplementary Fig. S6E). Whereas NF1 knockout tumors were found to be
insensitive to AZD1208, the survival of mice harboring NF1 wild type tumors was significantly prolonged upon PIM inhibitor treatment.
DISCUSSION
Even though neuroblastoma is the most common malignancy in infants, the number of treatment options is limited compared to more frequently occurring types of cancer in adults. Due to the low absolute number of patients, there is a lack of financial incentive for pharmaceutical companies to develop compounds that are solely used in neuroblastoma. To overcome this problem, novel therapeutic targets in neuroblastoma should ideally be targetable by drugs that are currently in use or development for more frequent adult malignancies.
There are several recurrent mutations in neuroblastoma that might represent vulnerabilities that can be targeted pharmacologically. For instance, ALK mutations occur in 8-12% of all neuroblastoma (29,30). This observation led to a phase I clinical trial assessing the efficacy of the ALK inhibitor crizotinib in neuroblastoma patients. However, out of the 11 patients with ALK-mutant tumors, only one patient demonstrated a complete response and two patients displayed stable disease upon crizotinib treatment (31). Another frequently occurring aberration is NF1 deficiency. We and others have previously reported the presence of NF1 mutations and the loss of NF1 protein in neuroblastoma (26,28). This is potentially clinically actionable due to the resulting activation of the RAS-MAPK pathway. Indeed, in childhood neurofibromatosis type 1–related plexiform neurofibromas, the MEK inhibitor selumetinib proved to be very effective, with partial responses in 17 out of 24 patients (32). Consistent with this, NF1 deficient neuroblastoma cells are more sensitive to MEK inhibition than their wild type counterparts, providing a rationale to evaluate the clinical efficacy of MEK inhibitors in NF1 deficient neuroblastoma (Eleveld et al., 2015; Woodfield et al., 2016).
However, ALK and NF1 mutations are present in only a small fraction of neuroblastomas. In the present study, we find that PIM kinase inhibitors may elicit clinical benefit in NF1 wild type tumors. This is of particular relevance, given that our data also indicate that high expression of PIM kinases is associated with poor clinical outcome. Furthermore, high PIM expression remained significantly associated with poor clinical outcome when tumors with low NF1 expression were excluded (Supplementary Fig. S6F). Thus, there is a significant unmet need to find better treatments for such patients.
The long-term benefit of targeted therapies is generally hampered by the development of resistance. In line with this observation, AZD1208 initially suppressed growth of KELLY cells, but did not prevent long-term tumor outgrowth in vivo (Fig. 4F). Additional research is necessary to identify rationally designed drug combinations with PIM inhibitors to prevent the outgrowth of resistant neuroblastoma cells. Current treatment regimens for (especially high-risk) neuroblastoma mostly include a combination of chemotherapeutic drugs. Interestingly, it has previously been demonstrated that PIM kinase inhibitors can enhance the efficacy of chemotherapeutic agents in triple-negative breast cancer xenografts (23). Similar observations were made in cell lines derived from different tumor tissues, in which PIM1 expression antagonized chemotherapy-induced apoptosis (33). It is therefore interesting to speculate that the addition of a PIM inhibitor might improve the efficacy of current treatment regimens.
In conclusion, we have identified PIM kinases as a novel therapeutic target in neuroblastoma. Furthermore, NF1 loss can be used as a biomarker to identify patients that do not benefit from PIM inhibitor treatment.
ACKNOWLEDGMENTS
We thank all members of the Bernards lab for helpful support and discussions. We thank the intervention unit of The Netherlands Cancer Institute for assistance with the
xenograft experiments. We thank Dr. R. Versteeg for making the R2 tool publicly available. This study was supported by grants from the Dutch Cancer Society, the Center for Cancer Genomics, and Stand Up to Cancer (SU2C-AACR-DT0912). The authors declare no competing financial interests.
REFERENCES
1. Marshall GM, Carter DR, Cheung BB, Liu T, Mateos MK, Meyerowitz JG, et al. The prenatal origins of cancer. Nat Rev Cancer 2014;14(4):277-89.
2. Cheung NK, Dyer MA. Neuroblastoma: developmental biology, cancer genomics and immunotherapy. Nat Rev Cancer 2013;13(6):397-411.
3. Maris JM. Recent advances in neuroblastoma. N Engl J Med
2010;362(23):2202-11.
