journal article·2025-03-19Open access

Mapping Tumor–Stroma–ECM Interactions in Spatially Advanced 3D Models of Pancreatic Cancer

Anna-Dimitra Kataki, Priyanka G. Gupta, Umber Cheema, Andrew Nisbet, Yaohe Wang, Hemant M. Kocher, Pedro A. Pérez-Mancera, Eirini G. Velliou

ACS Applied Materials & Interfaces· Volume 17· Issue 11

Abstract

High Resolution Image Download MS PowerPoint Slide Bioengineering-based in vitro tumor models are increasingly important as tools for studying disease progression and therapy response for many cancers, including the deadly pancreatic ductal adenocarcinoma (PDAC) that exhibits a tumor/tissue microenvironment of high cellular/biochemical complexity. Therefore, it is crucial for in vitro models to capture that complexity and to enable investigation of the interplay between cancer cells and factors such as extracellular matrix (ECM) proteins or stroma cells. Using polyurethane (PU) scaffolds, we performed a systematic study on how different ECM protein scaffold coatings impact the long-term cell evolution in scaffolds containing only cancer or only stroma cells (activated stellate and endothelial cells). To investigate potential further changes in those biomarkers due to cancer–stroma interactions, we mapped their expression in dual/zonal scaffolds consisting of a cancer core and a stroma periphery, spatially mimicking the fibrotic/desmoplastic reaction in PDAC. In our single scaffolds, we observed that the protein coating affected the cancer cell spatial aggregation, matrix deposition, and biomarker upregulation in a cell-line-dependent manner. In single stroma scaffolds, different levels of fibrosis/desmoplasia in terms of ECM composition/quantity were generated depending on the ECM coating. When studying the evolution of cancer and stroma cells in our dual/zonal model, biomarkers linked to cell aggressiveness/invasiveness were further upregulated by both cancer and stroma cells as compared to single scaffold models. Collectively, our study advances the understanding of how different ECM proteins impact the long-term cell evolution in PU scaffolds. Our findings show that within our bioengineered models, we can stimulate the cells of the PDAC microenvironment to develop different levels of aggressiveness/invasiveness, as well as different levels of fibrosis. Furthermore, we highlight the importance of considering spatial complexity to map cell invasion. Our work contributes to the design of in vitro models with variable, yet biomimetic, tissue-like properties for studying the tumor microenvironment’s role in cancer progression.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Cell Image Analysis Techniques · Mathematical Biology Tumor Growth · Single-cell and spatial transcriptomics

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

Affiliations

Centre for 3D models of Health and Disease, Division of Surgery and Interventional Science

University College London

School of Life and Health Sciences, Whitelands College

University of Roehampton

Department of Medical Physics and Biomedical Engineering

Centre for Cancer Biomarkers and Biotherapeutics, Barts Cancer Institute

Queen Mary University of London

Centre for Tumour Biology and Experimental Cancer Medicine, Barts Cancer Institute

Department of Molecular and Clinical Cancer Medicine

University of Liverpool

Funding

Medical Research Council · University College London

References (100+)

