类器官技术在卵巢癌药敏检测中的应用

doi:10.12280/gjfckx.20210949

摘要/Abstract

摘要：

卵巢癌是致死率最高的妇科恶性肿瘤,由于大多数卵巢癌患者在早期缺乏特异的症状和可靠的生物标志,约70%的卵巢癌患者在确诊时已经是晚期。现有的卵巢癌临床前研究模型包括细胞系、动物模型以及患者来源的肿瘤异种移植（patient-derived xenograft）模型和类器官（patient-derived organoid）等。传统的临床前模型具有其局限性,而类器官可以很好地维持原肿瘤的异质性,能模拟肿瘤生长的微环境,因此近年来其研究热度只增不减。目前,类器官主要应用在癌症的机制研究、预后预测和药物筛选等方面。但迄今为止,类器官培养技术还未完全成熟,为了克服类器官的局限性,3D共培养技术、微流体技术应运而生。综述类器官的起源、类器官在卵巢癌研究中的优势与局限性以及类器官在卵巢癌药敏检测中的应用。

关键词: 类器官, 药物筛选试验,抗肿瘤, 卵巢肿瘤, 癌, 个性化治疗

Abstract:

Ovarian cancer has the highest fatality rate among gynecologic malignant tumors. Because the majority of ovarian cancer patients lack of specific symptoms and reliable biomarkers in the early stage, about 70% of patients are diagnosed at an advanced stage. The already existing preclinical models of ovarian cancer include cancer cell lines, animal models, patient-derived xenograft, patient-derived organoid, etc. The traditional preclinical models have their limitations. Therefore, in recent years, organoids are very popular as they can maintain the heterogeneities of the original tumors and simulate tumor microenvironment. At present, organoids are mainly used in cancer mechanism research, prognosis prediction, drug screening and so on. But so far, the technology of organoid has not been fully mature. In order to overcome the origin of organoid, 3D organoid culture system and microfluidics have come into being. The article will introduce the origin of organoid, the advantages and limitations of organoid in ovarian cancer research, and the application of organoid in the ovarian cancer drug sensitivity test.

Key words: Organoids, Drug screening assays,antitumor, Ovarian neoplasms, Carcinoma, Individualized treatment

汪娅妮, 姜琦, 张雨晨, 诸海燕. 类器官技术在卵巢癌药敏检测中的应用[J]. 国际妇产科学杂志, 2022, 49(2): 181-185.

WANG Ya-ni, JIANG Qi, ZHANG Yu-chen, ZHU Hai-yan. Application of Organoids Technology in Drug Sensitivity Test of Ovarian Cancer[J]. Journal of International Obstetrics and Gynecology, 2022, 49(2): 181-185.