4. Yu AL, Gilman AL, Ozkaynak MF, London WB, Kreissman SG, Chen HX, et al. Anti-GD2 antibody with GM-CSF, interleukin-2, and isotretinoin for neuroblastoma. N Engl J Med 2010;363(14):1324-34.
5. Nawijn MC, Alendar A, Berns A. For better or for worse: the role of Pim oncogenes in tumorigenesis. Nat Rev Cancer 2011;11(1):23-34.
6. Miura O, Miura Y, Nakamura N, Quelle FW, Witthuhn BA, Ihle JN, et al.
Induction of tyrosine phosphorylation of Vav and expression of Pim-1 correlates with Jak2-mediated growth signaling from the erythropoietin receptor. Blood 1994;84(12):4135-41.
7. Stout BA, Bates ME, Liu LY, Farrington NN, Bertics PJ. IL-5 and granulocyte- macrophage colony-stimulating factor activate STAT3 and STAT5 and promote Pim-1 and cyclin D3 protein expression in human eosinophils. J Immunol 2004;173(10):6409-17.
8. Matikainen S, Sareneva T, Ronni T, Lehtonen A, Koskinen PJ, Julkunen I. Interferon-alpha activates multiple STAT proteins and upregulates
proliferation-associated IL-2Ralpha, c-myc, and pim-1 genes in human T cells. Blood 1999;93(6):1980-91.
9. Qian KC, Wang L, Hickey ER, Studts J, Barringer K, Peng C, et al. Structural basis of constitutive activity and a unique nucleotide binding mode of human Pim-1 kinase. J Biol Chem 2005;280(7):6130-7.
10. Zhang F, Beharry ZM, Harris TE, Lilly MB, Smith CD, Mahajan S, et al. PIM1 protein kinase regulates PRAS40 phosphorylation and mTOR activity in FDCP1 cells. Cancer Biol Ther 2009;8(9):846-53.
11. Lu J, Zavorotinskaya T, Dai Y, Niu XH, Castillo J, Sim J, et al. Pim2 is required for maintaining multiple myeloma cell growth through modulating TSC2 phosphorylation. Blood 2013;122(9):1610-20.
12. Tamburini J, Green AS, Bardet V, Chapuis N, Park S, Willems L, et al.
Protein synthesis is resistant to rapamycin and constitutes a promising therapeutic target in acute myeloid leukemia. Blood 2009;114(8):1618-27.
13. Yan B, Zemskova M, Holder S, Chin V, Kraft A, Koskinen PJ, et al. The PIM-2 kinase phosphorylates BAD on serine 112 and reverses BAD-induced cell death. J Biol Chem 2003;278(46):45358-67.
14. Aho TL, Sandholm J, Peltola KJ, Mankonen HP, Lilly M, Koskinen PJ. Pim-1 kinase promotes inactivation of the pro-apoptotic Bad protein by phosphorylating it on the Ser112 gatekeeper site. FEBS Lett 2004;571(1- 3):43-9.
15. Macdonald A, Campbell DG, Toth R, McLauchlan H, Hastie CJ, Arthur JS. Pim kinases phosphorylate multiple sites on Bad and promote 14-3-3 binding and dissociation from Bcl-XL. BMC Cell Biol 2006;7:1.
16. Zhang Y, Wang Z, Magnuson NS. Pim-1 kinase-dependent phosphorylation of p21Cip1/WAF1 regulates its stability and cellular localization in H1299 cells. Mol Cancer Res 2007;5(9):909-22.
17. Morishita D, Katayama R, Sekimizu K, Tsuruo T, Fujita N. Pim kinases promote cell cycle progression by phosphorylating and down-regulating p27Kip1 at the transcriptional and posttranscriptional levels. Cancer Res 2008;68(13):5076-85.
18. Bullock AN, Debreczeni J, Amos AL, Knapp S, Turk BE. Structure and substrate specificity of the Pim-1 kinase. J Biol Chem 2005;280(50):41675- 82.
19. Keeton EK, McEachern K, Dillman KS, Palakurthi S, Cao Y, Grondine MR, et al. AZD1208, a potent and selective pan-Pim kinase inhibitor, demonstrates efficacy in preclinical models of acute myeloid leukemia. Blood 2014;123(6):905-13.
