AccScience Publishing / IJB / Online First / DOI: 10.36922/ijb.1673
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RESEARCH ARTICLE

Increased stiffness of extracellular matrix enhanced chemoresistance in 3D-bioprinted ovarian cancer model

Ying Shan1† ,  Mingchang Pang2† ,  Liqian Wang3† ,  Yixin Mao4† ,  Ruiyi Yan2 ,  Chang Zhou5 ,  Jingyuan Ji5 ,  Yilei Mao2 ,  Ying Jin1* ,  Huayu Yang2*
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1 Department of Obstetrics and Gynecology, National Clinical Research Center for Obstetric & Gynecologic Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
2 Department of Liver Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
3 Department of Gynecology, The Affiliated Yantai Yuhuangding Hospital of Qingdao University, Yantai, China
4 Department of Geriatrics, Shanghai Eighth Peoples Hospital, Shanghai, China
5 Biomanufacturing Center, Department of Mechanical Engineering, Tsinghua University, Beijing, China
IJB, 1673 https://doi.org/10.36922/ijb.1673
Submitted: 24 August 2023 | Accepted: 21 November 2023 | Published: 18 January 2024
(This article belongs to the Special Issue Bioprinting process for tumor model development)
© 2024 by the Author(s). This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution 4.0 International License ( https://creativecommons.org/licenses/by/4.0/ )
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Abstract

Ovarian cancer is a gynecological malignancy with a high mortality rate. The ovarian cancer microenvironment is a crucial factor affecting the overall and progression-free survival rates of patients with ovarian cancer. The biophysical factors of the tumor microenvironment, such as stiffness, can affect the gene expression and behavior of tumor cells. In this study, we utilized 3D bioprinting technology to construct ovarian cancer tumor models with varying levels of stiffness in vitro to investigate the effect of extracellular matrix stiffness on drug resistance of tumor cells. Our findings indicate that increasing the stiffness of extracellular matrix can attenuate the sensitivity of tumor cells to chemotherapeutic agents. Additionally, the increased stiffness of 3D tumor model may promote malignant phenotypes, such as tumor stemness and tumor progression.

Keywords
3D bioprinting technology
Ovarian cancer
Tumor microenvironment
Stiffness
Drug resistance
Funding
This work was supported by the National Natural Science Foundation of China (Grant No. 32271470), National High Level Hospital Clinical Research Funding (2022-PUMCH-C-045), Beijing Natural Science Foundation (7212077), and CAMS Innovation Fund for Medical Sciences (CIFMS) (No.2021-I2M-1-058).
References
  1. Alkmin, S., Patankar, M. S. & Campagnola, P. J., 2022, Assessing the roles of collagen fiber morphology and matrix stiffness on ovarian cancer cell migration dynamics using multiphoton fabricated orthogonal image-based models. Acta Biomater, 153:342-354. doi: 10.1016/j.actbio.2022.09.037
  2. Lheureux, S., Braunstein, M. & Oza, A. M., 2019, Epithelial ovarian cancer: Evolution of management in the era of precision medicine. CA Cancer J Clin, 69(4):280-304. doi: 10.3322/caac.21559
