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CYP3A5 mediates basal and acquired therapy resistance in different subtypes of pancreatic ductal adenocarcinoma

Abstract

Although subtypes of pancreatic ductal adenocarcinoma (PDAC) have been described, this malignancy is clinically still treated as a single disease. Here we present patient-derived models representing the full spectrum of previously identified quasi-mesenchymal (QM-PDA), classical and exocrine-like PDAC subtypes, and identify two markers—HNF1A and KRT81—that enable stratification of tumors into different subtypes by using immunohistochemistry. Individuals with tumors of these subtypes showed substantial differences in overall survival, and their tumors differed in drug sensitivity, with the exocrine-like subtype being resistant to tyrosine kinase inhibitors and paclitaxel. Cytochrome P450 3A5 (CYP3A5) metabolizes these compounds in tumors of the exocrine-like subtype, and pharmacological or short hairpin RNA (shRNA)-mediated CYP3A5 inhibition sensitizes tumor cells to these drugs. Whereas hepatocyte nuclear factor 4, alpha (HNF4A) controls basal expression of CYP3A5, drug-induced CYP3A5 upregulation is mediated by the nuclear receptor NR1I2. CYP3A5 also contributes to acquired drug resistance in QM-PDA and classical PDAC, and it is highly expressed in several additional malignancies. These findings designate CYP3A5 as a predictor of therapy response and as a tumor cell–autonomous detoxification mechanism that must be overcome to prevent drug resistance.

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Figure 1: Subtype stratification of PDAC models and patients by using two markers.
Figure 2: Exocrine-like PDAC cells, which express CYP3A5, are resistant to TKIs.
Figure 3: CYP3A5 mediates drug resistance and is regulated by HNF4A and NR1I2 expression in exocrine-like PDAC cells in vitro.
Figure 4: CYP3A5 mediates drug resistance in exocrine-like PDAC cells in vivo.
Figure 5: CYP3A5 contributes to acquired resistance in QM-PDA and classical PDAC cells.
Figure 6: CYP3A5 contributes to drug resistance in other malignancies.

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References

  1. 1

    Hidalgo, M. Pancreatic cancer. N. Engl. J. Med. 362, 1605–1617 (2010).

    Article  CAS  PubMed  Google Scholar 

  2. 2

    Malvezzi, M., Bertuccio, P., Levi, F., La Vecchia, C. & Negri, E. European cancer mortality predictions for the year 2014. Ann. Oncol. 25, 1650–1656 (2014).

    Article  CAS  PubMed  Google Scholar 

  3. 3

    Siegel, R.L., Miller, K.D. & Jemal, A. Cancer statistics, 2015. CA Cancer J. Clin. 65, 5–29 (2015).

    Article  PubMed  Google Scholar 

  4. 4

    Burris, H.A. III et al. Improvements in survival and clinical benefit with gemcitabine as first-line therapy for patients with advanced pancreas cancer: a randomized trial. J. Clin. Oncol. 15, 2403–2413 (1997).

    Article  CAS  PubMed  Google Scholar 

  5. 5

    Conroy, T. et al. FOLFIRINOX versus gemcitabine for metastatic pancreatic cancer. N. Engl. J. Med. 364, 1817–1825 (2011).

    Article  CAS  PubMed  Google Scholar 

  6. 6

    Von Hoff, D.D. et al. Increased survival in pancreatic cancer with nab-paclitaxel plus gemcitabine. N. Engl. J. Med. 369, 1691–1703 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. 7

    Vincent, A., Herman, J., Schulick, R., Hruban, R.H. & Goggins, M. Pancreatic cancer. Lancet 378, 607–620 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  8. 8

    Moore, M.J. et al. Erlotinib plus gemcitabine compared with gemcitabine alone in patients with advanced pancreatic cancer: a phase 3 trial of the National Cancer Institute of Canada clinical trials group. J. Clin. Oncol. 25, 1960–1966 (2007).

    Article  CAS  PubMed  Google Scholar 

  9. 9

    Biankin, A.V. & Maitra, A. Subtyping pancreatic cancer. Cancer Cell 28, 411–413 (2015).

