journal article·2024-07Open access

Tumor‐On‐A‐Chip Model Incorporating Human‐Based Hydrogels for Easy Assessment of Metastatic Tumor Inter‐Heterogeneity

Cátia F. Monteiro, Inês A. Deus, Inês B. Silva, Iola F. Duarte, Catarina A. Custódio, João F. Mano

Advanced Functional Materials· Volume 34· Issue 30

Abstract

Abstract The coordinated migration of invasive tumor cells is a complex and dynamic mechanism driven by diverse cellular and molecular events. Unfortunately, the inherent heterogeneity within tumors raises multiple challenges in deciphering key biomarkers and novel therapeutic approaches to prevent tumor metastasis. Here, a microengineered tumor‐on‐a‐chip system incorporating human platelet lysate hydrogels is proposed to recreate the early metastatic process of tumor invasion and drug response. By co‐culturing human bone marrow mesenchymal stem cells with two tumor cell lines with distinct metastatic capability, the developed model can emulate the 3D tumor microarchitecture and inter‐heterogeneity regarding its intrinsic metastatic ability. The recreated microenvironment supports tumor and stromal cell movement, evidencing the synergistic tumor‐stromal cell and cell‐extracellular matrix interactions of an invading tumor. Through gene and protein expression analysis and exometabolomic profiling, this tumor‐on‐a‐chip platform provides evidence for the role of a dynamic environment as a key regulator of tumor metastatic ability. Additionally, the effect of doxorubicin treatment on tumor invasiveness and biomarker profile highlights the suitability of the established models for therapy assessment. Overall, this study presents a tumor‐on‐a‐chip model useful to pursue mechanistic studies on early metastatic events in a fully human‐derived microenvironment, while contributing with fundamental insights into biomolecular profiling.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: 3D Printing in Biomedical Research · Cancer Cells and Metastasis · Innovative Microfluidic and Catalytic Techniques Innovation

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

CICECO –Aveiro Institute of Materials Department of Chemistry University of Aveiro Campus Universitário de Santiago Aveiro 3810‐193 Portugal

Funding

Fundação para a Ciência e a Tecnologia · H2020 European Research Council · European Regional Development Fund · Ministério da Ciência, Tecnologia e Ensino Superior

References (62)

