Detection algorithm for the validation of human cell lines

Abstract

Cell lines are an important tool in understanding all aspects of cancer growth, development, metastasis and tumor cell death. There has been a dramatic increase in the number of cell lines and diversity of the cancers they represent; however, misidentification and cross-contamination of cell lines can lead to erroneous conclusions. One method that has gained favor for authenticating cell lines is the use of short tandem repeats (STR) to generate a unique DNA profile. The challenge in validating cell lines is the requirement to compare the large number of existing STR profiles against cell lines of interest, particularly when considering that the profiles of many cell lines have drifted over time and original samples are not available. We report here methods that analyze the variations and the proportional changes extracted from tetra-nucleotide repeat regions in the STR analysis. This technique allows a paired match between a target cell line and a reference database of cell lines to find cell lines that match within a user designated percentage cut-off quality matrix. Our method accounts for DNA instability and can suggest whether the target cell lines are misidentified or unstable.