20. Burger MT, Nishiguchi G, Han W, Lan J, Simmons R, Atallah G, et al.
Identification of N-(4-((1R,3S,5S)-3-Amino-5-methylcyclohexyl)pyridin-3-yl)-6- (2,6-difluorophenyl)- 5-fluoropicolinamide (PIM447), a Potent and Selective Proviral Insertion Site of Moloney Murine Leukemia (PIM) 1, 2, and 3 Kinase Inhibitor in Clinical Trials for Hematological Malignancies. J Med Chem 2015;58(21):8373-86.
21. Mikkers H, Nawijn M, Allen J, Brouwers C, Verhoeven E, Jonkers J, et al.
Mice deficient for all PIM kinases display reduced body size and impaired responses to hematopoietic growth factors. Mol Cell Biol 2004;24(13):6104- 15.
22. Horiuchi D, Camarda R, Zhou AY, Yau C, Momcilovic O, Balakrishnan S, et al. PIM1 kinase inhibition as a targeted therapy against triple-negative breast tumors with elevated MYC expression. Nat Med 2016;22(11):1321-9.
23. Braso-Maristany F, Filosto S, Catchpole S, Marlow R, Quist J, Francesch- Domenech E, et al. PIM1 kinase regulates cell death, tumor growth and chemotherapy response in triple-negative breast cancer. Nat Med 2016;22(11):1303-13.
24. Kocak H, Ackermann S, Hero B, Kahlert Y, Oberthuer A, Juraeva D, et al.
Hox-C9 activates the intrinsic pathway of apoptosis and is associated with spontaneous regression in neuroblastoma. Cell Death Dis 2013;4:e586.
25. Molenaar JJ, Koster J, Zwijnenburg DA, van Sluis P, Valentijn LJ, van der Ploeg I, et al. Sequencing of neuroblastoma identifies chromothripsis and defects in neuritogenesis genes. Nature 2012;483(7391):589-93.
26. Holzel M, Huang S, Koster J, Ora I, Lakeman A, Caron H, et al. NF1 is a tumor suppressor in neuroblastoma that determines retinoic acid response and disease outcome. Cell 2010;142(2):218-29.
27. Hirai H, Sootome H, Nakatsuru Y, Miyama K, Taguchi S, Tsujioka K, et al.
MK-2206, an allosteric Akt inhibitor, enhances antitumor efficacy by standard chemotherapeutic agents or molecular targeted drugs in vitro and in vivo. Mol Cancer Ther 2010;9(7):1956-67.
28. Eleveld TF, Oldridge DA, Bernard V, Koster J, Daage LC, Diskin SJ, et al.
Relapsed neuroblastomas show frequent RAS-MAPK pathway mutations. Nat Genet 2015;47(8):864-71.
29. Mosse YP, Laudenslager M, Longo L, Cole KA, Wood A, Attiyeh EF, et al.
Identification of ALK as a major familial neuroblastoma predisposition gene. Nature 2008;455(7215):930-5.
30. Bresler SC, Weiser DA, Huwe PJ, Park JH, Krytska K, Ryles H, et al. ALK mutations confer differential oncogenic activation and sensitivity to ALK inhibition therapy in neuroblastoma. Cancer Cell 2014;26(5):682-94.
31. Mosse YP, Lim MS, Voss SD, Wilner K, Ruffner K, Laliberte J, et al. Safety and activity of crizotinib for paediatric patients with refractory solid tumours or anaplastic large-cell lymphoma: a Children’s Oncology Group phase 1 consortium study. Lancet Oncol 2013;14(6):472-80.
32. Dombi E, Baldwin A, Marcus LJ, Fisher MJ, Weiss B, Kim A, et al. Activity of Selumetinib in Neurofibromatosis Type 1-Related Plexiform Neurofibromas. N Engl J Med 2016;375(26):2550-60.
33. Chen J, Kobayashi M, Darmanin S, Qiao Y, Gully C, Zhao R, et al. Pim-1 plays a pivotal role in hypoxia-induced chemoresistance. Oncogene 2009;28(28):2581-92.
Figure 1. PIM expression is a prognostic biomarker in neuroblastoma
(A-D) High PIM mRNA expression correlates with poor overall survival in neuroblastoma. Kaplan-Meier survival curves of the Kocak cohort (476 patients) demonstrate overall patient survival, using median PIM expression as a cut-off value for high versus low expression. High PIM1/2/3 indicates patients with high expression of either PIM1, -2, or -3. P-values were calculated using a log-rank test.