    Article  CAS  PubMed  Google Scholar 

  10. 10

    Kim, S. et al. Identifying molecular subtypes related to clinicopathologic factors in pancreatic cancer. Biomed. Eng. Online 13, S5 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  11. 11

    Collisson, E.A. et al. Subtypes of pancreatic ductal adenocarcinoma and their differing responses to therapy. Nat. Med. 17, 500–503 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. 12

    Guengrich, F.P. in Comprehensive Toxicology 2nd edn. (ed. McQueen, C.A.) 9.43–9.76 (Elsevier Ltd., Oxford, 2010).

  13. 13

    Rochat, B. Role of cytochrome P450 activity in the fate of anticancer agents and in drug resistance: focus on tamoxifen, paclitaxel and imatinib metabolism. Clin. Pharmacokinet. 44, 349–366 (2005).

    Article  CAS  PubMed  Google Scholar 

  14. 14

    Bruno, R.D. & Njar, V.C.O. Targeting cytochrome P450 enzymes: a new approach in anticancer drug development. Bioorg. Med. Chem. 15, 5047–5060 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. 15

    Michael, M. & Doherty, M.M. Drug metabolism by tumors: its nature, relevance and therapeutic implications. Expert Opin. Drug Metab. Toxicol. 3, 783–803 (2007).

    Article  CAS  PubMed  Google Scholar 

  16. 16

    Yachida, S. & Iacobuzio-Donahue, C.A. Evolution and dynamics of pancreatic cancer progression. Oncogene 32, 5253–5260 (2013).

    CAS  PubMed  Google Scholar 

  17. 17

    Biankin, A.V. et al. Pancreatic cancer genomes reveal aberrations in axon-guidance pathway genes. Nature 491, 399–405 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. 18

    Jones, S. et al. Core signaling pathways in human pancreatic cancers revealed by global genomic analyses. Science 321, 1801–1806 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. 19

    Uhlen, M. et al. Toward a knowledge-based Human Protein Atlas. Nat. Biotechnol. 28, 1248–1250 (2010).

    Article  CAS  PubMed  Google Scholar 

  20. 20

    Wolfgang, C.L. et al. Recent progress in pancreatic cancer. CA Cancer J. Clin. 63, 318–348 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  21. 21

    Hruban, R.H., Pitman, M.B. & Klimstra, D.S. Tumors of the Pancreas 6th edn. (American Registry of Pathology, Washington, D.C., 2007).

  22. 22

    Hong, D.S. et al. A phase 1 study of gemcitabine combined with dasatinib in patients with advanced solid tumors. Invest. New Drugs 31, 918–926 (2013).

    Article  CAS  PubMed  Google Scholar 

  23. 23

    George, T.J. Jr., Trevino, J.G. & Liu, C. Src inhibition is still a relevant target in pancreatic cancer. Oncologist 19, 211 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. 24

    Trevino, J.G. et al. Inhibition of SRC expression and activity inhibits tumor progression and metastasis of human pancreatic adenocarcinoma cells in an orthotopic nude mouse model. Am. J. Pathol. 168, 962–972 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. 25

    Ling, J. et al. Metabolism and excretion of erlotinib, a small-molecule inhibitor of epidermal growth factor receptor tyrosine kinase, in healthy male volunteers. Drug Metab. Dispos. 34, 420–426 (2006).

    Article  CAS  PubMed  Google Scholar 

  26. 26

    Christopher, L.J. et al. Metabolism and disposition of dasatinib after oral administration to humans. Drug Metab. Dispos. 36, 1357–1364 (2008).

    Article  CAS  PubMed  Google Scholar 

  27. 27

    Li, J., Zhao, M., He, P., Hidalgo, M. & Baker, S.D. Differential metabolism of gefitinib and erlotinib by human cytochrome P450 enzymes. Clin. Cancer Res. 13, 3731–3737 (2007).

    Article  CAS  PubMed  Google Scholar 

  28. 28

    Wang, L. et al. Identification of the human enzymes involved in the oxidative metabolism of dasatinib: an effective approach for determining metabolite formation kinetics. Drug Metab. Dispos. 36, 1828–1839 (2008).

