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Review
. 2024 May 27;14(8):3300-3316.
doi: 10.7150/thno.96027. eCollection 2024.

Building consensus on the application of organoid-based drug sensitivity testing in cancer precision medicine and drug development

Dongxi Xiang  1   2 , Aina He  3 , Rong Zhou  4   5 , Yonggang Wang  3 , Xiuying Xiao  6 , Ting Gong  7 , Wenyan Kang  8   9 , Xiaolin Lin  6 , Xiaochen Wang  10 ; PDO-based DST Consortium; Lianxin Liu  11   12 , Ye-Guang Chen  13   14 , Shaorong Gao  15   16   17 , Yingbin Liu  1   2
Affiliations
Review

Building consensus on the application of organoid-based drug sensitivity testing in cancer precision medicine and drug development

Dongxi Xiang et al. Theranostics. .

Abstract

Patient-derived organoids (PDOs) have emerged as a promising platform for clinical and translational studies. A strong correlation exists between clinical outcomes and the use of PDOs to predict the efficacy of chemotherapy and/or radiotherapy. To standardize interpretation and enhance scientific communication in the field of cancer precision medicine, we revisit the concept of PDO-based drug sensitivity testing (DST). We present an expert consensus-driven approach for medication selection aimed at predicting patient responses. To further standardize PDO-based DST, we propose guidelines for clarification and characterization. Additionally, we identify several major challenges in clinical prediction when utilizing PDOs.

Keywords: Drug sensitivity testing (DST); Expert consensus; Organoid; Patient-derived organoids (PDOs); Precision medicine.

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Conflict of interest statement

Competing Interests: Gengming Niu, Guiying Wei, and Shengping Xiao employees of Shanghai OneTar Biomedicine. This consensus represents only the opinions of the expert panel involved in this writing and has no legal force.

Figures

Figure 1
Figure 1
The application of organoid models. PDOs recapitulate the physiological features and function, providing a more authentic and effective technical platform. They have potential applications in various research areas such as constructing disease models, biological sample repositories, gene therapy, drug discovery, and precision medicine.
Figure 2
Figure 2
Cancer organoid models used in precision medicine (left) and the opportunities for drug discovery (right). Tumor organoids simulate the biological characteristics of tissues-of-origin, providing matched personalized treatment strategies. Currently reported tumor organoid models include but are not limited to esophageal, lung, breast, gastric, renal, colorectal, and liver cancers, etc. (left image). Meanwhile, tumor organoids are effective preclinical models for drug development, which can be used to discover novel drug targets, test drug dosages, explore diagnostic biomarkers, repurpose existing drugs, and conduct PDO-xenograft (PDOX) model, etc. (right image).
Figure 3
Figure 3
Process of organoid models for drug screening test (DST). They are summarized in three steps: 1) Sample acquisition: primary/metastatic tumors, biopsies, liquids, and patient-derived xenograft (PDX) samples, etc.; 2) Drug screening: including sample transportation, organoid formation, drug screening, and data analysis; 3) Treatment in the clinic: providing therapeutic options for patients with chemotherapy, radiotherapy, targeted therapy, immunotherapy, and combinational therapy, etc.
Figure 4
Figure 4
Challenges and improving direction of organoid models. The development of organoids currently faces certain challenges, which require researchers to continuously strive for improvement and overcome. They at least include 1) Sample acquisition and processing; 2) Standardized procedures; 3) Turnaround time; 4) Success rate of tumor organoid construction; 5) Simulation of the tumor microenvironment; 6) Optimization of culture media; 7) Determination of drug concentrations; 8) Optimization of tumor organoids; 9) Determination of clinical protocols; 10) Regulatory standards; 11) Consideration of time and financial costs.
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