Evaluation of Proton-Induced DNA Damage in 3D-Engineered Glioblastoma Microenvironments
Source abstract
Abstract
Glioblastoma (GBM) is a devastating cancer of the brain with an extremely poor prognosis. For this reason, besides clinical and preclinical studies, novel in vitro models for the assessment of cancer response to drugs and radiation are being developed. In such context, three-dimensional (3D)-engineered cellular microenvironments, compared to unrealistic two-dimensional (2D) monolayer cell culture, provide a model closer to the in vivo configuration. Concerning cancer treatment, while X-ray radiotherapy and chemotherapy remain the current standard, proton beam therapy is an appealing alternative as protons can be efficiently targeted to destroy cancer cells while sparing the surrounding healthy tissue. However, despite the treatment's compelling biological and medical rationale, little is known about the effects of protons on GBM at the cellular level. In this work, we designed novel 3D-engineered scaffolds inspired by the geometry of brain blood vessels, which cover a vital role in the colonization mechanisms of GBM cells. The architectures were fabricated by two-photon polymerization (2PP), cultured with U-251 GBM cells and integrated for the first time in the context of proton radiation experiments to assess their response to treatment. We employed Gamma H2A.X as a fluorescent biomarker to identify the DNA damage induced in the cells by proton beams. The results show a higher DNA double-strand breakage in 2D cell monolayers as compared to cells cultured in 3D. The discrepancy in terms of proton radiation response could indicate a difference in the radioresistance of the GBM cells or in the rate of repair kinetics between 2D cell monolayers and 3D cell networks. Thus, these biomimetic-engineered 3D scaffolds pave the way for the realization of a benchmark tool that can be used to routinely assess the effects of proton therapy on 3D GBM cell networks and other types of cancer cells.
Source: europepmc · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Nanoplatforms for cancer theranostics · Anesthesia and Neurotoxicity Research · Radiation Therapy and Dosimetry
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Precision and Microsystems Engineering, Delft University of Technology, Mekelweg 2, 2628 CD Delft, The Netherlands
Holland Proton Therapy Center (HollandPTC), Huismansingel 4, 2629 JH Delft, The Netherlands
Einthoven Laboratory for Vascular and Regenerative Medicine, Division of Thrombosis and Hemostasis, Department of Internal Medicine, Leiden University Medical Center, 2333 ZA Leiden, The Netherlands
Funding
Technische Universiteit Delft · Nederlandse Organisatie voor Wetenschappelijk Onderzoek
References (69)
Show source-provided references
1. 10.1021/acsbiomaterials.6b0037010.1021/acsbiomaterials.6b00370 ↗
2. 10.1089/adt.2014.57310.1089/adt.2014.573 ↗
3. 10.1016/j.tibtech.2018.01.00510.1016/j.tibtech.2018.01.005 ↗
4. 10.1016/j.brainresbull.2019.07.02010.1016/j.brainresbull.2019.07.020 ↗
5. 10.3390/CANCERS1304087410.3390/CANCERS13040874 ↗
6. 10.1021/ACSBIOMATERIALS.6B0008810.1021/ACSBIOMATERIALS.6B00088 ↗
7. 10.1021/ACSBIOMATERIALS.6B0012110.1021/ACSBIOMATERIALS.6B00121 ↗
8. 10.3390/BIOENGINEERING604011310.3390/BIOENGINEERING6040113 ↗
9. 10.1021/ACS.ANALCHEM.7B0082810.1021/ACS.ANALCHEM.7B00828 ↗
