Advertisement

MALDI Mass Spectrometry Imaging for Evaluation of Therapeutics in Colorectal Tumor Organoids

  • Xin Liu
  • Colin Flinders
  • Shannon M. Mumenthaler
  • Amanda B. Hummon
Research Article

Abstract

Patient-derived colorectal tumor organoids (CTOs) closely recapitulate the complex morphological, phenotypic, and genetic features observed in in vivo tumors. Therefore, evaluation of drug distribution and metabolism in this model system can provide valuable information to predict the clinical outcome of a therapeutic response in individual patients. In this report, we applied matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) to examine the spatial distribution of the drug irinotecan and its metabolites in CTOs from two patients. Irinotecan is a prodrug and is often prescribed as part of therapeutic regimes for patients with advanced colorectal cancer. Irinotecan shows a time-dependent and concentration-dependent permeability and metabolism in the CTOs. More interestingly, the active metabolite SN-38 does not co-localize well with the parent drug irinotecan and the inactive metabolite SN-38G. The phenotypic effect of irinotecan metabolism was also confirmed by a viability study showing significantly reduced proliferation in the drug treated CTOs. MALDI-MSI can be used to investigate various pharmaceutical compounds in CTOs derived from different patients. By analyzing multiple CTOs from a patient, this method could be used to predict patient-specific drug responses and help to improve personalized dosing regimens.

Graphical Abstract

Keywords

MALDI-MSI Colorectal tumor organoids Irinotecan 

Notes

Acknowledgments

The authors thank the Mass Spectrometry and Proteomics Facility at the University of Notre Dame. This research was funded through a generous donation from Michael A. Patterson and family. A.B.H. was supported by the National Institutes of Health (R01GM110406), and the National Science Foundation (CAREER Award, CHE-1351595). The UltrafleXtreme instrument (MALDI-TOF-TOF) was acquired through National Science Foundation award #1625944. The authors express their deepest gratitude to the Stephenson family: Emmet, Toni, and Tessa for the establishment of the Stephenson Family Personalized Medicine Center, which supports the generation and characterization of the patient-derived organoid biorepository.

They thank Erin Spiller for her efforts in establishing the patient-derived organoid model system in the authors’ laboratory.

Supplementary material

13361_2017_1851_MOESM1_ESM.docx (1.1 mb)
ESM 1 (DOCX 1160 kb)