  3. Vescarelli, E., Gerini, G., Megiorni, F. et al., 2020, MiR- 200c sensitizes Olaparib-resistant ovarian cancer cells by targeting Neuropilin 1. J Exp Clin Cancer Res, 39(1):3. doi: 10.1186/s13046-019-1490-7
  4. Wang, M., Zhou, J., Zhang, L. et al., 2019, Surgical treatment of ovarian cancer liver metastasis. Hepatobiliary Surg Nutr, 8(2):129-137. doi: 10.21037/hbsn.2018.12.06
  5. Herrera, F. G., Irving, M., Kandalaft, L. E. et al., 2019, Rational combinations of immunotherapy with radiotherapy in ovarian cancer. Lancet Oncol, 20(8):e417-e433. doi: 10.1016/s1470-2045(19)30401-2
  6. Raghavan, S., Mehta, P., Ward, M. R. et al., 2017, Personalized Medicine-Based Approach to Model Patterns of Chemoresistance and Tumor Recurrence Using Ovarian Cancer Stem Cell Spheroids. Clin Cancer Res, 23(22): 6934-6945. doi: 10.1158/1078-0432.CCR-17-0133
  7. Lee, A., Hudson, A. R., Shiwarski, D. J. et al., 2019, 3D bioprinting of collagen to rebuild components of the human heart. SCIENCE, 365(6452):482-487. doi: 10.1126/science.aav9051
  8. Lee, S., Sani, E. S., Spencer, A. R. et al., 2020, Human- Recombinant-Elastin-Based Bioinks for 3D Bioprinting of Vascularized Soft Tissues. Adv Mater, 32(45):e2003915. doi: 10.1002/adma.202003915
  9. Li, C., Jiang, Z. & Yang, H., 2022, Advances in 3D bioprinting technology for liver regeneration. Hepatobiliary Surg Nutr, 11(6):917-919. doi: 10.21037/hbsn-22-531
  10. Zhang, J., Yang, H. & Yang, H., 2022, Highlights of constructing liver-relevant in vitro models with 3D bioprinting. Hepatobiliary Surg Nutr, 11(6):896-898. doi: 10.21037/hbsn-22-486
  11. Neufeld, L., Yeini, E., Pozzi, S. et al., 2022, 3D bioprinted cancer models: from basic biology to drug development. Nat Rev Cancer, 22(12):679-692. doi: 10.1038/s41568-022-00514-w
  12. Tang, M., Xie, Q., Gimple, R. C. et al., 2020, Three-dimensional bioprinted glioblastoma microenvironments model cellular dependencies and immune interactions. Cell Res, 30(10):833-853. doi: 10.1038/s41422-020-0338-1
  13. Park, W., Bae, M., Hwang, M. et al., 2021, 3D Cell-Printed Hypoxic Cancer-on-a-Chip for Recapitulating Pathologic Progression of Solid Cancer. J Vis Exp, (167). doi: 10.3791/61945
  14. Hong, S. & Song, J. M., 2022, 3D bioprinted drug-resistant breast cancer spheroids for quantitative in situ evaluation of drug resistance. Acta Biomater, 138:228-239. doi: 10.1016/j.actbio.2021.10.031
  15. Mei, Y., He, C., Gao, C. et al., 2021, 3D-Printed Degradable Anti-Tumor Scaffolds for Controllable Drug Delivery. Int J Bioprint, 7(4):418. doi: 10.18063/ijb.v7i4.418
  16. Yi, H. G., Jeong, Y. H., Kim, Y. et al., 2019, A bioprinted human-glioblastoma-on-a-chip for the identification of patient-specific responses to chemoradiotherapy. Nat Biomed Eng, 3(7):509-519. doi: 10.1038/s41551-019-0363-x
  17. Shim, I. K., Yi, H. J., Yi, H. G. et al., 2017, Locally-applied 5-fluorouracil-loaded slow-release patch prevents pancreatic cancer growth in an orthotopic mouse model. Oncotarget, 8(25):40140-40151. doi: 10.18632/oncotarget.17370
  18. Hirschhaeuser, F., Menne, H., Dittfeld, C. et al., 2010, Multicellular tumor spheroids: an underestimated tool is catching up again. J Biotechnol, 148(1):3-15. doi: 10.1016/j.jbiotec.2010.01.012
