Abstract

Pancreatic ductal adenocarcinoma (PDAC) is characterized by KRAS- and autophagy-dependent tumorigenic growth, but the role of KRAS in supporting autophagy has not been established. We show that, to our surprise, suppression of KRAS increased autophagic flux, as did pharmacological inhibition of its effector ERK MAPK. Furthermore, we demonstrate that either KRAS suppression or ERK inhibition decreased both glycolytic and mitochondrial functions. We speculated that ERK inhibition might thus enhance PDAC dependence on autophagy, in part by impairing other KRAS- or ERK-driven metabolic processes. Accordingly, we found that the autophagy inhibitor chloroquine and genetic or pharmacologic inhibition of specific autophagy regulators synergistically enhanced the ability of ERK inhibitors to mediate antitumor activity in KRAS-driven PDAC. We conclude that combinations of pharmacologic inhibitors that concurrently block both ERK MAPK and autophagic processes that are upregulated in response to ERK inhibition may be effective treatments for PDAC.

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Code availability

All unique code generated to analyze RPPA data will be deposited into the following github: https://github.com/derlab/Bryant_Nature_2018. The code for generating heatmaps representing BLISS scores has been deposited into the following github: https://github.com/SamuelDGeorge/R_Utilities.

Data Availability

Binary sequence alignment/map (BAM) files of RNA-seq data from KRAS knockdown and ERK inhibitor treatment studies are available from the European Bioinformatics Institute European Nucleotide Archive database (http://www.ebi.ac.uk/ena/) with accession numbers PRJEB25797 and PRJEB25806, respectively. For the KRAS knockdown study, the sample accession numbers are ERS2363485ERS2363504. For the ERK inhibitor treatment study, the sample accession numbers are ERS2367000ERS2367034. All other data sets generated for the current study are available from the corresponding author upon request.

Additional information

Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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Acknowledgements

We thank A. Maitra (MD Anderson Cancer Center) for PDAC cell lines, D. Tuveson (Cold Spring Harbor Laboratory) for patient-derived organoids, and C. Kinsey and M. McMahon (Huntsman Cancer Center) for helpful discussions and communication of data before publication. K.L.B. is thankful to B. Elzer Jr. for continued inspiration. Support was provided by grants from the National Cancer Institute (NCI) (R01CA42978, R01CA175747, U01CA199235, P50CA196510, P01CA203657 and R35CA232113), the Department of Defense (W81XWH-15-1-0611), the Lustgarten Foundation (388222) and the Pancreatic Cancer Action Network/American Association for Cancer Research (AACR) (15-90-25-DER) (C.J.D. and A.D.C.). K.L.B. was supported by NCI T32CA009156 and a grant from the Pancreatic Cancer Action Network/AACR (15-70-25-BRYA). C.A.S. was supported by NCI T32CA009156 and F32CA232529. J.E.K. was supported by NCI T32CA009156 and F32 CA239328. A.M.W. was supported by American Cancer Society fellowship PF-18-061. B.P. was supported by the Deutsche Forschungsgemeinschaft (DFG PA 3051/1-1). G.A.H. was supported by NCI T32CA009156 and F32CA200313. T.K.H. was supported by NCI T32CA071341 and NCI F3180693. J.N.D. was supported by NCI T32CA071341. P.K.S. was supported by NCI grants R01 CA163649, R01 CA210439, R01 CA216853, and P30CA036727. A.C.K. was supported by NCI grants R01CA157490, R01CA188048 and P01CA117969, American Cancer Society Research Scholar Grant RSG-13-298-01-TBG, National Institutes of Health grant R01GM095567 and a grant from the Lustgarten Foundation. The Microscopy Services Laboratory, the UNC Flow Cytometry Core Facility and the Lenti-shRNA Core Facility (UNC) are supported in part by P30 CA016086 Cancer Center Core Support grant to the UNC Lineberger Comprehensive Cancer Center. Transmission electron microscopy was conducted in the High-Resolution Electron Microscopy Facility of the MD Anderson Cancer Center (supported by NIH P30CA016672).

