Patient-derived organoids and xenograft models in preclinical drug screening for gastric cancer: Recent progress and future perspective_CHINESE JOURNAL OF BASES AND CLINICS IN GENERAL SURGERY

Authors：

XU Xinxin ¹ , DAI Jianli ² , WANG Qianqian ² , XU Wei ¹ , CHEN Peng ¹ , LI Hongtao ¹ ,  FAN Ruifang ¹

1. Department of General Surgery, The 940th Hospital of Joint Logistics Support Force of Chinese People’s Liberation Army, Lanzhou 730050, P. R. China;
2. Institute of New Materials and Advanced Manufacturing, Beijing Academy of Science and Technology, Beijing 100089, P. R. China;

Corresponding author：

FAN Ruifang, Email: fanruif@163.com

Keywords：

gastric cancer; organoid; patient-derived tumor xenograft model; drug screening; personalized therapy

DOI：

10.7507/1007-9424.202406085

Video：

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Abstract Full text Figures/Tables Video References Cited by

Objective To summarize the research progress of patient-derived organoid (PDO) and patient-derived xenograft (PDX) models in preclinical drug screening for gastric cancer, aiming to provide a new perspective for precise drug screening and promote the application of personalized medicine and precision medicine for gastric cancer. Method A literature review was conducted on the use of PDO and PDX models in the basic research and preclinical drug screening for gastric cancer. Results The PDO and PDX models of gastric cancer exhibited a higher tumor biological simulation capability and a relatively accurate preclinical drug response prediction. However, they each have some certain limitations. The advent of organoid models based on xenografting, which combines the advantages of both, is expected to compensate for their respective shortcomings. These models can better reflect the heterogeneity of patients’ tumors and have unique advantages in the evaluation of new targeted drugs for specific molecular targets in gastric cancer, such as epidermal growth factor receptor. They show a certain correlation with the actual clinical response of patients, paving a new way for the development of new drugs, the study of drug action and resistance mechanisms, and personalized therapy. Conclusions PDO and PDX models, as a highly promising research platform, show a great potential in the screening of anti-tumor drugs and the development of personalized medical strategies.