参考文献 30

[1]	Sung H, Ferlay J, Siegel RL, et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries[J]. CA Cancer J Clin, 2021, 71(3):209-249. doi: 10.3322/caac.21660. doi: 10.3322/caac.21660
[2]	Maiorano BA, Maiorano MFP, Lorusso D, et al. Ovarian Cancer in the Era of Immune Checkpoint Inhibitors: State of the Art and Future Perspectives[J]. Cancers(Basel), 2021, 13(17):4438. doi: 10.3390/cancers13174438. doi: 10.3390/cancers13174438
[3]	Liu S, Kasherman L, Fazelzad R, et al. The use of bevacizumab in the modern era of targeted therapy for ovarian cancer: A systematic review and meta-analysis[J]. Gynecol Oncol, 2021, 161(2):601-612. doi: 10.1016/j.ygyno.2021.01.028. doi: 10.1016/j.ygyno.2021.01.028
[4]	Faro A, Boj SF, Clevers H. Fishing for intestinal cancer models: unraveling gastrointestinal homeostasis and tumorigenesis in zebrafish[J]. Zebrafish, 2009, 6(4):361-376. doi: 10.1089/zeb.2009.0617. doi: 10.1089/zeb.2009.0617 pmid: 19929219
[5]	Sato T, Stange DE, Ferrante M, et al. Long-term expansion of epithelial organoids from human colon, adenoma, adenocarcinoma, and Barrett′s epithelium[J]. Gastroenterology, 2011, 141(5):1762-1772. doi: 10.1053/j.gastro.2011.07.050. doi: 10.1053/j.gastro.2011.07.050
[6]	Broutier L, Mastrogiovanni G, Verstegen MM, et al. Human primary liver cancer-derived organoid cultures for disease modeling and drug screening[J]. Nat Med, 2017, 23(12):1424-1435. doi: 10.1038/nm.4438. doi: 10.1038/nm.4438 pmid: 29131160
[7]	Sachs N, de Ligt J, Kopper O, et al. A Living Biobank of Breast Cancer Organoids Captures Disease Heterogeneity[J]. Cell, 2018, 172(1/2):373-386.e10. doi: 10.1016/j.cell.2017.11.010. doi: 10.1016/j.cell.2017.11.010
[8]	Hill SJ, Decker B, Roberts EA, et al. Prediction of DNA Repair Inhibitor Response in Short-Term Patient-Derived Ovarian Cancer Organoids[J]. Cancer Discov, 2018, 8(11):1404-1421. doi: 10.1158/2159-8290.CD-18-0474. doi: 10.1158/2159-8290.CD-18-0474
[9]	Kopper O, de Witte CJ, Lõhmussaar K, et al. An organoid platform for ovarian cancer captures intra- and interpatient heterogeneity[J]. Nat Med, 2019, 25(5):838-849. doi: 10.1038/s41591-019-0422-6. doi: 10.1038/s41591-019-0422-6 pmid: 31011202
[10]	Phan N, Hong JJ, Tofig B, et al. A simple high-throughput approach identifies actionable drug sensitivities in patient-derived tumor organoids[J]. Commun Biol, 2019, 2:78. doi: 10.1038/s42003-019-0305-x. doi: 10.1038/s42003-019-0305-x
[11]	Hart PC, Bajwa P, Kenny HA. Modeling the Early Steps of Ovarian Cancer Dissemination in an Organotypic Culture of the Human Peritoneal Cavity[J]. Adv Exp Med Biol, 2021, 1330:75-94. doi: 10.1007/978-3-030-73359-9_5. doi: 10.1007/978-3-030-73359-9_5
[12]	Maenhoudt N, Defraye C, Boretto M, et al. Developing Organoids from Ovarian Cancer as Experimental and Preclinical Models[J]. Stem Cell Reports, 2020, 14(4):717-729. doi: 10.1016/j.stemcr.2020.03.004. doi: S2213-6711(20)30094-1 pmid: 32243841
[13]	Jabs J, Zickgraf FM, Park J, et al. Screening drug effects in patient-derived cancer cells links organoid responses to genome alterations[J]. Mol Syst Biol, 2017, 13(11):955. doi: 10.15252/msb.20177697. doi: 10.15252/msb.20177697
[14]	Ye W, Luo C, Li C, et al. Organoids to study immune functions, immunological diseases and immunotherapy[J]. Cancer Lett, 2020, 477:31-40. doi: 10.1016/j.canlet.2020.02.027. doi: 10.1016/j.canlet.2020.02.027
[15]	Usui T, Sakurai M, Enjoji S, et al. Establishment of a Novel Model for Anticancer Drug Resistance in Three-Dimensional Primary Culture of Tumor Microenvironment[J]. Stem Cells Int, 2016, 2016:7053872. doi: 10.1155/2016/7053872. doi: 10.1155/2016/7053872
