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84. Burt, J. M., Nelson, T. K., Simon, A. M. & Fang, J. S.
Connexin 37 profoundly slows cell cycle progression in
rat insulinoma cells. Am. J. Physiol. Cell Physiol. 295,
C1103–C1112 (2008).
85. Solan, J. L., Fry, M. D., TenBroek, E. M. & Lampe, P. D.
Connexin 43 phosphorylation at S368 is acute during
S and G2/M and in response to protein kinase C
activation. J. Cell Sci. 116 , 2203–2211 (2003).
86. Chen, S. C., Pelletier, D. B., Ao, P. & Boynton, A. L.
Connexin 43 reverses the phenotype of transformed cells
and alters their expression of cyclin/cyclin-dependent
kinases. Cell Growth Differ. 6, 681–690 (1995).
87. Zhang, Y. W., Morita, I., Ikeda, M., Ma, K. W. &
Murota, S. Connexin 43 suppresses proliferation of
osteosarcoma U2OS cells through post-
transcriptional regulation of p27. Oncogene 20,
4138–4149 (2001).
88. Sanchez-Alvarez, R., Paino, T., Herrero-Gonzalez, S.,
Medina, J. M. & Tabernero, A. Tolbutamide reduces
glioma cell proliferation by increasing connexin43,
which promotes the up-regulation of p21 and p27 and
subsequent changes in retinoblastoma
phosphorylation. Glia 54, 125–134 (2006).
89. Tanaka, M. & Grossman, H. B. Connexin 26 induces
growth suppression, apoptosis and increased efficacy
of doxorubicin in prostate cancer cells. Oncol. Rep. 11,
537–541 (2004).
90. Mesnil, M. et al. Negative growth control of HeLa cells
by connexin genes: connexin species specificity.
Cancer Res. 55, 629–639 (1995).
91. Iacobas, D. A., Scemes, E. & Spray, D. C. Gene
expression alterations in connexin null mice extend
beyond the gap junction. Neurochem. Int. 45,
243–250 (2004).
92. Saito-Katsuragi, M. et al. Role for connexin 26 in
metastasis of human malignant melanoma:
communication between melanoma and endothelial
cells via connexin 26. Cancer 110, 1162–1172 (2007).
93. Pollmann, M. A., Shao, Q., Laird, D. W. & Sandig, M.
Connexin 43 mediated gap junctional communication
enhances breast tumor cell diapedesis in culture.
Breast Cancer Res. 7, R522–R534 (2005).
94. Naoi, Y. et al. Connexin 26 expression is associated
with lymphatic vessel invasion and poor prognosis in
human breast cancer. Breast Cancer Res. Treat 106,
11–17 (2007).
95. Yano, T. et al. Connexin 32 as an anti-invasive and
anti-metastatic gene in renal cell carcinoma. Biol.
Pharm. Bull. 29, 1991–1994 (2006).
96. Li, Z., Zhou, Z. & Donahue, H. J. Alterations in Cx43
and OB-cadherin affect breast cancer cell metastatic
potential. Clin. Exp. Metastasis 25, 265–272 (2008).
97. Sato, H. et al. The inhibitory effect of connexin 32
gene on metastasis in renal cell carcinoma. Mol.
Carcinog. 47, 403–409 (2008).
98. Cohn, E. S. & Kelley, P. M. Clinical phenotype and
mutations in connexin 26 (DFNB1/GJB2), the most
common cause of childhood hearing loss. Am. J. Med.
Genet. 89, 130–136 (1999).
99. Nyquist, G. G. et al. Malignant proliferating pilar
tumors arising in KID syndrome: a report of two
patients. Am. J. Med. Genet. A 143, 734–741 (2007).
100. Collignon, F. et al. Altered expression of connexin
subtypes in mesial temporal lobe epilepsy in humans.
J. Neurosurg. 105, 77–87 (2006).
101. Proulx, E. et al. Functional contribution of specific brain
areas to absence seizures: role of thalamic gap-junctional
coupling. Eur. J. Neurosci. 23, 489–496 (2006).
102. Nemani, V. M. & Binder, D. K. Emerging role of gap
junctions in epilepsy. Histol. Histopathol. 20,
253–259 (2005).
103. Gabriel, H. D. et al. Transplacental uptake of glucose is
decreased in embryonic lethal connexin 26-deficient
mice. J. Cell Biol. 140, 1453–1461 (1998).
104. Kruger, O. et al. Defective vascular development in
connexin 45-deficient mice. Development 127,
4179–4193 (2000).
105. Yamakage, K., Omori, Y., Zaidan-Dagli, M. L., Cros,
M. P. & Yamasaki, H. Induction of skin papillomas,
carcinomas, and sarcomas in mice in which the
connexin 43 gene is heterologously deleted. J. Invest.
Dermatol. 114 , 289–294 (2000).
106. Evert, M., Ott, T., Temme, A., Willecke, K. &
Dombrowski, F. Morphology and morphometric
investigation of hepatocellular preneoplastic lesions
and neoplasms in connexin 32-deficient mice.
Carcinogenesis 23, 697–703 (2002).
107. Moennikes, O., Buchmann, A., Ott, T., Willecke, K. &
Schwarz, M. The effect of connexin 32 null mutation
on hepatocarcinogenesis in different mouse strains.
Carcinogenesis 20, 1379–1382 (1999).
108. Moennikes, O., Buchmann, A., Willecke, K., Traub, O.
& Schwarz, M. Hepatocarcinogenesis in female mice
with mosaic expression of connexin 32. Hepatology
32, 501–506 (2000).
109. King, T. J. et al. Deficiency in the gap junction protein
connexin 32 alters p27Kip1 tumor suppression and
MAPK activation in a tissue-specific manner.
Oncogene 24, 1718–1726 (2005).
110. Bakirtzis, G. et al. Targeted epidermal expression of
mutant connexin 26(D66H) mimics true Vohwinkel
syndrome and provides a model for the pathogenesis
of dominant connexin disorders. Hum. Mol. Genet. 12,
1737–1744 (2003).
111. Flenniken, A. M. et al. A Gja1 missense mutation in a
mouse model of oculodentodigital dysplasia.
Development 132, 4375–4386 (2005).
112. Kalcheva, N. et al. Gap junction remodeling and
cardiac arrhythmogenesis in a murine model of
oculodentodigital dysplasia. Proc. Natl Acad. Sci. USA
104, 20512–20516 (2007).
113. VanSlyke, J. K. & Musil, L. S. Dislocation and
degradation from the ER are regulated by cytosolic
stress. J. Cell Biol. 157, 381–394 (2002).
114. Musil, L. S. & Goodenough, D. A. Multisubunit
assembly of an integral plasma membrane channel
protein, gap junction connexin 43, occurs after exit
from the ER. Cell 74, 1065–1077 (1993).
