Abstract
Spontaneous and stimulated Raman spectromicroscopy is reported to investigate the cetuximab uptake in a head and neck cancer oral mucosa model and to unravel drug induced cellular changes in a label-free approach. Specifically, stimulated Raman spectromicroscopy is sensitive to probe the spatial distribution of cetuximab as well as drug-induced changes in spatial distributions of proteins, lipids, and DNA. The distinct vibrational bands of the CH3-stretch of proteins and the CH2-stretch of lipids indicate drug-induced cellular modifications, which are retrieved by a linear decomposition algorithm. Topical and systemic drug application pathways were studied, indicating an increased total protein content by a factor of ∼2 and ∼1.5, respectively, compared to an untreated control. Protein and lipid profiles as well as drug distributions were monitored, demonstrating the potential of Raman-based spectromicroscopy for probing changes induced by cetuixmab. Following cetuximab therapy, the relative protein content increases, while the lipid concentration decreases. Accumulation of lipid droplet-like structures near tumor cell membranes with less nucleic acid-like material in treated tumor oral mucosa models was also observed. The results are compared to related spectromicroscopy approaches involving fluorescence labels and label-free photothermal expansion indicating that stimulated Raman spectromicroscopy reveals sensitively biological post-treatment effects, while no reduction in tumor size occurs.
Acknowledgments
Financial support by Freie Universität Berlinis gratefully acknowledged. The help of the High-Performance Computing team at the ZEDAT, Freie Universität Berlin (B. Proppe, L. Bennett, B. Melchers), and Supercomputing Group HLRN of Zuse Institute Berlin (ZIB) Berlin is kindly acknowledged. Dr. B. Wassermann is gratefully acknowledged for helpful discussions. S. Thierbach is thanked for technical assistance.
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Research ethics: Not applicable.
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Informed consent: Not applicable.
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Author contributions: T.S.: Investigations, writing the original draft, review, editing, visualization. L.S.: Preparation of samples, writing, review, editing. C.Z.: Writing, review, editing, supervision, project administration, providing funding and resources. E.R.: Writing, review, editing, supervision, project administration, providing funding and resources.
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Use of Large Language Models, AI and Machine Learning Tools: None declared.
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Conflict of interest: The author states no conflict of interest.
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Research funding: Freie Universität Berlin.
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Data availability: The datasets generated and/or analyzed during the current study are available from the corresponding authors on reasonable request.
References
1. Johnson, D. E.; Burtness, B.; Leemans, C. R.; Lui, V. W. Y.; Bauman, J. E.; Grandis, J. R. Nat. Rev. Dis. Primers 2020, 6, 92; https://doi.org/10.1038/s41572-020-00224-3.Suche in Google Scholar PubMed PubMed Central
2. Gong, Y.; Bao, L.; Xu, T.; Yi, X.; Chen, J.; Wang, S.; Pan, Z.; Huang, P.; Ge, M. Mol. Cancer 2023, 22, 68; https://doi.org/10.1186/s12943-023-01769-z.Suche in Google Scholar PubMed PubMed Central
3. Barsouk, A.; Aluru, J. S.; Rawla, P.; Saginala, K.; Barsouk, A. Med. Sci. 2023, 11, 42; https://doi.org/10.3390/medsci11020042.Suche in Google Scholar PubMed PubMed Central
