Pancreatic Cancer pp 1203-1217 | Cite as

Differential Therapy Based on Tumor Heterogeneity in Pancreatic Cancer

  • Juan Iovanna
  • Benjamin Bian
  • Martin Bigonnet
  • Nelson Dusetti
Reference work entry

Abstract

A major impediment to the effective treatment of patients with pancreatic ductal adenocarcinoma (PDAC) is its molecular heterogeneity, which is reflected in an equally diverse pattern of clinical outcomes and in response to therapies. An efficient strategy in which PDAC samples were collected by endoscopic ultrasound-guided fine-needle aspiration (EUS-FNA) or surgery and preserved as patient-derived xenografts (PDX) and as a primary culture of epithelial cells was developed. Multiomics analysis, including transcriptomic and pharmacological studies, was performed on these PDX. As expected, significant molecular and phenotypic heterogeneity was observed. However, bioinformatic analysis was able to discriminate between patients with bad or better prognosis. Primary cultures of cells allowed to analyze their relative sensitivity to standard drugs (gemcitabine, 5FU, oxaliplatin, irinotecan active metabolite SN-38, and docetaxel), as well as more original anticancer drugs such as 5-aza-2′-deoxycytidine (5-AZA-dC) or the nicotinamide phosphoribosyltransferase (NAMPT) inhibitor FK866. The establishment of chemograms in vitro allowed to identify individual profiles of drug sensitivity. Remarkably, the response was extremely heterogeneous and patient dependent. It was also found that transcriptome analysis predicts the anticancer drug sensitivity of PDAC cells. Furthermore, an original strategy to identify PDAC dependent on the MYC oncogene and consequently more sensitive to bromodomain and extraterminal inhibitors (BETi) was developed. In conclusion, using this original approach, it was found that multiomics analysis of PDX could predict the clinical outcome of patients, the sensitivity to anticancer drugs, and the pharmacological response to new therapeutic strategies. This opens up a future setting in individualized medicine, aiming to stratify patients in order to select the most appropriate treatments for each group.

Keywords

Individualized Medicine PDX Chemograms Molecular Signatures Drug Sensitivity Tumor Heterogeneity 

