Theranostics 2021; 11(19):9667-9686. doi:10.7150/thno.62676 This issue
1. Graduate Institute of Oncology, National Taiwan University College of Medicine, Taipei, 10051, Taiwan.
2. Graduate Institute of Toxicology, National Taiwan University College of Medicine, Taipei, 10051, Taiwan.
3. Department of Internal Medicine, National Taiwan University Hospital and National Taiwan University College of Medicine, Taipei, 10051, Taiwan.
4. Institute of Statistical Science, Academia Sinica, Taipei, 11529, Taiwan.
5. College of Medicine, China Medical University, Taichung, 40402, Taiwan.
6. Rheumatic Diseases Research Center, China Medical University Hospital, Taichung, 40402, Taiwan.
7. Rheumatology and Immunology Center, China Medical University Hospital, Taichung, 40402, Taiwan.
8. Institute of Biomedical Sciences, National Chung Hsing University, Taichung, 40227, Taiwan.
9. Health Data Research Center, National Taiwan University, 10050, Taipei, Taiwan.
10. Chung-Shan Medical University, Taichung, 40201, Taiwan.
11. Department of Statistics, University of California, Los Angeles, Los Angeles, California, 90095, USA.
#Equal contributions to this work.
The tumorous niche may drive the plasticity of heterogeneity and cancer stemness, leading to drug resistance and metastasis, which is the main reason of treatment failure in most cancer patients. The aim of this study was to establish a tumor microenvironment (TME)-based screening to identify drugs that can specifically target cancer stem cells (CSCs) and cancer-associated fibroblasts (CAFs) in the TME.
Methods: Lung cancer patient-derived cancer cell and CAFs were utilized to mimic the TME and reproduce the stemness properties of CSCs in vitro and develop a high-throughput drug screening platform with phenotypical parameters. Limiting dilution assay, sphere-forming and ALDH activity assay were utilized to measure the cancer stemness characteristics. In vivo patient-derived xenograft (PDX) models and single-cell RNA sequencing were used to evaluate the mechanisms of the compounds in CSCs and CAFs.
Results: The TME-based drug screening platform could comprehensively evaluate the response of cancer cells, CSCs and CAFs to different treatments. Among the 1,524 compounds tested, several drugs were identified to have anti-CAFs, anticancer and anti-CSCs activities. Aloe-emodin and digoxin both show anticancer and anti-CSCs activity in vitro and in vivo, which was further confirmed in the lung cancer PDX model. The combination of digoxin and chemotherapy improved therapeutic efficacy. The single-cell transcriptomics analysis revealed that digoxin could suppress the CSCs subpopulation in CAFs-cocultured cancer cells and cytokine production in CAFs.
Conclusions: The TME-based drug screening platform provides a tool to identify and repurpose compounds targeting cancer cells, CSCs and CAFs, which may accelerate drug development and therapeutic application for lung cancer patients.
Keywords: Cancer-associated fibroblasts, cancer stem cells, drug screening, tumor microenvironment, high-throughput