115. Giepmans, B. N. et al. Gap junction protein
connexin-43 interacts directly with microtubules. Curr.
Biol. 11, 1364–1368 (2001).
116. Shaw, R. M. et al. Microtubule plus-end-tracking
proteins target gap junctions directly from the cell
interior to adherens junctions. Cell 128, 547–560
(2007).
117. Preus, D., Johnson, R., Sheridan, J. & Meyer, R.
Analysis of gap junctions and formation plaques
between reaggregating Novikoff hepatoma cells.
J. Ultrastruct. Res. 77, 263–276 (1981).
118. Evans, W. H., De Vuyst, E. & Leybaert, L. The gap
junction cellular internet: connexin hemichannels enter
the signalling limelight. Biochem. J. 397, 1–14
(2006).
119. McLachlan, E., Shao, Q. & Laird, D. W. Connexins and
gap junctions in mammary gland development and
breast cancer progression. J. Membr. Biol. 218,
107–121 (2007).
Acknowledgements
The authors thank E. Jewlel for compiling some literature on
this topic and P. Lampe, M. Mesnil, I. Plante, M. Sandig and
L. Matsuuchi for their critical reading of the manuscript. The
authors also apologize to the numerous authors who have
contributed to this exciting field but whose work was not cited
in this short article. C.C.N. and D.W.L. are supported by
grants from Canadian Institutes of Health Research, Canada
Breast Cancer Research Alliance, and the Canada Research
Chairs Program.
Competing interests statement
The authors declare no competing financial interests.
DATABASES
OMIM: http://www.ncbi.nlm.nih.gov/omim
keratitis–ichthyosis–deafness
UniProtKB: http://www.uniprot.org
caveolin 1 | Cx26 | Cx32 | Cx37 | Cx43 | Cx45 | N-cadherin |
NOV | TSG101
FURTHER INFORMATION
Christian C. Naus’ homepage:
http://www.cellphys.ubc.ca/faculty_pages/naus.html
Dale W. Laird’s homepage:
http://www.uwo.ca/anatomy/laird/index.htm
ALL LINKS ARE ACTIVE IN THE ONLINE PDF
MODELS OF CANCER SERIES — SCIENCE AND SOCIETY
Cell line misidentification:
the beginning of the end
American Type Culture Collection Standards Development Organization
Workgroup ASN-0002
Abstract | Cell lines are used extensively in research and drug development as
models of normal and cancer tissues. However, a substantial proportion of cell lines
is mislabelled or replaced by cells derived from a different individual, tissue or
species. The scientific community has failed to tackle this problem and consequently
thousands of misleading and potentially erroneous papers have been published
using cell lines that are incorrectly identified. Recent efforts to develop a standard
for the authentication of human cell lines using short tandem repeat profiling is an
important step to eradicate this problem.
Cell lines are used extensively in biomedical
research as in vitro models. The validity
of the data obtained often depends on the
identity of the cell line, particularly when it
is being used as a surrogate for the tissue of
origin. Surprisingly, the frequency of cell line
misidentification is high, and consequently
the ascribed origin of a cell line is often
incorrect. This problem has been known
for over 50 years and has been described as
the most compelling quality-control issue
confronting the scientific community1.
Based on analyses of cell lines submitted to
international cell banks, the incidence of
misidentification in 1977 was 16%2 and in
1999 was 18%3. Until recently, the authentic-
ity of cell lines used in biomedical research
has received little attention. This Science
and Society article has been written by the
members of the American Type Culture
Collection (ATCC) Standards Development
Organization (SDO) Workgroup ASN-0002
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© 20 Macmillan Publishers Limited. All rights reserved10
(BOX 1), a working group currently develop-
ing a standard for human cell line authen-
tication. The ATCC SDO was formed in
2007 to develop best practices (standards)
for use in the life sciences and to promote
their use globally, using a consensus-driven
process that balances the viewpoints of
industry, government, regulatory agencies
and academia. We expect that the draft
standard (BOX 2) will be available for public
review and comment in 2010 and subse-
quently the final draft will be approved by
the American National Standards Institute
(ANSI).
Here we describe the causes and scien-
tific effects of cell line misidentification, its
history and the efforts taken to solve the
problem. The various methods currently
available for authenticating cell lines are
discussed and a recommendation is made
for the use of short tandem repeat (STR)
profiling for authenticating human cell lines.
Perhaps of the greatest importance, a univer-
sal database of human cell line STR profiles
is under construction.
Discovery of cell line misidentification
Misidentification of human and animal
cell cultures is a long-standing problem,
and awareness of this problem dates back
to the 1950s (TIMELINE). Karyotyping and
immuno logical approaches were first used
for cell line authentication4–6. Extensive
species misidentification was reported,
leading to the establishment of a bank
of authenticated cell lines at the ATCC
in 1962.
Misidentification within species could
not be detected in 1962, but in 1966 Stanley
Gartler (FIG. 1a) introduced the concept
of biochemical polymorphisms to dis-
tinguish human cell lines on the basis of
their isozyme expression. At the Second
Decennial Review Conference on Cell,
Tissue and Organ Culture in 1966, Gartler
reported that 18 human cell lines suppos-
edly of independent origins were all HeLa
cells7, the first human cancer cell line to
be established in culture8. The examples
included cells claimed to be derived from
normal intestinal epithelium (Int-407), nor-
mal amnion (WISH), normal liver (Chang
liver), laryngeal cancer (Hep-2) and oral
cancer (KB). The HeLa cell line was derived
from a glandular cervical cancer in a female
patient named Henrietta Lacks and, because
of its celebrated status, was distributed inter-
nationally and passed from laboratory to
laboratory. Then, as today, many scientists
were oblivious to the possibility of cross-
contamination. HeLa cells are particularly
robust and fast-growing and consequently
can rapidly overgrow other cells.
