Cancer Cell Lines Can Predict Treatment Response, Improve Personalized Therapy

Patient-derived cancer cell lines contain most of the genetic changes found in patients' tumors and could be used to determine tumor response to treatment, increasing the success rate of new personalized therapies for cancer.1

Researchers discovered a strong association between many genetic mutations in cancer samples and the sensitivity to particular drugs. These results could aid doctors in predicting the best available drugs or the most appropriate clinical trials for each patient.

"If a cell line has the same genetic features as a patient's tumor, and that cell line responded to a specific drug, we can focus new research on this finding. This could ultimately help assign cancer patients into more precise groups based on how likely they are to respond to therapy,” said Francesco Iorio, PhD, postdoctoral researcher at the European Bioinformatics Institute (EMBL-EBI) and the Wellcome Trust Sanger Institute, Hinxton, United Kingdom, and a co-author.

The systematic, large-scale study combined molecular data from laboratory cancer cell lines, drug sensitivity, and patients. Researchers examined oncogenic mutations in more than 11,000 patient samples from 29 different tumors types to construct a catalogue of the genetic changes causing cancer in patients. These mutations were mapped onto 1000 cancer cell lines.

Next, researchers tested the sensitivity of the cell lines to 265 different cancer medications to elucidate how these mutations affect sensitivity. The genetic mutations found in cancer samples from patients were also found in cancer cell lines in the laboratory, suggesting these cell lines are helpful models for the identification of therapies that would work best in different patients.

In addition, many of the genetic mutations found in the patient samples can individually and in combination influence whether a particular medication affects cancer cell survival. These results suggest cancer cell lines should be better used to determine which medications or clinical trials would provide the most effective treatment for a particular patient.

"We need better ways to figure out which groups of patients are more likely to respond to a new drug before we run complex and expensive clinical trials. Our research shows that cancer cell lines do capture the molecular alterations found in tumors, and so can be predictive of how a tumor will respond to a drug,” concluded Ultan McDermott, clinical scientist at the Sanger Institute, and a co-author.

Reference

1. Iorio F, Knijnenburg TA, Vis DJ, et al. A landscape of pharmacogenomic interactions in cancer. Cell. 2016 Jul 5. doi: 10.1016/j.cell.2016.06.017. [Epub ahead of print]

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