Sphingolipid pathway as a biosensor of cancer chemosensitivity: a proof of principle





cancer, tumor chemosensitivity, sphingolipids, systems biology, chemotherapy, fuzzy logic


Cancer is a complex genetic disease with reduced treatment alternatives due to tumor heterogeneity and drug multiresistance emergence. The sphingolipid (SL) metabolic pathway integrates different responses of cellular stress signals and defines cell survival. Therefore, we suggest studying the perturbations on the sphingolipid pathway (SLP) caused by chemotherapeutic drugs using a systems biology approach to evaluate its functionality as a drug response sensor. We used a sphingomyelin-BODIPY (SM-BOD) sensor to study SL metabolism by flow cytometry and live cell imaging in different cancer models. To decode pathway complexity, we implemented Gussian mixture models, ordinary differential equations models, unsupervised classification algorithms and a fuzzy logic approach to assess its utility as a chemotherapy response sensor. Our results show that chemotherapeutic drugs perturb the SLP in different ways in a cell line-specific manner. In addition, we found that few SM-BOD fluorescence features predict chemosensitivity with high accuracy. Finally, we found that the relative species composition of SL appears to contribute to the resulting cytotoxicity of many treatments. This report offers a conceptual and mathematical framework for developing personalized mathematical models to predict and improve cancer therapy.


Al Daoud, E., & Al-Daoud, E. (2010). Cancer Diagnosis Using Modified Fuzzy Network. Universal Journal of Computer Science and Engineering Technology, 1(2), 73-78. https://www.researchgate.net/publication/49582994

Barteneva, N. S., Fasler-Kan, E., & Vorobjev, I. A. (2012). Imaging flow cytometry: coping with heterogeneity in biological systems. The Journal of Histochemistry and Cytochemistry: Official Journal of the Histochemistry Society, 60(10), 723-733. https://doi.org/10.1369/0022155412453052

Bensimon, A., Heck, A. J. R., & Aebersold, R. (2012). Mass spectrometry-based proteomics and network biology. Annual Review of Biochemistry, 81, 379-405. https://doi.org/10.1146/annurev-biochem-072909-100424

Bonhoure, E., Pchejetski, D., Aouali, N., Morjani, H., Levade, T., Kohama, T., & Cuvillier, O. (2006). Overcoming MDR-associated chemoresistance in HL-60 acute myeloid leukemia cells by targeting sphingosine kinase-1. Leukemia, 20(1), 95-102. https://doi.org/10.1038/sj.leu.2404023

Bosl, W. J. (2007). Systems biology by the rules: hybrid intelligent systems for pathway modeling and discovery. BMC Systems Biology, 1, 13. https://doi.org/10.1186/1752-0509-1-13

Chai, L., McLaren, R. P., Byrne, A., Chuang, W.-L., Huang, Y., Dufault, M. R., … Jiang, Y. A. (2011). The chemosensitizing activity of inhibitors of glucosylceramide synthase is mediated primarily through modulation of P-gp function. International Journal of Oncology, 38(3), 701-711. https://doi.org/10.3892/ijo.2010.888

Chuan Yang, Caibo Yang, Yosef Yarden, K.W.To, K. & Liwu Fu. (2021). The prospects of tumor chemosensitivity testing at the single-cell level. Drug Resistance Updates, 54. https://doi.org/10.1016/j.drup.2020.100741

Dupre, T. V., Doll, M. A., Shah, P. P., Sharp, C. N., Siow, D., Megyesi, J., … Siskind, L. J. (2017). Inhibiting glucosylceramide synthase exacerbates cisplatin-induced acute kidney injury. Journal of Lipid Research, 58(7), 1439-1452. https://doi.org/10.1194/jlr.M076745

Dyatlovitskaya, E. V., Kandyba, A. G., Kozlov, A. M., & Somova, O. G. (2001). Sphinganine in sphingomyelins of tumors and mouse regenerating liver. Biochemistry (Moscow), 66(5), 502-504. https://doi.org/10.1023/A:1010250600604

Erlich, S., Miranda, S. R., Visser, J. W., Dagan, A., Gatt, S., & Schuchman, E. H. (1999). Fluorescence-based selection of gene-corrected hematopoietic stem and progenitor cells from acid sphingomyelinase-deficient mice: implications for Niemann-Pick disease gene therapy and the development of improved stem cell gene transfer procedures. Blood, 93(1), 80-86. https://doi.org/10.1182/blood.v93.1.80

Fernandis, A. Z., & Wenk, M. R. (2009). Lipid-based biomarkers for cancer. Journal of Chromatography B, 877(26), 2830-2835. https://doi.org/10.1016/j.jchromb.2009.06.015

