Application of Microfluidic Technology in Ovarian Cancer Disease Modeling, Drug Evaluation, and Precision Medicine

doi:10.12280/gjfckx.20240523

Abstract

Abstract:

Ovarian cancer is the third most common malignant tumor of the female reproductive system worldwide, with a five-year survival rate of only 40%. The lack of early diagnostic methods and chemotherapy resistance are significant challenges in the diagnosis and treatment of ovarian cancer. Microfluidic technology, an integrated analytical technique that uses microchips to control fluid flow, offers notable advantages such as high sensitivity, high throughput and low cost. Additionally, this technology can simulate the tumor microenvironment at the micro/nanoscale, facilitating the study of interactions between tumor cells and the immune system. In recent years, microfluidic technology has been widely used in medical research, drug development, and precision medicine, among other areas of life science. In the context of ovarian cancer research, microfluidic technology can be utilized for tumor modeling, early detection of tumor biomarkers, and screening of anti-cancer drugs, providing innovative perspective and future directions for early diagnosis and precision treatment of ovarian cancer.

Key words: Ovarian neoplasms, Lab-on-a-chip devices, Tumor microenvironment, Drug screening assays, antitumor, Precision medicine, Microfluidic technology

ZHANG Jian-nan, GUO Xin, GUO Nan, NING Wen-ting, YU Hong-xin, SHANG Hai-xia. Application of Microfluidic Technology in Ovarian Cancer Disease Modeling, Drug Evaluation, and Precision Medicine[J]. Journal of International Obstetrics and Gynecology, 2024, 51(5): 560-565.

References 38

[1]	Siegel RL, Miller KD, Wagle NS, et al. Cancer statistics, 2023[J]. CA Cancer J Clin, 2023, 73(1):17-48. doi: 10.3322/caac.21763.
[2]	郑荣寿, 陈茹, 韩冰峰, 等. 2022年中国恶性肿瘤流行情况分析[J]. 中华肿瘤杂志, 2024, 46(3):221-231. doi: 10.3760/cma.j.cn112152-20240119-00035.
[3]	Chliara MA, Elezoglou S, Zergioti I. Bioprinting on Organ-on-Chip: Development and Applications[J]. Biosensors(Basel), 2022, 12(12):1135. doi: 10.3390/bios12121135.
[4]	Ren K, Zhou J, Wu H. Materials for microfluidic chip fabrication[J]. Acc Chem Res, 2013, 46(11):2396-2406. doi: 10.1021/ar300314s.
[5]	Ko J, Song J, Lee Y, et al. Understanding organotropism in cancer metastasis using microphysiological systems[J]. Lab Chip, 2024, 24(6):1542-1556. doi: 10.1039/d3lc00889d. pmid: 38192269
[6]	Huang D, Man J, Jiang D, et al. Inertial microfluidics: Recent advances[J]. Electrophoresis, 2020, 41(24):2166-2187. doi: 10.1002/elps.202000134.
[7]	孙漩嵘, 徐卓敏, 蔡悦. 微流控技术在纳米药物载体制备中的应用[J]. 中国药学杂志, 2020, 55(8):573-579. doi: 10.11669/cpj.2020.08.001.
[8]	Ibrahim LI, Hajal C, Offeddu GS, et al. Omentum-on-a-chip: A multicellular, vascularized microfluidic model of the human peritoneum for the study of ovarian cancer metastases[J]. Biomaterials, 2022,288:121728. doi: 10.1016/j.biomaterials.2022.121728.
[9]	Aleman J, Skardal A. A multi-site metastasis-on-a-chip microphysiological system for assessing metastatic preference of cancer cells[J]. Biotechnol Bioeng, 2019, 116(4):936-944. doi: 10.1002/bit.26871. pmid: 30450540
[10]	Na JT, Hu SY, Xue CD, et al. A microfluidic system for precisely reproducing physiological blood pressure and wall shear stress to endothelial cells[J]. Analyst, 2021, 146(19):5913-5922. doi: 10.1039/d1an01049b.
[11]	Mi F, Hu C, Wang Y, et al. Recent advancements in microfluidic chip biosensor detection of foodborne pathogenic bacteria: a review[J]. Anal Bioanal Chem, 2022, 414(9):2883-2902. doi: 10.1007/s00216-021-03872-w.
[12]	Baka Z, Stiefel M, Figarol A, et al. Cancer-on-chip technology: current applications in major cancer types, challenges and future prospects[J]. Prog Biomed Eng, 2022, 4(3):032001. doi:10.1088/2516-1091/ac8259.
[13]	Davoodi E, Sarikhani E, Montazerian H, et al. Extrusion and Microfluidic-based Bioprinting to Fabricate Biomimetic Tissues and Organs[J]. Adv Mater Technol, 2020, 5(8):1901044. doi: 10.1002/admt.201901044.
[14]	Li Z, Xu X, Wang D, et al. Recent advancements in nucleic acid detection with microfluidic chip for molecular diagnostics[J]. Trends Analyt Chem, 2023,158:116871. doi: 10.1016/j.trac.2022.116871.
[15]	Li SS, Ip CK, Tang MY, et al. Modeling Ovarian Cancer Multicellular Spheroid Behavior in a Dynamic 3D Peritoneal Microdevice[J]. J Vis Exp, 2017(120):55337. doi: 10.3791/55337.
[16]	Saha B, Mathur T, Tronolone JJ, et al. Human tumor microenvironment chip evaluates the consequences of platelet extravasation and combinatorial antitumor-antiplatelet therapy in ovarian cancer[J]. Sci Adv, 2021, 7(30):eabg5283. doi: 10.1126/sciadv.abg5283.
[17]	Surendran V, Rutledge D, Colmon R, et al. A novel tumor-immune microenvironment (TIME)-on-Chip mimics three dimensional neutrophil-tumor dynamics and neutrophil extracellular traps (NETs)-mediated collective tumor invasion[J]. Biofabrication, 2021, 13(3):10.1088/1758-5090/abe1cf. doi: 10.1088/1758-5090/abe1cf.
[18]	Scott AL, Jazwinska DE, Kulawiec DG, et al. Paracrine Ovarian Cancer Cell-Derived CSF1 Signaling Regulates Macrophage Migration Dynamics in a 3D Microfluidic Model that Recapitulates In Vivo Infiltration Patterns in Patient-Derived Xenografts[J]. Adv Healthc Mater,2024 May 28:e2401719. doi: 10.1002/adhm.202401719.
[19]	Wimalachandra DC, Li Y, Liu J, et al. Microfluidic-Based Immunomodulation of Immune Cells Using Upconversion Nanoparticles in Simulated Blood Vessel-Tumor System[J]. ACS Appl Mater Interfaces, 2019, 11(41):37513-37523. doi: 10.1021/acsami.9b15178.
[20]	Libbrecht S, Vankerckhoven A, de Wijs K, et al. A Microfluidics Approach for Ovarian Cancer Immune Monitoring in an Outpatient Setting[J]. Cells, 2023, 13(1):7. doi: 10.3390/cells13010007.