4. Wolchok, J. D.; Chiarion Sileni, V.; Gonzalez, R.; Rutkowski, P.; Grob, J.-J.; Cowey, C. L.; Lao, C. D.; Wagstaff, J.; Schadendorf, D.; Ferrucci, P. F.; Smylie, M.; Dummer, R.; Hill, A.; Hogg, D.; Haanen, J.; Carlino, M. S.; Bechter, O.; Maio, M.; Marquez Rodas, I.; Guidoboni, M.; McArthur, G.; Lebbé, C.; Ascierto, P.A.; Long, G. V.; Cebon, J.; Sosman, J.; Postow, M. A.; Callahan, M. K.; Walker, D.; Rollin, L.; Bhore, R.; Hodi, F. S.; Larkin, J. New Engl. J. Med. 2017, 377, 1345.10.1056/NEJMoa1709684Suche in Google Scholar PubMed PubMed Central
5. Gronbach, L.; Wolff, C.; Klinghammer, K.; Stellmacher, J.; Jurmeister, P.; Alexiev, U.; Schäfer-Korting, M.; Tinhofer, I.; Keilholz, U.; Zoschke, C. Biomaterials 2020, 258, 120277; https://doi.org/10.1016/j.biomaterials.2020.120277.Suche in Google Scholar PubMed
6. Germer, G.; Schwartze, L.; Garcia-Miller, J.; Balansin-Rigon, R.; Groth, L.; Rühl, I.; Patoka, P.; Zoschke, C.; Rühl, E. Analyst 2024, 149, 2122; https://doi.org/10.1039/d3an01877f.Suche in Google Scholar PubMed
7. Alexiev, U.; Rühl, E. Drug Delivery and Targeting; Schaefer-Korting, M., Schubert, U., Eds.; Springer Nature Switzerland: Cham, 2024; p 153.10.1007/164_2023_684Suche in Google Scholar PubMed
8. Dazzi, A.; Prater, C. B. Chem. Rev. 2017, 117, 5146; https://doi.org/10.1021/acs.chemrev.6b00448.Suche in Google Scholar PubMed
9. Kästner, B.; Johnson, C. M.; Hermann, P.; Kruskopf, M.; Pierz, K.; Hoehl, A.; Hornemann, A.; Ulrich, G.; Fehmel, J.; Patoka, P.; Rühl, E.; Ulm, G. ACS Omega 2018, 3, 4141; https://doi.org/10.1021/acsomega.7b01931.Suche in Google Scholar PubMed PubMed Central
10. Kästner, B.; Marschall, M.; Hornemann, A.; Metzner, S.; Patoka, P.; Cortes, S.; Wübbeler, G.; Hoehl, A.; Rühl, E.; Elster, C. Meas. Sci. Technol. 2024, 35, 015403; https://doi.org/10.1088/1361-6501/acfc27.Suche in Google Scholar
11. Sbroscia, M.; Di Gioacchino, M.; Ascenzi, P.; Crucitti, P.; di Masi, A.; Giovannoni, I.; Longo, F.; Mariotti, D.; Naciu, A. M.; Palermo, A.; Taffon, C.; Verri, M.; Sodo, A.; Crescenzi, A.; Ricci, M. A. Sci. Rep. 2020, 10, 13342; https://doi.org/10.1038/s41598-020-70165-0.Suche in Google Scholar PubMed PubMed Central
12. Hanna, K.; Krzoska, E.; Shaaban, A. M.; Muirhead, D.; Abu-Eid, R.; Speirs, V. Brit. J. Cancer 2022, 126, 1125; https://doi.org/10.1038/s41416-021-01659-5.Suche in Google Scholar PubMed PubMed Central
13. Feofanov, A. V.; Grichine, A. I.; Shitova, L. A.; Karmakova, T. A.; Yakubovskaya, R. I.; Egret-Charlier, M.; Vigny, P. Biophys. J. 2000, 78, 499; https://doi.org/10.1016/s0006-3495(00)76612-4.Suche in Google Scholar
14. Huang, L.; Sun, H.; Sun, L.; Shi, K.; Chen, Y.; Ren, X.; Ge, Y.; Jiang, D.; Liu, X.; Knoll, W.; Zhang, Q.; Wang, Y. Nat. Commun. 2023, 14, 48; https://doi.org/10.1038/s41467-022-35696-2.Suche in Google Scholar PubMed PubMed Central
15. Chen, C.; Zhao, Z.; Qian, N.; Wei, S.; Hu, F.; Min, W. Nat. Commun. 2021, 12, 3405; https://doi.org/10.1038/s41467-021-23700-0.Suche in Google Scholar PubMed PubMed Central
16. Freudiger, C. W.; Min, W.; Saar, B. G.; Lu, S.; Holtom, G. R.; He, C.; Tsai, J. C.; Kang, J. X.; Xie, X. S. Science 2008, 322, 1857; https://doi.org/10.1126/science.1165758.Suche in Google Scholar PubMed PubMed Central
17. Lu, F.-K.; Basu, S.; Igras, V.; Hoang, M. P.; Ji, M.; Fu, D.; Holtom, G. R.; Neel, V. A.; Freudiger, C. W.; Fisher, D. E.; Xie, X. S. Proc. Nat. Acad. Sci. 2015, 112, 11624; https://doi.org/10.1073/pnas.1515121112.Suche in Google Scholar PubMed PubMed Central
18. Hill, A. H.; Fu, D. Anal. Chem. 2019, 91, 9333; https://doi.org/10.1021/acs.analchem.9b02095.Suche in Google Scholar PubMed
