腫瘤治療中的抗藥性問題一直是個重大挑戰，對於治療結果和癌症復發的預後產生重要的影響。肺癌患者經常面臨癌症藥物產生抗藥性的困境，這表示原本對治療藥物敏感的癌細胞不再對其產生反應，從而使治療效果降低或無法有效控制疾病進展。眾多研究指出腫瘤異質性是導致抗藥性的主要原因之一。
在本研究中，提出了一種仿肺腫瘤實驗室微晶片，旨在探究這一問題。通過晶片高斯結構的設計，成功實現了腫瘤微環境中的基質細胞在晶片各個腔室中的數量上呈現高斯分布，並與肺癌細胞進行共培養以模擬多種腫瘤異質性的情況。同時，我們運用介電泳技術使癌細胞與基質細胞能夠緊密排列，並利用生物相容性的光固化水膠GelMA提供細胞生長支架以更貼近真實肺腫瘤的環境。
透過實驗結果的分析，觀察到共培養中纖維母細胞比例的增加會使癌細胞對藥物產生更強抵抗能力。特別是HCC827癌細胞與Wi38纖維母細胞比例為1比2.57時，相較於1比0.56的組別而言，癌細胞存活率由56.3%上升至68.5%。結果顯示腫瘤微環境中的纖維母細胞扮演重要角色，可能透過產生細胞外基質形成保護環境，降低藥物療效。綜上所述，本研究成功開發了仿肺腫瘤微晶片，驗證了基質細胞在腫瘤微環境中的抗藥性影響。此微流體晶片為深入研究腫瘤異質性和抗藥性提供了一個重要的研究工具，同時有助於癌症研究和新藥開發。期望這些成果有助於對抗藥性機制的理解，改善肺癌患者的治療效果和生活品質。

The issue of drug resistance in tumor treatment has always been a major challenge, with significant implications for treatment outcomes and cancer recurrence. Lung cancer patients often face the dilemma of drug resistance, where cancer cells that were once sensitive to treatment drugs no longer respond to them, leading to reduced treatment efficacy and ineffective disease control. Numerous studies have identified tumor heterogeneity as one of the main causes of drug resistance.
In this study, we propose a lung-tumor-mimicking microfluidic chip to investigate this problem. By designing a Gaussian structure in the chip, we successfully achieved a Gaussian distribution of stromal cells in different chambers, mimicking various tumor microenvironment conditions. Additionally, we employed dielectrophoresis technology to tightly arrange cancer cells and stromal cells while utilizing the biocompatible photopolymer GelMA as a cell growth scaffold to mimic the real lung tumor environment better.
Through the analysis of experimental results, it was observed that an increased proportion of fibroblast cells in the co-culture process enhanced the drug resistance capabilities of cancer cells, resulting in higher survival rates. In summary, this study successfully developed a lung tumor mimicking microfluidic chip and demonstrated the significant impact of stromal cells on drug resistance in the tumor microenvironment. The proposed microfluidic chip platform provides a valuable research tool for investigating the influence of different tumor microenvironments on drug resistance. It offers a valuable testing platform for cancer research and drug development. These research findings are expected to contribute to a better understanding of the mechanisms underlying drug resistance, accelerate the development and screening of new drugs, and ultimately improve treatment outcomes and quality of life for lung cancer patients.

1. Ferlay, J., et al., Cancer statistics for the year 2020: An overview. International journal of cancer, 2021. 149(4): p. 778-789.
2. Perez-Warnisher, M.T., M.P.C. de Miguel, and L.M. Seijo, Tobacco use worldwide: legislative efforts to curb consumption. Annals of global health, 2018. 84(4): p. 571.
3. Tseng, C.-H., et al., The relationship between air pollution and lung cancer in nonsmokers in Taiwan. Journal of Thoracic Oncology, 2019. 14(5): p. 784-792.
4. Air Pollution and Cancer. Available from: http://publications.iarc.fr/_publications/media/download/3692/e67ee17589f8759dc6d811c03c7b061a11827ee3.pdf.
5. Judy, J.W., Microelectromechanical systems (MEMS): fabrication, design and applications. Smart materials and Structures, 2001. 10(6): p. 1115.