[21]	Ip CK, Li SS, Tang MY, et al. Stemness and chemoresistance in epithelial ovarian carcinoma cells under shear stress[J]. Sci Rep, 2016,6:26788. doi: 10.1038/srep26788.
[22]	Hassan AA, Artemenko M, Tang M, et al. Ascitic fluid shear stress in concert with hepatocyte growth factor drive stemness and chemoresistance of ovarian cancer cells via the c-Met-PI3K/Akt-miR-199a-3p signaling pathway[J]. Cell Death Dis, 2022, 13(6):537. doi: 10.1038/s41419-022-04976-6. pmid: 35676254
[23]	Saadati A, Soodabeh H, Fanaz B, et al. A novel biosensor for the monitoring of ovarian cancer tumor protein CA 125 in untreated human plasma samples using a novel nano-ink: a new platform for efficient diagnosis of cancer using paper based microfluidic technology[J]. Anal Methods, 2020, 12:1639-1649. doi:10.1039/d0ay00299b.
[24]	Wu Y, Wang C, Wang P, et al. A high-performance microfluidic detection platform to conduct a novel multiple-biomarker panel for ovarian cancer screening[J]. RSC Adv, 2021, 11(14):8124-8133. doi: 10.1039/d0ra10200h. pmid: 35423342
[25]	Kalluri R, LeBleu VS. The biology, function, and biomedical applications of exosomes[J]. Science, 2020, 367(6478):eaau6977. doi: 10.1126/science.aau6977.
[26]	Shi J. Considering Exosomal miR-21 as a Biomarker for Cancer[J]. J Clin Med, 2016, 5(4):42. doi: 10.3390/jcm5040042.
[27]	Sung CY, Huang CC, Chen YS, et al. Isolation and quantification of extracellular vesicle-encapsulated microRNA on an integrated microfluidic platform[J]. Lab Chip, 2021, 21(23):4660-4671. doi: 10.1039/d1lc00663k.
[28]	Zhang P, Zhou X, He M, et al. Ultrasensitive detection of circulating exosomes with a 3D-nanopatterned microfluidic chip[J]. Nat Biomed Eng, 2019, 3(6):438-451. doi: 10.1038/s41551-019-0356-9. pmid: 31123323
[29]	Zhao Z, Yang Y, Zeng Y, et al. A microfluidic ExoSearch chip for multiplexed exosome detection towards blood-based ovarian cancer diagnosis[J]. Lab Chip, 2016, 16(3):489-496. doi: 10.1039/c5lc01117e. pmid: 26645590
[30]	Kim H, Lim M, Kim JY, et al. Circulating Tumor Cells Enumerated by a Centrifugal Microfluidic Device as a Predictive Marker for Monitoring Ovarian Cancer Treatment: A Pilot Study[J]. Diagnostics(Basel), 2020, 10(4):249. doi: 10.3390/diagnostics10040249.
[31]	Jou HJ, Chou LY, Chang WC, et al. An Automatic Platform Based on Nanostructured Microfluidic Chip for Isolating and Identification of Circulating Tumor Cells[J]. Micromachines(Basel), 2021, 12(5):473. doi: 10.3390/mi12050473.
[32]	Wang HF, Liu Y, Wang T, et al. Tumor-Microenvironment-on-a-Chip for Evaluating Nanoparticle-Loaded Macrophages for Drug Delivery[J]. ACS Biomater Sci Eng, 2020, 6(9):5040-5050. doi: 10.1021/acsbiomaterials.0c00650.
[33]	Arellano JA, Howell TA, Gammon J, et al. Use of a highly parallel microfluidic flow cell array to determine therapeutic drug dose response curves[J]. Biomed Microdevices, 2017, 19(2):25. doi: 10.1007/s10544-017-0166-3. pmid: 28378146
[34]	Dadgar N, Gonzalez-Suarez AM, Fattahi P, et al. A microfluidic platform for cultivating ovarian cancer spheroids and testing their responses to chemotherapies[J]. Microsyst Nanoeng, 2020,6:93. doi: 10.1038/s41378-020-00201-6.
[35]	VandenHeuvel SN, Chau E, Mohapatra A, et al. Macrophage Checkpoint Nanoimmunotherapy Has the Potential to Reduce Malignant Progression in Bioengineered In Vitro Models of Ovarian Cancer[J]. ACS Appl Bio Mater,2024 Apr 1. doi: 10.1021/acsabm.4c00076.
[36]	Buckley M, Kramer M, Johnson B, et al. Mechanical activation and expression of HSP27 in epithelial ovarian cancer[J]. Sci Rep, 2024, 14(1):2856. doi: 10.1038/s41598-024-52992-7.
[37]	Simeone K, Guay-Lord R, Lateef MA, et al. Paraffin-embedding lithography and micro-dissected tissue micro-arrays: tools for biological and pharmacological analysis of ex vivo solid tumors[J]. Lab Chip, 2019, 19(4):693-705. doi: 10.1039/c8lc00982a. pmid: 30671574
[38]	Xin L, Xiao W, Che L, et al. Label-Free Assessment of the Drug Resistance of Epithelial Ovarian Cancer Cells in a Microfluidic Holographic Flow Cytometer Boosted through Machine Learning[J]. ACS Omega, 2021, 6(46):31046-31057. doi: 10.1021/acsomega.1c04204. pmid: 34841147