Show source-provided references
1. 10.3322/caac.2182010.3322/caac.21820 ↗
2. 10.18632/oncotarget.2401910.18632/oncotarget.24019 ↗
3. 10.1002/ijc.2287110.1002/ijc.22871 ↗
4. 10.1186/s13014-019-1345-610.1186/s13014-019-1345-6 ↗
5. 10.1016/j.drudis.2017.01.01210.1016/j.drudis.2017.01.012 ↗
6. 10.1053/j.gastro.2012.11.03710.1053/j.gastro.2012.11.037 ↗
7. 10.1016/j.trecan.2024.11.00510.1016/j.trecan.2024.11.005 ↗
8. 10.1002/ags3.1222510.1002/ags3.12225 ↗
9. 10.1016/j.canlet.2021.08.02910.1016/j.canlet.2021.08.029 ↗
10. 10.3389/fonc.2021.75131110.3389/fonc.2021.751311 ↗
11. 10.1038/s41392-021-00659-410.1038/s41392-021-00659-4 ↗
12. 10.3892/ol.2018.867810.3892/ol.2018.8678 ↗
13. 10.1016/j.yexcr.2020.11198410.1016/j.yexcr.2020.111984 ↗
14. 10.1186/s12967-019-2058-110.1186/s12967-019-2058-1 ↗
15. 10.1038/s41419-019-1320-z10.1038/s41419-019-1320-z ↗
16. 10.1091/mbc.E23-02-007510.1091/mbc.E23-02-0075 ↗
17. 10.1038/s41571-020-0363-510.1038/s41571-020-0363-5 ↗
18. Velliou, E.; Gupta, P.; Ricci, C.; Danti, S. Chapter 11─Biomaterial-based in vitro models for pancreatic cancer. In Biomaterials for 3D Tumor Modeling, Kundu, S. C.; Reis, R. L., Eds. Elsevier, 2020; pp 235–249.10.1016/B978-0-12-818128-7.00011-3 ↗
19. 10.1016/j.addr.2021.04.01810.1016/j.addr.2021.04.018 ↗
20. 10.3389/fbioe.2021.66050210.3389/fbioe.2021.660502 ↗
21. 10.3748/wjg.v20.i26.847110.3748/wjg.v20.i26.8471 ↗
22. 10.7150/thno.4244110.7150/thno.42441 ↗
23. 10.3390/pr901004510.3390/pr9010045 ↗
24. 10.1111/j.1349-7006.2012.02297.x10.1111/j.1349-7006.2012.02297.x ↗
25. 10.13172/2052-9643--1-60710.13172/2052-9643--1-607 ↗
26. 10.1259/bjr.2020139710.1259/bjr.20201397 ↗
27. 10.3390/cancers1323608010.3390/cancers13236080 ↗
28. 10.3390/cancers1304093010.3390/cancers13040930 ↗
29. 10.3390/cancers1312294010.3390/cancers13122940 ↗
30. 10.1016/j.jmrt.2021.09.04110.1016/j.jmrt.2021.09.041 ↗
31. 10.1002/smtd.20200120710.1002/smtd.202001207 ↗
32. 10.1016/j.actbio.2013.04.02810.1016/j.actbio.2013.04.028 ↗
33. 10.1038/s41467-021-25921-910.1038/s41467-021-25921-9 ↗
34. 10.1038/s41563-021-01085-110.1038/s41563-021-01085-1 ↗
35. 10.1039/C8RA02633E10.1039/C8RA02633E ↗
36. 10.1002/adbi.20230058010.1002/adbi.202300580 ↗
37. 10.3389/fbioe.2020.0029010.3389/fbioe.2020.00290 ↗
38. 10.1039/C9RA09123H10.1039/C9RA09123H ↗
39. 10.1186/s13046-017-0654-610.1186/s13046-017-0654-6 ↗
40. 10.3390/cancers1405127410.3390/cancers14051274 ↗
41. 10.1016/j.actbio.2016.11.07210.1016/j.actbio.2016.11.072 ↗
42. 10.1016/j.jbiotec.2010.01.00810.1016/j.jbiotec.2010.01.008 ↗
43. 10.1038/s41416-020-0973-910.1038/s41416-020-0973-9 ↗
44. 10.1089/ten.tec.2015.028010.1089/ten.tec.2015.0280 ↗
45. 10.2353/ajpath.2009.09013110.2353/ajpath.2009.090131 ↗
46. 10.1016/j.biomaterials.2020.12007710.1016/j.biomaterials.2020.120077 ↗
47. 10.1016/j.bbrc.2019.05.10110.1016/j.bbrc.2019.05.101 ↗
48. 10.3390/cancers1205130510.3390/cancers12051305 ↗