    Article  CAS  PubMed  Google Scholar 

  29. 29

    Barretina, J. et al. The Cancer Cell Line Encyclopedia enables predictive modeling of anticancer drug sensitivity. Nature 483, 603–607 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. 30

    Ding, X. & Zhang, Q.Y. in Comprehensive Toxicology 2nd edn. (ed. McQueen, C.A.) 4.9–4.29 (Elsevier, Oxford, 2010).

  31. 31

    Jänne, P.A., Gray, N. & Settleman, J. Factors underlying sensitivity of cancers to small-molecule kinase inhibitors. Nat. Rev. Drug Discov. 8, 709–723 (2009).

    Article  CAS  PubMed  Google Scholar 

  32. 32

    Haaz, M.C., Rivory, L., Riché, C., Vernillet, L. & Robert, J. Metabolism of irinotecan (CPT-11) by human hepatic microsomes: participation of cytochrome P450 3A and drug interactions. Cancer Res. 58, 468–472 (1998).

    CAS  PubMed  Google Scholar 

  33. 33

    Sonnichsen, D.S. & Relling, M.V. Clinical pharmacokinetics of paclitaxel. Clin. Pharmacokinet. 27, 256–269 (1994).

    Article  CAS  PubMed  Google Scholar 

  34. 34

    Burk, O. et al. The induction of cytochrome P450 3A5 (CYP3A5) in the human liver and intestine is mediated by the xenobiotic sensors pregnane X receptor (PXR) and constitutively activated receptor (CAR). J. Biol. Chem. 279, 38379–38385 (2004).

    Article  CAS  PubMed  Google Scholar 

  35. 35

    Burk, O. & Wojnowski, L. Cytochrome P450 3A and their regulation. Naunyn Schmiedebergs Arch. Pharmacol. 369, 105–124 (2004).

    Article  CAS  PubMed  Google Scholar 

  36. 36

    Tirona, R.G. et al. The orphan nuclear receptor HNF-4α determines PXR- and CAR-mediated xenobiotic induction of CYP3A4. Nat. Med. 9, 220–224 (2003).

    Article  CAS  PubMed  Google Scholar 

  37. 37

    Tompkins, L.M. & Wallace, A.D. Mechanisms of cytochrome P450 induction. J. Biochem. Mol. Toxicol. 21, 176–181 (2007).

    Article  CAS  PubMed  Google Scholar 

  38. 38

    Yuan, X. et al. Identification of an endogenous ligand bound to a native orphan nuclear receptor. PLoS One 4, e5609 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. 39

    Koutsounas, I., Theocharis, S., Patsouris, E. & Giaginis, C. Pregnane X receptor (PXR) at the crossroads of human metabolism and disease. Curr. Drug Metab. 14, 341–350 (2013).

    Article  CAS  PubMed  Google Scholar 

  40. 40

    Wu, B., Li, S. & Dong, D. 3D structures and ligand specificities of nuclear xenobiotic receptors CAR, PXR and VDR. Drug Discov. Today 18, 574–581 (2013).

    Article  CAS  PubMed  Google Scholar 

  41. 41

    Michael, M. & Doherty, M.M. Tumoral drug metabolism: overview and its implications for cancer therapy. J. Clin. Oncol. 23, 205–229 (2005).

    Article  CAS  PubMed  Google Scholar 

  42. 42

    Pavek, P. & Dvorak, Z. Xenobiotic-induced transcriptional regulation of xenobiotic-metabolizing enzymes of the cytochrome P450 superfamily in human extrahepatic tissues. Curr. Drug Metab. 9, 129–143 (2008).

    Article  CAS  PubMed  Google Scholar 

  43. 43

    Ding, X. & Kaminsky, L.S. Human extrahepatic cytochromes P450: function in xenobiotic metabolism and tissue-selective chemical toxicity in the respiratory and gastrointestinal tracts. Annu. Rev. Pharmacol. Toxicol. 43, 149–173 (2003).

    Article  CAS  PubMed  Google Scholar 

  44. 44

    Downie, D. et al. Profiling cytochrome P450 expression in ovarian cancer: identification of prognostic markers. Clin. Cancer Res. 11, 7369–7375 (2005).