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1. 何林烨, 王艺超, 李志辉. 2022年中国甲状腺癌流行情况分析: 基于《中国肿瘤登记年报》2005–2018年数据. 中国普外基础与临床杂志, 2024, 31(7): 790-795.
2. Machlowska J, Baj J, Sitarz M, et al. Gastric cancer: epidemiology, risk factors, classification, genomic characteristics and treatment strategies. Int J Mol Sci, 2020, 21(11): 4012. doi: 10.3390/ijms21114012.
3. Thrift AP, El-Serag HB. Burden of gastric cancer. Clin Gastroenterol Hepatol, 2020, 18(3): 534-542.
4. Bray F, Laversanne M, Sung H, et al. Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin, 2024, 74(3): 229-263.
5. Liu X, Meltzer SJ. Gastric cancer in the era of precision medicine. Cell Mol Gastroenterol Hepatol, 2017, 3(3): 348-358.
6. Wang Y, Zhang L, Yang Y, et al. Progress of gastric cancer surgery in the era of precision medicine. Int J Biol Sci, 2021, 17(4): 1041-1049.
7. Matsuoka T, Yashiro M. Precision medicine for gastrointestinal cancer: Recent progress and future perspective. World J Gastrointest Oncol, 2020, 12(1): 1-20.
8. Guan WL, He Y, Xu RH. Gastric cancer treatment: recent progress and future perspectives. J Hematol Oncol, 2023, 16(1): 57.
9. Li A, Walling J, Kotliarov Y, et al. Genomic changes and gene expression profiles reveal that established glioma cell lines are poorly representative of primary human gliomas. Mol Cancer Res, 2008, 6(1): 21-30.
10. Gillet JP, Calcagno AM, Varma S, et al. Redefining the relevance of established cancer cell lines to the study of mechanisms of clinical anti-cancer drug resistance. Proc Natl Acad Sci U S A, 2011, 108(46): 18708-18713.
11. Veninga V, Voest EE. Tumor organoids: Opportunities and challenges to guide precision medicine. Cancer Cell, 2021, 39(9): 1190-1201.
12. Wang W, Li Y, Lin K, et al. Progress in building clinically relevant patient-derived tumor xenograft models for cancer research. Animal Model Exp Med, 2023, 6(5): 381-398.
13. Tentler JJ, Tan AC, Weekes CD, et al. Patient-derived tumour xenografts as models for oncology drug development. Nat Rev Clin Oncol, 2012, 9(6): 338-350.
14. Waseem M, Wang BD. Organoids: An emerging precision medicine model for prostate cancer research. Int J Mol Sci, 2024, 25(2): 1093. doi: 10.3390/ijms25021093.
15. Song X, Hou K, Zhou H, et al. Liver organoids and their application in liver cancer research. Regen Ther, 2023, 25: 128-137.
16. Drost J, Clevers H. Organoids in cancer research. Nat Rev Cancer, 2018, 18(7): 407-418.
17. Xu H, Jiao D, Liu A, et al. Tumor organoids: applications in cancer modeling and potentials in precision medicine. J Hematol Oncol, 2022, 15(1): 58. doi: 10.1186/s13045-022-01278-4.
18. 周永杰, 石毓君. 类器官研究进展及展望. 中国普外基础与临床杂志, 2022, 29(6): 716-718.
19. Yoshida GJ. Applications of patient-derived tumor xenograft models and tumor organoids. J Hematol Oncol, 2020, 13(1): 4. doi: 10.1186/s13045-019-0829-z.
20. Ramos Zapatero M, Tong A, Opzoomer JW, et al. Trellis tree-based analysis reveals stromal regulation of patient-derived organoid drug responses. Cell, 2023, 186(25): 5606-5619.
21. Kang Y, Deng J, Ling J, et al. 3D imaging analysis on an organoid-based platform guides personalized treatment in pancreatic ductal adenocarcinoma. J Clin Invest, 2022, 132(24): e151604. doi: 10.1172/JCI151604.
22. Li G, Ma S, Wu Q, et al. Establishment of gastric signet ring cell carcinoma organoid for the therapeutic drug testing. Cell Death Discov, 2022, 8(1): 6. doi: 10.1038/s41420-021-00803-7.
23. Yan HHN, Siu HC, Law S, et al. A comprehensive human gastric cancer organoid biobank captures tumor subtype heterogeneity and enables therapeutic screening. Cell Stem Cell, 2018, 23(6): 882-897.
24. Vlachogiannis G, Hedayat S, Vatsiou A, et al. Patient-derived organoids model treatment response of metastatic gastrointestinal cancers. Science, 2018, 359(6378): 920-926.
25. Gao M, Lin M, Rao M, et al. Development of patient-derived gastric cancer organoids from endoscopic biopsies and surgical tissues. Ann Surg Oncol, 2018, 25(9): 2767-2775.
26. Steele NG, Chakrabarti J, Wang J, et al. An organoid-based preclinical model of human gastric cancer. Cell Mol Gastroenterol Hepatol, 2019, 7(1): 161-184.
27. Li J, Xu H, Zhang L, et al. Malignant ascites-derived organoid (MADO) cultures for gastric cancer in vitro modelling and drug screening. J Cancer Res Clin Oncol, 2019, 145(11): 2637-2647.
28. Song H, Park JY, Kim JH, et al. Establishment of patient-derived gastric cancer organoid model from tissue obtained by endoscopic biopsies. J Korean Med Sci, 2022, 37(28): e220. doi: 10.3346/jkms.2022.37.e220.