(E-G) PIM1 and -2 expression is highest in stage 4 neuroblastoma patients (Kocak cohort). P-values were calculated using a one-way ANOVA and Dunnett’s test. p ≤ 0.05 (*), p ≤ 0.01 (**), p ≤ 0.001 (***), and p ≤ 0.0001 (****)
(H) PIM expression in MYCN amplified and non-amplified tumors (Kocak cohort). P- values were calculated using an unpaired T-test. p ≤ 0.01 (**)
Figure 2. PIM kinases are expressed in neuroblastoma and are a potential therapeutic target
(A) Neuroblastoma cell lines express PIM kinases. Western blot of lysates generated from 14 neuroblastoma cell lines.
(B-C) Knockdown of PIM reduces cell line viability. KELLY and SH-SY5Y cell lines were plated in 96-well plates, transfected with a scrambled siRNA (siCTRL) or siRNAs targeting PIM1, -2, or -3, cultured for 5 days, and viability was measured using CellTiter-Blue (n=3).
(D) Neuroblastoma cell lines demonstrate differential sensitivity to AZD1208 in a colony formation assay. Cells were plated in 6-well plates and treated with increasing concentrations of AZD1208. Drug-containing medium was refreshed every 3 days. Cells were fixed, stained, and scanned when untreated wells reached confluency (n=3).
(E) AZD1208-resistant cell lines demonstrate sustained mTOR signaling upon treatment. Cells were treated with 2 μM AZD1208 for 0, 24, and 48 hours followed by western blot analysis (n=3).
Figure 3. A CRISPR-Cas9 genetic screen identifies mediators of PIM inhibitor resistance
(A) Schematic outline of the resistance screen. KELLY cells were infected with the genome wide GECKO library A and cultured in the presence or absence of 2 μM AZD1208. After 30 days, genomic DNA was isolated, gRNA sequences were PCR amplified, and the abundance of each gRNA in the treated versus untreated condition was determined by next generation sequencing.
(B) The screen identifies loss of NF1 and genes regulating AKT/mTOR signaling as potential resistance mechanisms. The x-axis depicts the average number of sequencing reads in the untreated/treated samples. The y-axis depicts the log2 fold change in abundance of gRNAs in the treated versus untreated population. A log2 fold change of 5 was used as cut-off to select hits.
(C) CRISP/Cas9-mediated knockout of NF1, PTEN, TSC1, STK11, or DEPDC5 induces resistance to AZD1208. KELLY cells were plated in 6-well plates and treated with AZD1208. Drug-containing medium was refreshed every 3 days. Cells were fixed, stained, and scanned when untreated wells reached confluency (n=3).
(D) CRISP/Cas9-mediated knockout of NF1, PTEN, TSC1, STK11, or DEPDC5 results in sustained mTOR signaling upon PIM inhibition. KELLY cells were treated with 2 μM AZD1208 for 48 hours, followed by western blot analysis (n=3).
(E) NF1 loss correlates with AZD1208 resistance in a panel of neuroblastoma cell lines. Western blot of lysates generated from 14 neuroblastoma cell lines.
Figure 4. NF1 loss induces PIM inhibitor resistance
(A-D) NF1 loss results in resistance to AZD1208 and PIM-447 in a colony formation assay. KELLY and SH-SY5Y cells were plated in 6-well plates and treated with increasing concentrations of AZD1208 or PIM-447. Drug-containing medium was refreshed every 3 days. Cells were fixed, stained, and scanned when untreated wells of each particular cell line reached confluency (n=3).
(E) NF1 knockout results in enhanced MAPK and AKT signaling and sustained mTOR signaling upon PIM inhibition. KELLY cell lines were treated with 2 μM AZD1208 for 0, 24, and 48 hours followed by western blot analysis (n=3).
(F) PIM inhibition suppresses tumor growth of NF1 wild type KELLY cells in a xenograft model. KELLY cells (1.106 cells) were subcutaneously implanted in NMRI mice. Once tumors were established (80mm3), animals were treated with vehicle or AZD1208 (90 mg/kg).
Author Manuscript Published OnlineFirst on February 13, 2018; DOI: 10.1158/1535-7163.MCT-17-0868 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited.
PIM kinases are a potential prognostic PIM447 biomarker and therapeutic target in neuroblastoma
Diede Brunen, Romy C de Vries, Cor Lieftink, et al.
Mol Cancer Ther Published OnlineFirst February 13, 2018.