6. Phan, H.P., et al., Robust free‐standing nano‐thin SiC membranes enable direct photolithography for MEMS sensing applications. Advanced Engineering Materials, 2018. 20(1): p. 1700858.
7. The Future of MEMS. Available from: https://www.semi.org/en/blogs/technology-trends/the-future-of-mems.
8. Beebe, D.J., et al., Microfluidic tectonics: a comprehensive construction platform for microfluidic systems. Proceedings of the National Academy of Sciences, 2000. 97(25): p. 13488-13493.
9. Du, G., Q. Fang, and J.M. den Toonder, Microfluidics for cell-based high throughput screening platforms—A review. Analytica chimica acta, 2016. 903: p. 36-50.
10. Srinivasan, V., V.K. Pamula, and R.B. Fair, An integrated digital microfluidic lab-on-a-chip for clinical diagnostics on human physiological fluids. Lab on a Chip, 2004. 4(4): p. 310-315.
11. Medzhitov, R., Origin and physiological roles of inflammation. Nature, 2008. 454(7203): p. 428-435.
12. Grivennikov, S.I., F.R. Greten, and M. Karin, Immunity, inflammation, and cancer. Cell, 2010. 140(6): p. 883-899.
13. Singh, N., et al., Inflammation and cancer. Annals of African Medicine, 2019. 18(3): p. 121.
14. Cancer. Available from:
https://www.who.int/en/news-room/fact-sheets/detail/cancer.
15. Cao, Y., et al., Population-wide impact of long-term use of aspirin and the risk for cancer. JAMA Oncology, 2016. 2(6): p. 762-769.
16. Dubin, S. and D. Griffin, Lung cancer in non-smokers. Missouri Medicine, 2020. 117(4): p. 375.
17. What is Non-Small Cell Lung Carcinoma. Available from: https://2020.igem.org/Team:iBowu-China/Description.
18. Malhotra, J., et al., Risk factors for lung cancer worldwide. European Respiratory Journal, 2016. 48(3): p. 889-902.
19. Akhtar, N. and J.G. Bansal, Risk factors of Lung Cancer in nonsmoker. Current problems in cancer, 2017. 41(5): p. 328-339.
20. Omar Lababede, M., M. W Richard Webb, and M. Eugene C Lin, Imaging in Lung Cancer Staging 2019: Medscape.
21. Spill, F., et al., Impact of the physical microenvironment on tumor progression and metastasis. Current opinion in biotechnology, 2016. 40: p. 41-48.
22. Zhang, J. and N. Veeramachaneni, Targeting interleukin-1β and inflammation in lung cancer. Biomarker Research, 2022. 10(1): p. 1-9.
23. Correia, A.L. and M.J. Bissell, The tumor microenvironment is a dominant force in multidrug resistance. Drug resistance updates, 2012. 15(1-2): p. 39-49.
24. Schultz, G.S., G. Ladwig, and A. Wysocki, Extracellular matrix: review of its roles in acute and chronic wounds. World wide wounds, 2005. 2005: p. 1-18.
25. Bani, M., et al., Contribution of tumor endothelial cells to drug resistance: anti-angiogenic tyrosine kinase inhibitors act as p-glycoprotein antagonists. Angiogenesis, 2017. 20(2): p. 233-241.
26. Bergers, G., et al., Benefits of targeting both pericytes and endothelial cells in the tumor vasculature with kinase inhibitors. The Journal of clinical investigation, 2003. 111(9): p. 1287-1295.
27. Quail, D.F. and J.A. Joyce, Microenvironmental regulation of tumor progression and metastasis. Nature Medicine, 2013. 19(11): p. 1423-1437.
28. Chen, Y., et al., Tumor-associated macrophages: an accomplice in solid tumor progression. Journal of biomedical science, 2019. 26(1): p. 1-13.
29. Gordon, S.R., et al., PD-1 expression by tumour-associated macrophages inhibits phagocytosis and tumour immunity. Nature, 2017. 545(7655): p. 495-499.
30. Kogure, A., N. Kosaka, and T. Ochiya, Cross-talk between cancer cells and their neighbors via miRNA in extracellular vesicles: an emerging player in cancer metastasis. Journal of biomedical science, 2019. 26(1): p. 1-8.
31. Chen, X. and E. Song, Turning foes to friends: targeting cancer-associated fibroblasts. Nature reviews Drug discovery, 2019. 18(2): p. 99-115.
32. Liu, T., et al., Cancer-associated fibroblasts: an emerging target of anti-cancer immunotherapy. Journal of hematology & oncology, 2019. 12(1): p. 1-15.
33. Kalluri, R., The biology and function of fibroblasts in cancer. Nature Reviews Cancer, 2016. 16(9): p. 582-598.
34. Chen, C., et al., Role of cancer‑associated fibroblasts in the resistance to antitumor therapy, and their potential therapeutic mechanisms in non‑small cell lung cancer. Oncology Letters, 2021. 21(5): p. 1-12.
35. Sun, X.-x. and Q. Yu, Intra-tumor heterogeneity of cancer cells and its implications for cancer treatment. Acta Pharmacologica Sinica, 2015. 36(10): p. 1219-1227.
36. Burrell, R.A., et al., The causes and consequences of genetic heterogeneity in cancer evolution. Nature, 2013. 501(7467): p. 338-345.
37. Gillies, R.J., D. Verduzco, and R.A. Gatenby, Evolutionary dynamics of carcinogenesis and why targeted therapy does not work. Nature Reviews Cancer, 2012. 12(7): p. 487-493.
38. Junttila, M.R. and F.J. De Sauvage, Influence of tumour micro-environment heterogeneity on therapeutic response. Nature, 2013. 501(7467): p. 346-354.
39. Ramón y Cajal, S., et al., Clinical implications of intratumor heterogeneity: challenges and opportunities. Journal of Molecular Medicine, 2020. 98: p. 161-177.
40. Gerber, D.E., Targeted therapies: a new generation of cancer treatments. American family physician, 2008. 77(3): p. 311-319.
41. Yuan, M., et al., The emerging treatment landscape of targeted therapy in non-small-cell lung cancer. Signal transduction and targeted therapy, 2019. 4(1): p. 61.
42. Tan, C.-S., et al., Third generation EGFR TKIs: current data and future directions. Molecular cancer, 2018. 17(1): p. 1-14.
43. Tian, G., et al., The overall survival benefit in Chinese ALK+ NSCLC patients received targeted therapies. Journal of Thoracic Disease, 2022. 14(6): p. 2201.
44. Ou, X., et al., Microfluidic chip electrophoresis for biochemical analysis. Journal of separation science, 2020. 43(1): p. 258-270.
45. Zhang, Y., et al., An all-in-one microfluidic device for parallel DNA extraction and gene analysis. Biomedical microdevices, 2010. 12: p. 1043-1049.
46. Sonnenberg, A., et al., Rapid electrokinetic isolation of cancer-related circulating cell-free DNA directly from blood. Clinical chemistry, 2014. 60(3): p. 500-509.
47. Cao, Z., et al., Dielectrophoresis‐based protein enrichment for a highly sensitive immunoassay using Ag/SiO2 nanorod arrays. Small, 2018. 14(12): p. 1703265.
48. Hughes, M.P., Fifty years of dielectrophoretic cell separation technology. Biomicrofluidics, 2016. 10(3).
49. Henslee, E.A., et al., Selective concentration of human cancer cells using contactless dielectrophoresis. Electrophoresis, 2011. 32(18): p. 2523-2529.
50. Park, S., et al., Continuous dielectrophoretic bacterial separation and concentration from physiological media of high conductivity. Lab on a Chip, 2011. 11(17): p. 2893-2900.
51. Yang, F., et al., Extraction of cell‐free whole blood plasma using a dielectrophoresis‐based microfluidic device. Biotechnology journal, 2019. 14(3): p. 1800181.
52. Moon, H.-S., et al., Continuous separation of breast cancer cells from blood samples using multi-orifice flow fractionation (MOFF) and dielectrophoresis (DEP). Lab on a Chip, 2011. 11(6): p. 1118-1125.
53. Punjiya, M., et al., A flow through device for simultaneous dielectrophoretic cell trapping and AC electroporation. Scientific Reports, 2019. 9(1): p. 11988.