29. Zu M, Hao X, Ning J, et al. Patient-derived organoid culture of gastric cancer for disease modeling and drug sensitivity testing. Biomed Pharmacother, 2023, 163: 114751. doi: 10.1016/j.biopha.2023.114751.
30. McDonald HG, Harper MM, Hill K, et al. Creation of EGD-derived gastric cancer organoids to predict treatment responses. Cancers (Basel), 2023, 15(11): 3036.
31. Xu J, Gong J, Li M, et al. Gastric cancer patient-derived organoids model for the therapeutic drug screening. Biochim Biophys Acta Gen Subj, 2024, 1868(4): 130566. doi: 10.1016/j.bbagen.2024.130566.
32. Schmäche T, Fohgrub J, Klimova A, et al. Stratifying esophago-gastric cancer treatment using a patient-derived organoid-based threshold. Mol Cancer, 2024, 23(1): 10. doi: 10.1186/s12943-023-01919-3.
33. Zhao Y, Li S, Zhu L, et al. Personalized drug screening using patient-derived organoid and its clinical relevance in gastric cancer. Cell Rep Med, 2024, 5(7): 101627. doi: 10.1016/j.xcrm.2024.101627.
34. Li X, Nadauld L, Ootani A, et al. Oncogenic transformation of diverse gastrointestinal tissues in primary organoid culture. Nat Med, 2014, 20(7): 769-777.
35. Li X, Ootani A, Kuo C. An air-liquid interface culture system for 3D organoid culture of diverse primary gastrointestinal tissues. Methods Mol Biol, 2016, 1422: 33-40.
36. Neal JT, Li X, Zhu J, et al. Organoid modeling of the tumor immune microenvironment. Cell, 2018, 175(7): 1972-1988.
37. Chakrabarti J, Holokai L, Syu L, et al. Mouse-Derived Gastric Organoid and Immune Cell Co-culture for the Study of the Tumor Microenvironment. Methods Mol Biol, 2018, 1817: 157-168.1817-1157.
38. Chakrabarti J, Koh V, Steele N, et al. Disruption of Her2-Induced PD-L1 Inhibits Tumor Cell Immune Evasion in Patient-Derived Gastric Cancer Organoids. Cancers (Basel), 2021, 13(24): 6158.
39. 中国抗癌协会肿瘤多学科诊疗专业委员会, 中国抗癌协会肿瘤内分泌专业委员会. 肿瘤类器官诊治平台的质量控制标准中国专家共识(2022年版). 中国癌症杂志, 2022, 32(7): 657-668.
40. Abdolahi S, Ghazvinian Z, Muhammadnejad S, et al. Patient-derived xenograft (PDX) models, applications and challenges in cancer research. J Transl Med, 2022, 20(1): 206.
41. Okada S, Vaeteewoottacharn K, Kariya R. Application of Highly Immunocompromised Mice for the Establishment of Patient-Derived Xenograft (PDX) Models J. Cells, 2019, 8 (8).
42. Hidalgo M, Amant F, Biankin AV, et al. Patient-derived xenograft models: an emerging platform for translational cancer research. Cancer Discov, 2014, 4(9): 998-1013.
43. Liu Y, Wu W, Cai C, et al. Patient-derived xenograft models in cancer therapy: technologies and applications. Signal Transduct Target Ther, 2023, 8(1): 160.
44. Murayama T, Gotoh N. Patient-Derived Xenograft Models of Breast Cancer and Their Application. Cells, 2019, 8(6): 621.
45. Byrne AT, Alférez DG, Amant F, et al. Interrogating open issues in cancer precision medicine with patient-derived xenografts. Nat Rev Cancer, 2017, 17(4): 254-268.
46. Tian H, Lyu Y, Yang YG, et al. Humanized Rodent Models for Cancer Research. Front Oncol, 2020 Sep 11: 10: 1696.
47. Perova Z, Martinez M, Mandloi T, et al. PDCM Finder: an open global research platform for patient-derived cancer models. Nucleic Acids Res, 2023, 51(D1): D1360-D1366.1360-1366.
48. Jin J, Xu Y, Huo L, et al. An improved strategy for CRISPR/Cas9 gene knockout and subsequent wildtype and mutant gene rescue. PLoS One, 2020, 15(2): e0228910.
49. Jin J, Yoshimura K, Sewastjanow-Silva M, et al. Challenges and Prospects of Patient-Derived Xenografts for Cancer Research. Cancers (Basel), 2023, 15(17): 4352.
50. Busuttil RA, Liu DS, Di Costanzo N, et al. An orthotopic mouse model of gastric cancer invasion and metastasis. Sci Rep, 2018, 8(1): 825.
51. Giraud J, Bouriez D, Seeneevassen L, et al. Orthotopic Patient-Derived Xenografts of Gastric Cancer to Decipher Drugs Effects on Cancer Stem Cells and Metastatic Dissemination. Cancers (Basel), 2019, 11(4): 560.
52. Wang H, Lu J, Tang J, et al. Establishment of patient-derived gastric cancer xenografts: a useful tool for preclinical evaluation of targeted therapies involving alterations in HER-2, MET and FGFR2 signaling pathways. BMC Cancer, 2017, 17(1): 191.
53. Moy RH, Walch HS, Mattar M, et al. Defining and Targeting Esophagogastric Cancer Genomic Subsets With Patient-Derived Xenografts. JCO Precis Oncol, 2022 Feb: 6: e2100242.
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