    Article  CAS  PubMed  Google Scholar 

  45. 45

    Hukkanen, J. et al. Induction and regulation of xenobiotic-metabolizing cytochrome P450s in the human A549 lung adenocarcinoma cell line. Am. J. Respir. Cell Mol. Biol. 22, 360–366 (2000).

    Article  CAS  PubMed  Google Scholar 

  46. 46

    Murray, G.I., Patimalla, S., Stewart, K.N., Miller, I.D. & Heys, S.D. Profiling the expression of cytochrome P450 in breast cancer. Histopathology 57, 202–211 (2010).

    Article  PubMed  Google Scholar 

  47. 47

    Bergheim, I. et al. Cytochrome P450 levels are altered in patients with esophageal squamous-cell carcinoma. World J. Gastroenterol. 13, 997–1002 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. 48

    Dhaini, H.R. et al. Cytochrome P450 CYP3A4/5 expression as a biomarker of outcome in osteosarcoma. J. Clin. Oncol. 21, 2481–2485 (2003).

    Article  CAS  PubMed  Google Scholar 

  49. 49

    Gharavi, N. & El-Kadi, A.O.S. Expression of cytochrome P450 in lung tumor. Curr. Drug Metab. 5, 203–210 (2004).

    Article  CAS  PubMed  Google Scholar 

  50. 50

    McFadyen, M.C., Melvin, W.T. & Murray, G.I. Cytochrome P450 CYP1B1 activity in renal cell carcinoma. Br. J. Cancer 91, 966–971 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. 51

    Oyama, T. et al. Expression of cytochrome P450 in tumor tissues and its association with cancer development. Front. Biosci. 9, 1967–1976 (2004).

    Article  CAS  PubMed  Google Scholar 

  52. 52

    Oyama, T. et al. Cytochrome P450 in non-small-cell lung cancer related to exogenous chemical metabolism. Front. Biosci. (Schol. Ed.) 4, 1539–1546 (2012).

    Article  Google Scholar 

  53. 53

    Schmidt, R. et al. CYP3A4, CYP2C9 and CYP2B6 expression and ifosfamide turnover in breast cancer tissue microsomes. Br. J. Cancer 90, 911–916 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. 54

    Sugawara, M. et al. Expressions of cytochrome P450, UDP-glucuronosyltranferase and transporter genes in monolayer carcinoma cells change in subcutaneous tumors grown as xenografts in immunodeficient nude mice. Drug Metab. Dispos. 38, 526–533 (2010).

    Article  CAS  PubMed  Google Scholar 

  55. 55

    Basseville, A. et al. Irinotecan induces steroid and xenobiotic receptor (SXR) signaling to detoxification pathway in colon cancer cells. Mol. Cancer 10, 80 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. 56

    Kuehl, P. et al. Sequence diversity in CYP3A promoters and characterization of the genetic basis of polymorphic CYP3A5 expression. Nat. Genet. 27, 383–391 (2001).

    Article  CAS  PubMed  Google Scholar 

  57. 57

    Westlind-Johnsson, A. et al. Comparative analysis of CYP3A expression in human liver suggests only a minor role for CYP3A5 in drug metabolism. Drug Metab. Dispos. 31, 755–761 (2003).

    Article  CAS  PubMed  Google Scholar 

  58. 58

    Walsky, R.L. et al. Selective mechanism-based inactivation of CYP3A4 by CYP3cide (PF-04981517) and its utility as an in vitro tool for delineating the relative roles of CYP3A4 versus CYP3A5 in the metabolism of drugs. Drug Metab. Dispos. 40, 1686–1697 (2012).

    Article  CAS  PubMed  Google Scholar 

  59. 59

    Vermeulen, L. et al. Single-cell cloning of colon cancer stem cells reveals a multilineage differentiation capacity. Proc. Natl. Acad. Sci. USA 105, 13427–13432 (2008).

    Article  PubMed  Google Scholar 

  60. 60

    Subramanian, A. et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl. Acad. Sci. USA 102, 15545–15550 (2005).

    Article  CAS  Google Scholar 

  61. 61

    Li, B. & Dewey, C.N. RSEM: accurate transcript quantification from RNA-seq data with or without a reference genome. BMC Bioinformatics 12, 323 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. 62

    Leek, J.T., Johnson, W.E., Parker, H.S., Jaffe, A.E. & Storey, J.D. The sva package for removing batch effects and other unwanted variation in high-throughput experiments. Bioinformatics 28, 882–883 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. 63

    Parker, H.S., Corrada Bravo, H. & Leek, J.T. Removing batch effects for prediction problems with frozen surrogate variable analysis. PeerJ 2, e561 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  64. 64

    Huber, W., von Heydebreck, A., Sültmann, H., Poustka, A. & Vingron, M. Variance stabilization applied to microarray data calibration and to the quantification of differential expression. Bioinformatics 18 (suppl. 1), S96–S104 (2002).

    Article  PubMed  Google Scholar 

  65. 65

    Tusher, V.G., Tibshirani, R. & Chu, G. Significance analysis of microarrays applied to the ionizing radiation response. Proc. Natl. Acad. Sci. USA 98, 5116–5121 (2001).

    Article  CAS  Google Scholar 

  66. 66

    Stenzinger, A. et al. High SIRT1 expression is a negative prognosticator in pancreatic ductal adenocarcinoma. BMC Cancer 13, 450 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. 67

    R Development Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2008).

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Acknowledgements

We thank E. Soyka, S. Bauer and A. Hieronymus for excellent technical assistance. We also thank the microarray and the next-generation sequencing (NGS) unit of the Genomics and Proteomics Core Facility, DKFZ, for providing expression profiling, NGS and related services, and all members of the flow cytometry core facility for excellent support. We thank DKFZ-HIPO for technical support and funding through grant no. HIPO-015 (M.S., R.E., N.A.G., O.S., T.H., A.T. and M.R.S.). This work was supported in part by the Dietmar Hopp Foundation and the BioRN Spitzencluster 'Molecular- and Cell-based Medicine' (E.M.N., C.E., E.E., C.K., V.V., W.N., C.R., J.E., F.M.Z., A.T. and M.R.S.), the German Bundesministerium für Bildung und Forschung (BMBF) e:Med program for systems biology (PANC-STRAT consortium, grant no. 01ZX1305; A.T., M.R.S., M.S., R.E., N.A.G., T.H., O.S., A.S., A.M. and W.W.), the Helmholtz Preclinical Comprehensive Cancer Center (E.E., A.T. and M.R.S.) and the DKFZ-NCT program NCT3.0 (A.T., M.R.S., O.E., M.S., R.E., N.A.G., T.H. and O.S.). A.S. was supported by a fellowship from the NCT–Heidelberg School of Oncology (HSO). E.E. is recipient of an EMBO long-term fellowship (ALTF 344-2013). The collection and processing of the specimens via PancoBank was supported by Heidelberger Stiftung Chirurgie (M.W.B.), BMBF (grant no. 01GS08114; M.W.B.) and Biomaterial Bank Heidelberg–BMBH (BMBF grant no. 01EY1101; A.S. and W.W.).

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E.M.N. and C.E. share first authorship, and A.S. and E.E. share second authorship of this paper. E.M.N. and C.E. established, conducted and analyzed the experiments; A.S., A.M. and W.W. performed immunohistological analyses of all of the tissue specimens presented and performed respective data analyses; E.E. did the immunofluorescence staining experiments and analyses on publicly available data sets; B.K., W.N. and C.R. performed RNA expression analyses on the PDAC validation cohort; C.K., V.V., J.E., F.M.Z., O.E., M.S. and R.E. provided technical and experimental support; C.L. and M.K. conducted and analyzed LC-MS/MS experiments; X.J. and A.K.-S. performed activity area calculations; P.N., M.B. and B.V.S. provided PDAC tissue microarray characterization; N.A.G., T.H., O.S., J.W. and M.W.B. provided samples of individuals with PDAC; A.T. and M.R.S. supervised the project; E.N., C.E., A.T. and M.R.S. developed the concept, designed experimental studies, analyzed the data and wrote the manuscript.

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Correspondence to Andreas Trumpp or Martin R Sprick.

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Noll, E., Eisen, C., Stenzinger, A. et al. CYP3A5 mediates basal and acquired therapy resistance in different subtypes of pancreatic ductal adenocarcinoma. Nat Med 22, 278–287 (2016). https://doi.org/10.1038/nm.4038

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