Organoid (Jul 2022)

A method for culturing patient-derived lung cancer organoids from surgically resected tissues and biopsy samples

  • Yu Ri Ko,
  • Ji Min Kim,
  • Younsoo Kang,
  • Minsuh Kim,
  • Se Jin Jang

DOI
https://doi.org/10.51335/organoid.2022.2.e19
Journal volume & issue
Vol. 2

Abstract

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Background The cancer model system maintaining genetic and phenotypic characteristics of human cancers is crucial for the study of precision cancer medicine. In this respect, patient-derived cancer organoids have been developed as a preclinical cancer model with significant advantages over previous cancer models including PDX and cell lines. Patient-derived cancer organoids are generated through the process of self-organization of cancer cells in the tissue tissues, resulting in recapitulating phenotypic and genetic attributes of their parental tissues. For this reason, cancer organoids can be used in drug development and personalized medicine. Therefore, the development of effective cancer organoid culture methods is required in the cancer research field. Methods All lung cancer samples were obtained from Asan medical center (Seoul, South Korea) with consent from patients. For this study, lung cancer tissues were obtained by surgery and EBUS-TBNA. To generate LCOs from these samples, we used two different methods according to the source of tissues. Results This method improves the efficiency of LCOs setups composed of pure cancer cells and describes an additional procedure for reconstructing LCOs after cryopreservation. We confirmed that stock LCOs had the ability to self-organization and retain the morphological and genetic characteristics of their parental tissues. They also maintain their responsive property to certain anticancer drugs after thawing. Conclusion This study described a detailed protocol for establishing LCO from surgically resected tumor tissues and endoscopic biopsy samples. Also, we demonstrated that the LCO model generated by using these methods enables anticancer drug screening at the individual patient level.

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