Box 1 | Authors and members of workgroup ASN-0002
• Christine Alston-Roberts, Standards Specialist, ATCC,
10801 University Boulevard, Manassas, VA 20110, USA
• Rita Barallon, Ph.D., Service Business Manager, Life and Food
Sciences Life Sciences, LGC, Queens Road, Teddington, Middlesex,
TW11 0LY, UK
• Steven R. Bauer*, Ph.D., FDA/Center for Biologics Evaluation and
Research, Chief, Cell and Tissue Therapy Branch, Division of Cellular
and Gene Therapies, Office of Cellular, Tissue and Gene Therapies,
NIH Building 29B 2NN10 HFM-740, 8800 Rockville Pike, Bethesda,
MD 20892, USA
• John Butler, Ph.D., Biochemical Science Division (831), Advanced
Chemical Science Laboratory (227), Room B226, NIST, 100 Bureau
Drive, Stop 8312, Gaithersburg, MD 20899-8312, USA
• Amanda Capes-Davis, Ph.D., CellBank Australia, Children’s Medical
Research Institute, Westmead, New South Wales, Australia
• Wilhelm G. Dirks, Ph.D., Molecular Biology, DSMZ — German
Collection of Microorganisms and Cell Cultures, Inhoffenstr. 7b,
38124 Braunschweig, Germany
• Eugene Elmore, Ph.D., Project Scientist, Department of Radiation
Oncology, University of California, Medical Sciences I, B146D, Irvine,
CA 92697, USA
• Manohar Furtado, Ph.D., Vice President, R & D, Applied Markets
Division, Applied Biosystems, 850 Lincoln Centre Drive, MS404-1,
Foster City, CA 94404, USA
• Liz Kerrigan, Director, Standards and Certification, ATCC,
10801 University Boulevard, Manassas, VA 20110, USA
• Margaret C. Kline, Research Biologist, Biochemical Science Division
(831), Advanced Chemical Science Laboratory (227), Room B226,
National Institutes of Standards and Technology,100 Bureau Drive,
Stop 8312, Gaithersburg, MD 20899-8312, USA
• Arihiro Kohara, Ph.D., Scientist, National Institute of Biomedical
Innovation, Department Biomedical Services, Laboratory of Cell
Cultures, 7-6-8 Saito-Asagi, Ibaraki, Osaka, Japan 567-0085
• Georgyi V. Los, M.D., Ph.D., Honorary Fellow, Neuroscience Training
Program, University of Wisconsin-Madison, 1300 University Avenue,
Madison, WI 53706, USA
• Roderick A.F. MacLeod, Ph.D., Cytogenetics Laboratory, DSMZ —
German Collection of Microorganisms and Cell Cultures, Inhoffenstr.
7b, 38124 Braunschweig, Germany
• John R. W. Masters, Ph.D., FCRPath, Professor of Experimental
Pathology, University College London, 67 Riding House Street, London,
W1W 7EJ, UK
• Mark Nardone, Director, Bio-Trac Program, The Foundation for the
Advanced Education in the Sciences at the National Institutes of
Health, Bethesda, MD 20892, USA
• Roland M. Nardone, Ph.D., Professor Emeritus, Catholic University of
America, Cell and Molecular Biology, 620 Michigan Avenue NE,
Washington, DC 20064, USA
• Raymond W. Nims, Ph.D., Consultant, RMC Pharmaceutical Solutions
Inc., 2150 Miller Drive, Suite A, Longmont, CO 80501, USA
• Paul J. Price, Ph.D., CSO, Research and Development, Room B-33,
D-Finitive Cell Technology, 1023 Wappoo Rd, Charleston, SC 29407, USA
• Yvonne A. Reid, Ph.D., Collection Scientist, Cell Biology Collection,
ATCC, 10801 University Boulevard, Manassas, VA 20110, USA
• Jaiprakash Shewale, Ph.D., Director, Biology, Applied Markets/Genetic
Systems, Life Technologies, 850 Lincoln Centre Drive, Foster City,
CA 94404, USA
• Anton F. Steuer, Ph.D., Principal Scientist, BioReliance, 14920 Brochart
Road, Rockville, MD 20850, USA
• Douglas R. Storts, Ph.D., Head of Research, Nucleic Acid Technologies,
Promega Corporation, 2800 Woods Hollow Road, Madison,
WI 53711, USA
• Gregory Sykes, Biologist, ATCC, 10801 University Blvd., Manassas,
VA 20110, USA
• Zenobia Taraporewala*, Ph.D., FDA/Center for Biologics Evaluation
and Research, Reviewer, Division of Cellular and Gene Therapies,
Office of Cellular, Tissue, and Gene Therapies, 1401 Rockville Pike,
Room 200N, Rockville, MD 20892, USA
• Jim Thomson, Innovation and Support Team, LGC, Queens Rd,
Teddington, TW11 0LY, UK
*S. R. B. and Z. T. did not contribute as authors to this Perspective.
PERSPECTIVES
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© 20 Macmillan Publishers Limited. All rights reserved10
Denial and complacency
There was resistance and some hostility to
Gartler’s findings even among scientists
“who should have known better”, accord-
ing to Gartler but one scientist, Walter
Nelson-Rees (FIG. 1b), took particular note
of Gartler’s talk. Nelson-Rees ran a cell
bank at Berkeley under contract for the
National Cancer Institute. With his col-
leagues he developed karyotyping methods
for authenticating cell lines and in a series
of papers he showed there was extensive
cross-contamination among the suppos-
edly unique cultures sent to the bank (for
example, see REF. 9). Nelson-Rees’s work
showed widespread cross-contamination
by HeLa cells and for some years all cell
lines were under suspicion of being HeLa
cells until proven otherwise. He developed
methods for cell identification and raised
awareness of the problem in the scientific
literature and through correspondence with
individual scientists affected by the prob-
lem. Nelson-Rees’s last contribution to the
subject was published in 2009, soon after
his death10.
When Nelson-Rees first published his
findings, some scientists ignored or denied
the evidence and continued to publish
papers containing false information11. As a
consequence, Nelson-Rees felt that he had
no option but to highlight the papers (and
consequently the individuals) using cross-
contaminated cell lines. At that time (and
possibly today), Nelson-Rees’s behaviour was
regarded as unscientific and he was attacked
by many colleagues. He was branded a self-
appointed vigilante and his contract termi-
nated by the National Institutes of Health
(NIH) in 1981. After this, cell line misiden-
tification went largely unchecked and the
problem escalated. For the next 10–20 years,
cell banks distributed many cell lines under
their false names.
Estimating how much misleading and
erroneous research is attributable to cross-
contamination or misidentification of cell
lines has been difficult. The use of misidenti-
fied cultures increased about 10-fold in the
PubMed database (see Further information
for a link) between 1969 and 2004, and the
papers that used cultured cells increased
only 2–2.5-fold during the same time
period12,13. By 2004, HeLa was just the tip of
the iceberg, and many other cell lines mas-
queraded under various guises in laborato-
ries worldwide.
A survey that profiled active cell culture
workers found that of 483 respondents,
32% used HeLa cells, 9% unwittingly were
using HeLa contaminants, only 33% of
the investigators tested their cell lines for
authenticity and 35% obtained their cell lines
from other laboratories rather than from a
major repository12.
Although complacency and, in some
cases, denial have been the primary
responses to cell line misidentification over
the past five decades, a few individuals
have devoted a great deal of personal effort
into remediation of the problem. Among
the largely independent efforts were let-
ters to editors from concerned individuals
requesting that readers be alerted about the
problem, and that authors be required to pro-
vide evidence that the cell lines used in their
studies were neither cross-contaminated
nor misidentified. These efforts were largely
ignored in the period after Nelson-Rees’s
contract was terminated, despite the devel-
opment of DNA-fingerprinting techniques,
which brought new and more reproduc-
ible methods that once again revealed the
extent of cell line misidentification in the
early 1990s14.