Author information

Affiliations

  1. Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

    • Kirsten L. Bryant
    • , Clint A. Stalnecker
    • , Daniel Zeitouni
    • , Jennifer E. Klomp
    • , Andrew M. Waters
    • , Samuel D. George
    • , Garima Tomar
    • , Björn Papke
    • , G. Aaron Hobbs
    • , Adrienne D. Cox
    •  & Channing J. Der
  2. Cancer and Cell Biology Division, Translational Genomics Research Institute, Phoenix, AZ, USA

    • Sen Peng
  3. Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

    • Andrey P. Tikunov
    •  & Jeffrey M. Macdonald
  4. Eppley Institute for Cancer Research, University of Nebraska Medical Center, Omaha, NE, USA

    • Venugopal Gunda
    • , Gennifer D. Goode
    • , Nina V. Chaika
    •  & Pankaj K. Singh
  5. Center for Applied Proteomics and Molecular Medicine, George Mason University, Fairfax, VA, USA

    • Mariaelena Pierobon
    •  & Emanuel F. Petricoin III
  6. Department of Molecular and Cellular Oncology, Division of Basic Science Research, The University of Texas MD Anderson Cancer Center, Houston, TX, USA

    • Liang Yan
    •  & Haoqiang Ying
  7. Curriculum in Genetics and Molecular Biology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

    • Tikvah K. Hayes
    • , J. Nathaniel Diehl
    •  & Channing J. Der
  8. Sarah W. Stedman Nutrition and Metabolism Center & Duke Molecular Physiology Institute, Department of Medicine, Duke University, Durham, NC, USA

    • Yingxue Wang
    •  & Guo-Fang Zhang
  9. Center for Personalized Medicine, Roswell Park Cancer Center, Buffalo, NY, USA

    • Agnieszka K. Witkiewicz
  10. Department of Molecular and Cell Biology, Roswell Park Cancer Center, Buffalo, NY, USA

    • Erik S. Knudsen
  11. Department of Cancer Biology, Mayo Clinic, Phoenix, AZ, USA

    • Nhan L. Tran
  12. Department of Molecular and Integrative Physiology; Department of Internal Medicine, Division of Gastroenterology and University of Michigan Comprehensive Cancer Center, Ann Arbor, MI, USA

    • Costas A. Lyssiotis
  13. Perlmutter Cancer Center, NYU Langone Medical Center, New York City, NY, USA

    • Alec C. Kimmelman
  14. Department of Radiation Oncology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

    • Adrienne D. Cox
  15. Department of Pharmacology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

    • Adrienne D. Cox
    •  & Channing J. Der

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Contributions

K.L.B. and C.J.D. designed the study; A.C.K. and C.J.D. provided resources and critical input; K.L.B., A.C.K. and C.J.D. worked on methodology; K.L.B., S.P., A.P.T. and V.G. did formal analyses; K.L.B., C.A.S., J.E.K., D.Z., S.P., A.P.T., M.P., A.M.W., L.Y., T.K.H., B.P., V.G., G.T., J.N.D., S.D.G, N.V.C., G.D.G., G.A.H., C.A.L., Y.W. and A.K.W. did investigation; H.Y. and C.J.D. provided resources; K.L.B. and C.J.D. wrote the original draft; K.L.B., C.A.S., P.K.S., C.A.L., H.Y., A.D.C., A.C.K. and C.J.D. wrote, reviewed and edited the manuscript; K.L.B. and C.J.D. worked on visualization; C.J.D., E.S.K., P.K.S., E.F.P.III., J.M.M., N.L.T., G.-F.Z. and H.Y. supervised the project; C.J.D. administered the project.

Competing interests

C.J.D. is on the Scientific Advisory Board of Mirati Therapeutics. A.C.K. has financial interests in Vescor Therapeutics, LLC. A.C.K. is an inventor on patents pertaining to KRAS-regulated metabolic pathways, redox control pathways in pancreatic cancer, targeting GOT1 as a therapeutic approach, and the autophagic control of iron metabolism. A.C.K. is on the Scientific Advisory Board of Cornerstone/Rafael Pharmaceuticals.

Corresponding author

Correspondence to Channing J. Der.

