Scientists have now shown that cancer cell lines derived from patient samples have many of the same genetic abnormalities seen in the tumors they were sampled from. Different cancer cell lines show varied responses to different drugs, allowing researchers to potentially develop new cancer treatments. The findings are detailed in a paper just published in the journal Cell.
A team of scientists from the Wellcome Trust Sanger Institute, the Netherlands Cancer Institute, and the European Bioinformatics Institute analyzed 11,289 samples from different patients. The samples represented 29 tumor categories. They derived 1001 laboratory-grown cancer cell lines, just like the ones currently used in research studies. The team found that the genetic mutations in the cancer cell lines matched the mutations found in the original type of tumor. These mutations affect tumor behavior, including growth and how they respond to different types of treatment. The researchers then tested each cell line for drug sensitivity, experimenting with 265 different cancer medications. They found that the mutations present in each cancer cell line could be used to predict which drugs would be the most effective.
Cancer cell lines are much more practical to study in laboratories compared to living tumors. These new findings show that these laboratory cell lines share many of the same genetic mutations as the original tumor samples. The various genetic abnormalities found in tumors are predictive of cancer behavior, growth, and drug resistance. This is significant because it means that the cancer cell lines will react to medications the same way as the tumors, allowing for improved cancer treatments. If scientists test individual cell lines to find out which specific drugs each line is most affected by, we can develop treatments personalized for that exact type of tumor. The authors believe their findings will lead to further studies designed to identify which drugs are best for each form of cancer.
Iorio et al. A Landscape of Pharmacogenomic Interactions in Cancer. Cell (2016).