Glaysher, S., & Cree, I. A. (2011). Cell Sensitivity Assays: The ATP-based Tumor Chemosensitivity Assay. In Methods in molecular biology (Clifton, N.J.), 731, 247-257. https://doi.org/10.1007/978-1-61779-080-5_21

Guillermet-Guibert, J., Davenne, L., Pchejetski, D., Saint-Laurent, N., Brizuela, L., Guilbeau-Frugier, C., … Bousquet, C. (2009). Targeting the sphingolipid metabolism to defeat pancreatic cancer cell resistance to the chemotherapeutic gemcitabine drug. Molecular Cancer Therapeutics, 8(4), 809-820. https://doi.org/10.1158/1535-7163.MCT-08-1096

Hannun, Y. A., & Obeid, L. M. (2008). Principles of bioactive lipid signalling: Lessons from sphingolipids. Nature Reviews Molecular Cell Biology, 9(2), 139-150. https://doi.org/10.1038/nrm2329

Iessi, E., Marconi, M., Manganelli, V., Sorice, M., Malorni, W., Garofalo, T., & Matarrese, P. (2020). On the role of sphingolipids in cell survival and death. In International Review of Cell and Molecular Biology 1(351). https://doi.org/10.1016/bs.ircmb.2020.02.004

Kenchegowda, M., Rahamathulla, M., Hani, U., Begum, M. Y., Guruswamy, S., Osmani, R. A. M., … Gowda, D. V. (2022). Smart Nanocarriers as an Emerging Platform for Cancer Therapy: A Review. Molecules, 27(1). https://doi.org/10.3390/molecules27010146

Kitano, H. (2004). Cancer as a robust system: Implications for anticancer therapy. Nature Reviews Cancer, 4(3), 227-235. https://doi.org/10.1038/nrc1300

Koval, M., & Pagano, R. E. (1991). Intracellular transport and metabolism of sphingomyelin. Biochimica et Biophysica Acta, 1082(2), 113-125. https://doi.org/10.1016/0005-2760(91)90184-j

Kroll, A., Cho, H. E., & Kang, M. H. (2020). Antineoplastic Agents Targeting Sphingolipid Pathways. Frontiers in Oncology, 10, 833. https://doi.org/10.3389/fonc.2020.00833

Lacour, S., Hammann, A., Grazide, S., Lagadic-Gossmann, D., Athias, A., Sergent, O., … Dimanche-Boitrel, M.-T. (2004). Cisplatin-induced CD95 redistribution into membrane lipid rafts of HT29 human colon cancer cells. Cancer Research, 64(10), 3593-3598. https://doi.org/10.1158/0008-5472.CAN-03-2787

Lippert, T. H., Ruoff, H.-J., & Volm, M. (2008). Intrinsic and acquired drug resistance in malignant tumors. The main reason for therapeutic failure. Arzneimittel-Forschung, 58(6), 261-264. https://doi.org/10.1055/s-0031-1296504

Lukow, D. A., & Sheltzer, J. M. (2021). Chromosomal instability and aneuploidy as causes of cancer drug resistance. Trends in Cancer, 8(1), 43-53. https://doi.org/10.1016/j.trecan.2021.09.002

Machala, M., Procházková, J., Hofmanová, J., Králiková, L., Slavík, J., Tylichová, Z., … Vondráček, J. (2019). Colon cancer and perturbations of the sphingolipid metabolism. International Journal of Molecular Sciences, 20(23). https://doi.org/10.3390/ijms20236051

Molina-Mora, J. A., Kop-Montero, M., Quirós-Fernández, I., Quirós, S., Crespo-Mariño, J. L. & Mora-Rodríguez, R. A. (2018). A hybrid mathematical modeling approach of the metabolic fate of a fluorescent sphingolipid analogue to predict cancer chemosensitivity. Computers in Biology and Medicine, 97(April), 8-20. https://doi.org/10.1016/j.compbiomed.2018.04.008

Molina-Mora, J. A., & Mora-Rodríguez, R. A. (2016). Identification of cancer chemosensitivity by ODE and GMM modeling of heterogeneous cellular response to perturbations in fluorescent sphingolipid metabolism. 2016, IEEE 36th Central American and Panama Convention, CONCAPAN 2016. https://doi.org/10.1109/CONCAPAN.2016.7942347

Molino, S., Tate, E., McKillop, W., & Medin, J. A. (2017). Sphingolipid pathway enzymes modulate cell fate and immune responses. Immunotherapy, 9(14), 1185-1198. https://doi.org/10.2217/imt-2017-0089

