Establishing 3-Dimensional Spheroids from Patient-Derived Tumor Samples and Evaluating their Sensitivity to Drugs

Neta Moskovits, Ella Itzhaki, Nataly Tarasenko, Eva Chausky, Avital Bareket-Samish, Aleksandr Kaufman, Raisa Meerson, Salomon M. Stemmer

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Despite remarkable advances in understanding tumor biology, the vast majority of oncology drug candidates entering clinical trials fail, often due to a lack of clinical efficacy. This high failure rate illuminates the inability of the current preclinical models to predict clinical efficacy, mainly due to their inadequacy in reflecting tumor heterogeneity and the tumor microenvironment. These limitations can be addressed with 3-dimensional (3D) culture models (spheroids) established from human tumor samples derived from individual patients. These 3D cultures represent real-world biology better than established cell lines that do not reflect tumor heterogeneity. Furthermore, 3D cultures are better than 2-dimensional (2D) culture models (monolayer structures) since they replicate elements of the tumor environment, such as hypoxia, necrosis, and cell adhesion, and preserve the natural cell shape and growth. In the present study, a method was developed for preparing primary cultures of cancer cells from individual patients that are 3D and grow in multicellular spheroids. The cells can be derived directly from patient tumors or patient-derived xenografts. The method is widely applicable to solid tumors (e.g., colon, breast, and lung) and is also cost-effective, as it can be performed in its entirety in a typical cancer research/cell biology lab without relying on specialized equipment. Herein, a protocol is presented for generating 3D tumor culture models (multicellular spheroids) from primary cancer cells and evaluating their sensitivity to drugs using two complementary approaches: a cell-viability assay (MTT) and microscopic examinations. These multicellular spheroids can be used to assess potential drug candidates, identify potential biomarkers or therapeutic targets, and investigate the mechanisms of response and resistance.

Original languageEnglish
Article numbere64564
JournalJournal of Visualized Experiments
Volume2022
Issue number190
DOIs
StatePublished - 16 Dec 2022
Externally publishedYes

Bibliographical note

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© 2022 JoVE Journal of Visualized Experiments.

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