  19. Abhinand, C. S., Raju, R., Soumya, S. J. et al., 2016, VEGF-A/ VEGFR2 signaling network in endothelial cells relevant to angiogenesis. J Cell Commun Signal, 10(4):347-354. doi: 10.1007/s12079-016-0352-8
  20. Sun, L., Yang, H., Wang, Y. et al., 2020, Application of a 3D Bioprinted Hepatocellular Carcinoma Cell Model in Antitumor Drug Research. Front Oncol, 10:878. doi: 10.3389/fonc.2020.00878
  21. Mao, S., He, J., Zhao, Y. et al., 2020, Bioprinting of patient-derived in vitro intrahepatic cholangiocarcinoma tumor model: establishment, evaluation and anti-cancer drug testing. Biofabrication, 12(4):045014. doi: 10.1088/1758-5090/aba0c3
  22. Xie, F., Sun, L., Pang, Y. et al., 2021, Three-dimensional bio-printing of primary human hepatocellular carcinoma for personalized medicine. BIOMATERIALS, 265:120416. doi: 10.1016/j.biomaterials.2020.120416
  23. Yang, H., Sun, L., Pang, Y. et al., 2021, Three-dimensional bioprinted hepatorganoids prolong survival of mice with liver failure. GUT, 70(3):567-574. doi: 10.1136/gutjnl-2019-319960
  24. Tebon, P. J., Wang, B., Markowitz, A. L. et al., 2023, Drug screening at single-organoid resolution via bioprinting and interferometry. Nat Commun, 14(1):3168. doi: 10.1038/s41467-023-38832-8
  25. Mazzocchi, A., Soker, S. & Skardal, A., 2019, 3D bioprinting for high-throughput screening: Drug screening, disease modeling, and precision medicine applications. Appl Phys Rev, 6(1). doi: 10.1063/1.5056188
  26. Wang, M., Zhao, J., Zhang, L. et al., 2017, Role of tumor microenvironment in tumorigenesis. J Cancer, 8(5):761-773. doi: 10.7150/jca.17648
  27. Yang, M., Lu, J., Zhang, G. et al., 2021, CXCL13 shapes immunoactive tumor microenvironment and enhances the efficacy of PD-1 checkpoint blockade in high-grade serous ovarian cancer. J Immunother Cancer, 9(1). doi: 10.1136/jitc-2020-001136
  28. Ding, Q., Dong, S., Wang, R. et al., 2020, A nine-gene signature related to tumor microenvironment predicts overall survival with ovarian cancer. Aging (Albany NY), 12(6):4879-4895. doi: 10.18632/aging.102914
  29. Di Modugno, F., Colosi, C., Trono, P. et al., 2019, 3D models in the new era of immune oncology: focus on T cells, CAF and ECM. J Exp Clin Cancer Res, 38(1):117. doi: 10.1186/s13046-019-1086-2
  30. Hinshaw, D. C. & Shevde, L. A., 2019, The Tumor Microenvironment Innately Modulates Cancer Progression. Cancer Res, 79(18):4557-4566. doi: 10.1158/0008-5472.CAN-18-3962
  31. Elhanani, O., Ben-Uri, R. & Keren, L., 2023, Spatial profiling technologies illuminate the tumor microenvironment. CANCER CELL, 41(3):404-420. doi: 10.1016/j.ccell.2023.01.010
  32. Wei, X., Lou, H., Zhou, D. et al., 2021, TAGLN mediated stiffness-regulated ovarian cancer progression via RhoA/ ROCK pathway. J Exp Clin Cancer Res, 40(1):292. doi: 10.1186/s13046-021-02091-6
  33. Kim, J., Jang, J. & Cho, D. W., 2021, Controlling Cancer Cell Behavior by Improving the Stiffness of Gastric Tissue- Decellularized ECM Bioink With Cellulose Nanoparticles. Front Bioeng Biotechnol, 9:605819. doi: 10.3389/fbioe.2021.605819
