Dataset Information

A Clinical Genomics-Guided Prioritizing Strategy Enables Selecting Proper Cancer Cell Lines for Biomedical Research.

ABSTRACT: Selecting appropriate cell lines to represent a disease is crucial for the success of biomedical research, because the usage of less relevant cell lines could deliver misleading results. However, systematic guidance on cell line selection is unavailable. Here we developed a clinical Genomics-guided Prioritizing Strategy for Cancer Cell Lines (CCL-cGPS) and help to guide this process. Statistical analyses revealed CCL-cGPS selected cell lines were among the most appropriate models. Moreover, we observed a linear correlation between the drug response and CCL-cGPS score of cell lines for breast and thyroid cancers. Using RT4 cells selected by CCL-GPS, we identified mebendazole and digitoxin as candidate drugs against bladder cancer and validate their promising anticancer effect through in vitro and in vivo experiments. Additionally, a web tool was developed. In conclusion, CCL-cGPS bridges the gap between tumors and cell lines, presenting a helpful guide to select the most suitable cell line models.

SUBMITTER: Shao X

PROVIDER: S-EPMC7662851 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A Clinical Genomics-Guided Prioritizing Strategy Enables Selecting Proper Cancer Cell Lines for Biomedical Research.

Shao Xin X Wang Yi Y Lu Xiaoyan X Hu Yang Y Liao Jie J Li Junying J Chen Xuechun X Yu Yunru Y Ai Ni N Ying Meidan M Fan Xiaohui X

iScience 20201028 11

Selecting appropriate cell lines to represent a disease is crucial for the success of biomedical research, because the usage of less relevant cell lines could deliver misleading results. However, systematic guidance on cell line selection is unavailable. Here we developed a clinical Genomics-guided Prioritizing Strategy for Cancer Cell Lines (CCL-cGPS) and help to guide this process. Statistical analyses revealed CCL-cGPS selected cell lines were among the most appropriate models. Moreover, we o ...[more]

PMID: 33225250

Similar Datasets

Project description:Systematic collection of fresh tissues for research at the time of diagnostic image-guided breast biopsy has the potential to fuel a wide variety of innovative studies. Here we report the initial experience, including safety, feasibility and laboratory proof-of-principle, with the collection and analysis of research specimens obtained via breast core needle biopsy immediately following routine clinical biopsy at a single institution over a 14-month period. Study eligibility criteria consisted of patients age 18 or older who were undergoing a clinical breast needle biopsy. Patients providing informed consent underwent one or two additional core biopsies following collection of all necessary clinical specimens. In total, 395 patients were approached and 270 consented to the research study, yielding a 68.4% consent rate. Among consenting patients, 238 lesions were biopsied for research, resulting in 446 research specimens collected. No immediate complications were observed. During the same period, zero complications were reported among the non-research procedures (1622 breast biopsy procedures). Representative research core specimens showed high diagnostic concordance with clinical core biopsies. Flow cytometry demonstrated consistent recovery of hundreds to thousands of viable cells per research core. Among a group of HER2+ tumor research specimens, HER2 assessment by flow cytometry correlated highly with immunohistochemistry (IHC) staining, and in addition revealed extensive inter- and intra-tumoral variation in HER2 levels of potential clinical relevance. Suitability for single-cell transcriptomic analysis was demonstrated for a triple-negative tumor core biopsy, revealing substantial cellular diversity in the tumor immune microenvironment, including a prognostically relevant T cell subpopulation. Thus, collection of fresh tissues for research purposes at the time of diagnostic breast biopsy is safe, feasible and efficient, and may provide a high-yield mechanism to generate a rich tissue repository for a wide variety of cross-disciplinary research.

Dataset Information

A Clinical Genomics-Guided Prioritizing Strategy Enables Selecting Proper Cancer Cell Lines for Biomedical Research.

Publications

A Clinical Genomics-Guided Prioritizing Strategy Enables Selecting Proper Cancer Cell Lines for Biomedical Research.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure