3D printing for the quantitative evaluation of anticancer agent against cancer stem cell文献综述

 2022-12-24 13:37:59

开题报告内容Content：（包括拟研究或解决的问题、采用的研究手段及文献综述，不少于2000字）Including objectives, methods adopted and literature review, no less than 2000 words

The tumor microenvironment is very complex with interactions between the cells and the extra-cellular components, and has profound effect on therapeutic response and clinical outcome.[1,2] The tumor microenvironment composed of various cell types and extra-cellular components that are surrounding tumor cells. The extra-cellular matrix (ECM) mainly composed of collagen, providing physical support for cell attachment, proliferation and migration. And stromal cells like cancer-associated fibroblasts, adipocytes, endothelial, and immune cells also play pivotal role in tumor progression and metastasis. Tumors that have dense collagen structure in stroma exhibit lower drug penetration.[3,4] Therefore, the composition and organization of the ECM can form a physical barrier for drug delivery and affect the treatments. And the attachment of tumor cells to stromal or to extracellular matrix components can also blunt therapeutic response. In addition, soluble factors such as TGF-beta;1 and IL-6 secreted by cancer associated fibroblasts also contribute to the drug resistance.[5-8] Tumor vasculature which provide oxygen and nutrient and significantly influence the growth and metastasis of tumors. Compared with the vascular network in healthy tissue, tumor vasculature shows abnormal morphology. Accordingly, distance from vascular beds has been shown to be crucial for the distribution of drugs to all cells in the tumor.[9] Moreover, density of microvessels and expression of the VEGF are also reported as crucial prognostic factors for poor outcome in various cancers.[10,11]

Nowadays, the main challenge in developing new anti-cancer agents is the discrepancy in the in vitro to in vivo efficacy of candidates drugs. New anticancer agents and therapeutic targets currently under development are usually evaluated using 2D cell cultures of diseased human cells or animal models such as xenograft models , chemically induced models and genetically modified models during the preclinical trial phase.[12]Obviously, monolayer models are lack of spatial complexity to represent human physiological conditions.[13] Thus 2D tumor models are too simple to recapitulate the 3D tumor microenvironment and cancer cells poorly retain their original phenotype. Compared with 2D models, animal models are physiologically competent. However, animal models are costly expensive and always related to moral problems. In addition, they may probably lead to an incorrect predictions about the drug efficacy due to species difference between humans and animals.[14] Therefore, researchers turned to 3D in vitro tumor models to overcome these problems.

3D bioprinting can be defined as the simultaneous depositing of living cells and bioinks with a prescribed layer-by-layer stacking organization to fabricate bioengineered constructs. 3D bioprinting not only has the ability to deliver various types of cells with multiple biological components, but provide a single step fabrication process to produce biomimetic tissue with vascular networks.[16,17]. Therefore, this technology has a lot of advantages in fabricating in vitro tumor models of high biological and physiological relevance. According to the depositing method, bioprinting processes are divided into laser-assisted printing, stereolithography(SLA)-based printing, jetting-based printing and extrusion-based printing.[18-20]

3D bioprinted in vitro tumor models not only can reduce the number of needed animals to cut the cost of the preclinical trials, but also can predict the efficacy of the anti-cancer agents more accurately. Therefore during this period I will learn about the 3D bioprinting and in vitro tumor engineering method, then provide an overview of different types of tumor models constructed by 3D bioprinting technology including commonly used models like spheroids and other more complicated tumor mimicking models containing vascular networks, discuss the merits and demerits of these models and whether they can recapitulate the tumor microenironment.

Reference:

  1. Ting Wu, Yun Dai, Tumor microenvironment and therapeutic response, Cancer Letters[J], 2017,387: 61-68.
  2. Gokhan Bahcecioglu, Gozde Basara, Bradley W Ellis, Xiang Ren, Pinar Zorlutuna,Breast cancer models: Engineering the tumor microenvironment,Acta Biomaterialia [J], 2020,106:1-21.
  3. R. Grantab, S. Sivananthan, I.F. Tannock The penetration of anticancer drugs through tumor tissue as a function of cellular adhesion and packing density of tumor cells Cancer Res [J], 2006, 66:1033-1039.
  4. P.A. Netti, D.A. Berk, M.A. Swartz, A.J. Grodzinsky, R.K. Jain Role of extracellular matrix assembly in interstitial transport in solid tumors Cancer Res [J], 2000, 60: 2497-2503
  5. N. Erez, S. Glanz, Y. Raz, C. Avivi, I. Barshack Cancer associated fibroblasts express pro-inflammatory factors in human breast and ovarian tumors Biochem. Biophys. Res. Commun [J], 2013, 437: 397-402.
  6. K.H. Paraiso, K.S. Smalley Fibroblast-mediated drug resistance in cancer Biochem. Pharmacol [J], 2013, 85:1033-1041.
  7. J.K. Mulligan, T.A. Day, M.B. Gillespie, S.A. Rosenzweig, M.R. Young Secretion of vascular endothelial growth factor by oral squamous cell carcinoma cells skews endothelial cells to suppress T-cell functions Hum. Immunol, 2009, 70: 375-382.
  8. J.K. Mulligan, M.R. Young Tumors induce the formation of suppressor endothelial cells in vivo Cancer Immunol. Immunother, 2010, 59: 267-277.
  9. O. Tredan, C.M. Galmarini, K. Patel, I.F. Tannock Drug resistance and the solid tumor microenvironment Natl. Cancer Inst, 2007, 99:1441-1454.
  10. P. Zhan, J. Wang, X.J. Lv, Q. Wang, L.X. Qiu, X.Q. Lin, et al. Prognostic value of vascular endothelial growth factor expression in patients with lung cancer: a systematic review with meta-analysis Thorac. Oncol, 2009, 4:1094-1103.
  11. G. Des Guetz, B. Uzzan, P. Nicolas, M. Cucherat, J.F. Morere, R. Benamouzig, et al. Microvessel density and VEGF expression are prognostic factors in colorectal cancer. Meta-analysis of the literature Br. J. Cancer, 2006, (94):1823-1832
  12. P. McGonigle, B. Ruggeri, Animal models of human disease: Challenges in enabling translation,Biochemical Pharmacology,2014, 87:162-171.
  13. Derek Yip, Cheul H. Cho, A multicellular 3D heterospheroid model of liver tumor and stromal cells in collagen gel for anti-cancer drug testing, Biochemical and Biophysical Research Communications, 2013, 433(3):327-332.
  14. Mak I.W., Evaniew N., Ghert M. Lost in translation: animal models and clinical trials in cancer treatment. Am J Transl Res, 2014,6: 114-118.
  15. Son, B.; Lee, S.; Youn, H.; Kim, E.; Kim, W.; Youn, B. The role of tumor microenvironment in therapeutic resistance. Oncotarget, 2017, 8:3933.
  16. J.S. Miller, K.R. Stevens, M.T. Yang, B.M. Baker, D.-H.T. Nguyen, D.M. Cohen, E. Toro, A.A. Chen, P.A. Galie, X. Yu, Rapid casting of patterned vascular networks for perfusable engineered three-dimensional tissues, Nat. Mater. 2012, 11 (9): 768-774.
  17. D.B. Kolesky, K.A. Homan, M.A. Skylar-Scott, J.A. Lewis, Three-dimensional bioprinting of thick vascularized tissues, Proc. Natl. Acad. Sci., 2016, 113 (12) : 3179-3184.
  18. Ozler SB, Bakirci E, Kucukgul C, Koc B. Three-dimensional direct cell bioprinting for tissue engineering. J Biomed Mater Res B Appl Biomater. 2017;105(8):2530‐2544.
  19. S.V. Murphy, A. Atala, 3D bioprinting of tissues and organs, Nat. Biotechnol. 2014, 32 (8) : 773-785.
  20. C. Mandrycky, Z. Wang, K. Kim, D.-H. Kim, 3D bioprinting for engineering complex tissues, Biotechnol. Adv. 2016, 34 (4):422-434.

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