Patient-derived models of acquired resistance can identify effective drug combinations for cancer

Abstract

Targeted cancer therapies have produced substantial clinical responses, but most tumors develop resistance to these drugs. Here, we describe a pharmacogenomic platform that facilitates rapid discovery of drug combinations that can overcome resistance. We established cell culture models derived from biopsy samples of lung cancer patients whose disease had progressed while on treatment with epidermal growth factor receptor (EGFR) or anaplastic lymphoma kinase (ALK) tyrosine kinase inhibitors and then subjected these cells to genetic analyses and a pharmacological screen. Multiple effective drug combinations were identified. For example, the combination of ALK and MAPK kinase (MEK) inhibitors was active in an ALK-positive resistant tumor that had developed a MAP2K1 activating mutation, and the combination of EGFR and fibroblast growth factor receptor (FGFR) inhibitors was active in an EGFR mutant resistant cancer with a mutation in FGFR3. Combined ALK and SRC (pp60c-src) inhibition was effective in several ALK-driven patient-derived models, a result not predicted by genetic analysis alone. With further refinements, this strategy could help direct therapeutic choices for individual patients.

Copyright © 2014, American Association for the Advancement of Science.

Figures

Fig. 1. Screen schematic and proof of concept in a patient derived cell line

A. Schematic of the screen workflow. Cell line models of acquired resistance were obtained directly from biopsies of patients after the development of acquired resistance to either EGFR inhibitor or ALK inhibitor in the clinic. Screen drugs were tested as single agent and in the presence of a single fixed concentration of the primary TKI across 10 concentrations encompassing a 10,000-fold dilution range. After 72 hours, cell viability was determined with CellTiter-Glo. B. Phase contrast microscopy of cell line MGH170-1BB, derived from an EGFR mutant lung cancer metastatic lesion with acquired resistance to EGFR inhibitors. Scale bar, 100 μm C. Representation of screen data for the MGH170-1BB cell line. The y-axis represents the fold-change GI50 that resulted with addition of gefitinib (GI50 single agent/GI50 combination). Each bar is the result for an individual drug. The bars are color-coded blue when the percent decrease in AUC from single agent to combination was greater than 10%. Drugs were defined as “hits” when the GI50 shift was > 4 and the AUC change > 10% (see Materials and Methods) D. Left: The MET inhibitor crizotinib was more potent in combination with 1 μM gefitinib (in red) than as single agent (in black). Right: Crizotinib (1 μM) resensitizes the MGH170-1BB cells to gefitinib. Error bars are mean +/− SEM. E. Long-term proliferation assay of MGH170-1BB cells that had been exposed to the indicated drug for 7 days. Cells were stained using crystal violet. F. FISH analysis of a biopsy sample from a metastatic bone lesion obtained after the patient had progressed while on treatment with erlotinib. The scale bar represents 10 μm. The MET gene is represented in red and the EGFR gene in green. G. Quantitative PCR analysis demonstrating overexpression of MET in MGH170-1BB in comparison to normal DNA. DNA from HCC827 GR6, which has MET amplification (13), is presented as a reference. Error bars are mean −/+ SEM. This experiment was repeated 3 times.

Fig. 2. Representation of selected screen hits in independent resistant models

A. The pattern of hits across cell lines harboring the indicated oncogene are shown. Each column represents a cell line, and each row represents a target inhibited by the following drugs: Afatinib (EGFR), AZD0530 (SRC), BYL719 (PI3K), ABT-263 (BCL), Dovitinib or BGJ-398 (FGFR), MK2206 (AKT), OSI906 (IGFR), BI2536 (PLK), AZD6244 (MEK), AZD1152-HQPA (Aurora kinase B), MGCD265 (MET). Each drug is color-coded as indicated. B. The number and profile of all hit drugs for each model. Each box represents a single drug, and the drugs are color-coded by target. The white boxes indicate a hit that corresponds to a drug that is not among the targets listed. For resistant lines derived from a single parental line, only one representative model is presented except in the case of PC9, for which PC9 GR1 and PC9 GR2 are both presented due to the presence of a T790M mutation in PC9 GR2 only.

