Cell line identity finding by fingerprinting, an optimized resource for short tandem repeat profile authentication

Area of Science:

• * Cancer Research
• * Genomics
• * Biotechnology

Background:

• * Biological data generation from tumor cell lines is vital for cancer research.
• * Accurate cell line identity verification is essential for data interpretation and reproducibility.
• * Short Tandem Repeat (STR) DNA fingerprinting is the preferred method for cell line authentication.

Purpose of the Study:

• * To establish a homogeneous reference dataset of 300 widely used tumor cell lines.
• * To develop a software tool (CLIFF) for efficient and accurate cell line identity comparison.
• * To address challenges in cell line authentication due to genetic instability and data heterogeneity.

Main Methods:

• * DNA fingerprinting of 300 tumor cell lines using Short Tandem Repeat (STR) profiling across 16 loci.
• * Development of the Cell Line Identity Finding by Fingerprinting (CLIFF) software.
• * Implementation of an original identity score calculation within CLIFF for robust comparisons.

Main Results:

• * Creation of a large, standardized STR profiling dataset for 300 tumor cell lines.
• * CLIFF software enables reliable comparison of STR profiles from diverse sources.
• * The software facilitates accurate cell line identification even with genetic variations and differing locus usage.

Conclusions:

• * The provided dataset and CLIFF software enhance the reliability of cancer cell line authentication.
• * Standardized STR profiling and advanced comparison tools are critical for research integrity.
• * CLIFF supports the integration and analysis of both public and proprietary cell line identity data.