Extended data

  1. Extended Data Fig. 1 Genetic suppression of mutant KRAS increases autophagic flux in PDAC cell lines.

    a, Signaling diagram displaying the multiple ways the KRAS ERK MAPK and autophagy pathways were perturbed in this study, as well as the specific components in autophagic signaling that were inhibited and monitored. Red text denotes phosphorylation sites that were assayed, and genetic and pharmacologic inhibitors that were used. b, A panel of human PDAC lines were transduced with a lentiviral vector to stably express EGFP-LC3B and transiently transfected with siRNA targeting KRAS (KRAS) or a mismatch (MM) control oligo (72 h) and treated with chloroquine (12 h) to assess flux. Quantification of EGFP+ punctae area normalized to cell area (autophagic index). Mean autophagic index is plotted, with each individual data point representing one field containing at least ten analyzed cells. Data are representative of two biological replicates for Pa02C and PANC-1 cells, and one biological replicate for Panc10.05, HPAC, Pa14C and Pa04C cells. P values shown are from unpaired, two-sided t-test; error bars represent s.e.m. c, Representative images of EGFP-LC3B expressing cells described and quantified in b. Scale bar, 20 μm.

  2. Extended Data Fig. 2 Pharmacological inhibition of ERK1/ERK2 increases autophagic flux in PDAC cell lines.

    a, PDAC lines were transduced with a lentiviral vector to stably express EGFP-LC3B and treated with DMSO or SCH772984 (ERKi, 1 μM) for 24 h, and chloroquine was added (12 h) to assess flux. Mean autophagic index is plotted, with each individual data point representing one field containing at least ten analyzed cells. Data are representative of two independent experiments for HPAC and PANC-1 cells, and one independent experiment for Pa02C, Pa04C, Pa16C and HPAF-II cells. P values are from unpaired t-test; error bars denote s.e.m. b, Representative images of EGFP-LC3B-expressing cells described and quantified in a. Scale bar, 20 μm. c, PDAC cells were treated with SCH772984 (concentrations in µM shown) for 24 h, RNA was extracted and BECN1 and PRKAA1 gene expression was measured. mRNA levels were normalized to ACTB mRNA. Relative expression quantified via the double delta Ct method is plotted. Data are from one independent experiment; error bars represent s.d. of three technical replicates. d, PDAC cell lines were treated with SCH772984 (1 µM, ERKi) for a time course of 1, 4, 12 and 24 h. Shown are immunoblots to determine levels of phosphorylated Beclin-1 (pBeclin-1), total Beclin-1, phosphorylated ERK (pERK), total ERK and vinculin, and are representative of two independent experiments.

  3. Extended Data Fig. 3 ERK inhibition influences the transcription and activation of upstream mediators of autophagic signaling.

    a, Mean comparisons of RPPA data for markers of ERK activity. All 12 cell lines were averaged based on treatment condition and treated as biological replicates. P values are from two-sided, unpaired t-test (RSK-3) or Wilcoxon test (all other proteins) comparing the mean of cells treated with SCH772984 (ERKi, 1 μM, 24 h) to untreated vehicle control (DMSO); error bars denote s.e.m. b, Mean comparisons of RPPA data for apoptotic markers. Means were calculated as described in a; P values are from Wilcoxon test; error bars denote s.e.m. c, Signaling pathway correlation analysis of RPPA data after treatment with vehicle (DMSO) or SCH772984 (1 μM, 24 h). Spearman’s correlation coefficients among 14 signaling proteins were used to create the heatmap. All 12 cell lines were averaged based on treatment condition and treated as biological replicates. Unsupervised hierarchical clustering analysis was performed on correlation coefficients. Red color represents positive correlation, gray represents no correlation and blue represents negative correlation (***P < 0.0005, **P < 0.005, *P < 0.05 from two-sided, unpaired t-test). d, Normalized mean-peak intensities for IMP, AMP and hypoxanthine identified from triplicate LC–MS/MS experiments. The mean metabolite concentrations from SCH772984-treated (ERKi, 1 μM) samples are normalized to DMSO controls; P values are from two-sided, unpaired t-test; error bars denote s.e.m. of mean peak intensity across three biological replicates. e, PDAC cells were treated with SCH772984 (concentrations in µM shown) for 24 h and RNA was extracted to measure GABARAPL1, WIPI1, SQSTM1 and MYC (control for ERK inhibition) gene expression. mRNA levels were normalized to ACTB mRNA. Relative expression quantified via the double delta Ct method is plotted. Data are from one independent experiment; error bars represent s.d. of three technical replicates.