10. 10.1021/ACS.CHEMREV.9B0078910.1021/ACS.CHEMREV.9B00789 ↗
11. 10.1016/J.BIOACTMAT.2018.05.00510.1016/J.BIOACTMAT.2018.05.005 ↗
12. 10.3389/FBIOE.2020.55150510.3389/FBIOE.2020.551505 ↗
13. 10.1016/J.ADDMA.2018.04.02710.1016/J.ADDMA.2018.04.027 ↗
14. 10.1021/acsabm.1c0097010.1021/acsabm.1c00970 ↗
15. 10.1016/J.MATTOD.2018.02.00410.1016/J.MATTOD.2018.02.004 ↗
16. 10.1002/SMLL.20170062110.1002/SMLL.201700621 ↗
17. 10.1021/ACSABM.0C0079110.1021/ACSABM.0C00791 ↗
18. 10.1038/s41698-020-0121-210.1038/s41698-020-0121-2 ↗
19. 10.1021/ACSBIOMATERIALS.0C0153010.1021/ACSBIOMATERIALS.0C01530 ↗
20. 10.1021/ACSAMI.1C1363010.1021/ACSAMI.1C13630 ↗
21. 10.1007/S00401-016-1545-110.1007/S00401-016-1545-1 ↗
22. 10.3747/CO.22.243610.3747/CO.22.2436 ↗
23. 10.1016/B978-0-12-802997-8.00023-210.1016/B978-0-12-802997-8.00023-2 ↗
24. 10.2174/092986732466617051612320610.2174/0929867324666170516123206 ↗
25. 10.1016/J.INAT.2019.10055110.1016/J.INAT.2019.100551 ↗
26. 10.3892/MCO.2017.149910.3892/MCO.2017.1499 ↗
27. 10.21037/cco.2016.06.0310.21037/cco.2016.06.03 ↗
28. 10.1053/clon.2002.017410.1053/clon.2002.0174 ↗
29. 10.1016/J.RADONC.2018.12.02810.1016/J.RADONC.2018.12.028 ↗
30. 10.1016/J.IJROBP.2012.06.01210.1016/J.IJROBP.2012.06.012 ↗
31. 10.1088/0031-9155/56/11/N0110.1088/0031-9155/56/11/N01 ↗
32. 10.1038/nmeth.201910.1038/nmeth.2019 ↗
33. 10.3390/CANCERS1107094610.3390/CANCERS11070946 ↗
34. 10.1088/978-0-7503-1370-4ch110.1088/978-0-7503-1370-4ch1 ↗
35. 10.1186/1748-717X-4-3110.1186/1748-717X-4-31 ↗
36. 10.1002/glia.2033410.1002/glia.20334 ↗
37. 10.1002/(SICI)1097-0185(199805)251:1<87::AID-AR14>3.0.CO;2-710.1002/(SICI)1097-0185(199805)251:1<87::AID-AR14>3.0.CO;2-7 ↗
38. 10.1364/OE.21.01702810.1364/OE.21.017028 ↗
39. 10.1364/OL.45.00001310.1364/OL.45.000013 ↗
40. 10.3390/PHOTONICS812057710.3390/PHOTONICS8120577 ↗
41. 10.1016/j.cell.2006.06.04410.1016/j.cell.2006.06.044 ↗
42. 10.1016/j.isci.2020.10145010.1016/j.isci.2020.101450 ↗
43. 10.3389/fncel.2021.60525510.3389/fncel.2021.605255 ↗
44. 10.1093/NEUONC/NOW16410.1093/NEUONC/NOW164 ↗
45. 10.1016/j.yexcr.2016.09.00110.1016/j.yexcr.2016.09.001 ↗
46. 10.1093/neuonc/now16410.1093/neuonc/now164 ↗
47. 10.1016/J.TCB.2018.02.00110.1016/J.TCB.2018.02.001 ↗
48. 10.1371/journal.pone.017158210.1371/journal.pone.0171582 ↗
49. 10.1371/journal.pone.003846510.1371/journal.pone.0038465 ↗
50. 10.1038/s41467-020-17512-x10.1038/s41467-020-17512-x ↗
51. 10.1158/1535-7163.MCT-10-001010.1158/1535-7163.MCT-10-0010 ↗
52. 10.1038/srep0002810.1038/srep00028 ↗
53. 10.1038/sj.cdd.440063410.1038/sj.cdd.4400634 ↗
54. 10.1529/biophysj.108.14062410.1529/biophysj.108.140624 ↗
55. 10.1371/journal.pone.010177110.1371/journal.pone.0101771 ↗
56. 10.3390/IJMS2206317810.3390/IJMS22063178 ↗
57. 10.3389/FNANA.2017.0012810.3389/FNANA.2017.00128 ↗
58. 10.1007/s12195-018-00565-w10.1007/s12195-018-00565-w ↗
59. 10.1007/s10409-018-0814-810.1007/s10409-018-0814-8 ↗
60. 10.3389/fncel.2020.55838110.3389/fncel.2020.558381 ↗
61. 10.18632/ONCOTARGET.1390710.18632/ONCOTARGET.13907 ↗
62. 10.3390/cancers1209251110.3390/cancers12092511 ↗
63. 10.1186/1479-5876-4-1210.1186/1479-5876-4-12 ↗
64. 10.1007/s12210-013-0260-210.1007/s12210-013-0260-2 ↗
65. 10.1158/1078-0432.CCR-10-243510.1158/1078-0432.CCR-10-2435 ↗
66. 10.1038/sj.onc.121087810.1038/sj.onc.1210878 ↗
67. 10.18632/oncotarget.1264710.18632/oncotarget.12647 ↗
68. 10.1593/neo.11179410.1593/neo.111794 ↗
69. 10.1093/jrr/rrv01810.1093/jrr/rrv018 ↗