References

  1. 1.
    Siegel RL, Miller KD, Jemal A. Cancer statistics, 2016. CA Cancer J Clin. 2016;66(1):7–30.CrossRefGoogle Scholar
  2. 2.
    Kindler HL, Ioka T, Richel DJ, Bennouna J, Letourneau R, Okusaka T, et al. Axitinib plus gemcitabine versus placebo plus gemcitabine in patients with advanced pancreatic adenocarcinoma: a double-blind randomised phase 3 study. Lancet Oncol. 2011;12(3):256–62.CrossRefGoogle Scholar
  3. 3.
    Moore MJ, Goldstein D, Hamm J, Figer A, Hecht JR, Gallinger S, et al. Erlotinib plus gemcitabine compared with gemcitabine alone in patients with advanced pancreatic cancer: a phase III trial of the National Cancer Institute of Canada clinical trials group. Journal Clin Oncol. 2007;25(15):1960–6.CrossRefGoogle Scholar
  4. 4.
    Van Cutsem E, Vervenne WL, Bennouna J, Humblet Y, Gill S, Van Laethem JL, et al. Phase III trial of bevacizumab in combination with gemcitabine and erlotinib in patients with metastatic pancreatic cancer. J Clin Oncol. 2009;27(13):2231–7.CrossRefGoogle Scholar
  5. 5.
    Costello E, Greenhalf W, Neoptolemos JP. New biomarkers and targets in pancreatic cancer and their application to treatment. Nat Rev Gastroenterol Hepatol. 2012;9(8):435–44.CrossRefGoogle Scholar
  6. 6.
    Iovanna J, Mallmann MC, Goncalves A, Turrini O, Dagorn JC. Current knowledge on pancreatic cancer. Front Oncol. 2012;2:6. PubMed Pubmed Central PMCID: 3356035.CrossRefGoogle Scholar
  7. 7.
    Vincent A, Herman J, Schulick R, Hruban RH, Goggins M. Pancreatic cancer. Lancet. 2011;378(9791):607–20. PubMed Pubmed Central PMCID: 3062508.CrossRefGoogle Scholar
  8. 8.
    Conroy T, Desseigne F, Ychou M, Bouche O, Guimbaud R, Becouarn Y, et al. FOLFIRINOX versus gemcitabine for metastatic pancreatic cancer. N Engl J Med. 2011;364(19):1817–25.CrossRefGoogle Scholar
  9. 9.
    Burris HA 3rd, Moore MJ, Andersen J, Green MR, Rothenberg ML, Modiano MR, 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. 1997;15(6):2403–13.CrossRefGoogle Scholar
  10. 10.
    Collisson EA, Sadanandam A, Olson P, Gibb WJ, Truitt M, Gu S, et al. Subtypes of pancreatic ductal adenocarcinoma and their differing responses to therapy. Nat Med. 2011;17(4):500–3. PubMed Pubmed Central PMCID: 3755490.CrossRefGoogle Scholar
  11. 11.
    Noll EM, Eisen C, Stenzinger A, Espinet E, Muckenhuber A, Klein C, et al. CYP3A5 mediates basal and acquired therapy resistance in different subtypes of pancreatic ductal adenocarcinoma. Nat Med. 2016;22(3):278–87. PubMed Pubmed Central PMCID: 4780258.CrossRefGoogle Scholar
  12. 12.
    Moffitt RA, Marayati R, Flate EL, Volmar KE, Loeza SG, Hoadley KA, et al. Virtual microdissection identifies distinct tumor- and stroma-specific subtypes of pancreatic ductal adenocarcinoma. Nat Genet. 2015;47(10):1168–78. PubMed Pubmed Central PMCID: 4912058.CrossRefGoogle Scholar
  13. 13.
    Bailey P, Chang DK, Nones K, Johns AL, Patch AM, Gingras MC, et al. Genomic analyses identify molecular subtypes of pancreatic cancer. Nature. 2016;531(7592):47–52.CrossRefGoogle Scholar
  14. 14.
    Duconseil P, Gilabert M, Gayet O, Loncle C, Moutardier V, Turrini O, et al. Transcriptomic analysis predicts survival and sensitivity to anticancer drugs of patients with a pancreatic adenocarcinoma. Am J Pathol. 2015;185(4):1022–32.CrossRefGoogle Scholar
  15. 15.
    Geer RJ, Brennan MF. Prognostic indicators for survival after resection of pancreatic adenocarcinoma. American journal of surgery. 1993;165(1):68–72. discussion −3. PubMed.CrossRefGoogle Scholar
  16. 16.
    Moon HJ, An JY, Heo JS, Choi SH, Joh JW, Kim YI. Predicting survival after surgical resection for pancreatic ductal adenocarcinoma. Pancreas. 2006;32(1):37–43.CrossRefGoogle Scholar
  17. 17.
    Sohn TA, Yeo CJ, Cameron JL, Koniaris L, Kaushal S, Abrams RA, et al. Resected adenocarcinoma of the pancreas-616 patients: results, outcomes, and prognostic indicators. J Gastrointest Surg. 2000;4(6):567–79.CrossRefGoogle Scholar