[16]	Liu X, Flinders C, Mumenthaler SM, et al. MALDI Mass Spectrometry Imaging for Evaluation of Therapeutics in Colorectal Tumor Organoids[J]. J Am Soc Mass Spectrom, 2018, 29(3):516-526. doi: 10.1007/s13361-017-1851-4. doi: 10.1007/s13361-017-1851-4
[17]	Nanki Y, Chiyoda T, Hirasawa A, et al. Patient-derived ovarian cancer organoids capture the genomic profiles of primary tumours applicable for drug sensitivity and resistance testing[J]. Sci Rep, 2020, 10(1):12581. doi: 10.1038/s41598-020-69488-9. doi: 10.1038/s41598-020-69488-9
[18]	Lengyel E, Burdette JE, Kenny HA, et al. Epithelial ovarian cancer experimental models[J]. Oncogene, 2014, 33(28):3619-3633. doi: 10.1038/onc.2013.321. doi: 10.1038/onc.2013.321 pmid: 23934194
[19]	Byrne AT, Alférez DG, Amant F, et al. Interrogating open issues in cancer precision medicine with patient-derived xenografts[J]. Nat Rev Cancer, 2017, 17(4):254-268. doi: 10.1038/nrc.2016.140. doi: 10.1038/nrc.2016.140
[20]	Lancaster MA, Knoblich JA. Organogenesis in a dish: modeling development and disease using organoid technologies[J]. Science, 2014, 345(6194):1247125. doi: 10.1126/science.1247125. doi: 10.1126/science.1247125
[21]	Koshiyama M, Matsumura N, Konishi I. Recent concepts of ovarian carcinogenesis: type I and type II[J]. Biomed Res Int, 2014, 2014:934261. doi: 10.1155/2014/934261. doi: 10.1155/2014/934261
[22]	Lu P, Weaver VM, Werb Z. The extracellular matrix: a dynamic niche in cancer progression[J]. J Cell Biol, 2012, 196(4):395-406. doi: 10.1083/jcb.201102147. doi: 10.1083/jcb.201102147
[23]	Hynes RO. The extracellular matrix: not just pretty fibrils[J]. Science, 2009, 326(5957):1216-1219. doi: 10.1126/science.1176009. doi: 10.1126/science.1176009
[24]	McMillin DW, Negri JM, Mitsiades CS. The role of tumour-stromal interactions in modifying drug response: challenges and opportunities[J]. Nat Rev Drug Discov, 2013, 12(3):217-228. doi: 10.1038/nrd3870. doi: 10.1038/nrd3870 pmid: 23449307
[25]	Hidalgo M, Amant F, Biankin AV, et al. Patient-derived xenograft models: an emerging platform for translational cancer research[J]. Cancer Discov, 2014, 4(9):998-1013. doi: 10.1158/2159-8290.CD-14-0001. doi: 10.1158/2159-8290.CD-14-0001 pmid: 25185190
[26]	Chakrabarti J, Holokai L, Syu L, et al. Mouse-Derived Gastric Organoid and Immune Cell Co-culture for the Study of the Tumor Microenvironment[J]. Methods Mol Biol, 2018, 1817:157-168. doi: 10.1007/978-1-4939-8600-2_16. doi: 10.1007/978-1-4939-8600-2_16 pmid: 29959712
[27]	Fiorini E, Veghini L, Corbo V. Modeling Cell Communication in Cancer With Organoids: Making the Complex Simple[J]. Front Cell Dev Biol, 2020, 8:166. doi: 10.3389/fcell.2020.00166. doi: 10.3389/fcell.2020.00166 pmid: 32258040
[28]	Kenny HA, Krausz T, Yamada SD, et al. Use of a novel 3D culture model to elucidate the role of mesothelial cells, fibroblasts and extra-cellular matrices on adhesion and invasion of ovarian cancer cells to the omentum[J]. Int J Cancer, 2007, 121(7):1463-1472. doi: 10.1002/ijc.22874. doi: 10.1002/ijc.22874
[29]	Torabi S, Li L, Grabau J, et al. Cassie-Baxter Surfaces for Reversible, Barrier-Free Integration of Microfluidics and 3D Cell Culture[J]. Langmuir, 2019, 35(32):10299-10308. doi: 10.1021/acs.langmuir.9b01163. doi: 10.1021/acs.langmuir.9b01163
[30]	Xu R, Zhou X, Wang S, et al. Tumor organoid models in precision medicine and investigating cancer-stromal interactions[J]. Pharmacol Ther, 2021, 218:107668. doi: 10.1016/j.pharmthera.2020.107668. doi: 10.1016/j.pharmthera.2020.107668