Show source-provided references
1. 10.1038/nrc.2016.12310.1038/nrc.2016.123 ↗
2. 10.1038/s41568-020-00300-610.1038/s41568-020-00300-6 ↗
3. 10.1002/adtp.20180010810.1002/adtp.201800108 ↗
4. 10.1016/j.trecan.2020.10.00910.1016/j.trecan.2020.10.009 ↗
5. 10.1002/adhm.20200060810.1002/adhm.202000608 ↗
6. 10.1186/s12935-021-01853-810.1186/s12935-021-01853-8 ↗
7. 10.1002/advs.20190239810.1002/advs.201902398 ↗
8. 10.1016/j.actbio.2021.07.03410.1016/j.actbio.2021.07.034 ↗
9. 10.1002/biot.20170007910.1002/biot.201700079 ↗
10. Li X. · Cell Death Discov. · 2022 · 8 · 1
11. 10.1038/nrc308010.1038/nrc3080 ↗
12. 10.1038/s41568-018-0104-610.1038/s41568-018-0104-6 ↗
13. 10.1016/j.biomaterials.2019.11954710.1016/j.biomaterials.2019.119547 ↗
14. 10.1039/C8LC00596F10.1039/C8LC00596F ↗
15. 10.1002/advs.20220143610.1002/advs.202201436 ↗
16. 10.1016/j.biomaterials.2018.03.00510.1016/j.biomaterials.2018.03.005 ↗
17. 10.1002/advs.20190019510.1002/advs.201900195 ↗
18. 10.1002/adfm.20200244410.1002/adfm.202002444 ↗
19. 10.1002/advs.20200485610.1002/advs.202004856 ↗
20. 10.1002/bit.2687110.1002/bit.26871 ↗
21. 10.1016/j.mtbio.2022.10021910.1016/j.mtbio.2022.100219 ↗
22. Gumuscu B. · 2018 · 225
23. 10.1038/nrc.2017.9310.1038/nrc.2017.93 ↗
24. 10.1038/srep3664110.1038/srep36641 ↗
25. 10.1002/adhm.20180084910.1002/adhm.201800849 ↗
26. 10.1016/j.addr.2018.07.01110.1016/j.addr.2018.07.011 ↗
27. 10.1038/s41392-022-01259-610.1038/s41392-022-01259-6 ↗
28. 10.1038/bjc.2013.54910.1038/bjc.2013.549 ↗
29. 10.18632/oncotarget.517710.18632/oncotarget.5177 ↗
30. 10.7150/thno.2958010.7150/thno.29580 ↗
31. 10.3390/cancers1304068310.3390/cancers13040683 ↗
32. 10.3390/cancers1504122110.3390/cancers15041221 ↗
33. 10.3892/mmr.2017.763710.3892/mmr.2017.7637 ↗
34. 10.1038/s41467-020-18794-x10.1038/s41467-020-18794-x ↗
35. 10.1080/15384047.2023.218414510.1080/15384047.2023.2184145 ↗
36. 10.1016/j.critrevonc.2019.02.01010.1016/j.critrevonc.2019.02.010 ↗
37. 10.1126/scitranslmed.300424910.1126/scitranslmed.3004249 ↗
38. 10.1038/s41551-019-0397-010.1038/s41551-019-0397-0 ↗
39. 10.1002/adhm.20200088010.1002/adhm.202000880 ↗
40. 10.1038/s41551-019-0495-z10.1038/s41551-019-0495-z ↗
41. 10.1016/j.biomaterials.2013.11.05010.1016/j.biomaterials.2013.11.050 ↗
42. 10.1038/s41551-021-00743-810.1038/s41551-021-00743-8 ↗
43. 10.1038/s41467-021-21615-410.1038/s41467-021-21615-4 ↗
44. 10.1158/1078-0432.CCR-05-166410.1158/1078-0432.CCR-05-1664 ↗
45. 10.1016/S1470-2045(18)30332-210.1016/S1470-2045(18)30332-2 ↗
46. 10.3390/ph1606080210.3390/ph16060802 ↗
47. 10.1007/s00280-010-1521-810.1007/s00280-010-1521-8 ↗
48. Deryugina E. I. · Matrix Biol. · 2015 · 94 · 44
49. 10.1007/s12032-015-0633-810.1007/s12032-015-0633-8 ↗
50. 10.1016/j.biopha.2016.04.02910.1016/j.biopha.2016.04.029 ↗
51. 10.1126/sciadv.160127310.1126/sciadv.1601273 ↗
52. 10.1038/s41467-018-03777-w10.1038/s41467-018-03777-w ↗
53. 10.1016/j.tcb.2019.05.00510.1016/j.tcb.2019.05.005 ↗
54. 10.3390/ijms2105189210.3390/ijms21051892 ↗
55. 10.1371/journal.pcbi.100910410.1371/journal.pcbi.1009104 ↗
56. 10.3390/metabo1007026810.3390/metabo10070268 ↗
57. 10.1021/acs.biochem.7b0001510.1021/acs.biochem.7b00015 ↗
58. 10.3389/fonc.2023.115033210.3389/fonc.2023.1150332 ↗
59. 10.1038/s41568-020-0273-y10.1038/s41568-020-0273-y ↗
60. 10.1016/j.tibtech.2020.01.00310.1016/j.tibtech.2020.01.003 ↗
61. 10.1016/j.biomaterials.2016.11.01410.1016/j.biomaterials.2016.11.014 ↗
62. Chen W. · J. Visualized Exp. · 2014 · 8