Abstract
SummaryLung cancer is an extremely heterogeneous disease, and its treatment remains one of the most challenging tasks in medicine. Few existing laboratory lung cancer models can faithfully recapitulate the diversity of the disease and predict therapy response. Here, we establish 12 patient-derived organoids from the most common lung cancer subtype, lung adenocarcinoma (LADC). Extensive gene and histopathology profiling show that the tumor organoids retain the histological architectures, genomic landscapes, and gene expression profiles of their parental tumors. Patient-derived lung cancer organoids are amenable for biomarker identification and high-throughput drug screening in vitro. This study should enable the generation of patient-derived lung cancer organoid lines, which can be used to further the understanding of lung cancer pathophysiology and to assess drug response in personalized medicine.
Highlights
Lung cancer is the leading cause of cancer-related mortality globally
We demonstrated the utility of lung adenocarcinoma (LADC) organoid lines as a model for drug testing to identify new therapeutic targets and advance personalized medicine
Establishment of a Living Biobank of Patient-Derived LADC Organoids Surgically resected lung adenocarcinoma samples were obtained from untreated patients under informed consent
Summary
Lung cancer is the leading cause of cancer-related mortality globally. Every year, an estimated 1.82 million people are diagnosed with lung cancer and 1.56 million die from the disease (Ferlay et al, 2015). There are two main histological subtypes of NSCLC: lung squamous-cell carcinoma (LSCC) and lung adenocarcinoma (LADC) (Molina et al, 2008). LADC has been the most predominant subtype of lung cancer since 1980s in the United States, and its incidence rates have been rising, whereas LSCC rates have been declining (Devesa et al, 2005; Patel et al, 2015). Owing to tumor heterogeneity among patients, clinical outcomes are usually unsatisfactory. The overall 5-year survival rate for lung cancer is 18% for all cancer stages combined in the United States (Siegel et al, 2018). In which treatment regimens are individually tailored to each patient based on tumor characteristics, is believed to improve clinical outcomes. The development of precision medicine for LADC has been hampered by the lack of in vitro models in which the efficacy of candidate therapeutic regimens can be assessed
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