Roland Nardone (FIG. 1c) started the
second crusade in 2004. He gained the sup-
port of Joseph B. Perrone, who was then
Vice President for Standards at ATCC and
provided ideas and the matching outrage
needed to fuel the crusade. Together with
other concerned scientists, Nardone devel-
oped a comprehensive and coordinated
initiative that simultaneously sought to raise
awareness of the nature and magnitude of
the problem and canvassed the involve-
ment of individuals and organizations
concerned or affected by the problem1,15.
Such organizations included the NIH, the
Howard Hughes Medical Institute, heads
of funding organizations and their attorney
generals, leaders of professional societies and
editors of science journals.
Copies of a white paper, ‘Eradication
of cross-contaminated cell lines: a call for
action’ (subsequently published by Nardone
in 2007 (REF. 15)) were distributed to thou-
sands of scientists. The white paper presented
what seemed to be a straightforward solu-
tion: funding agencies would require cell line
authentication as a condition for the receipt
of funds and journals would have a similar
requirement for manuscripts submitted for
publication. This approach was met initially
with indifference. Nevertheless, over a period
of 4 years, several substantial milestones
were reached1. An open letter16 to Michael
O. Leavitt, Secretary of Health and Human
Resources, led the NIH to re-examine the
situation. On November 28 2007, the NIH
published an addition to its guidelines for
research in the form of a notice regarding
authentication of cultured cell lines calling
for diligence and more careful peer review17.
Two factors have driven this progress.
One is heightened awareness. The other
is the outrage of scientists angered by the
failure of funding agencies and journals to
address the problem and allowing it to fester
and amplify for 50 years. Many scientists
now accept the need for a standardized
method of human cell line authentication
to satisfy the new requirements. ASN-0002
will be the first step towards a universally
adopted standard.
Examples and impact
Cross-contamination and misidentification
have a long history with many examples, but
it is difficult to judge which have been the
most substantial and costly.
The classic case already described is con-
tamination by HeLa cells, of which there are
several examples (see REFS 7,9 for example).
It is astonishing that many of these cell lines
Box 2 | ATCC SDO standards development process
•American Type Culture Collection (ATCC) Standard Development Office (SDO) Consensus
Standards Partnership (CSP) members recommend a new standard.
•Recommendation forwarded to ATCC SDO steering committee for review and vote.
•Project Initiation Notification System (PINS) published in American National Standards Institute
(ANSI) Standards Action for 30-day public comment period, concurrent with CSP (ATCC SDO
members) review.
•Recommendation for workgroup chair(s) sent to ATCC SDO steering committee for vote.
•Workgroup established; (ASN-0002), which includes stakeholders from academia, industry and
government, and proceeds to draft the standard (see BOX 1 for members of the workgroup).
•ASN-0002 workgroup forwards draft standard to steering committee for internal review.
Workgroup edits draft standard and forwards to ANSI and CSP (ATCC SDO membership) for
concurrent 45-day public review.
•ASN-0002 workgroup responds to all comments and resolves any differences. If there are no
substantial changes to the standard, the standard is submitted to the ANSI board of standards
review for final action and publication as an ANSI-approved standard.
PERSPECTIVES
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© 20 Macmillan Publishers Limited. All rights reserved10
Nature Reviews | Cancer
ac
b
have continued to be used under their false
descriptions in respected journals for over
40 years after they were first shown to be
HeLa cells (BOX 3).
T24 is another fast-growing cell line that
has contaminated many supposedly distinct
bladder cancer cell lines (BOX 3). ECV304
was originally claimed to be a spontane-
ously transformed human normal endothe-
lial cell line, but later shown to be T24
bladder cancer cells18. Surprisingly, the
demonstration that ECV304 cells are not
endothelial cells had little effect on its
use as a model for endothelial cells in
publications (FIG. 2).
The putative human prostate cancer cell
lines TSU-Pr1 and JCA-1 are also derived
from T24 bladder cancer cells19. These find-
ings were published in Cancer Research, but
that did not prevent TSU-Pr1 cells being
used as a prostate cancer cell model in a later
paper in Cancer Research (BOX 3).
DNA-fingerprinting analysis revealed
that the NCI/ADR-RES cell line was actu-
ally an ovarian tumour cell line, OVCAR-8,
rather than a breast cancer cell line.
Around 300 papers have been published
using the incorrect identification of the
NCI/ADR-RES cell line20. NCI/ADR-RES
is included in the NCI60 panel of cell lines,
which has been subject to STR profiling
(discussed below)21.
A paper describing misidentification of
oesophageal cell lines stated “Experimental
results based on these contaminated cell
lines have led to ongoing clinical trials
recruiting EAC [oesophageal adenocarci-
noma] patients, to more than 100 scientific
publications, and to at least three National
Institutes of Health cancer research grants
and 11 US patents”(REF. 22).
The consequences of widespread misi-
dentification and cross-contamination of cell
lines are immeasurable. In addition to the
waste of millions of dollars of public money,
time and intellectual resources, there is the
loss of confidence in published work, and
the integrity of science suffers.
Over 50 years of suppression. Why?
Three constituencies share responsibility for
cell line misidentification — individual
scientists, scientific journals and funding
agencies. For most of the past 50 years it
is only individual scientists who have
addressed the issue. Nevertheless, it is hard
to escape the conclusion that many scientists
have knowingly used misidentified cell lines
in publications (for example, the evidence in
FIG. 2). Furthermore, authors are often reluc-
tant to publish corrections to the literature
based on cell line misidentification.
John Maddox, the editor of Nature
in 1980, wrote an editorial about a high-
profile case of cross-contamination entitled
‘Responsibility for trust in research’ (REF. 23).
With an almost complete lack of insight
into the problem he suggested that “there
is no reason to suppose that the few cases
[of cross-contamination] that have come to
light are in any sense the tip of the iceberg”.
In the same editorial, scientists like Nelson-
Rees were vilified, as the article made the
point that it would be tragic if these civilized
habits (that is, truth in research) “were to be
corrupted by the activities of self-appointed
vigilantes”. The history of cell line cross-con-
tamination indicates that truth and trust are
not as universal among the scientific com-
munity as many scientists wish to believe.
The responses of editors of scientific
journals to the problem continue to be
illuminating. There have been hundreds
of papers in scientific journals describing
examples of misidentification and, until
recently, no remedial action has been taken
to eradicate the problem by journals or
funding agencies. The editor of an influ-
ential tissue culture journal was asked to
consider introducing authentication as a
requirement for publication and replied
that it would be financial suicide. Editors of
other journals also refused to consider such
quality-control measures on the basis that
introducing such a hurdle to publication
would substantially reduce the number of
authors willing to submit manuscripts to
their journal.