54. Huang, K., et al., Microchip system for patterning cells on different substrates via negative dielectrophoresis. IEEE Transactions on Biomedical Circuits and Systems, 2019. 13(5): p. 1063-1074.
55. D'Amico, L., et al., Isolation and concentration of bacteria from blood using microfluidic membraneless dialysis and dielectrophoresis. Lab on a Chip, 2017. 17(7): p. 1340-1348.
56. Ding, J., et al., Concentration of Sindbis virus with optimized gradient insulator-based dielectrophoresis. Analyst, 2016. 141(6): p. 1997-2008.
57. Iswardy, E., et al., A bead-based immunofluorescence-assay on a microfluidic dielectrophoresis platform for rapid dengue virus detection. Biosensors and Bioelectronics, 2017. 95: p. 174-180.
58. Ibsen, S., et al., Recovery of drug delivery nanoparticles from human plasma using an electrokinetic platform technology. Small, 2015. 11(38): p. 5088-5096.
59. Fundamentals of Probability and Statistics, 2/e (Paperback).
60. Probability density function for the normal distribtion. Available from: https://zh.wikipedia.org/wiki/%E6%AD%A3%E6%80%81%E5%88%86%E5%B8%83#/media/File:Normal_Distribution_PDF.svg.
61. Natural Inheritance. Available from:
https://galton.org/books/natural-inheritance/pdf/galton-nat-inh-1up-clean.pdf.
62. Pohl, H.A., The motion and precipitation of suspensoids in divergent electric fields. Journal of Applied Physics, 1951. 22(7): p. 869-871.
63. Lapizco‐Encinas, B.H., On the recent developments of insulator‐based dielectrophoresis: A review. Electrophoresis, 2019. 40(3): p. 358-375.
64. Cummings, E.B. and A.K. Singh, Dielectrophoresis in microchips containing arrays of insulating posts: theoretical and experimental results. Analytical Chemistry, 2003. 75(18): p. 4724-4731.
65. Gagnon, Z.R., Cellular dielectrophoresis: Applications to the characterization, manipulation, separation and patterning of cells. ELECTROPHORESIS, 2011. 32(18): p. 2466-2487.
66. Kuzyk, A., Dielectrophoresis at the nanoscale. Electrophoresis, 2011. 32(17): p. 2307-2313.
67. Zhang, H., H. Chang, and P. Neuzil, DEP-on-a-chip: Dielectrophoresis applied to microfluidic platforms. Micromachines, 2019. 10(6): p. 423.
68. Guo, J., H. Zeng, and Y. Chen, Emerging nano drug delivery systems targeting cancer-associated fibroblasts for improved antitumor effect and tumor drug penetration. Molecular pharmaceutics, 2020. 17(4): p. 1028-1048.
69. Plava, J., et al., Recent advances in understanding tumor stroma-mediated chemoresistance in breast cancer. Molecular cancer, 2019. 18: p. 1-10.
70. Sun, M., et al., Synthesis and properties of gelatin methacryloyl (GelMA) hydrogels and their recent applications in load-bearing tissue. Polymers, 2018. 10(11): p. 1290.
71. Chen, Y.C., et al., Functional human vascular network generated in photocrosslinkable gelatin methacrylate hydrogels. Advanced functional materials, 2012. 22(10): p. 2027-2039.
72. Yue, K., et al., Synthesis, properties, and biomedical applications of gelatin methacryloyl (GelMA) hydrogels. Biomaterials, 2015. 73: p. 254-271.
73. CCK-8 protocol.; Available from: https://www.dojindo.eu.com/TechnicalManual/Manual_CK04.pdf.
74. Naumov, G.N., et al., Combined vascular endothelial growth factor receptor and epidermal growth factor receptor (EGFR) blockade inhibits tumor growth in xenograft models of EGFR inhibitor resistance. Clinical Cancer Research, 2009. 15(10): p. 3484-3494.
75. Mukohara, T., et al., Differential effects of gefitinib and cetuximab on non–small-cell lung cancers bearing epidermal growth factor receptor mutations. Journal of the National Cancer Institute, 2005. 97(16): p. 1185-1194.