  4. Extended Data Fig. 4 Genetic silencing of KRAS and ERK inhibition reduces glycolytic flux in PDAC.

    a, Normalized mean-peak intensities for indicated glycolytic metabolites identified from triplicate LC–MS/MS experiments. The mean metabolite concentrations from SCH772984-treated (ERKi, 1 μM) samples are normalized to DMSO controls and plotted for the seven PDAC lines assayed; P values are from two-sided, unpaired t-test; error bars denote s.e.m. Mean of three independent experiments is plotted. b, PDAC cells stably expressing EGFP-mCherry-LC3B were treated with SCH772984 (ERKi, 1 µM, 16 h) or cultured in medium containing dialyzed FBS and no glucose (16 h). Mean autophagic index is plotted, with each individual data point representing one field containing at least ten analyzed cells. Data for all cell lines are representative of two biological replicates; P values are from two-sided, unpaired t-test; error bars denote s.e.m.

  5. Extended Data Fig. 5 Genetic silencing of KRAS and ERK inhibition alters mitochondrial dynamics in PDAC.

    a, PDAC cells were transduced with the mitophagy probe COX8-mCherry-EGFP and treated with DMSO or SCH772984 (ERKi, 1 µM, 24 h). To assess mitophagy, the proportion of mCherry-only vesicles was quantified in relation to the total area of mitochondria (that is, EGFP+ and mCherry+). This proportion is represented as percentage mitophagy, with each individual data point representing one field containing at least ten analyzed cells; P values are from two-sided, unpaired t-test; error bars denote s.e.m. b, Representative images of HPAC and Pa14C cell lines expressing COX8-EGFP-mCherry quantified in l. Scale bar, 5 μm. c, Immunoblot analysis of PDAC cells treated with DMSO or SCH772984 (ERKi, 1 μM, 24 h) to determine the expression levels of PINK1, VDAC, phosphorylated ERK (pERK), total ERK and vinculin, representative of three independent experiments. d, PDAC cells were transiently transfected with siRNA constructs targeting KRAS (KRAS 1 and KRAS 2) or a mismatch (MM) control construct (72 h). Shown are representative images of mitochondrial morphologies after KRAS knockdown. Green, Anti-TOMM20; blue, DAPI. Scale bar, 20 μm. e, Quantification of mitochondrial morphologies observed in cells shown in d. Some 50 cells per condition per repetition were blindly scored and data are the mean of four independent experiments; error bars denote s.e.m.

  6. Extended Data Fig. 6 Genetic silencing of KRAS decreases oxygen consumption in PDAC.

    a, iKRAS 192 cells, derived from the doxycycline (Dox)-inducible iKRAS mouse model, were cultured without doxycycline (24 h) to turn off Kras G12D expression. TMRE (200 nM) was added to the medium for 20 min and staining was analyzed by FACS. Median TMRE signal normalized to doxycycline ON is plotted and is the mean of six independent experiments; P values are from two-sided, unpaired t-test; error bars denote s.e.m. b, OCR response after doxycycline withdrawal (24 h) in iKRAS 192 cells. Mean oxygen consumption is plotted and is the mean of six independent experiments; P values are from two-sided, unpaired t-test comparing –Dox to +Dox, which was normalized to 1 for each measurement; error bars denote s.e.m. c, PDAC cell lines were transiently transfected with two siRNA constructs targeting KRAS (KRAS 1 or KRAS 2) or a mismatched control (MM). OCR response of PDAC cells after knockdown (60 h). Data are the mean of three independent experiments for each line, P values are from two-sided, unpaired t-test, comparing KRAS KD to MM, which was normalized to 100 for each measurement; error bars denote s.e.m.

