Cell lines—a cell culture developed in a lab from a single cell causing all cells to have the same genetic makeup—are a popular tool to analyze breast cancer biology and test drug candidates. However, sometimes a drug that shows promising preclinical performance fails when used in the clinic. To further the understanding of cell line biology compared with tumors, researchers have begun analyzing large volumes of data, called big data, consisting of genomic data from cell lines and tumors. The analysis revealed that there were discrepancies between the cell lines and tumors.
"The differences between cell lines and tumor samples have raised the critical question to what extent cell lines can capture the makeup of tumors," stated Bin Chen, PhD, Assistant Professor at the College of Human Medicine at Michigan State University, and senior author of the study, published in Nature Communications.
The investigators used the epithelial cell line of metastatic mammary adenocarcinoma, MDA-MB-231, to compare with patient tumor samples of basal-like metastatic breast cancer and found that MDA-MB-231 cells share few genomic similarities with the patient tumor sample.
In addition, the researchers came up with a potential solution for the discrepancies between cell lines and tumor samples; they identified that organoids—tissue cultures taken from stem cells to replicate the complexity of an organ—bear more resemblance to the transcriptome of metastatic breast cancer samples taken from patients than cell lines do.
"Studies have shown that organoids can preserve the structural and genetic makeup of the original tumors," commented Dr. Chen. "We found at the gene expression level, it was able to do this, more so than other cell lines."
Dr. Chen concluded, "Our study demonstrates the power of leveraging open data to gain insights on cancer. Any advances we can make in early research will help us facilitate the discovery of better therapies for people with breast cancer down the road."
For More Information
Liu K, Newbury PA, Glicksberg BS, et al (2019). Evaluating cell lines as models for metastatic breast cancer through integrative analysis of genomic data. Nat Commun, 10:2138. DOI:10.1038/s41467-019-10148-6
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