Purpose: Gastrointestinal stromal tumors (GIST) generally harbor activating mutations in the receptor tyrosine kinase KIT or in the related platelet-derived growth factor receptor alpha (PDGFRA). GIST treated with imatinib mesylate or second-line therapies that target mutant forms of these receptors generally escape disease control and progress over time. Inhibiting additional molecular targets may provide more substantial disease control. Recent studies have implicated the PI3K/AKT pathway in the survival of imatinib mesylate–resistant GIST cell lines and tumors.

Experimental Design: Here, we performed in vitro and in vivo studies evaluating the novel combination of imatinib mesylate with the AKT inhibitor MK-2206 in GIST. Whole-transcriptome sequencing (WTS) of xenografts was performed to explore the molecular aspects of tumor response to this novel combination and to potentially identify additional therapeutic targets in GIST.

Results: This drug combination demonstrated significant synergistic effects in a panel of imatinib mesylate–sensitive and -resistant GIST cell lines. Furthermore, combination therapy provided significantly greater efficacy, as measured by tumor response and animal survival, in imatinib mesylate–sensitive GIST xenografts as compared with treatment with imatinib mesylate or MK-2206 alone. WTS implicated two neural genes, brain expressed X-linked 1 and neuronal pentraxin I, whose expression was significantly upregulated in combination-treated tumors compared with tumors treated with the two monotherapies.

Conclusions: These studies provide strong preclinical justification for combining imatinib mesylate with an AKT inhibitor as a front-line therapy in GIST. In addition, the WTS implicated the BCL-2/BAX/BAD apoptotic pathway as a potential mechanism for this enhanced combination effect. Clin Cancer Res; 23(1); 171–80. ©2016 AACR.

Translational Relevance

Resistance to tyrosine kinase inhibitors represents a major limitation in treatment of GIST. Current standard of care for advanced inoperable GIST involves sequential application of kinase inhibitors that target the activated forms of KIT or PDGFRA receptors found in GIST. Although a number of trials are underway using drug combinations with imatinib mesylate, remarkably only one early-phase trial has a component that will use a combination (MEK162 plus imatinib mesylate) in untreated GIST. Therefore, there is an unmet need and clinical opportunity to explore, in GIST, combinations that may be able to prevent development of resistance mechanisms through targeting signaling pathways at multiple points. Our studies demonstrate that the novel combination of imatinib mesylate with the AKT inhibitor, MK-2206 provided significantly improved efficacy compared with either monotherapy, as measured by tumor response and animal survival in GIST xenografts. These results provide justification for development of studies evaluating this combination in GIST patients.

Gastrointestinal stromal tumor (GIST) is the most common mesenchymal tumor of the gastrointestinal tract, afflicting up to 6,000 new patients annually in the United States (1). Clinical management of advanced GIST has been transformed by the application of tyrosine kinase inhibitors (TKI) that target the mutant forms of KIT and PDGFRA that are found in approximately 90% of GIST. Currently, the standard of care for advanced GIST involves the sequential application of these TKIs, beginning with imatinib mesylate. Treatment with imatinib mesylate produces an objective response or stable disease in >80% of patients with metastatic and/or unresectable GIST. However, the success of imatinib mesylate in these patients is tempered by the reality that treatment increases the median time to tumor progression by just 2 years (2–4). Second- and third-line therapies, sunitinib and regorafenib, provide additional disease stabilization measured in months (5, 6). For clinical management of GIST to improve, new therapeutic targets and/or treatment modalities must be identified.

Functional and correlative studies in GIST cell lines and patient samples have established that the PI3K/AKT pathway is critical to survival in imatinib mesylate–resistant GIST (7–11). Recently, a mathematical approach applied to the evolutionary dynamics of solid tumors in response to treatment emphasized the need for concurrently targeting different pathways, or different parts of a pathway, to prevent the establishment of disease resistant to individual drugs (12). Therefore, using agents directed at distinct components of critical signaling pathways in GIST warrants further investigation.

This approach was recently tested in two preclinical studies evaluating imatinib mesylate in combination with PI3K inhibitors (PI3Ki) in GIST xenograft models (13, 14). In the first study (2013), a pan-inhibitor of class I PI3K, called GDC-0941, was administered as a single agent or in combination with imatinib mesylate to a panel of imatinib mesylate–sensitive and resistant xenografts (14). GDC-0941 led to stable disease in a subset of these models (dependent on mutational status), whereas the combination of GDC-0941 and imatinib mesylate actually induced tumor shrinkage. Furthermore, the combination-treated tumors exhibited prolonged responses even after discontinuation of treatment. A follow-up study (2014) utilized the same panel of GIST xenografts to evaluate three additional PI3Ki: buparlisib, a pan-PI3Ki, BEZ 235, a dual PI3K/mTOR inhibitor, and BYL719, a selective inhibitor of the PI3K catalytic p110α subunit (13). Similar to the previous study, all three PI3Ki demonstrated significant antitumor effects as monotherapies; however, superior responses were observed in combination with imatinib mesylate (13). To date, several clinical trials have been conducted with inhibitors of the PI3K/AKT pathway in GIST, but few clinical trials have evaluated these inhibitors in combination with imatinib mesylate (15). One phase II clinical trial evaluated perifosine, an AKT inhibitor, in imatinib mesylate–refractory GIST with minimal activity observed (16). Two additional phase I studies are ongoing to determine the recommended tolerated doses of the PI3Ki, BKM120, and BYL719, in combination with imatinib mesylate (https://clinicaltrials.gov/).

In this study, we sought to evaluate MK-2206, a highly selective AKT inhibitor that is currently being tested in a number of phase I/II clinical trials in combination with chemotherapeutic agents and/or targeted therapies in various malignancies (17, 18). MK-2206 has not yet been evaluated in GIST as a single agent or in combination with imatinib mesylate. Here, we report significantly enhanced combination effects between MK-2206 and imatinib mesylate in a panel of imatinib mesylate–sensitive and resistant GIST cell lines. The combination was also effective in controlling the growth of GIST cells in three-dimensional (3D) spheroid culture. Furthermore, dual inhibition of KIT and AKT in GIST xenografts provided impressive, extended disease stabilization, and improved survival. Finally, following the efficacy study, in-depth transcriptome analysis of extracted GIST xenografts identified specific tumor molecular responses that are potentially relevant to treatment-induced disease stabilization or regression.

Cell lines, compounds, and antibodies

The GIST-T1 tumor cell line possessing a heterozygous mutation in KIT exon 11 was kindly provided by Takahiro Taguchi (Kochi University, Kochi, Japan) (19). The GIST882 tumor cell line possessing a homozygous mutation in KIT exon 13, the GIST-T1/829 subline derived from parental GIST-T1 cells possessing a secondary A829P kinase domain mutation, and the GIST430 tumor cell line possessing a primary KIT exon 11 deletion with a secondary mutation (V654A substitution) were all generously provided by Jonathan A. Fletcher (Dana Farber Cancer Institute, Boston, MA) (20). Cells were grown as described in ref. 11 (GIST-T1), ref. 21 (GIST882), and ref. 20 (GIST-T1/829 and GIST430) and were routinely (last tested April 2016) monitored by Sanger sequencing to confirm their KIT mutation status and cell line identity. Imatinib mesylate (Gleevec) was obtained from the Fox Chase Cancer Center (FCCC) Pharmacy, dissolved in sterile PBS, and stored at −20°C. MK-2206 was obtained from CTEP, dissolved in DMSO, and stored at −20°C. All antibodies used in this study were purchased from Cell Signaling Technology, except β-actin (Sigma), and used according to the manufacturer's instructions.

Cell proliferation/viability assay

To test in vitro drug sensitivity, tumor cells were plated in 96-well plates at optimal seeding densities in complete media and incubated overnight. Wells were then treated in triplicate with varying doses of MK-2206 and/or imatinib mesylate. Cell proliferation and viability were measured at 72 hours after treatment using the CellTiter Blue Viability Assay (Promega). The metabolic activity of viable cells was quantified 3 hours after the addition of CellTiter Blue reagent using an EnVision microplate reader (Perkin Elmer). Assays were performed as three independent experiments with a minimum of three technical replicates in each treatment arm. From the cell viability data, synergy between MK-2206 and imatinib mesylate was evaluated by the Chou–Talalay combination index (CI) method (22) as described previously (23). CalcuSyn Version 2.1 (BioSoft; ref. 24) was used to calculate the CI values at each molar ratio evaluated. Drug combinations that yielded CI values <1 were considered to be synergistic (25, 26).

Drug sensitivity in spheroid culture

Spheroids were formed in Corning 96 Well Flat Clear Bottom White Polystyrene TC-Treated Microplates (Corning). Wells were coated in 1.5% UltraPure Agarose (Invitrogen Corporation) solution prepared in DMEM. GIST-T1 and GIST430 cells were suspended atop the agar layer in complete DMEM (9,000 cells/well) and left undisturbed for 96 hours at 37°C and 5% CO2. Resulting spheroids were treated with appropriate drug(s) in 50-μL complete DMEM. Spheroids were imaged at 4× magnification by EVOS FL Digital Inverted Microscope (AMG) after 72 hours of drug treatment. Spheroid surface area was measured using ImageJ software (NIH, Bethesda, MD). The CellTiter-Glo Luminescent Cell Viability Assay (Promega) was performed after imaging, with luminescence measured by EnVision Plate Reader. Three independent experiments were performed with a minimum of three technical replicates in each treatment arm. Statistical analyses were conducted using GraphPad Prism Version 6.05 (GraphPad Software). Surface area and viability of treated spheroids were normalized to vehicle-treated spheroids of the same cell line. Comparison of treatment arms was performed with one-way ANOVA. Post hoc comparisons were made using the Bonferroni multiple comparisons method.

Preparation of whole cell extract from cells and immunoblot assays

The whole cell extracts (WCE) were prepared and evaluated by immunoblot assay as described previously (11).

GIST xenografts and drug administration

All studies involving animals followed procedures approved by the FCCC Institutional Animal Care and Use Committee. GIST-T1 cells were washed and subsequently resuspended in PBS at a density of 3 × 106 cells/100 μL. One hundred microliters of cells in PBS were mixed thoroughly with 100 μL of Matrigel Matrix (BD Biosciences) and the suspension was injected subcutaneously into the right flanks of SCID mice (CB.17/SCID, obtained from the FCCC breeding colony). Tumor volume was calculated using the formula: tumor volume (mm3) = (smallest diameter2 × largest diameter)/2. When tumors reached approximately 300 mm3, mice were randomized into four treatment arms: arm 1, vehicle; arm 2, imatinib mesylate at 50 mg/kg daily (oral); arm 3, MK-2206 at 120 mg/kg 3×/week (oral); arm 4, imatinib mesylate and MK-2206 at monotherapy doses. Treatment was continued until the tumors exceeded >10% of their body weight or the animals demonstrated distress or weight loss >10% as per the local Institutional Animal Care and Use Committee guidelines.

Tumor growth modeling

Tumor volume was measured for every mouse in each of the four treatment arms (vehicle, imatinib mesylate, MK-2206, and combination) at a total of 24 distinct time points, from baseline (Day 0) until study conclusion (Day 119). A longitudinal model based on the generalized estimating equations approach (with an autoregressive correlation structure) was used to model the effect of treatment and time on tumor volume. A linear time-effect was included in the model for the logarithm of tumor volume and interacted with treatment. Overall survival (at the end of the study) and tumor volume (at 5 weeks) were compared between treatment groups using the log rank and Mann–Whitney tests, respectively. All tests were two-sided and used a type I error of 5%. The package geepack (27) and survival in the R statistical language and environment was used in these computations.

Immunohistochemical analysis

Apoptosis was assessed using an antibody recognizing cleaved caspase-3 (Cell Signaling Technology). Immunohistochemical staining was performed on 5-μm slides. After deparaffinization and rehydration, sections were subjected to heat-induced epitope retrieval by immersion in a 0.01 mol/L citrate buffer (pH 6.0). Endogenous peroxidase activity was blocked for 15 minutes in 3% hydrogen peroxide in methanol. Nonspecific binding was blocked by treatment with a blocking reagent (Protein Block Serum-Free, DAKO) for 30 minutes at room temperature. The slides were then incubated overnight with primary antibody at 4°C in a humidified chamber. Immunodetection was performed by using the Sensitive Link-Label (Biotin-based) IHC Detection Systems.

Whole-transcriptome sequencing of GIST xenografts

Total RNA was isolated from flash-frozen xenograft tissue using TRIzol reagent (Life Technologies), quantified with a Nanodrop ND-1000 spectrophotometer (Thermo Scientific) and quality assessed with the Agilent 2100 BioAnalyzer. The majority of samples used had RNA integrity numbers (RIN) >8.5. mRNA-focused libraries were generated using the Illumina TruSeq RNA Sample Preparation Kit, followed by quality assurance and quantification using the Agilent 2100 Bioanalyzer and the KAPA Biosystems qPCR procedure. Library clusters were generated on-board the Illumina HiSEq 2500 followed by 2 × 100 cycles of paired-end SBS sequencing runs. An average of 76.1 million paired-end reads was generated per sample.

Reads considered valid by the Illumina HiSeq control software were assessed with our QC pipeline as follows: (i) samples with poor sequence quality were discarded on the basis of quality checks in FastQC (Babraham Institute, www.bioinformatics.babraham.ac.uk/projects/fastqc); (ii) standard QC criteria were applied to remove reads with >10% unknown bases or >50% low-quality bases (quality value <5); (iii) library quality metrics, including genomic mapping rates, coefficients of variations of coverage of each transcript, fraction of ribosomal RNA in each library and positional coverage biases were calculated using PicardTools (http://broadinstitute.github.io/picard); and (iv) samples with >90% Q30 bases and a rate of clean data (percentage of reads passing filter with respect to total number of raw reads) >50% were used for further analysis. Raw sequence reads were aligned to the human hg19 genome using the Tophat algorithm (28). Cufflinks (29) was implemented to assemble transcripts and estimate their abundance. Cuffdiff (30) was used to statistically assess expression changes in quantified genes in different conditions. We excluded genes with maximum fpkm (fragments per kilobase transcript per million reads) <5 across all conditions of interest. A FDR of 5% and fold-change (FC) >2 between groups were used as cutoffs to define significantly expressed genes.

qRT-PCR analysis

qRT-PCR was used to validate BEX1 expression in xenografts from the various treatment arms, as well as to evaluate changes in the expression of BEX1 in drug-treated GIST cell lines. qRT-PCR was carried out as described previously (31). TaqMan assays were purchased from Applied Biosystems: Hs00218464_m1 (brain expressed X-linked 1), Hs99999907_m1 (β2-microglobulin), and Hs99999909_m1 (hypoxanthine phosphoribosyltransferase 1).