  7. Extended Data Fig. 7 ERK and MEK inhibition synergizes with the inhibition of autophagy to reduce proliferation in human PDAC cells.

    a, A panel of PDAC cell lines (indicated lines shown as representative) were treated with a range of BVD-523 concentrations (BVD, 0.0195–10 µM) and a constant concentration of chloroquine (CQ, 6.25 μM) for 72 h and proliferation was monitored by the addition of MTT (3 h) at end of experiment. Normalized absorbance at 590 nm, comparing treatment conditions to BVD-only DMSO control, which was normalized to 100, is plotted and error bars denote s.d. of three technical replicates. Curves are representative of four independent experiments. b, PDAC cells (indicated) were treated with a range of binimetinib concentrations (0.005–2.5 µM) and indicated constant concentrations of chloroquine, and proliferation was quantified via live cell counting after 5 d of treatment. Shown are dose response curves and heatmaps representing BLISS independence scores. Plots are representative of three independent experiments. c, CI values for a panel of indicated PDAC cell lines treated with BVD-523 were calculated using Compusyn. d, A panel of PDAC cell lines were treated with a range of SCH772984 concentrations (0.0195–10 µM) and a constant concentration of chloroquine (6.25 μM) for 72 h, and proliferation was monitored by live cell counting. CI values for a panel of indicated PDAC cell lines were calculated using Compusyn.

  8. Extended Data Fig. 8 ERK inhibition synergizes with the inhibition of autophagy to reduce proliferation in subject-derived PDAC organoid models.

    a, Representative images of organoids from experiment described in Fig. 5e,f. Scale bar, 100 μm. Images are representative of five independent experiments. b, Quantification of organoid viability in representative wells shown in a, representative of five independent experiments. c, hT2 subject–derived organoids were grown for 10 d in the presence of indicated concentrations of chloroquine (CQ) and SCH772984 (ERKi). Growth curves shown are representative of five independent experiments. d, BLISS independence scores from experiment described in c. e, Representative images of organoids from d; scale bar, 100 μm. Images are representative of five independent experiments. f, Quantification of organoid viability in representative wells shown in e, representative of five independent experiments.

  9. Extended Data Fig. 9 ERK inhibition synergizes with the inhibition of autophagy to reduce tumor growth in PDAC PDX mouse models.

    a, Kaplan-Meier survival curves for tumor-bearing NSG mice described in Fig. 5g. b, Relative mouse weights throughout the course of the experiment described in Fig. 5g. Plotted is the mean percentage change in weight, normalized to weight at day 0 of treatment. c, Immunocompromised (NSG) mice with implanted KRAS-mutant PDX tumors AZ97 were treated with SCH772984 (ERKi) and hydroxychloroquine (HCQ) alone or in combination for the indicated days. Mean tumor volume normalized to tumor volume at day 0 of treatment is plotted over time; error bars denote s.e.m. The control and single-agent data are the mean of four independent tumors and the combination is the mean of five independent tumors. d, Kaplan-Meier survival curves for tumor-bearing NSG mice described in c. e, Images of representative tumors from AZ1013 PDAC PDX treatment groups. Images of control and ERKi-treated tumors are reproduced from Vaseva et al60.

  10. Extended Data Fig. 10 Inhibition of upstream regulators of autophagy reduces PDAC proliferation and synergizes with ERK inhibition.

    a, Additional PDAC cell lines (Pa14C and PANC-1) were treated with a two-fold dilution range (beginning at 50 µM) of the indicated autophagy inhibitors. Proliferation was assessed using live cell labeling with calcein AM. b, Additional PDAC cell lines were treated with a range of SCH772984 concentrations (ERKi, 0.0195–10 µM) and a constant concentration of each autophagy inhibitor: SBI-0206965 (SBI, 2 μM), MRT68921 (MRT, 500 nM) and Spautin-1 (SP-1, 1.25 μM). Proliferation was assessed by live cell counting. Normalized mean cell number, comparing treatment conditions to SCH (ERKi)-only DMSO control, which was normalized to 100, is plotted and error bars denote s.d. of three technical replicates. Curves are representative of three independent experiments. c, CI values for Spautin-1 + SCH772984 combination were calculated from representative data displayed in Fig. 6f for multiple cell lines. d, MIA PaCa-2 cells were treated with ARS-1620 (RASi, 3 µM), SBI-0206965 (SBI, 2 µM) or MRT68921 (MRT, 1 µM) alone or in combination (5 d). Apoptosis was monitored using FACS analysis of Annexin-V/propidium iodide-labeled cells. Percentage apoptotic cells (normalized to vehicle (DMSO) control) is plotted. Data are representative of two biological replicates.

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    Supplementary Figures 1–5, Supplementary Discussion, and Supplementary Tables 1–4

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https://doi.org/10.1038/s41591-019-0368-8

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