References

  1. 1.
    Grantab, R., Sivananthan, S., Tannock, I.F.: The penetration of anticancer drugs through tumor tissue as a function of cellular adhesion and packing density of tumor cells. Cancer Res. 66(2), 1033–1040 (2006)Google Scholar
  2. 2.
    Kyle, A.H., Huxham, L.A., Yeoman, D.M., Minchinton, A.I.: Limited tissue penetration of taxanes: a mechanism for resistance in solid tumors. Clin. Cancer Res. 13(9), 2804–2811 (2007)Google Scholar
  3. 3.
    Kyle, A.H., Huxham, L.A., Chiam, A.S.J., Sim, D.H., Minchinton, A.I.: Direct assessment of drug penetration into tissue using a novel application of three-dimensional cell culture. Cancer Res. 64(17), 6304–6309 (2004)Google Scholar
  4. 4.
    Liu, X., Hummon, A.B.: Chemical Imaging of platinum-based drugs and their metabolites. Sci. Rep. 6,1–10 (2016)Google Scholar
  5. 5.
    Liu, X., Weaver, E.M., Hummon, A.B.: Evaluation of therapeutics in three-dimensional cell culture systems by MALDI imaging mass spectrometry. Anal. Chem. 85(13), 6295–6302 (2013)Google Scholar
  6. 6.
    Lukowski, J.K., Weaver, E.M., Hummon, A.B.: Analyzing liposomal drug delivery systems in three-dimensional cell culture models using MALDI imaging mass spectrometry. Anal. Chem. 89(16), 8453–8458 (2017)Google Scholar
  7. 7.
    Weaver, E.M., Hummon, A.B., Keithley, R.B.: Chemometric analysis of MALDI mass spectrometric images of three-dimensional cell culture systems. Anal. Methods. 7(17), 7208–7219 (2015)Google Scholar
  8. 8.
    LaBonia, G.J., Lockwood, S.Y., Heller, A.A., Spence, D.M., Hummon, A.B.: Drug penetration and metabolism in 3D cell cultures treated in a 3D printed fluidic device: assessment of irinotecan via MALDI imaging mass spectrometry. Proteomics. 16(11-12), 1814–1821 (2016)Google Scholar
  9. 9.
    Feist, P.E., Sidoli, S., Liu, X., Schroll, M.M., Rahmy, S., Fujiwara, R., Garcia, B.A., Hummon, A.B.: Multicellular tumor spheroids combined with mass spectrometric histone analysis to evaluate epigenetic drugs. Anal. Chem. 89(5), 2773–2781 (2017)Google Scholar
  10. 10.
    Ahlf, D.R., Masyuko, R.N., Hummon, A.B., Bohn, P.W.: Correlated mass spectrometry imaging and confocal Raman microscopy for studies of three-dimensional cell culture sections. Analyst. 139(18), 4578–4585 (2014)Google Scholar
  11. 11.
    Ahlf Wheatcraft, D.R., Liu, X., Hummon, A.B.: Sample preparation strategies for mass spectrometry imaging of 3D cell culture models. J. Vis. Exp. 94, e52313, (2014)Google Scholar
  12. 12.
    Iyer, L., King, C.D., Whitington, P.F., Green, M.D., Roy, S.K., Tephly, T.R., Coffman, B.L., Ratain, M.J.: Genetic predisposition to the metabolism of irinotecan (CPT-11). Role of uridine diphosphate glucuronosyltransferase isoform 1A1 in the glucuronidation of its active metabolite (SN-38) in human liver microsomes. J. Clin. Invest. 101(4), 847–854 (1998)Google Scholar
  13. 13.
    Däster, S., Amatruda, N., Calabrese, D., Ivanek, R., Turrini, E., Droeser, R.A., Zajac, P., Fimognari, C., Spagnoli, G.C., Iezzi, G., Mele, V.: Induction of hypoxia and necrosis in multicellular tumor spheroids is associated with resistance to chemotherapy treatment. Oncotarget. 8(1), 1725–1736 (2017)Google Scholar
  14. 14.
    Senkowski, W., Zhang, X., Olofsson, M.H., Isacson, R., Höglund, U., Gustafsson, M., Nygren, P., Linder, S., Larsson, R., Fryknäs, M.: Three-dimensional cell culture-based screening identifies the anthelmintic drug nitazoxanide as a candidate for treatment of colorectal cancer. Mol. Cancer Ther. 14(6), 1504–1516 (2015)Google Scholar
  15. 15.
    Liang, X., Xu, X., Wang, F., Chen, X., Li, N., Wang, C., He, J.: E-cadherin knockdown increases β-catenin reducing colorectal cancer chemosensitivity only in three-dimensional cultures. Int. J. Oncol. 47(4), 1517–1527 (2015)Google Scholar
  16. 16.
    Sato, T., Stange, D.E., Ferrante, M., Vries, R.G., Van Es, J.H., Van Den Brink, S., Van Houdt, W.J., Pronk, A., Van Gorp, J., Siersema, P.D., Clevers, H.: Long-term expansion of epithelial organoids from human colon, adenoma, adenocarcinoma, and Barrett’s epithelium. Gastroenterology. 141(5), 1762–1772 (2011)Google Scholar
  17. 17.