  34. Tang, M., Tiwari, S. K., Agrawal, K. et al., 2021, Rapid 3D Bioprinting of Glioblastoma Model Mimicking Native Biophysical Heterogeneity. Small, 17(15):e2006050. doi: 10.1002/smll.202006050
  35. Yang, X., Wang, G., Huang, X. et al., 2020, RNA-seq reveals the diverse effects of substrate stiffness on epidermal ovarian cancer cells. Aging (Albany NY), 12(20):20493-20511. doi: 10.18632/aging.103906
  36. Pietilä, E. A., Gonzalez-Molina, J., Moyano-Galceran, L. et al., 2021, Co-evolution of matrisome and adaptive adhesion dynamics drives ovarian cancer chemoresistance. Nat Commun, 12(1):3904. doi: 10.1038/s41467-021-24009-8
  37. Ouyang, L., Yao, R., Zhao, Y. et al., 2016, Effect of bioink properties on printability and cell viability for 3D bioplotting of embryonic stem cells. Biofabrication, 8(3):035020. doi: 10.1088/1758-5090/8/3/035020
  38. Li, C., Jin, B., Sun, H. et al., 2022, Exploring the function of stromal cells in cholangiocarcinoma by three-dimensional bioprinting immune microenvironment model. Front Immunol, 13:941289. doi: 10.3389/fimmu.2022.941289
  39. Singha, B., Gatla, H. R., Manna, S. et al., 2014, Proteasome inhibition increases recruitment of IκB kinase β (IKKβ), S536P-p65, and transcription factor EGR1 to interleukin-8 (IL-8) promoter, resulting in increased IL-8 production in ovarian cancer cells. J Biol Chem, 289(5):2687-2700. doi: 10.1074/jbc.M113.502641
  40. Javellana, M., Eckert, M. A., Heide, J. et al., 2022, Neoadjuvant Chemotherapy Induces Genomic and Transcriptomic Changes in Ovarian Cancer. Cancer Res, 82(1):169-176. doi: 10.1158/0008-5472.CAN-21-1467
  41. du Manoir, S., Delpech, H., Orsetti, B. et al., 2022, In high-grade ovarian carcinoma, platinum-sensitive tumor recurrence and acquired-resistance derive from quiescent residual cancer cells that overexpress CRYAB, CEACAM6, and SOX2. J Pathol, 257(3):367-378. doi: 10.1002/path.5896
  42. Yamawaki, K., Mori, Y., Sakai, H. et al., 2021, Integrative analyses of gene expression and chemosensitivity of patient-derived ovarian cancer spheroids link G6PD-driven redox metabolism to cisplatin chemoresistance. Cancer Lett, 521:29-38. doi: 10.1016/j.canlet.2021.08.018
  43. Kang, Y., Nagaraja, A. S., Armaiz-Pena, G. N. et al., 2016, Adrenergic Stimulation of DUSP1 Impairs Chemotherapy Response in Ovarian Cancer. Clin Cancer Res, 22(7):1713- 1724. doi: 10.1158/1078-0432.Ccr-15-1275
  44. Andreoli, M., Persico, M., Kumar, A. et al., 2014, Identification of the first inhibitor of the GBP1:PIM1 interaction. Implications for the development of a new class of anticancer agents against paclitaxel resistant cancer cells. J Med Chem, 57(19):7916-7932. doi: 10.1021/jm5009902
  45. Xiao, Y., Lai, Y., Yu, Y. et al., 2021, The Exocrine Differentiation and Proliferation Factor (EXDPF) Gene Promotes Ovarian Cancer Tumorigenesis by Up-Regulating DNA Replication Pathway. Front Oncol, 11:669603. doi: 10.3389/fonc.2021.669603
  46. Zhang, Y., Qiu, J. G., Jia, X. Y. et al., 2023, METTL3- mediated N6-methyladenosine modification and HDAC5/ YY1 promote IFFO1 downregulation in tumor development and chemo-resistance. Cancer Lett, 553:215971. doi: 10.1016/j.canlet.2022.215971