19. Hislop, E. W.; Tipping, W. J.; Faulds, K.; Graham, D. Anal. Chem. 2022, 94, 8899; https://doi.org/10.1021/acs.analchem.2c00236.Suche in Google Scholar PubMed PubMed Central
20. Hu, F.; Chen, Z.; Zhang, L.; Shen, Y.; Wei, L.; Min, W. Angew. Chem. Int. Ed. 2015, 54, 9821; https://doi.org/10.1002/anie.201502543.Suche in Google Scholar PubMed PubMed Central
21. Fu, D.; Zhou, J.; Zhu, W. S.; Manley, P. W.; Wang, Y. K.; Hood, T.; Wylie, A.; Xie, X. S. Nat. Chem. 2014, 6, 614; https://doi.org/10.1038/nchem.1961.Suche in Google Scholar PubMed PubMed Central
22. Wei, L.; Hu, F.; Shen, Y.; Chen, Z.; Yu, Y.; Lin, C.-C.; Wang, M. C.; Min, W. Nat. Meth. 2014, 11, 410; https://doi.org/10.1038/nmeth.2878.Suche in Google Scholar PubMed PubMed Central
23. Wanjiku, B.; Yamamoto, K.; Klossek, A.; Schumacher, F.; Pischon, H.; Mundhenk, L.; Rancan, F.; Judd, M. M.; Ahmed, M.; Zoschke, C.; Kleuser, B.; Rühl, E.; Schäfer-Korting, M. Anal. Chem. 2019, 91, 7208; https://doi.org/10.1021/acs.analchem.9b00519.Suche in Google Scholar PubMed
24. Zhang, L.; Shi, L.; Shen, Y.; Miao, Y.; Wei, M.; Qian, N.; Liu, Y.; Min, W. Nat. Biomed. Eng. 2019, 3, 402; https://doi.org/10.1038/s41551-019-0393-4.Suche in Google Scholar PubMed PubMed Central
25. Hu, F.; Shi, L.; Min, W. Nat. Meth. 2019, 16, 830; https://doi.org/10.1038/s41592-019-0538-0.Suche in Google Scholar PubMed
26. Ozeki, Y.; Dake, F.; Kajiyama, S. I.; Fukui, K.; Itoh, K. Opt. Express 2009, 17, 3651; https://doi.org/10.1364/oe.17.003651.Suche in Google Scholar PubMed
27. Klossek, A.; Thierbach, S.; Rancan, F.; Vogt, A.; Blume-Peytavi, U.; Rühl, E. Eur. J. Pharm. Biopharm. 2017, 116, 76; https://doi.org/10.1016/j.ejpb.2016.11.001.Suche in Google Scholar PubMed
28. Nelder, J. A.; Mead, R. Comput. J. 1965, 7, 308; https://doi.org/10.1093/comjnl/7.4.308.Suche in Google Scholar
29. Azzopardi, N.; Lecomte, T.; Ternant, D.; Boisdron-Celle, M.; Piller, F.; Morel, A.; Gouilleux-Gruart, V.; Vignault-Desvignes, C.; Watier, H.; Gamelin, E.; Paintaud, G. Clin. Cancer Res. 2011, 17, 6329; https://doi.org/10.1158/1078-0432.ccr-11-1081.Suche in Google Scholar
30. Choe, C. S.; Lademann, J.; Darvin, M. E. Laser Phys. 2014, 24, 105601; https://doi.org/10.1088/1054-660x/24/10/105601.Suche in Google Scholar
31. Li, S.; Schmitz, K. R.; Jeffrey, P. D.; Wiltzius, J. J. W.; Kussie, P.; Ferguson, K. M. Cancer Cell 2005, 7, 301; https://doi.org/10.1016/j.ccr.2005.03.003.Suche in Google Scholar PubMed
32. Takahashi, J.; Nakamura, S.; Onuma, I.; Zhou, Y.; Yokoyama, S.; Sakurai, H. Sci. Rep. 2022, 12, 11561; https://doi.org/10.1038/s41598-022-15838-8.Suche in Google Scholar PubMed PubMed Central
33. Tipping, W. J.; Merchant, A. S.; Fearon, R.; Tomkinson, N. C. O.; Faulds, K.; Graham, D. RSC Chem. Biol. 2022, 3, 1154; https://doi.org/10.1039/d2cb00160h.Suche in Google Scholar PubMed PubMed Central
34. Sepp, K.; Lee, M.; Bluntzer, M. T. J.; Helgason, G. V.; Hulme, A. N.; Brunton, V. G. J. Med. Chem. 2020, 63, 2028; https://doi.org/10.1021/acs.jmedchem.9b01546.Suche in Google Scholar PubMed PubMed Central
35. Percot, A.; Lafleur, M. Biophys. J. 2001, 81, 2144; https://doi.org/10.1016/s0006-3495(01)75862-6.Suche in Google Scholar
36. Greve, T. M.; Andersen, K. B.; Nielsen, O. F. Spectrosc. Int. J. 2008, 22, 437; https://doi.org/10.1155/2008/969217.Suche in Google Scholar
37. Vyumvuhore, R.; Tfayli, A.; Duplan, H.; Delalleau, A.; Manfait, M.; Baillet-Guffroy, A. Analyst 2013, 138, 4103; https://doi.org/10.1039/c3an00716b.Suche in Google Scholar PubMed
38. Larion, M.; Dowdy, T.; Ruiz-Rodado, V.; Meyer, M. W.; Song, H.; Zhang, W.; Davis, D.; Gilbert, M. R.; Lita, A. Biosensors 2018, 9, 5; https://doi.org/10.3390/bios9010005.Suche in Google Scholar PubMed PubMed Central