MK-2206 and imatinib have enhanced combination effects on in vitro GIST cell growth

Although many tumors in the clinical setting exhibit early and often dramatic responses to targeted monotherapies, they commonly develop resistance to individual agents within months. A growing body of evidence now suggests that targeting multiple pathways by means of combination treatment may be a more beneficial approach. Given the success observed with PI3K inhibitors in combination with imatinib mesylate in GIST models (13, 14), we set out to examine the effects of combined inhibition of AKT (a downstream effector of PI3K) and KIT in a panel of imatinib mesylate–sensitive and -resistant GIST cell lines. We selected MK-2206, a highly selective, allosteric, pan-AKT inhibitor for our combination studies. MK-2206 is an orally available agent that inhibits AKT activity in a non-ATP competitive manner requiring the Pleckstrin homology domain of AKT (32).

We evaluated the effects of MK-2206 and imatinib mesylate on the growth of imatinib mesylate–sensitive and -resistant GIST cell lines (GIST-T1, GIST882, GIST-T1/829, and GIST430), as single agents and in combination at four molar ratios. Shown in Fig. 1A are the dose–response data for MK-2206, imatinib mesylate, and their combination at a molar ratio of 3:1 (MK-2206:imatinib mesylate). In all four cell lines, treatment with this combination resulted in enhanced sensitivity to the drugs. This is evident when comparing the IC50 and IC80 concentrations of the drugs used as single agents versus in combination (Supplementary Table S1). Furthermore, we quantified synergy between the two drugs using CalcuSyn software (24), which uses the Chou–Talalay algorithm (22) to calculate CI values. CI values <1 are considered to be synergistic (25, 26). Supplementary Table S2 lists the calculated CI values for all four molar ratios that were evaluated in each of the GIST cell lines. These data are depicted as a heatmap in Fig. 1B.

Figure 1.

Drug combination of MK-2206 and imatinib mesylate (IM). A, The points represent the average viability ± SEM after 72-hour drug treatment at the indicated concentrations of MK-2206 (), imatinib mesylate (), and the combination (; constant 3:1 molar ratio of MK-2206:imatinib mesylate, graphs show the concentration of imatinib mesylate in the combination treatments), for the various GIST cell lines as a percentage of vehicle-treated cells. The curve-fit lines were generated using nonlinear regression analysis in GraphPad Prism. B, The heatmap depicts the CI values for the drug combinations at various molar ratios in each cell line. CI values were calculated with CalcuSyn software using the Chou–Talalay method. CI values <1 suggest synergy between MK-2206 and imatinib mesylate. C, Representative images of GIST-T1 and GIST430 spheroids after 72-hour drug treatment. GIST-T1 spheroids were treated with vehicle, 192 nmol/L MK-2206, 64 nmol/L imatinib mesylate, or the combination (192 nmol/L MK-2206 and 64 nmol/L imatinib mesylate). GIST430 spheroids were treated with vehicle, 3 μmol/L MK-2206, 1 μmol/L imatinib mesylate, or the combination (3 μmol/L MK-2206 and 1 μmol/L imatinib mesylate). D, Bars represent average viability ± SEM after 72-hour treatment at the indicated concentrations of drugs, for GIST-T1 and GIST430 spheroids as a percentage of vehicle-treated spheroids. Viability was measured using the CellTiter-Glo cell viability assay. E, Spheroids were imaged after 72 hours treatments and surface area was calculated using ImageJ software. Bars represent the average surface area ± SEM of GIST-T1 and GIST430 spheroids as a percentage of vehicle-treated spheroids. All spheroid data were analyzed using GraphPad Prism, with comparisons of treatment groups performed with one-way ANOVA and post hoc comparisons made using the Bonferroni multiple comparisons method. *, P ≤ 0.01; **, P ≤ 0.001.

Figure 1.

Drug combination of MK-2206 and imatinib mesylate (IM). A, The points represent the average viability ± SEM after 72-hour drug treatment at the indicated concentrations of MK-2206 (), imatinib mesylate (), and the combination (; constant 3:1 molar ratio of MK-2206:imatinib mesylate, graphs show the concentration of imatinib mesylate in the combination treatments), for the various GIST cell lines as a percentage of vehicle-treated cells. The curve-fit lines were generated using nonlinear regression analysis in GraphPad Prism. B, The heatmap depicts the CI values for the drug combinations at various molar ratios in each cell line. CI values were calculated with CalcuSyn software using the Chou–Talalay method. CI values <1 suggest synergy between MK-2206 and imatinib mesylate. C, Representative images of GIST-T1 and GIST430 spheroids after 72-hour drug treatment. GIST-T1 spheroids were treated with vehicle, 192 nmol/L MK-2206, 64 nmol/L imatinib mesylate, or the combination (192 nmol/L MK-2206 and 64 nmol/L imatinib mesylate). GIST430 spheroids were treated with vehicle, 3 μmol/L MK-2206, 1 μmol/L imatinib mesylate, or the combination (3 μmol/L MK-2206 and 1 μmol/L imatinib mesylate). D, Bars represent average viability ± SEM after 72-hour treatment at the indicated concentrations of drugs, for GIST-T1 and GIST430 spheroids as a percentage of vehicle-treated spheroids. Viability was measured using the CellTiter-Glo cell viability assay. E, Spheroids were imaged after 72 hours treatments and surface area was calculated using ImageJ software. Bars represent the average surface area ± SEM of GIST-T1 and GIST430 spheroids as a percentage of vehicle-treated spheroids. All spheroid data were analyzed using GraphPad Prism, with comparisons of treatment groups performed with one-way ANOVA and post hoc comparisons made using the Bonferroni multiple comparisons method. *, P ≤ 0.01; **, P ≤ 0.001.

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To evaluate the effects of the drugs as single agents or in combination on 3D GIST cell growth, spheroid formation assays were performed. Three-dimensional multicellular tumor spheroids have become a valuable model in the study of anticancer agents because they more accurately mimic what is occurring physiologically. GIST-T1 and GIST430 cells formed dense, uniformly spherical cultures with true cell-to-cell contacts that remained intact upon physical manipulation, all of which are characteristics of a true spheroid (Fig. 1C). Treatment of the GIST430 spheroids with either of the single agents, MK-2206 or imatinib mesylate, resulted in a decrease in cell viability relative to vehicle-treated spheroids (Fig. 1D). However, treatment of these spheroids with the combination resulted in a significantly greater reduction in cell viability that was statistically significant (Fig. 1D). The GIST-T1 spheroids were treated at lower drug concentrations due to the sensitivity of GIST-T1 cells to imatinib mesylate, but the 3:1 molar ratio of drugs was maintained. Treatment of GIST-T1 spheroids with imatinib mesylate resulted in a decrease in cell viability, whereas treatment with MK-2206 had no significant effect relative to vehicle-treated spheroids. In contrast, the combination-treated GIST-T1 spheroids resulted in a substantial decrease in cell viability. These same trends were observed when spheroid size was used to gauge the effects of the treatments alone or in combination (Fig. 1E).