  18. 18.
    You DD, Lee HG, Heo JS, Choi SH, Choi DW. Prognostic factors and adjuvant chemoradiation therapy after pancreaticoduodenectomy for pancreatic adenocarcinoma. J Gastroint Surg. 2009;13(9):1699–706.CrossRefGoogle Scholar
  19. 19.
    Wasif N, Ko CY, Farrell J, Wainberg Z, Hines OJ, Reber H, et al. Impact of tumor grade on prognosis in pancreatic cancer: should we include grade in AJCC staging? Ann Surg Oncol. 2010;17(9):2312–20. PubMed Pubmed Central PMCID: 2924500.CrossRefGoogle Scholar
  20. 20.
    Rochefort MM, Ankeny JS, Kadera BE, Donald GW, Isacoff W, Wainberg ZA, et al. Impact of tumor grade on pancreatic cancer prognosis: validation of a novel TNMG staging system. Ann Surg Oncol. 2013;20(13):4322–9.CrossRefGoogle Scholar
  21. 21.
    Penchev VR, Rasheed ZA, Maitra A, Matsui W. Heterogeneity and targeting of pancreatic cancer stem cells. Clin Cancer Res. 2012;18(16):4277–84. PubMed Pubmed Central PMCID: 3422767.CrossRefGoogle Scholar
  22. 22.
    Issa JP. Decitabine. Curr Opin Oncol. 2003;15(6):446–51.CrossRefGoogle Scholar
  23. 23.
    Kantarjian H, Issa JP, Rosenfeld CS, Bennett JM, Albitar M, DiPersio J, et al. Decitabine improves patient outcomes in myelodysplastic syndromes: results of a phase III randomized study. Cancer. 2006;106(8):1794–803.CrossRefGoogle Scholar
  24. 24.
    Blum W, Schwind S, Tarighat SS, Geyer S, Eisfeld AK, Whitman S, et al. Clinical and pharmacodynamic activity of bortezomib and decitabine in acute myeloid leukemia. Blood. 2012;119(25):6025–31. PubMed Pubmed Central PMCID: 3383015.CrossRefGoogle Scholar
  25. 25.
    Cowan LA, Talwar S, Yang AS. Will DNA methylation inhibitors work in solid tumors? A review of the clinical experience with azacitidine and decitabine in solid tumors. Epigenomics. 2010;2(1):71–86.CrossRefGoogle Scholar
  26. 26.
    Ehrlich M. Cancer-linked DNA hypomethylation and its relationship to hypermethylation. Curr Top Microbiol Immunol. 2006;310:251–74.PubMedGoogle Scholar
  27. 27.
    Esteller M. Relevance of DNA methylation in the management of cancer. Lancet Oncol. 2003;4(6):351–8.CrossRefGoogle Scholar
  28. 28.
    Teodoridis JM, Strathdee G, Brown R. Epigenetic silencing mediated by CpG island methylation: potential as a therapeutic target and as a biomarker. Drug Resist Updat. 2004;7(4–5):267–78.CrossRefGoogle Scholar
  29. 29.
    Egger G, Liang G, Aparicio A, Jones PA. Epigenetics in human disease and prospects for epigenetic therapy. Nature. 2004;429(6990):457–63.CrossRefGoogle Scholar
  30. 30.
    Omura N, Goggins M. Epigenetics and epigenetic alterations in pancreatic cancer. Int J Clin Exp Pathol. 2009;2(4):310–26. PubMed Pubmed Central PMCID: 2615589.PubMedGoogle Scholar
  31. 31.
    Gayet O, Loncle C, Duconseil P, Gilabert M, Lopez MB, Moutardier V, et al. A subgroup of pancreatic adenocarcinoma is sensitive to the 5-aza-dC DNA methyltransferase inhibitor. Oncotarget. 2015;6(2):746–54. PubMed Pubmed Central PMCID: 4359252.CrossRefGoogle Scholar
  32. 32.
    Li A, Omura N, Hong SM, Goggins M. Pancreatic cancer DNMT1 expression and sensitivity to DNMT1 inhibitors. Cancer Biol Ther. 2010;9(4):321–9. PubMed Pubmed Central PMCID: 2920347.CrossRefGoogle Scholar
  33. 33.
    Olesen UH, Christensen MK, Bjorkling F, Jaattela M, Jensen PB, Sehested M, et al. Anticancer agent CHS-828 inhibits cellular synthesis of NAD. Biochem Biophys Res Commun. 2008;367(4):799–804.CrossRefGoogle Scholar
  34. 34.
    Bi TQ, Che XM. Nampt/PBEF/visfatin and cancer. Cancer Biol Ther. 2010;10(2):119–25.CrossRefGoogle Scholar
  35. 35.
    Hasmann M, Schemainda I. FK866, a highly specific noncompetitive inhibitor of nicotinamide phosphoribosyltransferase, represents a novel mechanism for induction of tumor cell apoptosis. Cancer Res. 2003;63(21):7436–42.PubMedGoogle Scholar
  36. 36.
