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Keywords = ANSI/ATCC standards

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38 pages, 5718 KB  
Review
Genetic Insights into the Economic Toll of Cell Line Misidentification: A Comprehensive Review
by Ralf Weiskirchen
Med. Sci. 2026, 14(1), 25; https://doi.org/10.3390/medsci14010025 - 5 Jan 2026
Viewed by 1595
Abstract
Cell line misidentification, first exposed when HeLa cells were shown to contaminate dozens of “unique” cultures, now compromises roughly one in five lines and renders thousands of papers potentially unreliable, propagating unreliable data through hundreds of thousands of citations. The financial fallout is [...] Read more.
Cell line misidentification, first exposed when HeLa cells were shown to contaminate dozens of “unique” cultures, now compromises roughly one in five lines and renders thousands of papers potentially unreliable, propagating unreliable data through hundreds of thousands of citations. The financial fallout is vast with irreproducible research linked to faulty cell stocks costing the United States an estimated $28 billion each year. Today, authentication is rapid, cheap and highly accurate. Modern 24-plex short tandem repeat (STR) kits, analyzed by six-dye capillary electrophoresis and benchmarked against public databases, verify a culture in half a day for less than €40, lowering the probability of mistaken identity to less than 10–15. Complementary SNP panels, low-pass genome sequencing, digital PCR and nascent methylation “age clocks” close remaining blind spots such as aneuploidy or mixed-species co-cultures. Monte-Carlo modeling shows that even at a contamination risk of 0.07% routine STR testing yields a five-year return on investment above 3000% for a mid-size lab. Reflecting this evidence, ANSI/ATCC standards, NIH and Horizon Europe grants, major journals and FDA/EMA guidelines now encourage, recommend, or make authentication mandatory. This review discusses the historical roots and economic losses resulting from cell misidentification and contamination and offers a pragmatic roadmap to prevent working with falsified cell lines. It is further discussed that FAIR-compliant data archiving and integration of STR workflows into laboratory data management systems will allow laboratories to shift from sporadic testing of cell quality to continuous, artificial intelligence-supported assessments. Full article
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