Over the past 2 years attitudes have
begun to change, with journals, such
as In Vitro Cellular and Developmental
Biology, International Journal of Cancer,
Figure 1 | Pioneers of awareness of cell line misidentification. a | Stanley Gartler b | Walter
Nelson-Rees c | Roland Nardone
Timeline | Key milestones in the effort to address cell line misidentification
1952 1958 1962 1966 1974 1980 1981 2005 2007 2009
Interspecies cross-
contamination
shown
HeLa cell line established
from Henrietta Lacks
ATCC starts
curating cell lines
Nelson-Rees confirms and
extends Stan Gartler’s findings
NIH terminates
contract of
Nelson-Rees
NIH issues guidelines to avoid
the use of misidentified cell lines
Stan Gartler shows intraspecies
cross-contamination between
human cell lines
John Maddox describes
individuals like Nelson-Rees
as “self-appointed vigilantes”
(1981–2005) Cross-contamination
spreads beyond HeLa cells
Roland Nardone starts the
second crusade against
cross-contamination
Nature calls for a
global database of
cell line STR profiles
ATCC, American Type Culture Collection; NIH, National Institutes of Health; STR, short tandem repeat
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Cell Biochemistry and Biophysics and the
American Association for Cancer Research
(AACR) journals, demanding that all cell
lines are authenticated before publication.
Nature has indicated that first the funding
organizations have to demand authentica-
tion and provide the necessary funds. Once
they do, Nature will require cell line identi-
fication prior to publication24. In the mean-
time, the funding organizations continue to
ignore the problem.
The constituency with the most power to
maintain standards in science is the fund-
ing agencies. Surprisingly, these have been
resistant to addressing or even acknowledg-
ing the problem of cell line misidentifica-
tion. For example, the NIH advisory note
issued in 2007 ignores the fact that indi-
vidual scientists and reviewers have failed
to overcome this problem. As an editorial in
Nature pointed out, the advisory note merely
enforces the status quo24.
Attempts to address the problem by indi-
vidual scientists have met with unhelpful
responses from funding bodies, which have
tended to deny or belittle the problem. A
recent public statement by a senior scientist
from Cancer Research UK made light of cell
line misidentification, saying that “this issue
raises its head every few years”. Funding
bodies seem to be threatened by the issue
and are resistant to engaging with scientists
who try to address the problem and often
attempt to disparage and discredit those
who try to find a solution.
Any of the major funding organizations
that support biomedical research in the
United States or United Kingdom could
have eradicated cell line misidentification
during the past 10 years for less than the
cost of the average project grant by funding
the measures outlined in this Science and
Society article. Yet, these funding agencies
have repeatedly ignored and in some cases
suppressed debate, and continued to pro-
vide grants for research using false cell lines.
There could be wider implications concern-
ing the role of funding agencies in the control
of scientific misrepresentation and fraud.
Zero tolerance of cell line misidentifica-
tion is needed from both journals and fund-
ing agencies. There are signs that Nardone’s
crusade is gaining influence and the standard
for human cell line identification will be
tangible evidence of Nardone’s legacy.
Causes of cell line misidentification
Most cell lines are established in academic
environments in which tissue culture is
often regarded as a technique requiring lit-
tle skill and essential facilities, such as flow
cabinets and incubators, are used without
restriction. In these circumstances, it is not
surprising that attempts to establish new
cell lines often lead to cross-contamination.
Among 550 leukaemia and lymphoma cell
lines submitted to the Deutsche Sammlung
von Mikroorganismen und Zellkulturen
GmbH (DSMZ; German Collection of
Microorganisms and Cell Cultures; please
see Further information for a link) cell bank,
59/395 (15%) submitted by originators
and 23/155 (15%) submitted by secondary
sources were false25. Presumably most of the
cell lines submitted by the secondary sources
had also been cross-contaminated or mis-
identified by the originators.
There are many causes of cell culture
misidentification and every laboratory is at
risk. Perhaps the most straightforward cause
is mislabelling of a cell culture vessel during
routine manipulation. Factors contributing
to this error include operator workload, lack
of attention, or distractions during manipu-
lation of cell lines.
Cross-contamination of a culture and
subsequent overgrowth by the contaminating
cell type is another frequent cause of cell line
misidentification. The chances of this occur-
ring are increased by the use of shared rea-
gents, repeated use of the same pipette during
re-feeding operations and manipulation of
multiple cultures at the same time without
adequate isolation of one cell type from
another. When cross-contamination happens,
one cell type may rapidly outgrow the other,
leading to a pure culture of the contaminating
cells in four or five passages26.
Intentional co-cultivation during propa-
gation of human stem or primary cells using
a feeder layer derived from another species
Box 3 | Examples of the use of cell lines under false descriptions
The examples discussed below were picked at random from PubMed searches. The impact of the
false descriptions ranges from minor to invalidation of the conclusions. The individual authors
have been failed by peer review. The papers indicate that the editors and some of the reviewers of
these journals (and by inference most scientific journals) are unaware of the extent of cell line
misidentification, and indicate a general lack of awareness throughout the scientific community.
HeLa cervical cancer cells
•Int-407 (described as “non-transformed intestinal epithelial cells”) in Br. J. Cancer 101, 1596
(2009), EMBO J. 22, 5003 (2003) and J. Biol. Chem. 280, 13538 (2005)
•WISH (described as “non-transformed amniotic epithelial cells”) in Mol. Pharmacol. 69, 796
(2006), Endocrinology 147, 2490 (2006) and J. Biol. Chem. 278, 31731 (2003)
•Chang liver (described as “normal liver cells”) in Oncogene 28, 3526 (2009), Proteomics 14, 2885
(2008) and J. Biol. Chem. 279, 28106 (2000)
•HEp-2 (described as “laryngeal cancer”) in Investig. New Drugs 26, 111–118 (2008),
Carcinogenesis 29, 1519 (2008) and J. Biol. Chem. 283, 36272 (2008)
•KB (described as “oral cancer”) in Biochem. Pharmacol. 73,1901–1909 (2007), Clin. Cancer Res. 14,
8161(2008) and J. Biol. Chem. 280, 23829 (2005)
•HeLa, Int-407 and HEp-2 cells were used as three distinct cell lines in the same study in Cancer
Res. 69, 632 (2009)
The scientists that use these cell lines sometimes use them under their false descriptions in many
publications. For example, one group has used Int-407 as a model of normal intestinal cells since
1988 and during the past 10 years has published in the Biochemical Journal (2 papers), Biochemical
Society Transactions, British Journal of Cancer, Cancer Research (2 papers), Carcinogenesis,
Experimental Cell Research (3 papers), Gastroenterology (2 papers), Journal of Biological Chemistry
(3 papers), Journal of Cell Physiology, Journal of Cell Science (3 papers), Oncogene, PLoS One and
several other journals.