Combination treatment inhibits signaling downstream of KIT

To test the effects of drug treatment on signaling downstream of KIT, we performed immunoblotting on GIST cell lines treated with MK-2206, imatinib mesylate, or their combination. Following imatinib mesylate treatment, constitutive activation of AKT was observed in two imatinib mesylate–resistant GIST cell lines, GIST-T1/829 and GIST430 (Fig. 2), providing further support for targeting AKT in GIST. Significant inhibition of AKT was observed in all four cell lines treated with MK-2206. Interestingly, all GIST cell lines treated with MK-2206 alone also demonstrated elevated levels (up to approximately 3-fold) of activated MAPK, suggesting that GIST cells can compensate for AKT inhibition through increased MAPK signaling. Therefore, targeting AKT alone may not be sufficient to inhibit GIST cell growth and survival. Notably, treatment with the combination of MK-2206 and imatinib mesylate inhibited activation of AKT, MAPK, and other signaling proteins (GSK3β, S6) downstream of KIT (Fig. 2).

Figure 2.

The combination of MK-2206 and imatinib mesylate (IM) inhibits constitutive activation of effectors downstream of KIT. Immunoblot assays of WCEs from GIST-T1, GIST-T1/829, GIST430, and GIST882 treated with 1 μmol/L imatinib mesylate, 3 μmol/L MK-2206, or the combination for 6 hours. Equal quantities (30 μg) of WCE from each sample were subjected to immunoblotting with specific antibodies, as indicated. β-Actin served as a loading control.

Figure 2.

The combination of MK-2206 and imatinib mesylate (IM) inhibits constitutive activation of effectors downstream of KIT. Immunoblot assays of WCEs from GIST-T1, GIST-T1/829, GIST430, and GIST882 treated with 1 μmol/L imatinib mesylate, 3 μmol/L MK-2206, or the combination for 6 hours. Equal quantities (30 μg) of WCE from each sample were subjected to immunoblotting with specific antibodies, as indicated. β-Actin served as a loading control.

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Combination treatment reduces tumor growth and improves survival in vivo

On the basis of these strong in vitro data, we hypothesized that there would be benefit in simultaneously inhibiting KIT and AKT to circumvent the rescue pathways that lead to clinical imatinib mesylate resistance. To test this hypothesis, we performed a GIST xenograft study under a FCCC Institutional Animal Care protocol. Xenografts were established using the GIST-T1 cell line (19), which harbors a heterozygous exon 11 KIT mutation, the most common and imatinib mesylate–responsive mutation in GIST. This model mirrors the majority of patients who commonly develop resistance to imatinib mesylate and provides an initial means of testing our working hypothesis. GIST-T1 xenografts were established subcutaneously in a total of 40 C.B17 SCID mice and randomized into four treatment arms: arm 1: vehicle, arm 2: imatinib mesylate, arm 3: MK-2206, and arm 4: imatinib mesylate and MK-2206. Both of the monotherapy arms showed some disease stabilization without tumor regression for a period of approximately 4 weeks of therapy, after which a subset of tumors (44% of imatinib mesylate–treated tumors and 37.5% of MK-2206–treated tumors) significantly increased in volume. In contrast, tumor volume measurements in arm four mice indicated significant disease stabilization or tumor regression. Tumors in the combination arm displayed an average of 33.4% tumor shrinkage at 12 weeks, and all but one of these tumors were still responsive after 17 weeks of therapy (Fig. 3A). Importantly, tumor response led to significant improvement in overall survival in the combination arm compared with both monotherapy arms (Fig. 3B). Median estimated survival times for the imatinib mesylate and MK-2206 monotherapy arms were 63.5 and 62 days, respectively, compared with 41 days for vehicle-treated mice. Impressively, at the end of the study (122 days), 90% of the mice treated with the combination were still responding and no vehicle- or monotherapy-treated mice were alive. After treatment discontinuation, we observed regrowth of these tumors after approximately 4 weeks.

Figure 3.

The combination of MK-2206 and imatinib mesylate (IM) significantly inhibits GIST growth in vivo and improves overall survival. A, Statistically significant decreases in the rate of tumor growth were observed due to treatment with imatinib mesylate (black), MK-2206 (green), and their combination (red) compared with vehicle (blue) (P = 1.23e−03, 6.37e−04, and 1.28e−08, respectively). Smoothed tumor growth curves (tumor volume vs. time) were computed for each treatment using the lowess smoother in the R statistical language (50). B, Kaplan–Meier estimate of the probability of overall survival for all 40 mice in the study. Statistically significant differences in overall survival were observed between the combination arm and each of the other arms (P < 0.001).

Figure 3.

The combination of MK-2206 and imatinib mesylate (IM) significantly inhibits GIST growth in vivo and improves overall survival. A, Statistically significant decreases in the rate of tumor growth were observed due to treatment with imatinib mesylate (black), MK-2206 (green), and their combination (red) compared with vehicle (blue) (P = 1.23e−03, 6.37e−04, and 1.28e−08, respectively). Smoothed tumor growth curves (tumor volume vs. time) were computed for each treatment using the lowess smoother in the R statistical language (50). B, Kaplan–Meier estimate of the probability of overall survival for all 40 mice in the study. Statistically significant differences in overall survival were observed between the combination arm and each of the other arms (P < 0.001).

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Transcriptome analysis identifies molecular response patterns in combination-treated xenografts

As a follow-up to the longitudinal xenograft study, a second xenograft study was carried out with the same four therapeutic arms described above. This study was designed to confirm the efficacy of the combination therapy as well as to allow the harvesting of tumors at an appropriate time point to investigate the tumor molecular responses using whole-transcriptome sequencing (WTS) approaches. Tumors were harvested after 5 weeks of treatment, a time point where tumor growth in the monotherapy arms began to resume, whereas disease control was maintained in the combination arm. As seen in Fig. 4A, tumor volumes in mice treated with the combination were significantly reduced in comparison with those treated with vehicle, imatinib mesylate, or MK-2206 alone. Histologic examination demonstrated increased levels of the apoptotic marker, cleaved caspase-3, in tumors from combination-treated mice compared with those treated with imatinib mesylate or MK-2206 alone (Supplementary Fig. S1). RNA isolated from tumors harvested after 5 weeks of treatment was subjected to WTS. The primary aim of this analysis was to identify transcripts that were differentially expressed in xenografts from the combination arm as compared with xenografts from the monotherapy arms. To rule out differences that may have been attributed to resumption of tumor growth in the monotherapy arms, we excluded tumors from those arms that were actively growing after 5 weeks of treatment. The subset of tumors whose volumes remained stable with imatinib mesylate or MK-2206 treatment alone we termed arms “2S” and “3S,” respectively. Using an FDR of 5%, and FC >2 as cut-offs, five genes were identified that were common to arm 4 versus arm 2S, and arm 4 versus arm 3S comparisons (Table 1). The upregulation of the brain expressed X-linked 1 (BEX1) gene under combination therapy was of particular interest, as this encoded protein has been implicated as a tumor-suppressor gene (TSG) in various cellular contexts (33–35). Similarly, neuronal pentraxin-1 (NPTX1), which is also strongly upregulated in response to the combination therapy, has been described as a potential TSG or biomarker in a variety of cancer types (36–38). qRT-PCR was used to validate the overexpression of BEX1 and NPTX1 RNA in these xenografts. BEX1 RNA levels were approximately 1.6-fold higher in combination-treated xenografts than in stable imatinib mesylate–treated xenografts (P = 0.0095) and approximately 3.0-fold higher than in stable MK-2206–treated xenografts (P = 0.0013; Fig. 4B). NPTX1 levels were also significantly increased in combination-treated xenografts as compared with stable imatinib mesylate–treated xenografts (approximately 4.6-fold; P = 0.0097) and stable MK-2206–treated xenografts (approximately 24-fold; P = 0.0013; Fig. 4C). To extend these observations to cellular models, qRT-PCR was used to determine the expression of BEX1 and NPTX1 in GIST cell lines treated for 72 hours with imatinib mesylate and MK-2206, alone and in combination. In imatinib mesylate–sensitive GIST-T1 cells treated with the combination, BEX1 RNA was increased approximately 1.5-fold (P = 0.020) in comparison with imatinib mesylate–treated cells and approximately 1.8-fold (P = 0.045) in comparison with MK-2206–treated cells. Similarly, in imatinib mesylate–resistant GIST430 cells treated with the combination, statistically significant BEX1 upregulation was observed in comparison with cells treated with imatinib mesylate (approximately 2.8-fold; P = 0.028) or MK-2206 (approximately 1.9-fold; P = 0.047) alone. NPTX1 expression levels in GIST-T1 cells treated with the combination were approximately 1.8- and 1.2-fold higher than in imatinib mesylate- and MK-2206–treated cells, respectively. NPTX1 expression was also slightly increased in GIST430 cells treated with the combination compared with imatinib mesylate only (approximately 1.4-fold). However, the expression differences for NPTX1 were not statistically significant in either cell line.