    Holen K, Saltz LB, Hollywood E, Burk K, Hanauske AR. The pharmacokinetics, toxicities, and biologic effects of FK866, a nicotinamide adenine dinucleotide biosynthesis inhibitor. Investig New Drugs. 2008;26(1):45–51.CrossRefGoogle Scholar
  37. 37.
    Hovstadius P, Larsson R, Jonsson E, Skov T, Kissmeyer AM, Krasilnikoff K, et al. A phase I study of CHS 828 in patients with solid tumor malignancy. Clin Can Res. 2002;8(9):2843–50.Google Scholar
  38. 38.
    von Heideman A, Berglund A, Larsson R, Nygren P. Safety and efficacy of NAD depleting cancer drugs: results of a phase I clinical trial of CHS 828 and overview of published data. Cancer Chemother Pharmacol. 2010;65(6):1165–72.CrossRefGoogle Scholar
  39. 39.
    Bi TQ, Che XM, Liao XH, Zhang DJ, Long HL, Li HJ, et al. Overexpression of Nampt in gastric cancer and chemopotentiating effects of the Nampt inhibitor FK866 in combination with fluorouracil. Oncol Rep. 2011;26(5):1251–7.PubMedGoogle Scholar
  40. 40.
    Travelli C, Drago V, Maldi E, Kaludercic N, Galli U, Boldorini R, et al. Reciprocal potentiation of the antitumoral activities of FK866, an inhibitor of nicotinamide phosphoribosyltransferase, and etoposide or cisplatin in neuroblastoma cells. J Pharmacol Exp Ther. 2011;338(3):829–40.CrossRefGoogle Scholar
  41. 41.
    Chini CC, Guerrico AM, Nin V, Camacho-Pereira J, Escande C, Barbosa MT, et al. Targeting of NAD metabolism in pancreatic cancer cells: potential novel therapy for pancreatic tumors. Clin Can Res. 2014;20(1):120–30. PubMed Pubmed Central PMCID: 3947324.CrossRefGoogle Scholar
  42. 42.
    Barraud M, Garnier J, Loncle C, Gayet O, Lequeue C, Vasseur S, et al. A pancreatic ductal adenocarcinoma subpopulation is sensitive to FK866, an inhibitor of NAMPT. Oncotarget. 2016;7(33):53783–96. PubMed Pubmed Central PMCID: 5288221.CrossRefGoogle Scholar
  43. 43.
    Dunne RF, Hezel AF. Genetics and biology of pancreatic ductal adenocarcinoma. Hematol Oncol Clin North Am. 2015;29(4):595–608.CrossRefGoogle Scholar
  44. 44.
    Waddell N, Pajic M, Patch AM, Chang DK, Kassahn KS, Bailey P, et al. Whole genomes redefine the mutational landscape of pancreatic cancer. Nature. 2015;518(7540):495–501. PubMed Pubmed Central PMCID: 4523082.CrossRefGoogle Scholar
  45. 45.
    Yachida S, Iacobuzio-Donahue CA. Evolution and dynamics of pancreatic cancer progression. Oncogene. 2013;32(45):5253–60. PubMed Pubmed Central PMCID: 3823715.CrossRefGoogle Scholar
  46. 46.
    Cohen R, Neuzillet C, Tijeras-Raballand A, Faivre S, de Gramont A, Raymond E. Targeting cancer cell metabolism in pancreatic adenocarcinoma. Oncotarget. 2015;6(19):16832–47. PubMed Pubmed Central PMCID: 4627277.CrossRefGoogle Scholar
  47. 47.
    Mancias JD, Kimmelman AC. Targeting autophagy addiction in cancer. Oncotarget. 2011;2(12):1302–6. PubMed Pubmed Central PMCID: 3282086.CrossRefGoogle Scholar
  48. 48.
    Mertz JA, Conery AR, Bryant BM, Sandy P, Balasubramanian S, Mele DA, et al. Targeting MYC dependence in cancer by inhibiting BET bromodomains. Proc Natl Acad Sci USA. 2011;108(40):16669–74. PubMed Pubmed Central PMCID: 3189078.CrossRefGoogle Scholar
  49. 49.
    Dang CV. c-Myc target genes involved in cell growth, apoptosis, and metabolism. Molecular and cellular biology. 1999;19(1):1–11. PubMed Pubmed Central PMCID: 83860.CrossRefGoogle Scholar
  50. 50.
    Dang CV. MYC on the path to cancer. Cell. 2012;149(1):22–35. PubMed Pubmed Central PMCID: 3345192.CrossRefGoogle Scholar
  51. 51.
    Prendergast GC. Mechanisms of apoptosis by c-Myc. Oncogene. 1999;18(19):2967–87.CrossRefGoogle Scholar
  52. 52.
    Schmidt EV. The role of c-myc in cellular growth control. Oncogene. 1999;18(19):2988–96.CrossRefGoogle Scholar
  53. 53.
    Morton JP, Sansom OJ. MYC-y mice: from tumour initiation to therapeutic targeting of endogenous MYC. Mol Oncol. 2013;7(2):248–58.CrossRefGoogle Scholar
  54. 54.