39. Jiang, X. Y.; McKinley, E. T.; Xie, J. P.; Li, H.; Xu, J. Z.; Gore, J. C. Sci. Rep. 2019, 9, 9540; https://doi.org/10.1038/s41598-019-45864-y.Suche in Google Scholar PubMed PubMed Central
40. Petan, T.; Jarc, E.; Jusović, M. Molecules 2018, 23, 1941; https://doi.org/10.3390/molecules23081941.Suche in Google Scholar PubMed PubMed Central
41. Cruz, A. L. S.; Barreto, E. D. A.; Fazolini, N. P. B.; Viola, J. P. B.; Bozza, P. T. Cell Death Dis. 2020, 11, 105; https://doi.org/10.1038/s41419-020-2297-3.Suche in Google Scholar PubMed PubMed Central
42. Huang, K.-C.; Li, J.; Zhang, C.; Tan, Y.; Cheng, J.-X.. iScience 2020, 23, 100953; https://doi.org/10.1016/j.isci.2020.100953.Suche in Google Scholar PubMed PubMed Central
43. Zhenzhen Li, H. L. X. L. Am. J. Cancer Res. 2020, 10, 4112.Suche in Google Scholar
44. Mehdizadeh, A.; Bonyadi, M.; Darabi, M.; Rahbarghazi, R.; Montazersaheb, S.; Velaei, K.; Shaaker, M.; Somi, M.-H.. BioImpacts 2017, 7, 31; https://doi.org/10.15171/bi.2017.05.Suche in Google Scholar PubMed PubMed Central
45. Mascheroni, P.; Boso, D.; Preziosi, L.; Schrefler, B. A.; Theoret, J. Biol. 2017, 421, 179; https://doi.org/10.1016/j.jtbi.2017.03.027.Suche in Google Scholar PubMed PubMed Central
46. Kästner, B.; Schmähling, F.; Hornemann, A.; Ulrich, G.; Hoehl, A.; Kruskopf, M.; Pierz, K.; Raschke, M. B.; Wübbeler, G.; Elster, C. Opt. Express 2018, 26, 18115; https://doi.org/10.1364/oe.26.018115.Suche in Google Scholar PubMed
47. Marschall, M.; Hornemann, A.; Wübbeler, G.; Hoehl, A.; Rühl, E.; Kästner, B.; Elster, C. Opt. Express 2020, 28, 38762.10.1364/OE.404959Suche in Google Scholar PubMed
48. Wübbeler, G.; Marschall, M.; Rühl, E.; Kästner, B.; Elster, C. Meas. Sci. Technol. 2022, 33, 035402; https://doi.org/10.1088/1361-6501/ac407a.Suche in Google Scholar
49. Metzner, S.; Kästner, B.; Marschall, M.; Wübbeler, G.; Wundrack, S.; Bakin, A.; Hoehl, A.; Rühl, E.; Elster, C. IEEE Trans. Instrum. Meas. 2022, 71, 4506208.10.1109/TIM.2022.3204072Suche in Google Scholar
Supplementary Material
This article contains supplementary material (https://doi.org/10.1515/zpch-2024-0824).
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Artikel in diesem Heft
- Frontmatter
- Preface
- Preface
- Contribution to “From Nanostructure to Function”
- Temporal airy pulses efficiency in thin glass dicing
- Surface investigations of bronze and brass statuary monuments in open-air exposure
- Dual dynamic voltammetric study of the formation of ferrate ions during the electrochemical dissolution of white cast iron in the transpassive region
- Cetuximab-induced changes to tumor oral mucosa models probed by stimulated Raman spectromicroscopy
- From nanostructure to function: hierarchical functional structures in chitin and keratin
- The influence of glycine on β-lactoglobulin amyloid fibril formation – computer simulation study
Artikel in diesem Heft
- Frontmatter
- Preface
- Preface
- Contribution to “From Nanostructure to Function”
- Temporal airy pulses efficiency in thin glass dicing
- Surface investigations of bronze and brass statuary monuments in open-air exposure
- Dual dynamic voltammetric study of the formation of ferrate ions during the electrochemical dissolution of white cast iron in the transpassive region
- Cetuximab-induced changes to tumor oral mucosa models probed by stimulated Raman spectromicroscopy
- From nanostructure to function: hierarchical functional structures in chitin and keratin
- The influence of glycine on β-lactoglobulin amyloid fibril formation – computer simulation study