Figure 4.

Treatment of GIST-T1 xenografts with the combination of MK-2206 and imatinib mesylate (IM) leads to reduced tumor volume and increased expression of BEX1 and NPTX1. A, Box-and-whisker plots of tumor volume measured after 5 weeks of treatment with vehicle (arm 1, blue), imatinib mesylate (IM; arm 2, white), MK-2206 (arm 3, green), or the combination (arm 4, red). In each plot, box height represents the interquartile range (IQR) where the top and bottom ends indicate the third and first quartiles, respectively. The solid black horizontal line inside the box represents the median value whereas the whiskers (the two solid horizontal lines at either end, connected by dotted lines) extend to the most extreme data points, which are no more than 1.5 times the IQR from the box in either direction. Tumor volume was significantly reduced in the combination arm versus the vehicle, imatinib mesylate, and MK-2206 arms (P = 0.0047, 0.047, and 0.0045, respectively. Two-tailed Mann–Whitney test). B and C, Values represent normalized BEX1 RNA expression (B) and NPTX1 expression (C) in GIST-T1 xenografts as determined by qRT-PCR. BEX1 and NPTX1 expression levels were normalized to the mean expression of B2M and HPRT. The error bars represent standard deviation. BEX1 and NPTX1 RNA levels were both significantly higher, as determined by the two-tailed Student t-test, in combination (arm 4) xenografts compared with vehicle (arm 1), imatinib mesylate (arm 2), and MK-2206 (arm 3) tumors. For BEX1, P values were 0.0026, 0.0095, and 0.0013, respectively (combination vs. vehicle, imatinib mesylate, and MK-2206). Similarly, for NPTX1, P values were 0.0074, 0.0097, and 0.0013, when comparing arm 4 to arms 1, 2, and 3, respectively.

Figure 4.

Treatment of GIST-T1 xenografts with the combination of MK-2206 and imatinib mesylate (IM) leads to reduced tumor volume and increased expression of BEX1 and NPTX1. A, Box-and-whisker plots of tumor volume measured after 5 weeks of treatment with vehicle (arm 1, blue), imatinib mesylate (IM; arm 2, white), MK-2206 (arm 3, green), or the combination (arm 4, red). In each plot, box height represents the interquartile range (IQR) where the top and bottom ends indicate the third and first quartiles, respectively. The solid black horizontal line inside the box represents the median value whereas the whiskers (the two solid horizontal lines at either end, connected by dotted lines) extend to the most extreme data points, which are no more than 1.5 times the IQR from the box in either direction. Tumor volume was significantly reduced in the combination arm versus the vehicle, imatinib mesylate, and MK-2206 arms (P = 0.0047, 0.047, and 0.0045, respectively. Two-tailed Mann–Whitney test). B and C, Values represent normalized BEX1 RNA expression (B) and NPTX1 expression (C) in GIST-T1 xenografts as determined by qRT-PCR. BEX1 and NPTX1 expression levels were normalized to the mean expression of B2M and HPRT. The error bars represent standard deviation. BEX1 and NPTX1 RNA levels were both significantly higher, as determined by the two-tailed Student t-test, in combination (arm 4) xenografts compared with vehicle (arm 1), imatinib mesylate (arm 2), and MK-2206 (arm 3) tumors. For BEX1, P values were 0.0026, 0.0095, and 0.0013, respectively (combination vs. vehicle, imatinib mesylate, and MK-2206). Similarly, for NPTX1, P values were 0.0074, 0.0097, and 0.0013, when comparing arm 4 to arms 1, 2, and 3, respectively.

Close modal
Table 1.

Differentially expressed genesa in xenografts from combination-treated mice

Gene symbolGene nameRatio, 4/2SbRatio, 4/3Sc
BEX1 Brain expressed X-linked 1 3.05 2.57 
NPTX1 Neuronal pentraxin I 4.26 9.60 
HSPA1A Heat shock 70 kDa protein 1A 3.25 2.67 
HSPA1B Heat shock 70 kDa protein 1B 3.47 2.34 
CXCL10 Chemokine (C-X-C motif) ligand 10 0.38 0.18 
Gene symbolGene nameRatio, 4/2SbRatio, 4/3Sc
BEX1 Brain expressed X-linked 1 3.05 2.57 
NPTX1 Neuronal pentraxin I 4.26 9.60 
HSPA1A Heat shock 70 kDa protein 1A 3.25 2.67 
HSPA1B Heat shock 70 kDa protein 1B 3.47 2.34 
CXCL10 Chemokine (C-X-C motif) ligand 10 0.38 0.18 

aCuffdiff was applied to WTS data to determine differentially expressed genes using a false discovery rate of 5%.

bRatio of normalized gene expression in tumors from combination-treated (arm 4) versus imatinib mesylate–treated mice with stable disease (arm 2S).

cRatio of normalized gene expression in tumors from combination-treated (arm 4) versus MK-2206–treated mice with stable disease (arm 3S).