    Rodríguez-Colman, M.J., Schewe, M., Meerlo, M., Stigter, E., Gerrits, J., Pras-Raves, M., Sacchetti, A., Hornsveld, M., Oost, K.C., Snippert, H.J., Verhoeven-Duif, N.: Interplay between metabolic identities in the intestinal crypt supports stem cell function. Nature. 543(7645), 424–427 (2017)Google Scholar
  18. 18.
    Shimokawa, M., Ohta, Y., Nishikori, S., Matano, M., Takano, A., Fujii, M., Date, S., Sugimoto, S., Kanai, T., Sato, T.: Visualization and targeting of LGR5+ human colon cancer stem cells. Nature. 545(7653), 187–192 (2017)Google Scholar
  19. 19.
    e Melo, F.D.S., Kurtova, A.V., Harnoss, J.M., Kljavin, N., Hoeck, J.D., Hung, J., Anderson, J.E., Storm, E.E., Modrusan, Z., Koeppen, H., Dijkgraaf, G.J.: A distinct role for Lgr5 + stem cells in primary and metastatic colon cancer. Nature. 543(7647), 676–680 (2017)Google Scholar
  20. 20.
    Beyaz, S., Mana, M.D., Roper, J., Kedrin, D., Saadatpour, A., Hong, S.J., Bauer-Rowe, K.E., Xifaras, M.E., Akkad, A., Arias, E., Pinello, L.: High fat diet enhances stemness and tumorigenicity of intestinal progenitors. Nature. 531(7592), 53–58 (2016)Google Scholar
  21. 21.
    Barretina, J., Caponigro, G., Stransky, N., Venkatesan, K., Margolin, A.A., Kim, S., Wilson, C.J., Lehár, J., Kryukov, G.V., Sonkin, D., Reddy, A.: The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity. Nature. 483(7391), 603–607 (2012)Google Scholar
  22. 22.
    Mouradov, D., Sloggett, C., Jorissen, R.N., Love, C.G., Li, S., Burgess, A.W., Arango, D., Strausberg, R.L., Buchanan, D., Wormald, S., O’Connor, L.: Colorectal cancer cell lines are representative models of the main molecular subtypes of primary cancer. Cancer Res. 74(12), 3238–3248 (2014)Google Scholar
  23. 23.
    Fujii, M., Shimokawa, M., Date, S., Takano, A., Matano, M., Nanki, K., Ohta, Y., Toshimitsu, K., Nakazato, Y., Kawasaki, K., Uraoka, T.: A colorectal tumor organoid library demonstrates progressive loss of niche factor requirements during tumorigenesis. Cell Stem Cell. 18(6), 827–838 (2016)Google Scholar
  24. 24.
    Ertel, A., Verghese, A., Byers, S.W., Ochs, M., Tozeren, A.: Pathway-specific differences between tumor cell lines and normal and tumor tissue cells. Mol. Cancer. 5(1), 1 (2006)Google Scholar
  25. 25.
    Sandberg, R., Ernberg, I.: The molecular portrait of in vitro growth by meta-analysis of gene-expression profiles. Genome Biol. 6(8), 1–15 (2005)Google Scholar
  26. 26.
    Walsh, A.J., Castellanos, J.A., Nagathihalli, N.S., Merchant, N.B., Skala, M.C.: Optical imaging of drug-induced metabolism changes in murine and human pancreatic cancer organoids reveals heterogeneous drug response. Pancreas. 45(6), 863–869 (2016)Google Scholar
  27. 27.
    Walsh, A.J., Cook, R.S., Sanders, M.E., Aurisicchio, L., Ciliberto, G., Arteaga, C.L., Skala, M.C.: Quantitative optical imaging of primary tumor organoid metabolism predicts drug response in breast cancer. Cancer Res. 74(18), 5184–5194 (2014)Google Scholar
  28. 28.
    Walsh, A.J., Cook, R.S., Skala, M.C.: Functional optical imaging of primary human tumor organoids for personalized drug screens. J. Nucl. Med. 58(9), 1367–1372 (2017)Google Scholar
  29. 29.
    Cheung, K.J., Gabrielson, E., Werb, Z., Ewald, A.J.: Collective invasion in breast cancer requires a conserved basal epithelial program. Cell. 155(7), 1639–1651 (2013)Google Scholar
  30. 30.
    Zhao, Y., Jin, Y., Hanson, A., Wu, M., Zhao, J.X.: Three-dimensional molecular imaging with photothermal optical coherence tomography. NanoBiotechnol. Protoc. 1026, 85–99 (2013)Google Scholar
  31. 31.
    Kuo, W.T., Lee, T.C., Yang, H.Y., Chen, C.Y., Au, Y.C., Lu, Y.Z., Wu, L.L., Wei, S.C., Ni, Y.H., Lin, B.R., Chen, Y.: LPS receptor subunits have antagonistic roles in epithelial apoptosis and colonic carcinogenesis. Cell Death Differ. 22(10), 1590–1604 (2015)Google Scholar
  32. 32.
    Shah, A.T., Heaster, T.M., Skala, M.C.: Metabolic imaging of head and neck cancer organoids. PLoS One. 12(1), 1–17 (2017)Google Scholar
  33. 33.
    Walsh, A.J., Cook, R.S., Manning, H.C., Hicks, D.J., Lafontant, A., Arteaga, C.L., Skala, M.C.: Optical metabolic imaging identifies glycolytic levels, subtypes, and early-treatment response in breast cancer. Cancer Res. 73(20), 6164–6174 (2013)Google Scholar
  34. 34.
    Walsh, A.J., Cook, R.S., Sanders, M.E., Arteaga, C.L., Skala, M.C.: Drug response in organoids generated from frozen primary tumor tissues. Sci. Rep. 6, 18889 (2016)CrossRefGoogle Scholar
  35. 35.
    van de Wetering, M., Francies, H.E., Francis, J.M., Bounova, G., Iorio, F., Pronk, A., van Houdt, W., van Gorp, J., Taylor-Weiner, A., Kester, L., McLaren-Douglas, A.: Prospective derivation of a living organoid biobank of colorectal cancer patients. Cell. 161(4), 933–945 (2015)Google Scholar
  36. 36.
    Buck, A., Halbritter, S., Späth, C., Feuchtinger, A., Aichler, M., Zitzelsberger, H., Janssen, K.P., Walch, A.: Distribution and quantification of irinotecan and its active metabolite SN-38 in colon cancer murine model systems using MALDI MSI. Anal. Bioanal. Chem. 407(8), 2107–2116 (2015)Google Scholar
  37. 37.
    Alexandrov, T., Becker, M., Deininger, S.O., Ernst, G., Wehder, L., Grasmair, M., von Eggeling, F., Thiele, H., Maass, P.: Spatial segmentation of imaging mass spectrometry data with edge-preserving image denoising and clustering. J. Proteome Res. 9(12), 6535–6546 (2010)Google Scholar
  38. 38.
    Alexandrov, T., Becker, M., Guntinas-Lichius, O., Ernst, G., von Eggeling, F.: MALDI-imaging segmentation is a powerful tool for spatial functional proteomic analysis of human larynx carcinoma. J. Cancer Res. Clin. Oncol. 139(1), 85–95 (2013)Google Scholar
  39. 39.
    Weaver, E.M., Hummon, A.B.: Imaging mass spectrometry: from tissue sections to cell cultures. Adv. Drug Deliv. Rev. 65(8), 1039–1055 (2013)Google Scholar
  40. 40.
    Liu, X., Hummon, A.B.: Mass spectrometry imaging of therapeutics from animal models to three-dimensional cell cultures. Anal. Chem. 87(19), 9508–9519 (2015)Google Scholar
  41. 41.
    Raynal, C., Pascussi, J.M., Leguelinel, G., Breuker, C., Kantar, J., Lallemant, B., Poujol, S., Bonnans, C., Joubert, D., Hollande, F., Lumbroso, S.: Pregnane × Receptor (PXR) expression in colorectal cancer cells restricts irinotecan chemosensitivity through enhanced SN-38 glucuronidation. Mol. Cancer. 9(1), 46 (2010)Google Scholar
  42. 42.
    Mathijssen, R.H., Van Alphen, R.J., Verweij, J., Loos, W.J., Nooter, K., Stoter, G., Sparreboom, A.: Clinical pharmacokinetics and metabolism of irinotecan (CPT-11). Clin. Cancer Res. 7(8), 2182–2194 (2001)Google Scholar
  43. 43.
    Candeil, L., Gourdier, I., Peyron, D., Vezzio, N., Copois, V., Bibeau, F., Orsetti, B., Scheffer, G.L., Ychou, M., Khan, Q.A., Pommier, Y.: ABCG2 overexpression in colon cancer cells resistant to SN38 and in irinotecan-treated metastases. Int. J. Cancer. 109(6), 848–854Google Scholar
  44. 44.
    Jansen, W.J., Hulscher, T.M., van Ark-Otte, J., Giaccone, G., Pinedo, H.M., Boven, E.: CPT-11 sensitivity in relation to the expression of P170-glycoprotein and multidrug resistance-associated protein. Br. J. Cancer. 77(3), 359–365 (1998)Google Scholar
  45. 45.
    Emmink, B.L., Van Houdt, W.J., Vries, R.G., Hoogwater, F.J., Govaert, K.M., Verheem, A., Nijkamp, M.W., Steller, E.J., Jimenez, C.R., Clevers, H., Rinkes, I.H.B.: Differentiated human colorectal cancer cells protect tumor-initiating cells from irinotecan. Gastroenterology. 141(1), 269–278 (2011)Google Scholar
  46. 46.
    Kühl, A.A., Erben, U., Cieluch, C., Spieckermann, S., Gröne, J., Lohneis, P., Pape, U.F., Arsenic, R., Utku, N.: Tissue-infiltrating plasma cells are an important source of carboxylesterase 2 contributing to the therapeutic efficacy of prodrugs. Cancer Lett. 378(1), 51–58 (2016)Google Scholar
  47. 47.
    Kobayashi, T., Yokota, H., Ohgiya, S., Iwano, H., Yuasa, A.: UDP-glucuronosyltransferase UGT1A7 induced in rat small intestinal mucosa by oral administration of 2-naphthoflavone. FEBS J. 258(3), 948–955 (1998)Google Scholar
  48. 48.
    Peters, W.H., Allebes, W.A., Jansen, P.L., Poels, L.G., Capel, P.J.: Characterization and tissue specificity of a monoclonal antibody against human uridine V-diphosphate- glucuronosyltransferase. Gastroenterology. 93(1), 162–169 (1987)Google Scholar

Copyright information

© American Society for Mass Spectrometry 2017

Authors and Affiliations

  1. 1.Department of Chemistry and Biochemistry and the Harper Cancer Research InstituteUniversity of Notre DameNotre DameUSA
  2. 2.Lawrence J. Ellison Institute for Transformative MedicineUniversity of Southern CaliforniaLos AngelesUSA

Personalised recommendations