Tracking cell lines using a ‘DNA-Action-DNA’ workflow

Novel biomedical insights start with cell lines. This requires cells to be cultured in an in vitro environment. However, under the influence of routine laboratory practices, cell lines can change both genetically and phenotypically over time [1–4].

Therefore, when it comes to cell line quality, it's surprising that a single genetic snapshot is considered sufficient to confirm genetic stability or identity. Given the rise in cheap DNA sequencing options available, it is time to transition cell culture practices to the 21st century and start periodic cell line monitoring with a DNA-Action-DNA workflow.

A DNA-Action-DNA workflow for tracking cell lines involves the following steps:

  1. DNA: a cell line is authenticated, checked for contamination, and assessed for genetic stability.

  2. Action: standard maintenance, and lab experiments -- such as drug treatments or genetic modifications -- are performed and documented.

  3. DNA: the cell line is re-assessed to determine the effect of lab procedures. Researchers can strategize the usage of specific cell populations based on the DNA results.

  4. Continue to repeat steps 2-3 to create the flow.

This workflow will keep every researcher organized. Researchers can catch errors in their cell lines earlier, saving time and resources.

Tracking cells in the clinic: cancer recurrence

Tracking cells through a DNA-Action-DNA workflow is not a new concept. Cancer diagnostics and targeted treatment strategies are highly reliant on periodic genetic analysis of cells. Genotype-driven therapies are applied increasingly in the clinic, as evidenced by the number of FDA-approved “companion diagnostics” [5]. Ongoing monitoring of genetic changes in tumors provides deeper insights into the health status and prognosis of cancer patients.

While the success of targeted therapy is promising, there is one major drawback. Cancer patients who demonstrate a positive response to a drug may eventually relapse through the emergence of a dominant drug-resistant clone in the tumor cell population.

Cell lines are key tools within the lab used to establish mechanisms of acquired drug resistance [6]. For instance, non-small cell lung cancer (NSCLC) patients often experience cancer recurrence after a seemingly effective treatment. About 50% of recurrences are linked to a secondary mutation in the same gene (EGFR).

A 2007 study by Jeffrey Engelman and colleagues set out to discover why the other 50% of relapses occurred [7]. They used an NSCLC cell line named HCC827, which they exposed to increasing dosages of Gefitinib for 6 months while waiting for resistant cells to appear. By comparing the genetic profiles of resistant and non-resistant cell lineages the study authors determined that four out of 18 lineages (22%) gained resistance through amplification of a ~60MB section on chromosome 7, containing the proto-oncogene MET [7].

In May 2020, the FDA approved the MET inhibitor Tabrecta (Capmatinib) to treat metastatic NSCLC [8].

This example illustrates the power of a DNA-Action-DNA workflow both for making discoveries in the laboratory, and helping patients more effectively in the clinic.

Tracking cells in context: stem cells and genetic instability

Routine genetic tracking is increasingly implemented to detect occurrences of genetic instability in stem cell research.

Taapken et al. [9] examined 1,700 iPSC and ESC populations at various stages in the cell culturing process (passages 1 – 150). Their paper, and others, revealed repeated amplifications of chromosomes 8, 12, 17, 20 and X. This suggests that duplication may provide cellular fitness advantages, allowing cells with these abnormalities to overgrow others with ‘normal’ ploidy. Chromosomal abnormalities appeared at various stages in the culturing process, including early (<20) and late (>20) passages.

The discovery that cells show genetic adaptation to in vitro growth has prompted new standards for stem cell culture. The stem cell community now checks genetic stability of cell cultures regularly via karyotyping.

Dr. Susan Solomon PhD, founder of the New York Stem Cell Foundation (NYSCF) and recipient of the 2020 Public Service Award from the International Society for Stem Cell Research, wrote with colleagues in “Raising the Standards of Stem Cell Line Quality” (Nature Cell Biology, 2016) [10]:

“Cell quality needs to be documented and reported with every released cell line. iPSCs should be scored for key properties that are particularly relevant to their future use: kar­yotype, pluripotency, in vitro differentiation potential and the absence of reprogramming components.”