The introduction (in 2002) of imatinib mesylate as a treatment for advanced and inoperable GIST remains a paradigm for molecularly targeted cancer therapy. Today, FDA-approved targeted therapies are part of the armamentarium for more than 25 different cancer types (http://www.cancer.gov/about-cancer/treatment/types/targeted-therapies/targeted-therapies-fact-sheet). Although these inhibitors have revolutionized the treatment of GIST and other malignancies, management of intrinsic and acquired resistance mechanisms remain a clinical challenge. Activation of the PI3K/AKT pathway, downstream of activated RTKs, has been shown to both predict and promote resistance to RTK inhibitors in GIST and in other malignancies (7, 9, 10, 39–41). Clinical trials are currently underway to investigate the use of PI3K/AKT inhibitors in combination with RTK inhibitors in CLL, melanoma, and NSCLC. Recently, PI3K inhibitors were combined with imatinib mesylate in preclinical studies using GIST xenografts, and this combination demonstrated superior and more durable responses as compared with either single agent (13, 14). Reduced or absent expression of the PTEN was significantly associated with imatinib mesylate treatment in GIST patient samples, and PTEN deficiency in vitro results in hyperactivation of AKT (9). Two recent studies in imatinib mesylate–sensitive and -resistant GIST cellular models established links between KIT activity (modified by specific KIT-targeting miRNAs), AKT expression and phosphorylation, and cell viability and apoptosis (42, 43). Hence, AKT stands out as an attractive target for combination therapy with imatinib mesylate. Here we set out to determine whether targeting AKT with the small-molecule inhibitor, MK-2206, in combination with imatinib mesylate can provide a more robust and durable response in GIST.

In this study, we demonstrate enhanced drug combination effects between imatinib mesylate and MK-2206 in a panel of imatinib mesylate–sensitive and -resistant GIST cell lines, using both two-dimensional (2D) and three-dimensional (3D) in vitro studies. Interestingly, the in vitro data from the 3D spheroid model of GIST-T1 (Fig. 1C–E) appeared to be a better predictor of in vivo drug efficacy than the data from the GIST-T1 2D monolayers (Fig. 1A and B), suggesting that the 3D spheroids may produce a growth environment that better correlates to the setting of tumors in vivo. Future in vitro drug studies should consider incorporating 3D spheroid models to gain a better understanding of in vivo drug efficacy. We show that although MK-2206 alone successfully inhibits AKT activation in all GIST cell lines, it also leads to increased activation of the MAPK pathway. This could mitigate the effects of AKT inhibition and potentially explain why minimal cytotoxicity was observed in GIST cells treated with MK-2206 alone. The presence of such compensatory mechanisms suggests that targeting AKT alone may not be sufficient to control GIST cell growth and survival and we believe that a combinatorial approach may be warranted. The results of these in vitro studies provided justification for investigating such an approach in vivo. We chose to use imatinib mesylate–sensitive GIST-T1 xenografts because they possess an exon 11 KIT mutation, as do the majority of patients who commonly develop resistance to imatinib mesylate. Therefore, this model provided an initial means of testing this combination as a front-line therapy in GIST. Both xenograft studies performed here showed reproducible and statistically significant decreases in the rate of tumor growth following treatment with imatinib mesylate and MK-2206 alone; however, resistance to both monotherapies was observed as tumors began to resume growth after approximately 5 weeks. In contrast, the combination of imatinib mesylate and MK-2206 inhibited tumor growth for an extended period of time and significantly increased overall survival. Impressively, the original in vivo study was continued for over 4 months, at which time all but one of the combination-treated mice were still alive. Incidentally, the mouse that died from this group had an initial tumor volume much larger (3-fold) than all others in this treatment arm, indicating the importance of targeting these tumors at smaller sizes. Together, these xenograft studies provide strong evidence for the initiation of future clinical studies evaluating the use of imatinib mesylate in combination with AKT inhibitors in patients with GIST.

To gain insight into the mechanism(s) responsible for the superior efficacy of this combination, and to probe the molecular responses to the various treatment modalities, we performed WTS on these tumors. This analysis focused our attention on two genes, BEX1 and NPTX1, whose expression was significantly upregulated in combination-treated tumors. BEX1, a gene with strong expression in neural tissue, is a member of a family of five genes that map to chromosome Xp22 that are involved in regulating signals from cell surface receptors (reviewed in ref. 44). NPTX1, one of several human pentraxins expressed primarily in nervous tissue, has been linked to the induction of neural lineage (45). The identification of two neural genes is particularly intriguing as it has been well established that GIST have both smooth muscle and neural elements (46). The WTS results for both BEX1 and NPTX1 were confirmed by qRT-PCR in the xenografts from the study, and the induction of BEX1 by the drug combination was also confirmed in imatinib mesylate–sensitive GIST-T1 and -resistant GIST430 cell lines, providing cellular models for exploring this finding. Numerous reports in the literature implicate BEX1 and NPTX1 as tumor-suppressor genes or biomarkers in various cancers (33–35, 37, 38). Both genes have been implicated in connection with proapoptotic pathways in different cellular contexts. A genome-wide epigenetic analysis in primary and immortalized glioma cell lines and patient samples implicated BEX1 and BEX2 as important epigenetically silenced genes whose reactivation increased sensitivity to chemotherapy-induced apoptosis (33). In a more mechanistic study of imatinib mesylate–resistant K562 chronic myeloid leukemia cells in which BEX1 expression is also silenced, re-expressed BEX1 protein restored imatinib mesylate sensitivity and induced apoptosis by binding to BCL-2 and suppressing the formation of antiapoptotic BCL-2/BAX heterodimers (47). Similar results have been described for BEX1 in acute myeloid leukemia (48). In a cellular model for neuronal cell death via oxygen glucose deprivation, NPTX1 protein expression was strongly induced via a PTEN–AKT–GSK3B–dependent mechanism; this induction was convincingly tied to enhanced mitochondrial translocation of proapoptotic BAD and BAX proteins and enhanced neuronal cell death (49). The literature on BEX1 and NPTX1 function, combined with the results from our cellular and preclinical data, suggests a model in which the imatinib mesylate and MK-2206 drug combination results in the induction of two genes that influence tumor cell fate by shifting the pro-/antiapoptotic balance toward cell death.

In conclusion, we have demonstrated enhanced combination effects between MK-2206, a novel allosteric AKT inhibitor, and imatinib mesylate in GIST preclinical models. This should provide justification for the development of further studies evaluating this combination in GIST patients. In addition, we have used deep transcriptome sequencing to implicate the BCL-2/BAX/BAD apoptotic pathway as a potential mechanism of this enhanced drug sensitivity.

No potential conflicts of interest were disclosed.

Conception and design: A.K. Godwin, M. von Mehren, L. Rink

Development of methodology: A.K. Godwin, L. Rink

Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): P. Zook, L. Gersz, A.K. Godwin, L. Rink

Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): P. Zook, H.B. Pathak, M.G. Belinsky, L. Gersz, K. Devarajan, Y. Zhou, A.K. Godwin, L. Rink

Writing, review, and/or revision of the manuscript: P. Zook, H.B. Pathak, M.G. Belinsky, K. Devarajan, A.K. Godwin, M. von Mehren, L. Rink

Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): A.K. Godwin, L. Rink

Study supervision: A.K. Godwin, L. Rink

We would like to acknowledge the following facilities at FCCC for their work contributing to this manuscript: Genomics facility, High Throughput Screening facility, Genotyping and Real-Time PCR facility, and the Laboratory Animal Facility. The authors would especially like to thank the GIST Cancer Research Fund for their continued support.