49. 10.1186/s12935-021-01853-810.1186/s12935-021-01853-8 ↗
50. 10.1016/j.ejphar.2020.17381410.1016/j.ejphar.2020.173814 ↗
51. 10.1021/acs.molpharmaceut.8b0107810.1021/acs.molpharmaceut.8b01078 ↗
52. 10.1021/acs.molpharmaceut.2c0026010.1021/acs.molpharmaceut.2c00260 ↗
53. 10.1159/00049147910.1159/000491479 ↗
54. 10.3390/cancers1105063810.3390/cancers11050638 ↗
55. 10.1186/1471-2407-13-9510.1186/1471-2407-13-95 ↗
56. 10.1038/srep1217510.1038/srep12175 ↗
57. 10.1590/1414-431X2013264710.1590/1414-431X20132647 ↗
58. 10.3390/ijms2117622510.3390/ijms21176225 ↗
59. 10.1088/1758-5090/ab7cb810.1088/1758-5090/ab7cb8 ↗
60. 10.1186/s12885-020-06867-510.1186/s12885-020-06867-5 ↗
61. 10.1186/1471-2407-12-1510.1186/1471-2407-12-15 ↗
62. 10.1038/s41598-020-66908-810.1038/s41598-020-66908-8 ↗
63. 10.3390/cancers1321554910.3390/cancers13215549 ↗
64. 10.1016/j.actbio.2018.08.00810.1016/j.actbio.2018.08.008 ↗
65. 10.1038/s41388-022-02557-710.1038/s41388-022-02557-7 ↗
66. 10.1016/j.tranon.2021.10110710.1016/j.tranon.2021.101107 ↗
67. 10.1177/088391151349034110.1177/0883911513490341 ↗
68. 10.1177/088391151663135510.1177/0883911516631355 ↗
69. 10.1002/adhm.20180095410.1002/adhm.201800954 ↗
70. 10.1016/j.biomaterials.2018.01.01210.1016/j.biomaterials.2018.01.012 ↗
71. 10.1016/j.actbio.2016.10.02710.1016/j.actbio.2016.10.027 ↗
72. 10.1007/s12274-019-2342-710.1007/s12274-019-2342-7 ↗
73. 10.1371/journal.pone.018887010.1371/journal.pone.0188870 ↗
74. 10.1073/pnas.101402610810.1073/pnas.1014026108 ↗
75. 10.3390/bioengineering803003710.3390/bioengineering8030037 ↗
76. 10.1016/S0939-6411(00)00090-410.1016/S0939-6411(00)00090-4 ↗
77. 10.1021/bm400449610.1021/bm4004496 ↗
78. 10.1016/j.biomaterials.2013.03.08610.1016/j.biomaterials.2013.03.086 ↗
79. 10.1039/C6RA08420F10.1039/C6RA08420F ↗
80. 10.1002/adhm.20210257410.1002/adhm.202102574 ↗
81. 10.4161/21592527.2014.95538610.4161/21592527.2014.955386 ↗
82. 10.1016/j.coche.2016.01.01210.1016/j.coche.2016.01.012 ↗
83. 10.1007/978-1-0716-3056-3_1310.1007/978-1-0716-3056-3_13 ↗
84. 10.1016/j.ejcb.2022.15122010.1016/j.ejcb.2022.151220 ↗
85. 10.1007/s00449-015-1401-z10.1007/s00449-015-1401-z ↗
86. 10.3390/jpm1205074610.3390/jpm12050746 ↗
87. 10.14348/molcells.2014.020710.14348/molcells.2014.0207 ↗
88. 10.1038/onc.2008.41210.1038/onc.2008.412 ↗
89. 10.1373/clinchem.2013.20637510.1373/clinchem.2013.206375 ↗
90. 10.1038/nprot.2008.7310.1038/nprot.2008.73 ↗
91. 10.1002/ijc.2037610.1002/ijc.20376 ↗
92. 10.3892/ijmm.2018.376410.3892/ijmm.2018.3764 ↗
93. 10.4161/cam.1895310.4161/cam.18953 ↗
94. 10.1007/s00018-019-03351-710.1007/s00018-019-03351-7 ↗
95. 10.1038/nm0195-2710.1038/nm0195-27 ↗
96. 10.1097/01.pas.0000135525.11566.b410.1097/01.pas.0000135525.11566.b4 ↗
97. 10.1007/s00432-024-05714-510.1007/s00432-024-05714-5 ↗
98. Sarkar F. H. · Minerva Chir. · 2009 · 64 · 489
99. 10.1007/BF0257448310.1007/BF02574483 ↗
100. 10.3389/fonc.2019.0137010.3389/fonc.2019.01370 ↗