The authors further elaborate:

Identity tracking is at the heart of cell authentication. […] every tissue deposited with a deriver should be immediately profiled and bar-coded, and rigorously tracked through all storage and processing steps."

And indeed, journals such as Stem Cell Research [11] are now publishing newly constructed iPSC/ESC lineages as resource papers, and these include data on (digital) karyotype, genetic identity, and some information on cell line provenance. (This publication used FIND Cell as the platform to track genetic stability and identity: [12])

How to implement a DNA-Action-DNA workflow

The clinic is rapidly adopting DNA-based decision making for treatment of patients. This DNA-based decision making can be extended to laboratory settings so that you cover your most precious resource – your cell lines.

The FIND Cell DNA-Action-DNA workflow can be implemented easily by researchers using cutting-edge, in-lab DNA sequencing technologies created by Illumina, Oxford Nanopore Technologies [13], and other companies.

Quick genetic verification in the laboratory

With just 20 mins of library prep (from gDNA) this benchtop DNA sequencer is making DNA-based cell tracking quick and easy. Photo: Researcher pipettes a DNA library into the MinION [13].

Photo credits: FIND Genomics.

Written by: Amanda Capes-Davis PhD, Tyer Joseph, and Sophie Zaaijer PhD

Illustrations: Kate White

Key references

  1. Liu Y, Mi Y, Mueller T, Kreibich S, Williams EG, Van Drogen A, et al. Multi-omic measurements of heterogeneity in HeLa cells across laboratories. Nat Biotechnol. 2019;37: 314–322.

  2. Ben-David U, Siranosian B, Ha G, Tang H, Oren Y, Hinohara K, et al. Genetic and transcriptional evolution alters cancer cell line drug response. Nature. 2018;560: 325–330.

  3. Malm M, Saghaleyni R, Lundqvist M, Giudici M, Chotteau V, Field R, et al. Evolution from adherent to suspension – systems biology of HEK293 cell line development. doi:10.1101/2020.01.29.924894

  4. Lin Y-C, Boone M, Meuris L, Lemmens I, Van Roy N, Soete A, et al. Genome dynamics of the human embryonic kidney 293 lineage in response to cell biology manipulations. Nat Commun. 2014;5: 4767.

  5. FDA. List of Cleared or Approved Companion Diagnostic Devices. In: U.S. Food and Drug Administration [Internet]. 2020 [cited 9 Jul 2020]. Available:

  6. Sharma SV, Haber DA, Settleman J. Cell line-based platforms to evaluate the therapeutic efficacy of candidate anticancer agents. Nat Rev Cancer. 2010;10: 241–253.

  7. Engelman JA, Zejnullahu K, Mitsudomi T, Song Y, Hyland C, Park JO, et al. MET amplification leads to gefitinib resistance in lung cancer by activating ERBB3 signaling. Science. 2007;316: 1039–1043.

  8. Office of the Commissioner. FDA Approves First Targeted Therapy to Treat Aggressive Form of Lung Cancer. In: U.S. Food and Drug Administration [Internet]. 5 Jun 2020 [cited 9 Jul 2020]. Available:

  9. Taapken SM, Nisler BS, Newton MA, Sampsell-Barron TL, Leonhard KA, McIntire EM, et al. Karotypic abnormalities in human induced pluripotent stem cells and embryonic stem cells. Nat Biotechnol. 2011;29: 313–314.

  10. Yaffe MP, Noggle SA, Solomon SL. Raising the standards of stem cell line quality. Nat Cell Biol. 2016;18: 236–237.

  11. Stem Cell Research journal. Lab Resource: Stem Cell Line | [cited 9 Jul 2020]. Available:

  12. Lu C, Sanjana NE. Generation of a knock-in MAP2-tdTomato reporter human embryonic stem cell line with inducible expression of NEUROG2/1 (NYGCe001-A). Stem Cell Res. 2019;41: 101643.

  13. Website: Oxford Nanopore Technologies - MinION:

Key words:



#cell culturing











© 2020 — FIND Genomics Inc., All Rights Reserved.