Testing cancer cell lines in vitro for drug sensitivity is a cornerstone of preclinical drug
development. Large publically available datasets can be found at The Genomics of Drug Sensitivity in Cancer Project
(GDSE) and The Cancer Cell Line Encyclopedia (CCLE).
Studies attempting to combine large public datasets and
analyzing for correlation questioned the reliability of the data due to limited
concordance, reported in [PMID: 24284626], discussed in [PMID:24284624] and a confirmation study here.
A new report in Nature describes different methods to analyze
the data from CCLE and GDSE and concludes that “data from either
study yields similar predictors of drug response” [PMID:26570998].
These papers demonstrate the continuing difficulty trying to
compare across large datasets. Such problems include comparing different
experimental protocols and measurements for drug sensitivity across studies,
trouble matching the drug and cell line names to ensure like comparison,
discordance in the genotyping data, and drugs that had few examples of cell
lines that were drug sensitive. As
always, attention to detail in the documentation and description of the
experiments can help mitigate some of these difficulties. While development of
standard testing protocols and data curation and reporting frameworks may lead
to better validation of drug response predictors going forward there will
always be the need for methods to filter the noise that is inevitable in large
datasets.
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