Mora-Rodríguez, R. A., & Molina-Mora, J. A. (2017). Characterization of heterogeneous response to chemotherapy by perturbation-based modeling of fluorescent sphingolipid metabolism in cancer cell subpopulations. 2016 IEEE 36th Central American and Panama Convention, CONCAPAN 2016. https://doi.org/10.1109/CONCAPAN.2016.7942346

Mora, R., Dokic, I., Kees, T., Hüber, C. M., Keitel, D., Geibig, R., … Régnier-Vigouroux, A. (2010). Sphingolipid rheostat alterations related to transformation can be exploited for specific induction of lysosomal cell death in murine and human glioma. Glia, 58(11), 1364-1383. https://doi.org/10.1002/glia.21013

Morales, A., Lee, H., Goñi, F. M., Kolesnick, R., & Fernández-Checa, J. C. (2007). Sphingolipids and cell death. Apoptosis, 12(5), 923-939. https://doi.org/10.1007/s10495-007-0721-0

Ogretmen, B. (2006). Sphingolipids in cancer: Regulation of pathogenesis and therapy. FEBS Letters, 580(23), 5467-5476. https://doi.org/10.1016/j.febslet.2006.08.052

Ogretmen, B. (2017). Sphingolipid metabolism in cancer signalling and therapy. Nature Reviews Cancer, 18(1), 33-50. https://doi.org/10.1038/nrc.2017.96

Quirós-Fernández, I., Molina-Mora, JA, Kop-Monteo, M., Salas-Hidalgo. E. & Mora-Rodríguez, R. (2018). Predicting cancer chemosensitivity based on intensity/distribution profiles of cells loaded with a fluorescent sphingolipid analogue. 2018 IEEE International Work Conference on Bioinspired Intelligence (IWOBI), 1-8. https://doi.org/10.1109/iwobi.2018.8464199

Singh, D. K., Ku, C. J., Wichaidit, C., Steininger, R. J., Wu, L. F., & Altschuler, S. J. (2010). Patterns of basal signaling heterogeneity can distinguish cellular populations with different drug sensitivities. Molecular Systems Biology, 6(369), 1-10. https://doi.org/10.1038/msb.2010.22

Singh, R. D., Marks, D. L. & Pagano, R. E. (2007). Using fluorescent sphingolipid analogs to study intracellular lipid trafficking. Current Protocols in Cell Biology. Boardhttps://doi.org/10.1002/0471143030.cb2401s35

Slack, M. D., Martinez, E. D., Wu, L. F., & Altschuler, S. J. (2008). Characterizing heterogeneous cellular responses to perturbations. Proceedings of the National Academy of Sciences of the United States of America, 105(49), 19306-19311. https://doi.org/10.1073/pnas.0807038105

Solomonov, A. V., Rumyantsev, E. V., Kochergin, B. A., & Antina, E. V. (2014). The Interaction of BODIPY with bovine serum albumin and its bilirubin complex. Biophysics, 59(1), 35-42. https://doi.org/10.1134/S0006350914010217

Tepper, A. D., Ruurs, P., Wiedmer, T., Sims, P. J., Borst, J., & Van Blitterswijk, W. J. (2000). Sphingomyelin hydrolysis to ceramide during the execution phase of apoptosis results from phospholipid scrambling and alters cell-surface morphology. Journal of Cell Biology, 150(1), 155-164. https://doi.org/10.1083/jcb.150.1.155

Torshabi, A. E., Riboldi, M., Fooladi, A. A. I., Mosalla, S. M. M., & Baroni, G. (2013). An adaptive fuzzy prediction model for real time tumor tracking in radiotherapy via external surrogates. Journal of Applied Clinical Medical Physics, 14(1), 102-114. https://doi.org/10.1120/jacmp.v14i1.4008

Truman, J. P., García-Barros, M., Obeid, L. M., & Hannun, Y. A. (2014). Evolving concepts in cancer therapy through targeting sphingolipid metabolism. Biochimica et Biophysica Acta - Molecular and Cell Biology of Lipids, 1841(8), 1174-1188. https://doi.org/10.1016/j.bbalip.2013.12.013

Van Meer, G., Wolthoorn, J., & Degroote, S. (2003). The fate and function of glycosphingolipid glucosylceramide. Philosophical Transactions of the Royal Society B: Biological Sciences, 358(1433), 869–873. https://doi.org/10.1098/rstb.2003.1266



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Sphingolipid pathway as a biosensor of cancer chemosensitivity: a proof of principle. (2022). Uniciencia, 36(1), 1-15. https://doi.org/10.15359/ru.36-1.44



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How to Cite

Sphingolipid pathway as a biosensor of cancer chemosensitivity: a proof of principle. (2022). Uniciencia, 36(1), 1-15. https://doi.org/10.15359/ru.36-1.44

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