This work was supported in part by grants from the NCI (R00 CA158065, to L. Rink; R01 CA106588, to M. von Mehren; and to A.K. Godwin, P30CA006927, Fox Chase Cancer Center) and from Temple University Genomics funding.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

1.
Corless
CL
,
Heinrich
MC
. 
Molecular pathobiology of gastrointestinal stromal sarcomas
.
Annu Rev Pathol
2008
;
3
:
557
86
.
2.
Blanke
CD
,
Demetri
GD
,
von Mehren
M
,
Heinrich
MC
,
Eisenberg
B
,
Fletcher
JA
, et al
Long-term results from a randomized phase II trial of standard- versus higher-dose imatinib mesylate for patients with unresectable or metastatic gastrointestinal stromal tumors expressing KIT
.
J Clin Oncol
2008
;
26
:
620
5
.
3.
Verweij
J
,
van Oosterom
A
,
Blay
JY
,
Judson
I
,
Rodenhuis
S
,
van der Graaf
W
, et al
Imatinib mesylate (STI-571 Glivec, Gleevec) is an active agent for gastrointestinal stromal tumours, but does not yield responses in other soft-tissue sarcomas that are unselected for a molecular target. Results from an EORTC Soft Tissue and Bone Sarcoma Group phase II study
.
Eur J Cancer
2003
;
39
:
2006
11
.
4.
Demetri
GD
. 
GIST 1, chemotherapy 0, with a brand new hitter up next
.
Cancer Invest
2002
;
20
:
853
4
.
5.
Demetri
GD
,
van Oosterom
AT
,
Garrett
CR
,
Blackstein
ME
,
Shah
MH
,
Verweij
J
, et al
Efficacy and safety of sunitinib in patients with advanced gastrointestinal stromal tumour after failure of imatinib: a randomised controlled trial
.
Lancet
2006
;
368
:
1329
38
.
6.
Demetri
GD
,
Reichardt
P
,
Kang
YK
,
Blay
JY
,
Rutkowski
P
,
Gelderblom
H
, et al
Efficacy and safety of regorafenib for advanced gastrointestinal stromal tumours after failure of imatinib and sunitinib (GRID): an international, multicentre, randomised, placebo-controlled, phase 3 trial
.
Lancet
2013
;
381
:
295
302
.
7.
Bauer
S
,
Duensing
A
,
Demetri
GD
,
Fletcher
JA
. 
KIT oncogenic signaling mechanisms in imatinib-resistant gastrointestinal stromal tumor: PI3-kinase/AKT is a crucial survival pathway
.
Oncogene
2007
;
26
:
7560
8
.
8.
Wang
CM
,
Huang
K
,
Zhou
Y
,
Du
CY
,
Ye
YW
,
Fu
H
, et al
Molecular mechanisms of secondary imatinib resistance in patients with gastrointestinal stromal tumors
.
J Cancer Res Clin Oncol
2010
;
136
:
1065
71
.
9.
Quattrone
A
,
Wozniak
A
,
Dewaele
B
,
Floris
G
,
Vanspauwen
V
,
Van Looy
T
, et al
Frequent mono-allelic loss associated with deficient PTEN expression in imatinib-resistant gastrointestinal stromal tumors
.
Mod Pathol
2014
;
27
:
1510
20
.
10.
Li
J
,
Dang
Y
,
Gao
J
,
Li
Y
,
Zou
J
,
Shen
L
. 
PI3K/AKT/mTOR pathway is activated after imatinib secondary resistance in gastrointestinal stromal tumors (GISTs)
.
Med Oncol
2015
;
32
:
111
.
11.
Tarn
C
,
Skorobogatko
YV
,
Taguchi
T
,
Eisenberg
B
,
von Mehren
M
,
Godwin
AK
. 
Therapeutic effect of imatinib in gastrointestinal stromal tumors: AKT signaling dependent and independent mechanisms
.
Cancer Res
2006
;
66
:
5477
86
.
12.
Bozic
I
,
Reiter
JG
,
Allen
B
,
Antal
T
,
Chatterjee
K
,
Shah
P
, et al
Evolutionary dynamics of cancer in response to targeted combination therapy
.
Elife
2013
;
2
:
e00747
.
13.
Van Looy
T
,
Wozniak
A
,
Floris
G
,
Sciot
R
,
Li
H
,
Wellens
J
, et al
Phosphoinositide 3-kinase inhibitors combined with imatinib in patient-derived xenograft models of gastrointestinal stromal tumors: rationale and efficacy
.
Clin Cancer Res
2014
;
20
:
6071
82
.
14.
Floris
G
,
Wozniak
A
,
Sciot
R
,
Li
H
,
Friedman
L
,
Van Looy
T
, et al
A potent combination of the novel PI3K Inhibitor, GDC-0941, with imatinib in gastrointestinal stromal tumor xenografts: long-lasting responses after treatment withdrawal
.
Clin Cancer Res
2013
;
19
:
620
30
.
15.
Patel
S
. 
Exploring novel therapeutic targets in GIST: focus on the PI3K/Akt/mTOR pathway
.
Curr Oncol Rep
2013
;
15
:
386
95
.
16.
Conley
AP AD
,
Ludwig
J
,
Ravi
V
,
Samuels
BL
,
Choi
H
,
Thall
PF
, et al
A randomized phase II study of perifosine (P) plus imatinib for patients with imatinib-resistant gastrointestinal stormal tumor (GIST)
.
J Clin Oncol
2009
;
27
:
10563
.
17.
Molife
LR
,
Yan
L
,
Vitfell-Rasmussen
J
,
Zernhelt
AM
,
Sullivan
DM
,
Cassier
PA
, et al
Phase 1 trial of the oral AKT inhibitor MK-2206 plus carboplatin/paclitaxel, docetaxel, or erlotinib in patients with advanced solid tumors
.
J Hematol Oncol
2014
;
7
:
1
.
18.
Yap
TA
,
Yan
L
,
Patnaik
A
,
Fearen
I
,
Olmos
D
,
Papadopoulos
K
, et al
First-in-man clinical trial of the oral pan-AKT inhibitor MK-2206 in patients with advanced solid tumors
.
J Clin Oncol
2011
;
29
:
4688
95
.
19.
Taguchi
T
,
Sonobe
H
,
Toyonaga
S
,
Yamasaki
I
,
Shuin
T
,
Takano
A
, et al
Conventional and molecular cytogenetic characterization of a new human cell line, GIST-T1, established from gastrointestinal stromal tumor
.
Lab Invest
2002
;
82
:
663
5
.
20.
Heinrich
MC
,
Marino-Enriquez
A
,
Presnell
A
,
Donsky
RS
,
Griffith
DJ
,
McKinley
A
, et al
Sorafenib inhibits many kinase mutations associated with drug-resistant gastrointestinal stromal tumors
.
Mol Cancer Ther
2012
;
11
:
1770
80
.
21.
Tuveson
DA
,
Willis
NA
,
Jacks
T
,
Griffin
JD
,
Singer
S
,
Fletcher
CD
, et al
STI571 inactivation of the gastrointestinal stromal tumor c-KIT oncoprotein: biological and clinical implications
.
Oncogene
2001
;
20
:
5054
8
.
22.
Chou
TC
,
Talalay
P
. 
Quantitative analysis of dose-effect relationships: the combined effects of multiple drugs or enzyme inhibitors
.
Adv Enzyme Regul
1984
;
22
:
27
55
.
23.
Pathak
HB
,
Zhou
Y