    Lin WC, Rajbhandari N, Liu C, Sakamoto K, Zhang Q, Triplett AA, et al. Dormant cancer cells contribute to residual disease in a model of reversible pancreatic cancer. Cancer Res. 2013;73(6):1821–30. PubMed Pubmed Central PMCID: 3602120.CrossRefGoogle Scholar
  55. 55.
    Walz S, Lorenzin F, Morton J, Wiese KE, von Eyss B, Herold S, et al. Activation and repression by oncogenic MYC shape tumour-specific gene expression profiles. Nature. 2014;511(7510):483–7.CrossRefGoogle Scholar
  56. 56.
    Wirth M, Mahboobi S, Kramer OH, Schneider G. Concepts to target MYC in pancreatic cancer. Mol Cancer Ther. 2016;15(8):1792–8.CrossRefGoogle Scholar
  57. 57.
    Annibali D, Whitfield JR, Favuzzi E, Jauset T, Serrano E, Cuartas I, et al. Myc inhibition is effective against glioma and reveals a role for Myc in proficient mitosis. Nat Commun. 2014;5:4632. PubMed Pubmed Central PMCID: 4143920.CrossRefGoogle Scholar
  58. 58.
    Fletcher S, Prochownik EV. Small-molecule inhibitors of the Myc oncoprotein. Biochim Biophys Acta. 2015;1849(5):525–43. PubMed Pubmed Central PMCID: 4169356.CrossRefGoogle Scholar
  59. 59.
    McKeown MR, Bradner JE. Therapeutic strategies to inhibit MYC. Cold Spring Harb Perspect Med. 2014;01:4(10). PubMed Pubmed Central PMCID: 4200208.Google Scholar
  60. 60.
    Soucek L, Whitfield J, Martins CP, Finch AJ, Murphy DJ, Sodir NM, et al. Modelling Myc inhibition as a cancer therapy. Nature. 2008;455(7213):679–83. PubMed Pubmed Central PMCID: 4485609.CrossRefGoogle Scholar
  61. 61.
    Delmore JE, Issa GC, Lemieux ME, Rahl PB, Shi J, Jacobs HM, et al. BET bromodomain inhibition as a therapeutic strategy to target c-Myc. Cell. 2011;146(6):904–17. PubMed Pubmed Central PMCID: 3187920.CrossRefGoogle Scholar
  62. 62.
    Kandela I, Jin HY, Owen K, Reproducibility Project: Cancer B. Registered report: BET bromodomain inhibition as a therapeutic strategy to target c-Myc. eLife. 2015;4:e07072. PubMed Pubmed Central PMCID: 4480271.PubMedPubMedCentralGoogle Scholar
  63. 63.
    Mazur PK, Herner A, Mello SS, Wirth M, Hausmann S, Sanchez-Rivera FJ, et al. Combined inhibition of BET family proteins and histone deacetylases as a potential epigenetics-based therapy for pancreatic ductal adenocarcinoma. Nat Med. 2015;21(10):1163–71. PubMed Pubmed Central PMCID: 4959788.CrossRefGoogle Scholar
  64. 64.
    Knoechel B, Roderick JE, Williamson KE, Zhu J, Lohr JG, Cotton MJ, et al. An epigenetic mechanism of resistance to targeted therapy in T cell acute lymphoblastic leukemia. Nat Genet. 2014;46(4):364–70. PubMed Pubmed Central PMCID: 4086945.CrossRefGoogle Scholar
  65. 65.
    Roderick JE, Tesell J, Shultz LD, Brehm MA, Greiner DL, Harris MH, et al. C-Myc inhibition prevents leukemia initiation in mice and impairs the growth of relapsed and induction failure pediatric T-ALL cells. Blood. 2014;123(7):1040–50. PubMed Pubmed Central PMCID: 3924926.CrossRefGoogle Scholar
  66. 66.
    Trabucco SE, Gerstein RM, Evens AM, Bradner JE, Shultz LD, Greiner DL, et al. Inhibition of bromodomain proteins for the treatment of human diffuse large B-cell lymphoma. Clin Can Res. 2015;21(1):113–22. PubMed PMID: 25009295. Pubmed Central PMCID: 4286476.CrossRefGoogle Scholar
  67. 67.
    Bian B, Bigonnet M, Gayet O, Loncle C, Maignan A, Gilabert M, et al. Gene expression profiling of patient-derived pancreatic cancer xenografts predicts sensitivity to the BET bromodomain inhibitor JQ1: implications for individualized medicine efforts. EMBO Mol Med. 2017;9:482–97. PubMed PMID: 28275007.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Juan Iovanna
    • 1
  • Benjamin Bian
    • 1
  • Martin Bigonnet
    • 1
  • Nelson Dusetti
    • 1
  1. 1.Centre de Recherche en Cancérologie de Marseille (CRCM), INSERM U1068, CNRS UMR 7258Aix-Marseille Université and Institut Paoli-Calmettes, Parc Scientifique et Technologique de LuminyMarseilleFrance

Personalised recommendations