  47. Zaid, T. M., Yeung, T. L., Thompson, M. S. et al., 2013, Identification of FGFR4 as a potential therapeutic target for advanced-stage, high-grade serous ovarian cancer. Clin Cancer Res, 19(4):809-820. doi: 10.1158/1078-0432.Ccr-12-2736
  48. Brancato, V., Oliveira, J. M., Correlo, V. M. et al., 2020, Could 3D models of cancer enhance drug screening? BIOMATERIALS, 232:119744. doi: 10.1016/j.biomaterials.2019.119744
  49. Zanoni, M., Cortesi, M., Zamagni, A. et al., 2020, Modeling neoplastic disease with spheroids and organoids. J Hematol Oncol, 13(1): 97. doi: 10.1186/s13045-020-00931-0
  50. Fan, Y., Sun, Q., Li, X. et al., 2021, Substrate Stiffness Modulates the Growth, Phenotype, and Chemoresistance of Ovarian Cancer Cells. Front Cell Dev Biol, 9:718834. doi: 10.3389/fcell.2021.718834
  51. Paradiso, F., Lenna, S., Gazze, S. A. et al., 2022, Mechanomimetic 3D Scaffolds as a Humanized In Vitro Model for Ovarian Cancer. Cells, 11(5). doi: 10.3390/cells11050824
  52. Barroso, M., Chheda, M. G., Clevers, H. et al., 2022, A path to translation: How 3D patient tumor avatars enable next generation precision oncology. CANCER CELL, 40(12):1448-1453. doi: 10.1016/j.ccell.2022.09.017
  53. Kim, J., Koo, B. K. & Knoblich, J. A., 2020, Human organoids: model systems for human biology and medicine. Nat Rev Mol Cell Biol, 21(10):571-584. doi: 10.1038/s41580-020-0259-3
  54. Zanella, E. R., Grassi, E. & Trusolino, L., 2022, Towards precision oncology with patient-derived xenografts. Nat Rev Clin Oncol, 19(11):719-732. doi: 10.1038/s41571-022-00682-6
  55. Zhuo, J., Su, R., Tan, W. et al., 2020, The ongoing trends of patient-derived xenograft models in oncology. Cancer Commun (Lond), 40(11):559-563. doi: 10.1002/cac2.12096
  56. Zong, X., Wang, W., Ozes, A. et al., 2020, EZH2-Mediated Downregulation of the Tumor Suppressor DAB2IP Maintains Ovarian Cancer Stem Cells. Cancer Res, 80(20):4371-4385. doi: 10.1158/0008-5472.Can-20-0458
  57. Sacks Suarez, J., Gurler Main, H., Muralidhar, G. G. et al., 2019, CD44 Regulates Formation of Spheroids and Controls Organ-Specific Metastatic Colonization in Epithelial Ovarian Carcinoma. Mol Cancer Res, 17(9):1801-1814. doi: 10.1158/1541-7786.Mcr-18-1205
  58. Zhao, Y., He, M., Cui, L. et al., 2020, Chemotherapy exacerbates ovarian cancer cell migration and cancer stem cell-like characteristics through GLI1. Br J Cancer, 122(11):1638-1648. doi: 10.1038/s41416-020-0825-7
  59. Wang, Y., Niu, X. L., Qu, Y. et al., 2010, Autocrine production of interleukin-6 confers cisplatin and paclitaxel resistance in ovarian cancer cells. Cancer Lett, 295(1):110-123. doi: 10.1016/j.canlet.2010.02.019
  60. Klinghammer, K., Walther, W. & Hoffmann, J., 2017, Choosing wisely - Preclinical test models in the era of precision medicine. Cancer Treat Rev, 55:36-45. doi: 10.1016/j.ctrv.2017.02.009
Conflict of interest
The authors declare that the research was carried out without any commercial or financial relationships that could be perceived as a potential conflict of interest.
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International Journal of Bioprinting, Electronic ISSN: 2424-8002 Print ISSN: 2424-7723, Published by AccScience Publishing
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