,
Sethi
G
,
Hirst
J
,
Schilder
RJ
,
Golemis
EA
, et al
A synthetic lethality screen using a focused siRNA library to identify sensitizers to dasatinib therapy for the treatment of epithelial ovarian cancer
.
PLoS One
2015
;
10
:
e0144126
.
24.
Chou
TC
,
Haybali
M
.
(1996–2007) CalcuSyn for Windows. Dose-effect analysis and synergism/antagonism quantification. Manual and Software
.
Cambridge, United Kingdom
:
Biosoft
; 
1987
.
25.
Chang
TT
,
Chou
TC
. 
Rational approach to the clinical protocol design for drug combinations: a review
.
Acta Paediatr Taiwan
2000
;
41
:
294
302
.
26.
Chou
TC
. 
Preclinical versus clinical drug combination studies
.
Leuk Lymphoma
2008
;
49
:
2059
80
.
27.
R Development Core Team RDC
.
R: A language and environment for statistical computing
.
Vienna, Austria
:
R Foundation for Statistical Computing
; 
2011
.
28.
Trapnell
C
,
Pachter
L
,
Salzberg
SL
. 
TopHat: discovering splice junctions with RNA-Seq
.
Bioinformatics
2009
;
25
:
1105
11
.
29.
Trapnell
C
,
Williams
BA
,
Pertea
G
,
Mortazavi
A
,
Kwan
G
,
van Baren
MJ
, et al
Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation
.
Nat Biotechnol
2010
;
28
:
511
5
.
30.
Trapnell
C
,
Hendrickson
DG
,
Sauvageau
M
,
Goff
L
,
Rinn
JL
,
Pachter
L
. 
Differential analysis of gene regulation at transcript resolution with RNA-seq
.
Nat Biotechnol
2013
;
31
:
46
53
.
31.
Rink
L
,
Skorobogatko
Y
,
Kossenkov
AV
,
Belinsky
MG
,
Pajak
T
,
Heinrich
MC
, et al
Gene expression signatures and response to imatinib mesylate in gastrointestinal stromal tumor
.
Mol Cancer Ther
2009
;
8
:
2172
82
.
32.
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 invitro and invivo
.
Mol Cancer Ther
2010
;
9
:
1956
67
.
33.
Foltz
G
,
Ryu
GY
,
Yoon
JG
,
Nelson
T
,
Fahey
J
,
Frakes
A
, et al
Genome-wide analysis of epigenetic silencing identifies BEX1 and BEX2 as candidate tumor suppressor genes in malignant glioma
.
Cancer Res
2006
;
66
:
6665
74
.
34.
Karakoula
K
,
Jacques
TS
,
Phipps
KP
,
Harkness
W
,
Thompson
D
,
Harding
BN
, et al
Epigenetic genome-wide analysis identifies BEX1 as a candidate tumour suppressor gene in paediatric intracranial ependymoma
.
Cancer Lett
2014
;
346
:
34
44
.
35.
Lee
CH
,
Wong
TS
,
Chan
JY
,
Lu
SC
,
Lin
P
,
Cheng
AJ
, et al
Epigenetic regulation of the X-linked tumour suppressors BEX1 and LDOC1 in oral squamous cell carcinoma
.
J Pathol
2013
;
230
:
298
309
.
36.
Zhou
C
,
Qin
Y
,
Xie
Z
,
Zhang
J
,
Yang
M
,
Li
S
, et al
NPTX1 is a novel epigenetic regulation gene and associated with prognosis in lung cancer
.
Biochem Biophys Res Commun
2015
;
458
:
381
6
.
37.
Tyburczy
ME
,
Kotulska
K
,
Pokarowski
P
,
Mieczkowski
J
,
Kucharska
J
,
Grajkowska
W
, et al
Novel proteins regulated by mTOR in subependymal giant cell astrocytomas of patients with tuberous sclerosis complex and new therapeutic implications
.
Am J Pathol
2010
;
176
:
1878
90
.
38.
Hagihara
A
,
Miyamoto
K
,
Furuta
J
,
Hiraoka
N
,
Wakazono
K
,
Seki
S
, et al
Identification of 27 5′ CpG islands aberrantly methylated and 13 genes silenced in human pancreatic cancers
.
Oncogene
2004
;
23
:
8705
10
.
39.
Berns
K
,
Horlings
HM
,
Hennessy
BT
,
Madiredjo
M
,
Hijmans
EM
,
Beelen
K
, et al
A functional genetic approach identifies the PI3K pathway as a major determinant of trastuzumab resistance in breast cancer
.
Cancer Cell
2007
;
12
:
395
402
.
40.
Han
SW
,
Kim
TY
,
Jeon
YK
,
Hwang
PG
,
Im
SA
,
Lee
KH
, et al
Optimization of patient selection for gefitinib in non-small cell lung cancer by combined analysis of epidermal growth factor receptor mutation, K-ras mutation, and Akt phosphorylation
.
Clin Cancer Res
2006
;
12
:
2538
44
.
41.
Vivanco
I
,
Rohle
D
,
Versele
M
,
Iwanami
A
,
Kuga
D
,
Oldrini
B
, et al
The phosphatase and tensin homolog regulates epidermal growth factor receptor (EGFR) inhibitor response by targeting EGFR for degradation
.
Proc Natl Acad Sci U S A
2010
;
107
:
6459
64
.
42.
Fan
R
,
Zhong
J
,
Zheng
S
,
Wang
Z
,
Xu
Y
,
Li
S
, et al
microRNA-218 increase the sensitivity of gastrointestinal stromal tumor to imatinib through PI3K/AKT pathway
.
Clin Exp Med
2015
;
15
:
137
44
.
43.
Ihle
MA
,
Trautmann
M
,
Kuenstlinger
H
,
Huss
S
,
Heydt
C
,
Fassunke
J
, et al
miRNA-221 and miRNA-222 induce apoptosis via the KIT/AKT signalling pathway in gastrointestinal stromal tumours
.
Mol Oncol
2015
;
9
:
1421
33
.
44.
Kazi
JU
,
Kabir
NN
,
Ronnstrand
L
. 
Brain-expressed X-linked (BEX) proteins in human cancers
.
Biochim Biophys Acta
2015
;
1856
:
226
33
.
45.
Boles
NC
,
Hirsch
SE
,
Le
S
,
Corneo
B
,
Najm
F
,
Minotti
AP
, et al
NPTX1 regulates neural lineage specification from human pluripotent stem cells
.
Cell Rep
2014
;
6
:
724
36
.
46.
Rink
L
,
Godwin
AK
. 
Clinical and molecular characteristics of gastrointestinal stromal tumors in the pediatric and young adult population
.
Curr Oncol Rep
2009
;
11
:
314
21
.
47.
Xiao
Q
,
Hu
Y
,
Liu
Y
,
Wang
Z
,
Geng
H
,
Hu
L
, et al
BEX1 promotes imatinib-induced apoptosis by binding to and antagonizing BCL-2
.
PLoS One
2014
;
9
:
e91782
.
48.
Lindblad
O
,
Li
T
,
Su
X
,
Sun
J
,
Kabir
NN
,
Levander
F
, et al
BEX1 acts as a tumor suppressor in acute myeloid leukemia
.
Oncotarget
2015
;
6
:
21395
405
.
49.
Al Rahim
M
,
Thatipamula
S
,
Hossain
MA
. 
Critical role of neuronal pentraxin 1 in mitochondria-mediated hypoxic-ischemic neuronal injury
.
Neurobiol Dis
2013
;
50
:
59
68
.
50.
Cleveland
WS
. 
Robust locally weighted regression and smoothing scatterplots
.
J Am Stat Assoc
1979
;
74
:
829
36
.