Fig. 3. MEK activation is a mechanism of resistance to ceritinib

A. Schematic of the derivation of model MGH034-2A. B. Representation of screen data for the MGH034-2A cell line. The y-axis represents the fold-change GI50 that resulted with addition of ceritinib (0.3 μM) (GI50 single agent/GI50 combination). The bars are color-coded blue when the percent decrease in AUC from single agent to combination was greater than 10%. C. Top: Primary screen data of the effect of ceritinib (0.3 μM) on AZD6244 effect in MGH034-2A. Bottom: A dose-response curve to ceritinib is shown in the presence and absence of a fixed concentration of the MEK inhibitor, AZD6244 (1 μM). D. Viability assay of MGH034-2A cells demonstrating the change in cell number after 6 days of treatment with vehicle, ceritinib (300 nM), AZD6244 (1 μM) or the combination of both drugs in comparison to the number of cells at the initiation of drug exposure. E. Western blot analysis of MGH034-2A. Cells were treated with vehicle, ceritinib (0.3 μM), AZD6244 (1 μM) or the combination of both drugs for 24 hours. Lysates were analyzed with antibodies to the indicated proteins. F. Subcutaneous xenografts of MGH034-2A grown in mice were used to determine in vivo efficacy by measuring change in tumor volume when treated as indicated. n=6 mice per group. G. Axial CT images of the chest demonstrate the patient’s disease burden after responding to ceritinib (5.5 weeks on treatment), and at the time of progression on ceritinib (after 9.5 months on treatment). The site of progression in the right lower lobe is indicated by an arrow. H. Table of allele frequencies for MAP2K1 and PIK3CA mutations discovered at autopsy in the patient.

Fig. 4. SRC inhibition restores sensitivity to ALK inhibitor in multiple models

A. Representation of the GI50 of AZD0530 in each screened model as a single-agent or in combination with the primary TKI. Models that were hits are color-coded red. The GI50s of cell lines in which AZD0530 scored as hits are connected by an arrow. The shaded area represents the GI50 values among the top 10% sensitive models for single agent values among all lines screened. B. GI50 of each ALK+ patient-derived model of acquired resistance to either crizotinib or ceritinib. Control cell line models of sensitivity (MGH006-1A, H3122, SU-DHL-1, KARPAS299, NB-1) and acquired resistance (MGH006-1A PFR1, MGH006-1A PFR2, H2228 PFR1, H3122 PFR1, H3122 PFR3, H3122 x4.2) to crizotinib are presented as standards for comparison. Models of sensitivity (H3122, H2228, MGH051-1B, H3122 PFR2, MGH021-2cl4, MGH006-1A, MGH026-1A, MGH039-1A) and acquired resistance (MGH021-5, H3122 LDKR1, H3122 LDKR2, H3122 LDKR2, H3122 LDRK4) to ceritinib are presented as standards for comparison. The GI50 of each model is presented as single-agent (black) and in combination with AZD0530 (1 μM) (red). The mean GI50 of the three experiments is presented. Arrows indicate hits identified by the screen. C. Dose-response curves to crizotinib in model MGH010-1A (crizotinib resistant) are presented. The left panel demonstrates the dose-response of single-agent crizotinib (black) in the absence or presence of AZD0530 (1 μM) (red). The middle panel presents the effect of crizotinib in cells with lentiviral overexpression of either wild-type SRC (black) or kinase-dead SRC (K295R, red). The right panel demonstrates the effect of lentiviral expression of GFP (black), or either of two SRC-targeted shRNAs (blue and red). D. Six-day viability assay of 4 ALK lines: MGH010-1A, MGH025-1A, MGH049-1A, MGH045-1A. Each panel presents percentage change in cell number after treatment with vehicle, ALK inhibitor (crizotinib 1 μM or ceritinib 300 nM), AZD0530 (1 μM) or the combination compared to cell number at the initiation of treatment.

Fig. 5. ALK inhibition and SRC signaling

A. Western blot analysis of MGH025-1A. Cells were treated with vehicle, crizotinib (1 μM), AZD0530 (1 μM) or the combination of both drugs for 24 hours. Lysates were analyzed with antibodies to the indicated proteins. B. Western blot analysis of patient-derived resistant ALK models treated for 24 hours with crizotinib (300 nM) or ceritinib (300 nM). Lysates were prepared and blotted with the indicated antibodies. C. Fold-change in gene expression (Log2) upon treatment with the indicated ALK inhibitor for 24 hours. Top: Upregulated genes annotated with the GO term “extracellular matrix”. Bottom: Downregulated genes annotated with the GO term “cell cycle” (top 30 genes only). D. MGH025-1A subcutaneous xenografts grown in mice were treated as indicated: Vehicle (n=4 mice), crizotinib 25 mg/kg daily (n=6 mice), AZD0530 50 mg/kg daily (n=5 mice), or the combination of both drugs (n=6 mice). Error bars are mean −/+ SEM. Asterisks indicate P<0.0001 by Dunn’s Multiple Comparison Test.