T24 bladder cancer cells
In 1999, ECV304 cells (originally described as spontaneously immortalized normal endothelial
cells) were shown to be T24 cells18.
Yet, many papers continue to describe ECV304 cells as endothelial, for example Nature Immunol.
6, 497 (2005) and Nature Biotechnol. 25, 921 (2007). Some studies use ECV304 cells in endothelial
research without claiming that they are endothelial cells, but not stating that they are T24 bladder
cancer cells, such as Proc. Natl Acad. Sci. USA 106, 6849 (2009). Some studies have used T24 and
one or more of its cross-contaminants as distinct bladder cancer cell lines, for example J. Urol. 181,
1372–1380 (2009). Some studies describe ECV304 as bladder cancer cells, but fail to state that
they are T24 cells, such as J. Biol. Chem. 285, 555–564 (2010).
In Cancer Research in 2001, it was shown that TSU-Pr1 are T24 bladder cancer cells (Cancer Res. 61,
6340–6344 (2001)). In the same journal, less than 3 years later, TSU-Pr1 cells were used as a prostate
cancer model (Cancer Res. 64, 1058–1066 (2004)). TSU-Pr1 continue to be used in some studies as a
model for prostate cancer, such as Endocrinology 147, 530–542 (2006) and Cancer Cell 5, 67 (2004).
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Nature Reviews | Cancer
0
20
40
60
80
100
120
140
160
Number of citations
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
Publishing year
131510
20
27
65
75
128
146
155
143138 136
124
110
103
Cites per year
‘Endothelial’
cites
131
(such as mouse 3T3 cells) can result in cross-
contamination and overgrowth of the human
cell line. Normally, feeder cells are rendered
incapable of proliferating, but if the growth
arrest procedure is inadequate, the feeder
cells can proliferate and displace the
human cells. Somatic cell hybridization
is unusual but can occur, as found in the
human mantle cell lymphoma line NCEB-1,
which carries seven mouse chromosomes27.
Xenografting can also lead to cell line
cross-contamination and misidentifica-
tion28. Recovered cell lines from xenografts
can be replaced by cells derived from the
host animal.
In general, cross-contamination results
in the complete and rapid displacement of
the less fit cell type. Two cell lines cannot
co-exist in the same culture environment for
extended periods unless there is a symbiotic
relationship, which as far as we know has
never been reported. Consequently, cell mix-
tures are discovered rarely. The only known
situation in which a cell population contains
a stable mixture of genomes over many pas-
sages is following somatic cell hybridization.
Simple, cheap quality-control meas-
ures can prevent or at least minimize
the consequences of misidentification.
Misidentification is rife because of a combi-
nation of lack of awareness and the failure to
include quality-control measures. The exten-
sive quality-control measures demanded
of the biopharmaceutical industry and
mandated in the applicable regulatory
documents are believed to have contributed
to the relatively low frequency of cell line
misidentification reported in this industry29.
Detection of cross-contamination
Many methods have been used to detect
cross-contamination, including isoenzyme
analysis, karyotyping, human leukocyte
antigen (HLA)-typing, immunotyping and
DNA fingerprinting. These methods can
authenticate a cell line, but with differing
levels of ambiguity and powers of discrimina-
tion (Supplementary information S1 (table)).
However, the data produced by these meth-
ods are not sufficiently reproducible between
laboratories to allow any of them to be used
for a standardized reference database.
Many laboratories have adopted STR
profiling to identify human cell lines.
STR profiling is the method used by forensic
analysts and depends on the simultaneous
amplification of multiple stretches of poly-
morphic DNA in a single tube. STR loci
consist of repetitive DNA sequences that have
varying numbers of repeats. Each STR locus
can be amplified and the amplified products
labelled with fluorophores of different col-
ours, making the products easy to distinguish
by size and colour (FIG. 3). STR analysis is
rapid, inexpensive, amenable to automation
and generates reproducible data in a format
suitable for a standard reference database. For
the quick, unambiguous authentication of cell
lines, STR analysis has the greatest value.
STR profiling — potential and limitations
DNA repeat sequences of 3–5 bases have
been used routinely for paternity testing,
forensic casework, and the identification of
victims of mass disaster for more than two
decades30–33. Consequently, STR profiling
was applied to cell line identification34–36.
There are several advantages to using STRs
for the authentication of human cell lines
(Supplementary information S2 (box)).
Cancer cell lines contain many genetic
alterations, and therefore the criteria used
to compare them using STR profiling
must be different to those used for nor-
mal tissue (Supplementary information
S3 (box)). Cancer cells often show loss of
heterozygosity (that is, loss of an allele,
which cannot be distinguished easily from
homozygosity) and can contain multiple
copies of alleles owing to DNA duplica-
tion. Similarly, during culture, cancer cell
lines can lose or more rarely gain a copy
of an allele (for examples, see REF. 34).
Consequently, sub-lines of the same cell
line may not have identical STR profiles.
Comparing identical alleles, a threshold of
75% identity has distinguished all known
cross-contaminated cell lines in published
datasets, and no two cell lines thought
to be derived from different individu-
als showed more than 50% identity21,34.
Consequently, there is a comfortable
cushion of 25% between cell lines that are
unique and those that show evidence of
cross-contamination. Any cell line found
with an identity level between 50 and 75%
should be regarded with suspicion.
Major issues in the interpretation of
genotypes from human cell lines include
heterozygote peak height imbalance (that is
the peak height or area of one allele is much
larger than the peak height or area of the
second allele), multiple alleles at a locus, and
allele dropout (no amplification product
of the expected size). Cancer cell lines are
aneuploid and consequently STR profiles
typically show heterozygous peak height
imbalances and/or multiple alleles at one or
more loci.
The cost of genotyping is a major con-
cern, but trivial in relation to the cost of the
work being done with the cell line. The cost
of STR profiling includes DNA extraction,
polymerase chain reaction (PCR) amplifi-
cation of STR loci, separation of amplified
products by capillary electrophoresis and
data analysis. Increasing the number of STR
loci, for example, from 6 to 15 would achieve
a much higher power of discrimination
(Supplementary information S4 (table)).
A major limitation of STR profiling is
that it will not detect contaminating cells
of another species, although if human
cells are overgrown by cells of another spe-
cies, the DNA will not amplify using human
or higher primate-specific STR primers.
PCR using species-specific primers can be
used to detect contaminating cells from
other species. If STR profiles have been
established for the other species (currently
restricted to a few commercially important
species), STR can be carried out to defini-
tively identify the contaminating cells.
For most of the established cell lines,
donor tissue is not available and many origi-
nators of widely used cell lines are retired
or deceased. In these cases, an assumption
has to be made, based on the oldest possible
cell stocks in repositories. These profiles will
need to be labelled as provisional to indicate
the absence of authentication back to the
original donor tissue.
Until the database described below is
available, there are limited resources avail-
able for comparing STR profiles. The ATCC
and DSMZ cell bank websites and Cell
Line Integrated Molecular Authentication
Figure 2 | Citations of T24 bladder cancer
cells referred to as normal endothelial cells.
The demonstration that ECV304 cells are not
endothelial cells had little effect on its use as a
model for endothelial cells in publications, as
shown by the graph. Data generated courtesy of
R.A.F. MacLeod, National Institute of Standards
and Technology.
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Cells
Database search
against previous
enrolled cell lines
Result
interpretation
Colour separation
STR allele separation
and sizing
DNA extraction
Multiplex PCR
to amplify STR
alleles
(CLIMA; see Further information for links)
database37 provide some information, and
at least two series of STR profiles have been
published21,34. Currently, one of the most
useful resources is the list of misidentified
cell lines collected by Amanda Capes-
Davis and Ian Freshney (supplementary
table in REF. 38), which can also be seen on
the European Collection of Cell Cultures
(ECACC; see Further information for a
link) website. All scientists should check
the names of the cell lines they are using
against this list.
The interactive database
It is proposed that a database will be
established to exploit available STR data
to validate the identity of human cell lines.
The interactive database will be accessible
to every one, but only the database admin-
istrators can make changes or additions.
The database will provide DNA profiles and
will allow laboratories to compare the STR
profiles of their lines, thereby facilitating the
validation of experimental data.
Universal criteria are needed for what
constitutes a good database. The standard
for cell line authentication will establish
an interactive database of validated DNA
profiles for each unique cell line and will
also put in place requirements for carry-
ing out and interpreting the STR assays.
The members of the standard committee
in conjunction with the National Center
for Biotechnology Information (NCBI) will
develop the requirements for the database
and the database will be maintained by
NCBI. The database will initially contain
Figure 3 | Short tandem repeat profiling
methodology. Short tandem repeat (STR) loci
consist of repetitive DNA sequences with varying
numbers of repeats. Each STR locus can be
polymerase chain reaction (PCR) amplified and
the amplified products labelled with fluorophores
of different colours, making the products easy to
distinguish by size and colour. Images courtesy of
J. Butler, National Institute of Standards and
Technology.
around 500 validated cell lines frequently
used by scientists and banked in major cell
repositories. The profile of each cell line will
be validated before it is submitted to the
database.
The most effective database to compare
cell line STR-profiling data would consist
of a common set of markers. However,
not all data have been collected for the
same STR loci or using the same genera-
tion of sequencing instruments. The use
of different primer sets for the same STR
markers is a common practice for the
forensic and human identity community,
which in the United States uses a core set
of 13 STR markers for data input into the
Federal Bureau of Investigation-maintained
Combined DNA Index System (CODIS). To
maintain the integrity of the data entered
into CODIS, laboratories must use CODIS-
approved STR-typing kits and instrumen-
tation, and follow strict quality assurance
standards39. Approved CODIS STR kits have
undergone extensive validation studies that
include concordance studies designed to
elucidate STR-typing differences that may
be seen with the use of different primer sets.
Similar protocols will be needed for STR
profiling of cell lines.
The future
Cell line verification by STR profiling
will have a substantial effect on scientific
research in terms of increased data cred-
ibility and less time, money and effort spent
studying misidentified cell lines. Accurate
identification of cell lines is crucial dur-
ing the development of cell-based medical
products to avoid the risks of exposing
human subjects to misidentified cells.
Although such misidentification can largely
be avoided by adherence to quality-control
measures, such as proper labelling and
tracking schemes during manufacture of
a cell-based product, the availability of a
standardized method for unambiguous cell
and tissue identification could contribute
to safety assurance when used to confirm
that a cell product came from the intended
donor and was not inadvertently mixed
with cells from other donors. This issue is
of great importance to personalized medi-
cine and the application of stem cell-based
technologies, including induced pluripotent
stem cells.
No single method is available that
provides all the information needed to
authenticate a human cell line. STR profil-
ing represents the optimal candidate at
this time. Consequently, the standard is
intended to evolve as new information
becomes available. The interactive, searchable
database openly available to everyone will
largely eradicate the use of misidentified
cell lines. Funding bodies and journals are
encouraged to adopt a policy of zero toler-
ance and demand proof that all cell lines are
as claimed.
For members of the ATCC Standards Development
Organization (SDO) Workgroup ASN-0002 see BOX 1
John R. W. Masters is at University College London,
67 Riding House Street, London W1W 7EJ, UK.
Correspondence to J.R.W.M.
e-mail: j.masters@ucl.ac.uk
doi:10.1038/nrc2852
Published online 7 May 2010
1. Nardone, R. M. Curbing rampant cross-contamination
and misidentification of cell lines. Biotechniques 45,
221–227 (2008).
2. Nelson-Rees, W. A. & Flandermeyer, R. R. Inter- and
intraspecies contamination of human breast tumor cell
lines HBC and BrCa5 and other cell cultures. Science
195, 1343–1344 (1977).
3. MacLeod, R. A. F. et al. Widespread intraspecies
cross-contamination of human tumor cell lines
arising at source. Int. J. Cancer 83, 555–563
(1999).
4. Rothfels, K. H., Axelrad, A. A., Siminovitch, L.,
McCulloch, E. A. & Parker, R. C. in Proc. 3rd Canadian
Cancer Conf. (ed. Begg, R. W.)189–214 (Academic
Press, New York,1958).
5. Defendi, V., Billimgham, R. E., Silvers, W. K. &
Moorhead, P. Immunological and karyological criteria
for identification of cell lines. J. Natl Cancer Inst. 25,
359–385 (1960).
6. Brand, K. G. & Syverton, J. T. Results of species-specific
hemagglutination tests on “transformed”,
nontransformed, and primary cell cultures. J. Natl
Cancer Inst. 28, 147–157 (1962).
7. Gartler, S. M. Genetic markers as tracers in cell
culture. Natl Cancer Inst. Monogr. 26, 167–195
(1967).
8. Gey, G. O., Coffman, W. D. & Kubicek, M. T. Tissue
culture studies of the proliferative capacity of cervical
carcinoma and normal epithelium. Cancer Res. 12,
264–265 (1952).
9. Nelson-Rees, W. A., Flandermeyer, R. R. &
Hawthorne, P. K. Banded marker chromosomes as
indicators of intraspecies cellular contamination.
Science 184, 1093–1096 (1974).
10. Lucey, B. P., Nelson-Rees, W. A. & Hutchins, G. M.
Henrietta Lacks, HeLa cells, and cell culture
contamination. Arch. Pathol. Lab. Med. 133,
1463–1467 (2009).
11. Nelson-Rees, W. A. Responsibility for truth in
research. Phil. Trans. R. Soc. Lond. B 356, 849–851
(2001).
12. Buehring, G. C., Eby, E. A. & Eby, M. J. Cell line cross-
contamination: how aware are mammalian cell
culturists of the problem and how to monitor it?
In Vitro Cell Dev. Biol. Anim. 40, 211–215 (2004).
13. Chatterjee, R. Cell biology. Cases of mistaken identity.
Science 315, 928–931 (2007).
14. Gilbert, D. A. et al. Application of DNA fingerprints for
cell-line individualization. Am. J. Hum. Genet. 47,
499–514 (1990).
15. Nardone, R. M. Eradication of cross-contaminated cell
lines: a call for action. Cell Biol. Toxicol. 23, 367–372
(2007).
16. Nardone, R. M. et al. An open letter regarding the
misidentification and cross-contamination of cell lines:
significance and recommendations for correction.
Japanese Collection of Research Bioresources Cell
Line Catalogue [online] http://cellbank.nibio.go.jp/
cellbank/qualitycontrol/OL7-11-07.pdf (2007).
17. National Institutes of Health. Notice Regarding
Authentication of Cultured Cell Lines. NIH Guide for
Grants and Contracts [online] http://grants.nih.gov/
grants/guide/notice-files/NOT-OD-08–017.html
(2007).
18. Dirks, W. G., Drexler, H. G. & MacLeod, R. A. F.
ECV304 (endothelial) is really T24 (bladder
carcinoma): cell line cross- contamination at source. In
Vitro Cell Dev. Biol. 35, 558–559 (1999).
PERSPECTIVES
NATURE R EVIEWS
|
CANCER VOLUME 10
|
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© 20 Macmillan Publishers Limited. All rights reserved10
19. van Bokhoven, A., Varella-Garcia, M., Korch C &
Miller, G. J. TSU-Pr1 and JCA-1 cells are derivatives of
T24 bladder carcinoma cells and are not of prostatic
origin. Cancer Res. 61, 6340–6344 (2001).
20. Liscovitch, M. & Ravid, D. A case study in
misidentification of cancer cell lines: MCF-7/AdrR cells
(re-designated NCI/ADR-RES) are derived from
OVCAR-8 human ovarian carcinoma cells. Cancer Lett.
245, 350–352 (2006).
21. Lorenzi, P. L. et al. DNA fingerprinting of the NCI-60
cell line panel. Mol. Cancer Ther. 8, 713–724 (2009).
22. Boonstra, J. J. et al. Verification and unmasking of
widely used human esophageal adenocarcinoma cell
lines. J. Natl Cancer Inst. 102, 1–4 (2010).
23. Maddox, J. Responsibility for trust in research. Nature
289, 211–212 (1981).
24. Miller, L. J. Identity crisis. Nature 457, 935–936
(2009).
25. Drexler, H. G., Dirks, W. G., Matsuo, Y. &
MacLeod, R. A. F. False leukemia-lymphoma cell lines:
an update on over 500 cell lines. Leukemia 17,
416–426 (2003).
26. Nims, R. W., Shoemaker, A. P., Bauernschub, M. A.,
Rec, L. J. & Harbell, J. W. Sensitivity of isoenzyme
analysis for the detection of interspecies cell line cross-
contamination. In Vitro Cell De v. Biol. Anim. 34,
35–39 (1998).
27. Drexler, H. G. & MacLeod, R. A. F. Mantle cell
lymphoma-derived cell lines: unique research tools.
Leukemia Res. 30, 911–913 (2006).
28. Pathak, S., Nemeth, M. & Multani, A. S. Human tumor
xenografts in nude mice are not always of human
origin: a warning signal. Cancer 86, 898–900 (1999).
29. Nims, R. W. & Herbstritt, C. J. Cell line authentication
using isoenzyme analysis: strategies for accurate
speciation and case studies for detection of cell line
cross-contamination using a commercial kit. BioPharm
Int. 18, 76–82 (2005).
30. Debenham, P. G. & Webb, M. B. Cell line
characterization by DNA fingerprinting; a review. Dev.
Biol. Stand. 76, 39–42 (1992).
31. Moretti, T. R. et al. Validation of short tandem repeats
(STRs) for forensic usage: performance testing of
fluorescent multiplex STR systems and analysis of
authentic and simulated forensic samples. J. Forensic
Sci. 46, 647–660 (2001).
32. Budowle, B., Shea, B., Niezgoda, S. &
Chakraborty, R. CODIS STR loci data from 41 sample
populations. J. Forensic Sci. 46, 453–489 (2001).
33. Butler, J. M. Forensic DNA Typing. Biology,
Technology, and Genetics of STR Markers, 2nd edn
(Academic Press, Burlington, USA, 2005).
34. Masters, J. R. et al. Short tandem repeat profiling
provides an international reference standard for
human cell lines. Proc. Natl Acad. Sci. USA 98,
8012–8017 (2001).
35. Parson, W. et al. Cancer cell line identification by short
tandem repeat profiling: powers and limitations.
FASEB J. 19, 434–436 (2005).
36. Schweppe, R. E. et al. DNA profiling analysis of 40
human thyroid cancer cell lines reveals cross-
contamination resulting in cell line redundancy and
misidentification. J. Clin. Endocrin. Metab. 93,
4331–4341 (2008).
37. Romano, P. et al. Cell Line Data Base: structure and
recent improvements towards molecular
authentication of human cell lines. Nucleic Acids Res.
37, D925–D932 (2009).
38. Capes-Davis, A. et al. Check your cultures! A list of
cross-contaminated or misidentified cell lines. Int. J.
Cancer 8 Feb 2010 [epub ahead of print].
39. Federal Bureau of Investigation. Standards and
Guidelines Quality Assurance Standards for Forensic
DNA Testing Laboratories. Federal Bureau of
Investigation Forensic Science Communications
[online] http://www.fbi.gov/hq/lab/fsc/backissu/
oct2008/standards/2008_10_standards01.htm
(2008).
Competing interests statement
The authors declare competing financial interests; see Web
version for details.
DATABASES
CLIMA database: http://bioinformatics.istge.it/clima
PubMed: http://www.ncbi.nlm.nih.gov/pubmed
FURTHER INFORMATION
ATCC SDO homepage: http://www.atccsdo.org
ATCC cell bank: http://www.atcc.org
DSMZ cell culture collection:
http://www.dsmz.de/human_and_animal_cell_lines
ECACC cell culture collection:
http://www.hpacultures.org.uk/collections/ecacc.jsp
SUPPLEMENTARY INFORMATION
See online article: S1 (table) | S2 (box) | S3 (box) | S4 (table)
ALL LINKS ARE ACTIVE IN THE ONLINE PDF
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